PROCEEDINGS OF
INTERNATIONAL SYMPOSIUM
ON SOIL MANAGEMENTFOR SUSTAINABLE AGRICULTURE

2017-PART 1INTERNATIONAL SYMPOSIUM ON SOIL
MANAGEMENT FOR SUSTAINABLE AGRICULTURE
2017
ORGANIZER:
THE UNITED GRADUATE SCHOOL OF AGRICULTURAL SCIENCE,
GIFU UNIVERSITY-PART 2UGSAS-GU & BWEL JOINT POSTER SESSIONON AGRICULTURAL
AND BASIN WATER ENVIRONMENTAL SCIENCES
CO-ORGANIZER:
GIFU UNIVERSITY REARING PROGRAM
FOR BASIN WATER ENVIRONMENTAL LEADERS

AUGUST 28 - 30, 2017
6TH FLOOR, UGSAS BLDG. GIFU UNIVERSITY, JAPANInternational Symposium
on Soil Management for Sustainable Agriculture 2017

DAY ONE: Monday, August 28

Time: 9:30-19:30
Venue: Main Seminar Room (6F in UGSAS Building, Gifu University)
Master of Symposium: Prof. Kohei Nakano (Gifu Univ.)
Time Table
9:30-10:00

Registration

10:00-10:05

Opening Remarks
Prof. Masateru SENGE (Dean of UGSAS, Gifu Univ.)

10:05-10:10

Welcome Speech
Dr. Fumiaki SUZUKI (Executive Director and Vice President of Gifu Univ.)

10:10-10:50

Keynote Speech 01
Prof. Yasushi MORI (Okayama Univ.): Soil Physical Rehabilitation

10:50-11:30

Keynote Speech 02
Assist. Prof. Yuki KOJIMA (Gifu Univ.): Soil Water and Energy Dynamics

Session 1 ―General Issue and Solution― Session Chair: Prof. Muhajir Utomo (Lampung Univ.)
11:30-11:55
01. Prof. Isril BERD (Andalas Univ.)
11:55-12:20

02. Dr. Komariah (Sebelas Maret Univ.)

12:20-12:30

Photo Session

12:30-13:40

Lunch Break (Light meals served)

Session 2 ―Soil Science― Session Chair: Assistant Prof. Keigo NODA (Gifu Univ.)
13:40-14:05
01. Prof. Muhajir UTOMO (Lampung Univ.)
14:05-14:30

02. Dr. Afandi (Lampung Univ.)

14:30-14:55

03. Mr. Didin Wiharso, M.Sc. (Lampung Univ.)

14:55-15:20

04. Dr. Nuyen Thi Hang NGA (Thuy Loi Univ.)

15:20-15:30

Coffee BreakSession 3 ―Watershed Management―Session Chair: Associate Prof. Takeo ONISHI (Gifu Univ.)
15:30-15:55
01. Dr. Khandra Fahmy (Andalas Univ.)
15:55-16:20

02. Dr. Muhammad MAKKY (Andalas Univ.)

16:20-16:45

03. Dr. Eri Gas EKAPUTRA (Andalas Univ.)

16:45-17:10

04. Mr. Fadli IRSYAD, M.Sc. (Andalas Univ.)

17:40-19:30

Dinner Meeting (At Gifu University Restaurant (1))

DAY TWO: Tuesday, August 29

Time: 9:00-17:40
Venue: Main Seminar Room (6F in UGSAS Building, Gifu University)
Master of Symposium: Prof. Ken HIRAMATSU (Gifu Univ.)
Time Table
9:00-9:30

Registration

9:30-10:10

Keynote Speech 03
Prof. Akira WATANABE (Nagoya Univ.): Soil Organic Matter Dynamics

10:10-10:50

Keynote Speech 04
Assoc. Prof. Fumitoshi IMAIZUMI (Shizuoka Univ.): Erosion Control Engineering

10:50-11:00

Coffee BreakSession 4 ―Soil Biology & Microbiology― Session Chair: Prof. Isril Berd (Andalas Univ.)
11:00-11:25
01. Dr. Retno Rosariastuti (Sebelas Maret Univ.)
11:25-11:50

02. Dr. Sudadi (Sebelas Maret Univ.)

11:50-12:15

03. Dr. Widyatmani Sih Dewi (Sebelas Maret Univ.)

12:15-13:20

Lunch Break (Light meals served)

Session 5 ―Soil Chemistry― Session Chair: Dr. Retno Rosariastuti (Sebelas Maret Univ.)
13:20-13:45
01. Prof. Fusheng Li (Guangxi Univ.)
13:45-14:10

02. Dr. Mujiyo (Sebelas Maret Univ.)

14:10-14:35

03. Ms. Dinh Thi Lan Phuong, M.Sc. (Tyui Loi Univ.)

14:35-15:10

Break & Preparation for Poster Presentation Session

15:10-17:00-PART 2- *Please refer to the next page for details.
UGSAS-GU & BWEL Joint Poster Session on
Agricultural and Basin Water Environmental Sciences

DAY THREE: Wednesday, August 30

Time: 10:00-17:00
Study Tour on Soil and Water Management
Visiting TANIGUMI Historic Temple and Local Irrigation System &TOKUYAMA DAM with Underground Facility for Water Management

UGSAS-GU & BWEL Joint Poster Session on Agricultural andBasin Water Environmental Sciences

DAY TWO: Tuesday, August 29

Time: 15:10-17:00
Venue: Main Seminar Room (6F in UGSAS Building, Gifu University)
Time Table
15:10-16:45

Poster Presentation

16:45-16:55

Best Presentation Award ceremony

16:55-17:00

Closing remarks
Prof. Fusheng LI (Head of the Promotion Office of Gifu University Rearing
Program for Basin Water Environmental Leaders (BWEL))

Presenters
P01: Tran Duy Quan (UGSAS-GU)
P02: Ning Li (UGSAS-GU)
P03: Dina Istiqomah (UGSAS-GU)
P04: Akash Chandela (UGSAS-GU)
P05: Daimon Syukri (UGSAS-GU)
P06: Witchulada Yungyuen (UGSAS-GU)
P07: Panyapon Pumkaeo (Graduate School of Integrated Science and Technology, Shizuoka
University)
P08: Arif Delviawan (Graduate School of Integrated Science and Technology, Shizuoka
University)
P09: Siwattra Choodej (UGSAS-GU)
P10: Jobaida Akther (UGSAS-GU)
P11: Annisyia Zarina Putri (Graduate School of Applied Biological Sciences, Gifu University)
P12: Masaya Toyoda (Graduate School of Engineering, Gifu University; BWEL)
P13: Tharangika Ranatunga (UGSAS-GU; BWEL)
P14: Shuailei Li (Graduate School of Natural Science and Technology, Gifu University; BWEL)
P15: Ruoming Cao (Graduate School of Applied Biological Sciences, Gifu University; BWEL)
P16: Fenglan Wang (UGSAS-GU; BWEL)
P17: Diana Hapsari (UGSAS-GU; BWEL)
P18: Ran Song (Graduate School of Engineering, Gifu University; BWEL)
P19: Chen Fang (UGSAS-GU; BWEL)
P20: Guangyu Cui (Graduate School of Engineering, Gifu University; BWEL)
P21: Ali Rahmat (UGSAS-GU; BWEL)
P22: Junfang Zhang (Graduate School of Engineering, Gifu University; BWEL)
P23: Siyu Chen (UGSAS-GU; BWEL)
P24: Wenjiao Li (Graduate School of Engineering, Gifu University; BWEL)
P25: Huijuan Shao (UGSAS-GU; BWEL)

― PART 1 ― KEYNOTE SPEECHESKEYNOTE SPEECHES
01: Soil Physical Rehabilitation –Artificial Macropore Installation to Restore Organic Matter inSoilsYasushi MORI・・・・・・・・・・・・・・・・・・・・・・・・・・・・・p. 2
02: Development of Soil Property Sensors Using Heat Transfer
Yuki KOJIMA, Yuta NAKANO・・・・・・・・・・・・・・・・・・・・・・・p. 4
03: Stability of Soil Organic Matter in Soil Management for Sustainable Agriculture
Akira WATANABE ・・・・・・・・・・・・・・・・・・・・・・・・・・・p. 6
04: Relationship between vegetation cover and sediment transport activities on mountainhillslopes
Fumitoshi IMAIZUMI・・・・・・・・・・・・・・・・・・・・・・・・・・p. 8
GUEST/ALUMNI PRESENTATIONSSESSION 1 ―General Issue and Solution―
01: Analysis study of landslide induced by earthqueke in Tandikat Partamuan, Padang
Pariaman District, West Sumatra, Indonesia
Isril BERD, Amrizal SAIDI, Skunda DILIAROSTAP・・・・・・・・・・・・・・・p. 12
02: SOIL RESOURCE ISSUES IN INDONESIA
Komariah and Masateru SENGE・・・・・・・・・・・・・・・・・・・・・・p.19
SESSION 2 ―Soil Science―
01: Soil Carbon Stock and Sequestration after 29 Years of No-tillage in Sumatra, Indonesia
Muhajir UTOMO, Jamalam LUMBANRAJA, Tamaluddin SYAM and Fajri Taufik AKBAR
・・・・・・・・・・・・・・・・・・・・・p.25
02: Soil Properties in Relation with the Incidence of Heart Rot Disease in Pineapple due toPhytophthora sp. in Humid Tropical Climate of Lampung, Indonesia
Afandi, P. Cahyono, G.alang I. Jaya, M.A.S. Syamsul Arif, Ivayani, and Auliana Afandi
・・・・・・・・・・・・・・・・・・・・p.30
03: Changes of soil morphology and properties in long-term soil management under humid
tropical regions of Lampung, Indonesia
Didin Wiharso, Muhajir Utomo and Afandi・・・・・・・・・・・・・・・・・p. 33
04: Application of bentonite to soil reclamation in drought areas of Ninh Thuan province,
Viet Nam
Nuyen Thi Hang NGA・・・・・・・・・・・・・・・・・・・・・・・・・・p. 40

SESSION 3 ―Watershed Management―
01: The Evaluation of Watershed Condition of Sumani Based in Solok Regency Based on Land
Characteristic
Delvi Yanti, Khandra Fahmy, Isril berd, Fery Arlius・・・・・・・・・・・・・・p. 44
02: Wisdom Agriculture Application in Oil Palm Industry for Promoting Healthy Soil andEmission Reduction
Muhammad MAKKY, Delviyanti, Isril BERD・・・・・・・・・・・・・・・・・p. 47
03: Soil and Water Conservation with Zero Runoff Model in Oil Palm Plantation
Eri Gas EKAPUTRA, Fadli IRSYAD・・・・・・・・・・・・・・・・・・・・・p. 58
04: Conservation Analysis of Kuranji Watershed using SWAT Application
Fadli IRSYAD, Eri Gas EKAPUTRA・・・・・・・・・・・・・・・・・・・・・p. 65
SESSION 4 ―Soil Biology & Microbiology―
01: Phytoremediation of Soil Contaminated by Chromium (Cr) of Industrial Waste Using
Mendong Plant (Fimbrystilis globulosa) in Its Combination With Agrobacterium Sp.I3 or
Organic Matter
Pungky Ferina, Supriyadi, Retno Rosariastuti・・・・・・・・・・・・・・・・p. 70
02: Potency of rhizobiota consortium as biofertilizer inoculants to inhibit basal rot andincrease yield
Sudadi, Hadiwiyono and Sumarno・・・・・・・・・・・・・・・・・・・・・p. 76
03: BIOCHAR AND AZOLLA FOR SUSTAINABLE RICE SOIL MANAGEMENT
Widyatmani Sih Dewi and Masateru SENGE・・・・・・・・・・・・・・・・・p. 80
SESSION 5 ―Soil Chemistry―
01: Emissions of CH4 and N2O and the relationships with soil properties under different
irrigation methods and nitrogen treatments
Fusheng Li・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・p.87
02: Methane Emissions in Paddy Field and Its Mitigation Options for Win-Win Solution
Mujiyo, Ken HIRAMATSU and Takeo ONISHI・・・・・・・・・・・・・・・・・p.89
03: Solutions for nutritional zinc management in paddy soils in the Red River Delta of Vietnam(Tien Lu region, Hung Yen province)
Dinh Thi Lan Phuong, Nguyen Thi Hang Nga・・・・・・・・・・・・・・・・・p. 95

― PART 2 ―UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences
P01: Research on cause of dam failure under view point of hydraulic fracturing – Case study
KE 2/20 REC dam failure in Vietnam
Tran Duy Quan, Shinichi Nishimura, Masateru Senge and Fumitoshi Imaizumi
・・・・・・・・・・・・・・・・・・・・・p. 100
P02: Data mining the efficiency of auction in origin market based on random forest-A casestudy of ATSUMI AREA, AICHI Prefecture Ning Li and Shigenori Maezawa・・・・・・・・・・・・・・・・・・・・・・p. 102
P03: Study of plant pathogenic genes of a soft rot disease causing bacterium, Dickeya dadantii
Dina Istiqomah and Naoto Ogawa・・・・・・・・・・・・・・・・・・・・・p. 104
P04: Augmentation of nuclease resistance and gene silencing by synthesizing 3’-end
nucleoside base modified small interfering RNAs
Akash Chandela and Yoshihito Ueno・・・・・・・・・・・・・・・・・・・・p. 106
P05: Maintenance of oligosaccharides content during soybean sprout cultivation bycontrolling temperature conditions
Daimon Syukri, Manasikan Thammawong and Kohei Nakano・・・・・・・・・・p. 108
P06: Effect of temperature on flavonoid metabolism in citrus juice sacs in vitro
Witchulada Yungyuen, Gang Ma, Lancui Zhang, Kazuki Yamawaki, Masaki Yahata,
Satoshi Ohta, Terutaka Yoshioka and Masaya Kato・・・・・・・・・・・・・・p. 110
P07: Bioconversion of AHX to AOH by Buttiauxella gaviniae A111
Panyapon Pumkaeo, Ayaka Kikuchi and Shinji Tokuyama・・・・・・・・・・・p. 112
P08: The characteristics of screened particle with different pulverization process and drying
condition
Arif Delviawan, Shigehiko Suzuki, Yoichi Kojima and Hikaru Kobor・・・・・・・p. 114
P09: Isolation, semi-synthesis of Costunolide from Saussurea lappa and their TNF-α inhibition
Siwattra Choodej, Khanitha Pudhom and Tohru Mitsunaga・・・・・・・・・・p. 116
P10: Protein-based functional analysis of renin and (pro) renin receptor genes in hypertensive
and diabetic Bangladeshi population: Pursuing the environment-induced molecular traits
Jobaida Akther, A. H. M. Nurun Nabi, Tsutomu Nakagawa, Fumiaki Suzuki and Akio
Ebihara・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・p. 118
P11: The budding yeast Saccharomyces cerevisiae requires Vitamin B1 (Thiamine) for
acetaldehyde tolerance
Annisyia Zarina Putri, Madoka Kubota, Haruka Matsuyama, Tetsushi Takagi, Mizuho
Inagaki, Masaya Shimada, Takashi Hayakawa and Tomoyuki Nakagawa・・・・・p. 120

P12: Comparison of typhoon HAIYAN (2013) and typhoon MELOR (0918) using pseudo-global
warming experiments
Masaya Toyoda, Jun Yoshino and Tomonao Kobayashi・・・・・・・・・・・・p. 122
P13: Controlling the process of denitrification in flooded rice soils by using microbial fuel cellapplications
Tharangika Ranatunga, Ken Hiramatsu and Takeo Onishi・・・・・・・・・・・p. 124
P14: Effect of aeration time on total coliform and E. coli concentrations in excess activatedsludgeShuailei Li, Guangyu Cui and Fusheng Li・・・・・・・・・・・・・・・・・・・p. 126
P15: The nitrogen cycling in a deciduous broad-leaved forest, central Japan
Ruoming Cao, Siyu Chen, Shinpei Yoshitake, Chiyuki Asai1 and Toshiyuki Ohtsuka
・・・・・・・・・・・・・・・・・・・・・p. 128
P16: Small hydraulic generation using irrigation facilities: Case study of Meiji Yousui district
Fenglan Wang, Keigo Noda, Kengo Ito and Masateru Senge・・・・・・・・・・p. 130
P17: Seasonal difference role on sediment rating curve at small broadleaves and coniferous
forest catchments in Kuraiyama, Japan
Diana Hapsari, Takeo Onishi, Masateru Senge, Fumitoshi Imaizumi and Ali Rahmat
・・・・・・・・・・・・・・・・・・・・・p. 132
P18: Effects of thermal treatment on the release of organic matter from wastewater sludge
Ran Song, Guangyu Cui, Huijuan Shao, Shuailei Li and Fusheng Li・・・・・・・・・・・・・・・・・・・・・p. 134
P19: Seismic risk evaluation of irrigation tanks -Case study of two irrigation tanks in
Ibigawa-cho, Gifu Prefecture, JapanChen Fang, Hideyoshi Shimizu, Shin-Ichi Nishimura, Ken Hiramatsu, Takeo Onishi and
Tatsuro Nishiyama・・・・・・・・・・・・・・・・・・・・・・・・・p. 136
P20: Malodor emission of activated sludge from municipal wastewater treatment process
after inoculation with sludge from a slaughtering house wastewater treatment facility
Guangyu Cui, Manami Mori, Yasushi Ishiguro and Fusheng Li・・・・・・・・・・・・・・・・・・・・・p. 138
P21: Hydrological characteristics under different vegetation types in small watershed, Central
Japan
Ali Rahmat, Keigo Noda, Kengo Ito and Masateru Senge・・・・・・・・・・・・p. 140
P22: Analysis of solar irradiance fluctuations for photovoltaic (PV) module outdoor
performance testingJunfang Zhang, Kota Watanabe, Tomonao Kobayashi and Jun Yoshino
・・・・・・・・・・・・・・・・・・・・・p. 142

P23: Structural change and biomass increment of a subtropical/warm-temperate
Lucidophyllous (evergreen broad-leaved) forest over a 28-year period, central Japan
Siyu Chen, Ruoming Cao, Shogo Kato, Shinpei Yoshitake, Akira Komiyama andToshiyuki Ohtsuka・・・・・・・・・・・・・・・・・・・・・・・・・・・p. 144
P24: Leaching behaviors of arsenic during temporary storage of tunnel spoil: evaluation basedon column test
Wenjiao Li, Tsutomu Sakakibara, Atsushi Umeda, Taro Tsuge and Fusheng Li・・・・・・・・・・・・・・・・・・・・・p. 146
P25: Sorption and distribution of cesium on different additives applied to contaminated soils
Huijuan Shao and Yongfen Wei・・・・・・・・・・・・・・・・・・・・・・p. 148

-PART 1INTERNATIONAL SYMPOSIUM ON SOIL MANAGEMENTFOR SUSTAINABLE AGRICULTURE

2017
KEYNOTE SPEECHESORGANIZER:
THE UNITED GRADUATE SCHOOL OF AGRICULTURAL SCIENCE,
GIFU UNIVERSITY

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
Keynote Speech: 01

Soil Physical Rehabilitation–Artificial Macropore Installation to Restore Organic Matter in Soils○Yasushi MORI
(Graduate School of Environmental and Life Science, OKAYAMA University）
SUMMARY
Artificial macropores constructed of fibrous material were installed in degraded red-yellow soils to enhancevertical infiltration without cultivation. Macropore and control (no macropore) plots were established and bulk density,
hydraulic conductivity, plant biomass and total carbon in soil were measured. The results after one-year macropore
installation were that bulk density was lower and hydraulic conductivity was relatively higher at macropore plot thanthey are at control plot. In addition, plant biomass and Total Carbon were larger at macropore plot. There was a concernthat introduced fresh water with nutrient and oxygen would decompose organic matter. However, enhancing infiltration
along with naturally occurred nutrient would positively affect plants grow, which helps carbon storage in soils.

Introduction

So our objective of this study was to enhancing verticalSoil is the largest terrestrial carbon storage, it contains

infiltration in degraded soils using artificial macropore,carbon as much as 3 times of plant biomass and two

while evaluating whether introduced water increases /times of the atmosphere. Surface layer is the most fertile

decreases organic matter in soils.

zone which is rich in organic matter. However, this fertile

Material and Methodzone is degraded from rough land management, and also

Artificial macropore was made by creating a verticalremoved by heavy rain, which is considered as the effecthole into the soil and bamboo fiber was inserted (Fig.1

of climate change. The typical characteristics of theseright). Capillary force caused by fibrous material

degraded soils are poor infiltration. Lack of organic

introduced vertical transport, while micropore (matrix)

matter fails to create soil aggregates and surface crustenhanced horizontal flow. Because artificial macopore

tends to be formed at the surface soils.

maintains its structure and is effective prior to saturation,

Traditional countermeasure for this situation iscultivation, turn over. It makes soil layer softer,

solutes

infiltrated

more

effectively

than

empty

macropores.

agricultural jobs easier and enhances infiltration.

We installed artificial macropores to degraded clayey

However, it may also break soil aggregates and makesoils to evaluate how they affected vertical infiltration,soils drier, which would be a cause of erosion and loss oforganic matter contents and vegetation. All the weeds

organic matter.

were removed at the beginning of this experiment and

X-ray CT images of the natural soils showed that root

four repetitive plots were prepared for macropore

created macropores were predominant (Fig.1 left). The
tubular pore networks helps water and solute movement.
The flow regime was controllable by water content or the
degree of saturation(Mori et al., 2013). Our idea was tomimic this natural soil pore structure, namely creating
artificial macropore to enhance infiltration and increaseorganic matter in soils. Our first trial has successfullyincreased organic matter in soils (Mori et al., 2014).
However, artificial macropores introduced also fresh air,water and nutrients. In that case, there would be aconcern that these fresh solutes and air decompose“pre-existed” organic matter.

Fig.1 Macropore structure in natural soil (left)and design of artificial macropore (right).

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
Keynote Speech: 01

management with/without nutrients and no macropores
management with/without nutrients. Nutrients would bedelivered by macropores, which would stimulate
biological activity.

Results and Discussions
One-year after installation of artificial macropores, soils
were sampled from four repetitive plots. Bulk density
was lower at macropore plot and there was not
significant difference at nutrient addition. Low bulk
density would be caused by plant shooting. And this low
bulk

densitycausedrelatively

higherhydraulicconductivity at macropore plot. Hydraulic conductivity
was relatively higher at macropore plot, while there isnot significant difference at nutrient addition (Fig.2).
Artificial macropore enhanced vertical infiltration which
introduced organic matter and nutrients into soil. Thissoil environment would be favorable for plant shooting
and the plant shooting may cause positive effect forporous structure construction and well-drained soil layer.
Total carbon was relatively higher at macropore plot,
and also there was not significant difference at nutrient
addition (Fig.3).

plot, and nutrient addition strongly affected the plantbiomass weight (Fig.4). Plant diversity was strongly
affected by nutrient addition.

Conclusions
In the course of experiments, following conclusions
were obtained.
(1)Bulk density was lower and hydraulic conductivity
was relatively higher at macropore plot than they are atcontrol plot.
(2)Plant biomass and diversity was larger at macropore

Plant biomass was significantly higher at macropore

平均透水係数 (cm/s)
Saturated hydraulicconductivity (cms-1)

Fig. 4 Plant biomass weight and weed flora
diversity

M区
Macropore

X区
Control

肥料区
No水区
nutrient Nutrinet

肥料区
No水区
nutrient Nutrinet

plot, and Total Carbon was higher at macropore plot thanthey are at control plot.
There was a concern that infiltrated fresh soil waterwith nutrient and oxygen would decompose organic

1.0E+00

matter. However, the total carbon did not at least
decrease at the macropore plot, moreover, recovered

1.0E-01

vegetation increased plant biomass. Therefore enhancing
infiltration along with naturally occurred nutrient would
1.0E-02

positively affect plants grow, which helps carbon storage
in soils. Artificial macropore enhanced water andnutrient infiltration with minimal soil disturbance, this1.0E-03

Fig.2 Hydraulic conductivity
artificial macropore installation

process also protected the organic matter in soils.
after

1-year

Acknowledgement
This work was partially supported by The Japan Society
for the Promotion of Science, NEXT program (GS021)(2011-2014), Grant-in-Aid for Scientific Research
KIBAN(B) 26292127 (2014-2016) and KIBAN(A)
17H01496 (2017-2021).

References

Fig.3 Total Cabon measurement after 1-year
artificial macropore installation.

Mori, Y., A. Suetsugu, Y. Matsumoto, A. Fujihara andK.Suyama (2013) Enhancing bioremediation ofoil-contaminated soils by controlling nutrient
dispersion using dual characteristics of soil pore
structure, Ecological Engineering, 51(2), 237-243.
Mori, Y., A. Fujihara, and K.Yamagishi (2014) Installing
artificial macropores in degraded soils to enhancevertical infiltration and increase soil carbon content,
Progress in Earth and Planetary Science 1: 30.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
Keynote Speech: 02

Development of Soil Property Sensors Using Heat Transfer○Yuki KOJIMA, Yuta NAKANO(Faculty of Engineering, Gifu University）
SUMMARY
Monitoring soil properties is important for precision agriculture, environmental preservation, and disasterprevention. A combination of utilizing heat transfer and latest technologies enables measuring soil properties whichhave been difficult to measure or improving currently available sensors greatly. Two sensors recently developed using
heat transfer, i.e., dual probe heat pulse matric potential sensor and heating time domain reflectometry sensor for soil ice
content determination, were introduced. The performance of these sensors were evaluated and benefits of these sensors
were discussed. Both sensor showed high accuracy (10% for DPHP matric potential sensor and 0.01 m3 m-3 for heating
TDR method) and some advantages over the other sensors. Those new sensors can contribute in many studies
associated with soils.

Introduction

same with that of the porous medium in equilibrium.

Monitoring soil properties (e.g., soil moisture, soil

Thus, the ψ of soil can be determined by knowing thedensity, etc.) is important for precision agriculture,

relationship between the thermal properties and ψ of theenvironmental preservation, and disaster prevention.

porous medium. Compared to the previous ψ sensor

Various sensors have been developed in order to measureusing “single” probe heat pulse technique (Reece, 1996),

the soil properties. In this report, two sensors recently

DPHP sensor can use two thermal properties while thedeveloped using heat transfer are introduced. The firstsingle probe uses only λ. The relationship between thesensor measures soil matric potential (ψ) by using athermal properties and ψ of the porous medium wereporous medium and dual probe heat pulse (DPHP)

determined by comparing C and λ measured by thetechnique. The ψ is an important indicator of soil dryness

developed sensor to ψ measured with commercialized

for plant growth. The developed sensor can be cheapersensor MPS-6 (METER Group Inc., Pullman, USA)and has a better performance than currently available

inserted in a soil under natural drying condition. In

sensors. The second sensor is a heating time domain

addition, temperature dependency of sensor outputs wasreflectometry (TDR) method to measure ice content inevaluated.

frozen soils (θI). Quantification of θI is important forii) Measuring soil ice content by heating TDR

understanding winter soil hydrology and frost heaving,

The schematic of the sensor is shown in Fig.1(b). The

but it has been difficult, in particular, at temperature

center stainless tube contains a heater wire and the others

range between ‒5°C and 0°C. The new sensor enables
measuring θI at this temperature range.

(a) Matric potential sensor using DPHP

Materials and Methodsi) Matric potential sensor using DPHP
A schematic and photo of the sensor are shown in
Fig.1(a). The sensor consists of a porous medium andtwo stainless tubes. One of the tube contains a heaterwire and the other contains a thermistor. A 15-second
heat pulse is generated by the heater, and temperature

Sintered kaolinite(b) Heating TDR method
90 mm

1.5 mmchange in the other tube 8-mm away from the heater isrecorded. Volumetric heat capacity (C) and thermal
conductivity (λ) of the porous medium were determinedby analyzing the temperature change. The ψ of soil is

Stainless tube

Epoxy box
Coaxial cable

Resistance heater
6 mm

Thermocouple

Thermocouples& heater wires

Fig. 1 Schematic of the developed sensors.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
Keynote Speech: 02

contains thermocouples. In frozen soils, not all of pore(a) C vs ψm(b) λ vs ψm

water freeze, i.e., some water remain in liquid form evenat temperatures below 0°C. The heating TDR method
first measures the liquid water content in frozen soil (θL),
and then melts the frozen soil by heating. After melting
the soil around the TDR probe, it measures total watercontent (θT). The θI can be determined by subtracting theθL from θT. Accuracies of θL, θT, and θI determinations
were evaluated by comparing them to those determinedby mass and a model.

Fig. 2 Relationship between thermal properties, (a)volumetric heat capacity and (b) thermal
conductivity, and matric potential of porous media.

Results and Discussioni) Matric potential sensor using DPHP
Obtained relationships between the thermal propertiesand ψ of porous media are shown in Fig. 2. The C and λof the porous media measured with the DPHP method

Line forEstimated θLwere converted to their corresponding logarithmic valueof ψ by means of two intersecting linear functions. The(a) Liquid water content& Total water content(b) Ice content

use of λ to determine ψ was found to yield more accurate
results than the use of C, and the accuracy of theFig. 3 Accuracy evaluation of determining liquid

determined ψ value was approximately 10%. The DPHP

water content, total water content, and ice content

ψ sensor was found to be less sensitive to temperature

determined with heating TDR.

than existing commercialized ψ sensors. The temperaturedependency evaluation presented that C showed only
<7% change by temperature variation while the othersensors showed 40-80% change in their outputs bytemperature variation (data not shown). Therefore, thedeveloped DPHP ψ sensor was found useful because it
can use either C or λ, depending on the magnitude of soil
temperature variation and required accuracy.
ii) Measuring soil ice content by heating TDR
Figure 3 shows the accuracy evaluation of heating TDR
method to determine θL, θT, and θI. The maximum errors
by the heating TDR measurement were 0.06 m3 m-3, 0.05
m3 m-3, and 0.01 m3 m-3 for θL, θT, and θI, respectively.
These accuracies were similar to the TDR measurements
accuracy (±0.05 m3 m-3). Errors in θL and θT canceled out
each other so that the error in θI became quite small. The
accuracy of θI determination with heating TDR method
was much smaller than that for other methods, e.g., Tianet al. (2015) reported that the error in θI determination
with thermo-TDR sensor was at most 0.20 m3 m-3. This
indicates that the heating TDR method is beneficial formany studies required accurate measurement of θI. The
only disadvantage of the heating TDR method was that
repeating measurements caused degradation of accuracy.
Vapor transfer from the heater toward outside of a TDR
sampling volume can occur due to the cycle of heating,and it results that water content around the sensor will

differ from those in natural conditions. In order to lessen
the influence of vapor transfer, large measurement
interval, e.g. >1day, may be preferred.

Conclusions
A combination of utilizing heat transfer and latest
technologies enables measuring soil properties which has
been difficult to measure or improving currently
available sensors greatly. In this study, the recently
developed two sensors using heat transfer, i.e., DPHP ψ
sensor and heating TDR method for θI determination,
were reported. The performance of these sensors were
presented and benefit of these sensors were discussed.
Both sensor showed high accuracy and some advantages
over the other sensors. Those new sensors can contributein many studies associated with soils.

Acknowledgement
This work was partly supported by grants from a projectof the NARO Bio-oriented Technology Research
Advancement Institution (Integration Research for
Agriculture and Interdisciplinary Fields).

Reference
Reece CF (1996) Evaluation of a line heat dissipation
sensor for measuring soil matric potential. Soil Sci.
Soc. Am. J.,60:1022-1028.
Tian Z, Heitman JL, Horton R., and Ren T (2015)
Determining soil ice content during freezing andthawing with thermo-time domain reflectometry.
Vadose Zone J.,doi:10.2136/vzj2014.12.0179.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
Keynote Speech: 03

Stability of Soil Organic Matter in Soil Management for Sustainable Agriculture○Akira WATANABE(Graduate School of Bioagricultural Sciences, Nagoya University）
SUMMARY
The stability of soil organic matter (SOM), which is required for maintaining soil quality suitable for agriculture, wasevaluated for soil managements that can increase SOM level, including continuous application of cattle manure (CM) toan upland field, long-term use as a rice paddy, and biochar application. 13C nuclear magnetic resonance (NMR) analysis
and physical fractionation indicated that none of mechanisms that stabilize SOM, i.e., structural alterations, occlusion insoil aggregates, and adsorption to clay minerals, preserved SOM derived from CM. 14C concentration, δ15N, 13C NMR
spectra, and C decomposition rate in a laboratory incubation suggested that the larger SOM content in the soils with alonger history of use as a rice paddy was due mainly to an enhancement in the accumulation of recently generated SOM
rather than the stable accumulation of humus over the years. The repetitive bamboo char application with/without CM
application to upland fields for 2–5 crop seasons did not significantly change CO2 flux. Soil C analysis confirmed nosignificant loss of char C. The effects of char application on N2O and CH4 fluxes and crop yield were not definitive.

Introduction
Maintenance or improvement of the level of SOM isgreenhouse gas (GHG) flux from soil, soil C content, andcrop yield were investigated over five crop seasons.

essential for sustainable agriculture and global C balance.

Materials and Methods

However, organic matter supplied to soil is lost within a

1. Accumulation of CM derived SOC in an upland fieldshort period, if any of mechanisms that stabilize SOM,

Plow layer soil samples collected from two plots ini.e., structural alterations, occlusion in soil aggregates,

Nagoya University Farm during a 28-y period ofand adsorption to clay minerals, does not function. To

continuous CM application at 40 t ha-1 y-1 (CM40 plot)

evaluate the progression of the stabilization of organic

or at 400/200 (0–19 y/19–28 y) t ha-1 y-1 (CM400 plot),fertilizer derived SOM in upland field, time-dependent

respectively, were used. 13C NMR spectra of the soilchanges in chemical structure and distribution during

samples were measured, and SOC distribution into fourphysical fractionation of soil organic C (SOC) in thefractions of free SOC (specific gravity (s.g.) of <1.6 gcontinuous CM application plots were examined. It is

cm-3; fSOC), free SOC occluded in aggregates (s.g. <1.6

generally recognized that SOM content is larger in riceg cm-3 fraction after shaking with glass beads; oSOC),

paddy fields compared to upland fields. However, it does

and SOC bound weakly (s.g. 1.6–2.0 g cm-3; wSOC) andnot guarantee the stable accumulation of SOM in paddy

strongly to soil minerals (s.g. >2.0 g cm-3; sSOC), duringsoils, because SOM decomposition can be suppressed

the successive heavy liquid separation was determined.

only by flooding. To find mechanism responsible for the

2. Accumulation of SOM in a rice paddy

enhanced accumulation of SOM in rice paddy, the plow

The soil samples used were collected in 16 fields

layer soils that have been used for irrigated ricewith estimated period of use as a rice paddy for 5–2000

production for different years were analyzed. We focused

years3) in the Hangzhou Bay, China. Soil samples were

silt/clay-humin, the acid- and alkali-insoluble fraction of

separated into sand and silt/clay on a 53-μm mesh sieve.

SOM bound to soil minerals, as a representative

After free SOM and soluble humus in silt/clay wererelatively stable SOM pool. An application of plantremoved, 14C concentration, δ15N, and 13C NMR spectra

residues after charring (structural modification) is a wayof the remaining SOM, humin, were measured.

to accumulate C in soil for a long period. However, field

Bioavailability of silt/clay-humin was evaluated frominvestigations of the effects of continuous char

CO2 production rate in a 4-month laboratory incubation.

application have been few. In the present study, the

3. GHG fluxes and C accumulation in char applied soils

effects of repetitive bamboo char application on

The following treatment plots were prepared in two

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
Keynote Speech: 03

upland fields in triplicate: Chemical fertilizer (CF) plot

to the accumulation of soil organic N derived from CF−1(Control plot); CM (10 t ha ) and CF applied plot (CMapplication or recent N2 fixation. 13C NMR analysis andplot); and bamboo char (20 t ha−1), CM, and CF applied

the incubation experiment showed that there were noplot (Char/CM plot). Crop rotation was: broccoli, sweet

relationships between C structures or decomposability

potatoes, broccoli, kabocha squash, and bok choy. Charand period of use as a rice paddy.

and CF applied plot (Char plot) was installed in one of

3. Effect of char application on GHG fluxes and SOC

two fields after the 3rd crop. CO2, CH4, and N2O fluxes

The application of CM or Char and CM enhanced

were measured periodically using the static chamber

CO2 flux (P < 0.05), except for winter season, while total

method. Plow layer soils were collected after each

CO2 flux was similar between the CM and Char/CM

harvest and total C content was determined. The freshplots and between the Char and Control plots. The

weight of the edible part was also measured at harvest.

differences in N2O flux between the Char/CM and CM

Results and Discussion

plots and between the Char and Control plots were also

1. Stability of CM derived SOC in an upland field

insignificant in most cases. CH4 flux was negligibly

13

The C NMR spectra of the CM40 and CM400 plot

small in all cases. The soil C content in the Char/CM andsoils did not show distinct variations with time,Char plots increased stepwise and no significant

suggesting that neither selective preservation of any C

mineralization over the five or two crop seasons wasfunctional group nor structural changes occured for thedetected in both fields. Although the yield of broccoli in

CM derived SOC. In the CM40 plot, fSOC and oSOC

the Char/CM plots was higher than that in the other plots

increased during the first 5 years, while the amounts ofat one of two fields, in general, the char application had

wSOC and sSOC did not vary. fSOC and oSOC also

no effect on crop yield.

increased in the CM400 plot. Those SOC pools started toConclusions

decrease in year 9 or 13, while wSOC increased.

Irrespective of the rate of application, almost CM derived

However, after the rate of CM application was reduced,

SOC was not stabilized in an upland field. A

wSOC decreased as well as fSOC. The sSOC showedchronological change that indicates an increase in the

only a slight increase since year 26. As such, physical or

stability of SOM was also not found in paddy soils.

chemical stabilization of CM derived SOC has not

Therefore,

advanced.

management that allows anaerobic conditions should be

2. Stability of SOM accumulated in rice paddy

organic

matterapplication

or

soil

continued to maintain SOM level. It is suggested that the

The amounts of organic C and N in the bulk soil,

simultaneous application of char and CM, or othersilt/clay, and silt/clay-humin tended to increase withorganic fertilizer, is an effective method to theincreasing estimated period of use as a rice paddy. If land

combination of a long-term improvement of soil physicaluse as a rice paddy preserves older C, the14Cand chemical properties and a short-term nutrient supply

concentration would be smaller as a function of the timeto crop, without an adverse effect on global warming.

of rice cultivation. However, the result was opposite,

Acknowledgements

1a). δ15N was lower in a soil with a longer history as a

These researches were supported by Grant-in-Aid for
Scientific Research from the JSPS (Nos. 23310005 and
16H04890) and the Strategic Japanese-Chinese
Cooperative Program on “Climate Change”.

rice paddy and a higher N content (Fig. 1b), possibly due

Referencessuggesting that the larger SOC content is the result of an

16

(a)

12

8

4

y = 0.00161e0.0645x
r² = 0.862

0
70

80

90

100

14C (pMC)

110

120

Amount of silt/clay-humin N (g kg-1 dry soil)

Amount of silt/clay-humin C (g kg-1 dry soil)

enhanced accumulation of recently generated SOM (Fig.

2.5

(b)

2.0
1.5
1.0

y = -0.259x + 2.20
r² = 0.872

0.5
0.0
0

1

2

3
4
δ15N (‰)

5

6

Fig. 1 Relationships between 14C concentration and amountof silt/clay-humin C (a) and between δ15N and amount ofsilt/clay-humin N (b) in the Hangzhou Bay paddy soils.

1) Nakahara S, Zou P, Ando H, Fu J, Cao Z, Nakamura T,
Sugiura Y, Watanabe A (2016) Stability of soil organiccarbon accumulated under long-term use as rice paddy.
J. Geophys. Res.: Biogeosciences,121:67–77.
2) Watanabe A, Ikeya K, Kanazaki Y, Makabe S, Sugiura
Y, Shibata A (2014) Five crop seasons’ records ofgreenhouse gas fluxes from upland fields withrepetitive applications of biochar and cattle manure. J.
Environ. Manage.,144:168–175.
3) Cheng YQ, Yang LZ, Cao ZH, Ci E, Yin S (2009)
Chronosequential changes of selected pedogenic
properties in paddy soils as compared with non-paddy
soils. Geoderma,151:31–41.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
Keynote Speech: 04

Relationship between vegetation cover and sediment transport activities
on mountain hillslopes○Fumitoshi IMAIZUMI(Faculty of Agriculture, Shizuoka University）
SUMMARY
In mountain areas, sediment is easily transported toward downslope affected by large gravitational force acting on thesediment. There are many kinds of sediment transport processes, including soil creep, rockfall, dry ravel, surface
erosion, and landslide. Soil creep, rockfall and dry ravel occurs occur during heavy rainfall events. In cold regions,freezing-thawing activities of groundwater also triggers those sediment transport processes. Surface erosion is causedby ground surface flow, while landslides are caused by increasing in the pore water pressure in the ground. Interceptionof rainfall by tree canopies reduce amount of rainfall reaching ground, potentially reduce sediment transport rate by soil
creep and dry ravel. Tree stems can trap rockfall and dry ravels coming from upper slopes. Because damage of groundsurface by raindrop can be reduced by understory, understory is also important for the soil conservation. Tree roots canreinforce soil strength, resulting in prevention of shallow landslides.

Introductionof which driving force is also gravity acting on the

In mountain areas, sediment is easily transported toward

sediment, are transport of individual sediment particles

downslope affected by large gravitational force acting on

by bounding, sliding, and rolling. Dry ravel occurs on

the sediment. Loss of surficial soil on mountainhillslopes just steeper than angle of repose, while rockfall

hillslopes affects growth of trees and crops. Transport ofoccurs on much steeper slopes. Rainfall,large volume of sediment sometimes causes severe

earthquake, freezing-thawing of ground water, andsediment disasters. In mountain areas, thus, soil

animals are triggering factors of the dry ravel andconservation is needed for protection of ecosystem androckfall.

sustainable human activity.

wind,

Surface erosion is caused by entrainment of ground

There are many types of sediment transportsurface sediment by ground surface water (Fig. 1).

processes in mountain areas. Factors triggering sediment

Disturbance of ground surface by the impact of raindroptransport are different among types. Effects of vegetation

facilitates the surface erosion. Landslide is movement ofon the conservation of sediment are also different among

thick soil mass (thickness > 1 m) above sliding surface insediment transport types. In this study, sedimenttransport in mountain hillslopes are summarized. In
addition, relationship between vegetation cover andsediment transport activities are discussed.

Types of Sediment Transport
There are many kinds of sediment transport processes,
including soil creep, rockfall, dry ravel, surface erosion(surface wash, sheet erosion), and landslide. Soil creep ismovement of soil mass with low velocity (millimeter todozens of centimeter per year). Because gravitational
force acting on soil mass is the most important driving
force for the soil creep, the soil creep is generally activeon the steep hillslopes (Imaizumi et al., 2015). Soil creep
is mainly triggered by water supply during rainfall events

Fig.1 Severe surface erosion in artificial forest

and freezing-thawing in winter. Rockfall and dry ravel,(Shizuoka prefecture, Japan)

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
Keynote Speech: 04

In some Japanese artificial forests with completely
closed crown only have poor understory because of dark
environment. In such forests, severe surface erosion canbe seen, because protection of the ground surface byunderstory is limited (Fig. 1).
Occurrence of landslides are also affected by thevegetation. Root of trees increases resistance of the soil
against sliding, preventing occurrence of landslides(Imaizumi et al., 2008; Imaizumi and Sidle, 2012). In
other words, removal of forest decreases soil strength,
resulting in increases in the landslide frequency. Because
root depth is generally shallower than 1 m, vegetation
Fig.2 Photograph of shallow landslides (Naraprefecture, Japan)

cannot contribute prevention of landslides with deep
sliding surface (called deep seated landslides).

Conclusion
Relationship between vegetation and sediment transport

the ground (Fig. 2). In case that the sliding surface
locates in the bedrock, thickness of the landslide
sometimes exceeds 50 m. Landslide is known as ahazardous phenomenon because of its large volume.
Many of landslides have been triggered by increases in
the pore water pressure in the ground during heavy
rainfall events. During earthquakes, increases in theacceleration along slope direction acting on the soil mass
also triggers landslides.

Relationship between vegetation cover andsediment transport
Rainfall is one of the important triggering factor of thesediment transport. Because soil creep and surface
erosion are affected by amount of rainfall reaching
ground surface, crown interception potentially reduce
sediment transport rate by them. In cold regions,frequency of soil creep, dry ravel, and rockfall is also
lowered by the tree crown, because tree crown reduce
daily changes of the ground temperature which cause
freezing-thawing of groundwater (Ueno et al., 2015).
Tree stems can trap sediments coming from upper slopes
as rockfall and dry ravel.
Grass cover also reduce surface erosion, because
grasses prevent raindrop directly hitting ground surface.

activity varies affected by types of sediment transport
processes. Because the type of dominating sedimenttransport processes changes by topography and climate,role of vegetation on the prevention of sedimenttransport is different among regions. Thus, when we
consider conservation of soil on mountain hillslopes, weneed to investigate dominating sediment transport type atfirst. Then, management of vegetation might be available
as a method of soil conservation.

Reference
Imaizumi F, Sidle RC, Togari-Ohta A, Shimamura M(2015) Temporal and spatial variation of infilling
processes in a landslide scar in a steep mountainous
region, Japan, Earth Surface Processes andLandforms: 40, 642-653.
Ueno K, Kurobe K, Imaizumi F, Nishii R (2015) Effects
of deforestation and weather on diurnal frost heaveprocesses on the steep mountain slopes in south
central Japan, Earth Surface Processes and Landforms,
40: 2013–2025.
Imaizumi F, Sidle RC, Kamei R (2008) Effects of forest
harvesting on the occurrence of landslides and debris
flows in steep terrain of central Japan, Earth Surface
Processes and Landforms, 33: 827-840.
Imaizumi F, Sidle RC (2012) Effect of forest harvestingon hydrogeomorphic processes in steep terrain ofcentral Japan, Geomorphology, 169: 109-122.

-PART 1INTERNATIONAL SYMPOSIUM ON SOIL MANAGEMENTFOR SUSTAINABLE AGRICULTURE

2017
GUESTS/ALUMNI PRESENTATIONSORGANIZER:
THE UNITED GRADUATE SCHOOL OF AGRICULTURAL SCIENCE,
GIFU UNIVERSITY

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 1 - General Issue and Solution -: 01

Analysis study of landslide induced by earthqueke in Tandikat Partamuan, Padang Pariaman
District, West Sumatra, Indonesia○ Isril BERD , Amrizal SAIDI, Skunda DILIAROSTA
1(1Faculty of Agriculture Technology, Andalas University,
2
Faculty of Agriculture, Andalas University)

SummaryThis study was conducted to analysis landslide induced by earthquake in Tandikat Partamuan, Padang Pariaman District,
West Sumatra, Indonesia. This study was conducted using survey method, which was done by field observing on
pumiceous tuff phenomenon affected by water flow in the study area. Soil and land characteristic data were used in thisstudy. Soil physical characteristic included soil texture (pipete method) and structure, bulk density (gravimetric method),permeability (Debodt method), solum depth (direct measure), and soil organic matter (walkley and Black method).
Land characteristic analysis were conducted by observing in the field and also analysing topographic map from google
earth programme, and land use analysis was conducted by using land use map. Analysis data of soil and landcharacteristic were used for landslide grade criterium from Zuidam (1979); Daekombe and Gardiner (1983); Cooke andDoorkamp (1994). Based on our field study showed that this location has high susceptibility for happening landslide
process. The climate of the location was wet tropical season which is caracteritized by more than 4000 mm rainfall per
years and evenly distributed whole years. The rolling and steep slope (> 45 % slope) hillocky and strongly dissected of
the study area were observed in the landslide site. Land use type also promotes landslide processes because coconut
trees and mixed garden growing in steep slope. The result of soil and land characteristic analysis showed that soil
characteristic of landslide has interval value 13 and land characteristic of landslide has interval value 20. By summing
the value of soil characteristics and land characteristics, the total 33. This grade showed that the risk level in landslidearea was quite high. Thus this study area have high interval value of landslide damage.

Introduction
Spectacular earthquake (7.9 SR) which happened on
Wednesday 30 September 2010 had epicentrum in Indian
Ocean which about 57 km Southwest of Pariaman within
71 km depth. This earthquake caused many victim ofpeople and destroyed houses, schools, and irrigation
channel in Padang Pariaman, Agam, Pesisir Selatan, andPasaman District and Padang City. According to Efendi(2009) the earthquake had killed 1000 people and haddamaged as well many houses, agricultural land such as
sawah, dry-lands, and about 650 animals.
According to the head of Agriculture office of West
Sumatra (Singgalang 14 October 2009), the impact ofearthquake on agricultural land had ± 88 damage
irrigation channel, 10592 ha of drained sawahs, half ofthe sawahs had found in Padang Pariaman District( approximately 5747 ha). The damaged area was foundin Mentawai district, Padang City, and few area inAgam district. The problem of the agricultural land will
decrease community income in west Sumatra and inturn will decrease food security.
The destruction of economic and irrigation facilities,
distribution of agriculture facilities had broken
community economy for many years in the future. Thus,
attention of government was needed to rehabilitate
earthquake impact for all of aspects, mainly to improve
community facilities such as irrigation facility for
agriculture land, and also rehabilitate house, office andschool damage. However, the improvement will needhigh cost. Besides that, earthquake also damaged large
areas in Lubuk Laweh, Cumanak and Kapalo Koto.
Approximately, there were a lot of sawahs and garden,
300 people and few villages had buried in the threevillages. Amount of the soil having become landslidewere estimated about 1,000,000 m3 of buried materials.

High potential of landslide event in Padang Pariaman
District, based on the result of a study from JapaneseInternational Cooperation Agency (JICA, 2009) showedthat there are 126 point of landslide potential event onsomelocations. Ueno (2009) ( JICA Workshop)
stated that high landslide potential was found in
Maninjau Caldera. They are parent material which
derived from pumiceous tuff andesite and hornblende
hypersthene puceous tuff of Maninjau caldera at 500 m
above sea level.
Landslide impact on agricultural land will involve
many factors. Heavy rainfall (> 4000 mm per years) in
the location will promote landslide event. It is caused bysoil porosity which is not able to infiltrate water into soil
profile and in turn, it will promote runoff and erosion.
The problem will decrease landuse cover on the soil.
Furthermore, agricultural land are un-functional toproduce staple food crop like rice and corn.
Based on geologic map of Padang Sheet (Kastowo,
Leo, Gafour, and Amin (1996) the landslide area,
consist of pumiceous tuff from Maninjau Caldera. This
material is slightly consolidated, soft, and light. Thus,
the area will be easy to cause landslide again in the
future, if the area cannot be protected. For getting themethod to prevent landslide event will be needed
collaborative research in the landslide susceptible area.
Based on the above description, landslide
phenomenon possibly happen for future, the research
will be needed to explain why pumiceous tuff (Qpt) andhorblende hephersthene pumiceous tuff (Qhpt) aresusceptible tolandslide in Tandikek Partamuan,
Padang Pariman District, West Sumatra.
The research is mainly to study pumiceous tuff
phenomenon to promote landslide event in Tandikek.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 1 - General Issue and Solution -: 01

And then the research will be conducted to improve soil
physical condition in order to get method for decreasing
the susceptibility of pumiceous tuff on landslide event.

Methods
The research was conducted at Tandikek, Partamuan,
Padang Pariman District. Soil analysis was conducted at
Soil Science Department Laboratory Agriculture Faculty
Andalas University. Water analysis was conducted in
UPTD Healthy Laboratory Agency. West Sumatra.
The research was conducted by using survey method bytravelling of all over the study area and by observing
pumiceous tuff phenomenon that is affected by waterflow and then land characteristic like topographic, landuse, and exposure of landslide event in the field. For
observing soil characteristics use soil physical data fromprevious research (Yunita, 2004) were used. Soil analysis
parameters consist of texture (pippete and filter method),
bulk density (gravimetric method), structure (fieldobservation), organic matter content (Walkley and Blackmethod), and soil permeability rate (Deboodt and Gabrielmethod). Land characteristic analysis was conducted byobserving in the field and also by using topographic map
derived from google earth programme, and land use
analysis was conducted by using landuse map. Analysis
of soil and land characteristics was evaluated by using
for landslide grade criterium from Zuidam (1979);
Daekombe and Gardiner (1983); Cooke and Doorkamp(1994) are presented in Table 1 and Table 2 and Table 3.
The analysis of landslide event was done in the field byusing different shooting camera for two time camera.

Figure 1 Location of the Study Area

Table 1 Criterium of soil characteristic landslide induced factors
No

Soil Characteristic
Description
Class code
< 25 cm
Very shallow
1
25- 60 cm
Shallow
2
1
Solum Depth
60- 90 cm
Medium3> 90 cm
Deep
4
S
Very coarse
1
LS,SiS,CS
Coarse2
2
Texture
L,SL,SiL,Si
Medium3
C,SiC,SC
Fine
4
Crumb
Very good
1
GranulerGood
2
3
Structure
Blocky, Platty, prismatic
Moderate
3Single grain, massive
Bad4> 5.01 %Very High1
3.01 - 5.0 %High
2
4
C-Organic
2.01- 3.0 %Moderate
3< 2.0 %
Low4
< 0.75 g/cm3
Very Good
10.75 - 1.25 g/cm3
Good
2
5
Bulk Density
1.25 - 1.50 g/cm3
Medium3> 1.50 g/cm3
Bad
4> 12.5 cm/hour
Very Fast
1
6.25-12.5 cm/hour
Fast2
6Permeability
2.0-6.25 cm/hour
Medium3< 2.0 cm/hourSlow
4
Source : Zuidam (1979): Daekombe dan Gardiner (1983); Cooke and Doorkamp (1994).
Where ; S = Sand, LS = Loamy Sand, SiS = Pasir berdebu, CS = Sandy Clay, L =Loam: SL = Sandy Loam, SiL = Silty Loam, Si =Silt, C = Clay, SC = Sandy Clay, SiC= Silty Clay. :Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 1 - General Issue and Solution -: 01
Table 2 Criterium of land characteristic landslide induced factors
No
Land characteristics
Description
Class code
0- 13 %
Smooth to undulating1
14-25 %
Sloping2
Slope1
gradien
26 - 40 %Slightly steep3> 40 %
Steep4< 15 mShorth1Medium2
Length of 15-50 m
2slope
50 - 250 m
Length3> 250 mVery length4< 3 % of area
Nothing, few
1
3-15 %
Medium2
Stone
3
exposure15-90 %
Much3
> 90 %
Very Much
4> 500 mDeep
1250-500 m
Medium2
Watertabl
4
e depth
100 -250 m
Slingthly shallow
3< 100 mShallow4
Ht (forest)
Good
1
Sm, Kc (Bush, Mixed Garden
Slightly Good2
5
LanduseS, Ut (sawahs, Upland)
Moderate3
P (resetlement)
Bad4> 0-30 mm /monthlow
130-60 mm/monthMedium2
6
Rainfall60- 90 mm/monthHigh3> 90 mm/month
Very High
4
Sources : Zuidam (1979): Daekombe dan Gardiner (1983); Cooke dan Doorkamp (1994).
Where: Ht = Forest; Sm = Bush, Kc = Mixed Garden; S = Sawahs; Ut = Upland; P = Resettlement

Class
I
II
III
IV
V
VI

Table 3 Grade Interval of landslide damage
Inteval Class
Criterium of landslide damage< 18
Very low
19-25
Low
26-32
Medium33-39
Slightly high
40-46
High
>47
Very High
Source : Zuidam (1979)

Results and Discussion

Water balance were computed by rainfall amount (mm)Etp month (mm) = + (water surplus) and - (water deficit).

1) Description of study area
Geographically, study site is located between 0o 28° to
0o 33° S and 100° 09° to 100° 18o E. The administrationof study site involves Tandikek, Partamuan, in Padang
Pariaman District, West Sumatra Province. The area site
is around 59 km from Padang City and 19 km from
Pariaman city. Exactly, study site is presented in Figure 1.
Tandikek study site is in western volcanic lower slopeof Mount Tandikek and a part of Mangau watershed. The
study area are passed by Mangau river to west direction itreaches Indian Ocean. When earthquake event, materialof landslide had covered Mangau River, so that the flowof water of Mangau stopped for 4 hours.

The study areas have rainfall approximately 4322 mm
per years and the distribution of rainfall even for every
years are ranging 171 mm - 603 mm for every month.
The condition does not limit crop growth, even it canhappen leaching nutrient. Based on monthly rainfall andyearly data, the study area could be classified as A type
(Oldeman, Irsal Las, and Darwis (1979), A type (Smith
and Fergusson, 1957) and Af type (Koppen method).

ClimateThe Climate of the study area is wet tropical rain, it
contributes on the landslide event for agricultural andresettlement land. The factors of climate affect thelandslide mostly amount of rainfall, rainy day, andrainfall intensity. Average temperature, relativity
humidity, wind speed, solar radiation data were needed tocompute Penman evapotranspiration in the study area.

Average temperature is ranging between 24.0-26.4 oC,
Maximum temperature is ranging between 30.9 to 31.8
OC, and minimum temperature is ranging between 21.1 to22.9 oC. Realtive humidity is ranging between 82-89 %.
Solar radiation is ranging between 8.1 to 69%. Wind
speed is ranging between 0.3-0.7 m/second. Air pressure
is ranging between 990.7 to 1002.6 mile bar anddirection of wind is Northwest.
Water balance of the study area reflected to differ
amount of water intake and outtake in hydrologic
processes. The value of water balance can give thereflection about fluctuation of water in the watershed;water reservoir, water will be infiltrated into soil, andsome is lost by runoff. Evapotranspiration value can beProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 1 - General Issue and Solution -: 01

Rainfall and Etp
PenmanFigure 2. Water balace 0f Tandikek
800
600
400
200
0
0

2

4

6

8

10

12

14

Month
Rainfall

EtP Penman

Figure 2 Evapotranspiration and water balance in Tandikek study area
gotten by using Cropwat program from AGLW/FAO
method. The result of Etp Penman computation andwater balance of the study area will be presented in
Figure 2. Figure 2 presented that the study area do nothave dry months in a year, but it usually has water
surplus along the years. It promotes to possibility
landslide event in the study area.
Geology and parent material of soil
Based on geology map of Padang quadrangle Sumatra(Kastowo, Leo, Gafoer dan Amin (1996) the most parent
material of soil in the study area consist of hornblende
hypersthene pumiceous tuff (Qhpt) and pumiceous tuff
and andesite (basalt) (Qpt).. Hornblende hypersthene
pumiceous tuff (Qhpt) consists of entirely of pumiceous
lapili, commonly ranging from 2 to 10 cm in diameter,
which content 3-10 % hornblende, hypersthene and biotit,
slightly consolidated. Pumiceous tuff and andesite(basalt) Qpt) consist of glass shard and 5 to 50%
pumiceous fragments 1-20cm in diameter, slightly
consolidated. There are some volcanic materials derived
from the eruption of Maninjau caldera.
Geomorphology and landform
The geomorphology of the study area consists of
volcanic plain and lower slope of volcanic mountain.
Volcanic plain consists of the area having slope gradient
ranging between 0 to 8 % and sometime are steep landsuch as in the slightly upper Mangau River. Volcanic
lower and midle slopes have slope gradient ranging
between 8-45%. Especially, in the Tandikek area, theslope gradient is ranging between 16-45%, but sometime,steeper (>45%). Besides that, we found river valley andriverine flood plain in the down of the river which
enlarge to the right and the left of the river. In the study
area also found hilly and hillocky landform that we saw
near Lubuk Laweh, Cumanak, and Kapalo Koto villages.
They were called bukit gunung tigo, bukit Cumanak, andBukit lubuk laweh. The hilly and hillocky landformhappened due to erosion, because the parent materials areslightly consolidated but they have steeper slope (>45 %). They are easy and more susceptible of landslidedisaster event.

Vegetation and land use
The study area used to have coconut garden, and mixed
garden which were grown by pinang, coconut, durians,
and others, then secondary forest was found on the top of
hilly and hillocky areas. In the river valley, riverine flood
plain and the volcanic plain were found sawahs,
sometimes coconut tree, and resettlement.
Land Unit and Soil Type
Based on Land unit map of Padang quadrangle from Soil
Research Centre and Agroclimate (1990) the study area
has four group of land unit that consists of;a. Vd 232 and Vd 233 land units; Volcanic plain andplato from acid tuff in the rolling (8-16 % slope),
moderately desected - strongly desected areas. They
are located between 40-700 m above sea level. Soiltype is dominated by Dystropept that covered 23556
ha or 4.06 %. The land units are distributed upper of
Ampalu river.
b. Vd 2.7.2 and Vd 2.7.3 land units; volcanic plainfrom intermediate tuff and lava that have hillocky
landform (>16% slope), moderately dissected tostrongly dissected. They are located between 50-495
m above sea level. Soil type is dominated by
Dystrandept that covered 6540 ha (1.13 %). Vd 273
land unit is found in the Sungai Geringging village(susceptible landslide event). Vd 272 land unit isfound in Kapalo Koto, Cumanak, and Padang Laweh
villages in the area that had landslide disaster
induced by earthquake 7.9 SR on September 30th,
2009.
c. Vab 2.10 .2 land unit is volcanic hilly fromintermediate tuff and lava having hilly area withslope gradient (>16%), moderately dissected which
is found on 100-2300 m above sea level. The soil
type is dominated by dystropept that cover 34689 ha
or 5.99 %. The land units are hilly and mountainy
land forms which is found in foot slope of mountTandikek.
d. Vd 2.10.2 land unit; volcanic hilly derived from acidtuff, slope gradient >16 %, moderately desected thatfound in 100-300 m above sea level. Soil type isProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 1 -General Issue and Solution-: 01

dominated humitropept that cover 1021 ha or 0.18 %from the area.
2) Landslide Analysis
Landslide disaster in West Sumatra has become into
emergence phase because it often happen such as Sago
mount, Pasaman District, Anai Valley landslide thatconnects Padang to Bukittinggi happening in West6
Sumatra has become warning and soon in outside ofWest Sumatra i.e: Mandahiling Natal Regence, Bogor,
Tawangmangu.
Landslide disaster in Tandikek study area was inducedby earthquake dated 30 September 2009, taking people
victim estimated 400 people. Landslide is moving earth
to follow sloping land that induced by gravitation force
and in turn the process will affected by high rainfall, land
use pattern was not suitable, soft parent material and badsoil physical properties. According to Zuidam (1979)
landslide process was characterized by soil and landcharacteristics. Soil characteristic consist of soil bulk
density, organic matter content, soil solum, soil
permeability and soil texture. Land characteristic consistof slope gradient, length of slope, stone exposure, watertable depth, land use, and amount of rainfall. Criterium ofsoil and characteristics are presented by Table 1 and 2
enclosed.
Soil Characteristics
a. Soil Solum
Soil type that covered Tandiek study area were
Dystranndept and Dystropept. The soil solum thatvariegated by degree of slopes. On Slope 25-45 %, soil

solum depth is ranging 60-90 cm, and the area slope >45 % usually is ranging 20-60 cm. Thus the criterium ofsoil solum depth is class code 2.
b. Soil Texture
Soil texture in the study area is classified in upper layer
are ranging loam to silty loam. Result of evaluation ofsoil texture is presented in Table 4 which in this tablevaluation of soil texture is classified by class 3.
c. Soil Structure
Determining of soil structure was conducted by theobservation in the field by using lup glass to see soil
structure shape. For soil classification of dystropept anddystrandept usually have crumb and granular structure.
In subsoil, soil structure are usually massive. Thus,
Based on the analysis soil characteristic, this soil areclassified by class 2 and class code 4.
d. Organic Matter Content and soil Bulk Density
Analysis of Organic matter content and soil bulk density
data are presented by Table 5.
In Table 2 are presented that soil organic matter content
in the study area is classified by high (>5.01 %) include
class code 1. While soil bulk density less than 0.75 g/cm3
is also include class code 1.
e. Soil Permeability
Soil permeability in the study area is presented in Table 6.
In Table 3.3 showed that soil permeability in the study
area are ranging 0.79 to 11.29 cm/hour (Slow to quick)especially for sawah, mixed garden and coconut tree land
use type. It was classified by class code 3 and class code
4.

Table 4 Soil Texture under different landuse type in Tandikek study area
No

Landuse Type

1
2
3
4
5

Mixed Garden
SawahsForestCinnamum tree
Coconut Tree

Sand
Silt
(%)
(%)
16
73
24
74
27
57
22
75
30
56
Source : Yunita (2003)

Clay
(%)
11
2
16
3
14

Class
Silt loam
Silt loam
Silt loam
Silt loam
Silt loam

Code
3
3
3
3
3

Table 5 Soil bulk density and soil organic matter content under different landuse typeNo

Landuse123
45

Mixed Garden
SawahsForestCinnamum tree
Coconut Tree

Soil Bulk density
Code
Soil Organic matter(g/cm3) *
(%)*
0.58
1
21.10
0.42
1
18.92
0.44
1
20.81
0.41
1
22.13
0.57
1
19.62
Source: *) Yunita (2003)

Table 6 Soil permeability in the Tandikek study area
No
1
2
3
4
5

LandusePermeability (cm/jam) *Mixed Garden
0.79
Sawahs
4.07
Forest10.24
Cinnamum tree
11.29
Coconut Tree
4.94
Source: *) Yunita (2003).

Code
4
3
1
1
3

Code
1
1
1
1
1

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 1 -General Issue and Solution-: 01

Figure 3 The soil that easy to erode by flow water because the soil is soft and weak from pumiceous tuff

Figure 4 Land-use in the study area

No
1
2
3
4
5
6

No
1
2
3
4
5
6

Table 7 Total of soil characteristic and land characteristic class code
Soil Charatersitic
Soil Properties
Adverbial
Soil Solum Depth
25- 60 cm
Shallow
Texturu
L,SL,SiL,Si
Medium
Structure
Single grain, massive
Poor
C-Organic Content> 5,01 %Very High
Bulk Density< 0,75 g/cm3
Very Good
Soil Permebility
2,0-6,25 cm/jam
MediumTotal

Land Characteristic
Slope gradient
Length of slope
Stone Exposure
Soil Water Table
LanduseRainfall
Total

Table 8 Total land characteristic code
Land properties
Adverbial> 40 %
Steeply
50 - 250 m
Length15-90 % of area
Much
> 100 mShallow
Sm, KcModerately Good> 90 mm/month
Very HighLand Characteristica. Slope degree and length of slope
Based on observation in the Tandikek studty area, thedominant slope gradient is generally>5% gradient mainly
for forest, mixed garden and coconut tree landuse type.
The length of slope in the study area are ranging 50-250 m.
Thus, for slope gradient and length of slope evaluation areclassified by respectively class code 4 and class code 3.

Class Code
2
3
4
1
1
3
13

Class Code
4
3
3
4
2
4
20

b. Stone Exposure
Based on result of observation in the Tandiek study area,stone expossure is classified by many or class 3.
c. Water table Depth
Based on result of observation in the Tandiek study area,
water table depth is classified by slightly shallow because
was found massive layer in the sub soil layer. While,water table depth is classified by slightly shallow. This

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 1 -General Issue and Solution-: 01

layer is shear plane for landslide event (Figure 3). Water
table depth is classified by class coder 3.

2.
3.

d. Land-use Type
Land-use type in the Tandike study area is presented in
Figure 6 and Table 3. In Figure 4 and Table 3 showed that
land-use type in the study area are sawahs, bush, mixed
garden, coconut tree garden. Especially, the steep area arefound coconut tree and bush. Based on land characteristic
criterium, the study area are classified to class code 3.

4.

e. Rainfall
Based on rainfall data in the study area showed thatamount of 171 mm (July is the lowest rainfall per month)
to 605 mm (September is the highest rainfall per month)(see Table 2.). Thus characteristic rainfall is classified toclass 4.
Result of Landslide Analysis
Based on result description above, we can conclude that
presented in Table 7 and Table 8.
By summing class code of landslide event of soil
characteristic and land characteristic are 13+20=33.
Based on the criterium of landslide induced factors, theTandikek study area is classified by high. It was explainedthat the soil is weak and soft and also easy to happen gully
erosion. When we went to the field showed that the depthof gully increased in short time. The depth of the gullyincreased around 50 cm in two weeks. Soil texture in the
topsoil are silt loam and coarse texture in the subsoil. We
assumed that this condition can be caused by the parent
material of the soil are hornblende hypherstyne pumiceous
tuff (Qhpt) and pumiceus tuff (Qpt). Thus, landslidedisaster will be often happened in the study area. Besidethat the study area have high rainfall and many steep slope
area and also mislanduse.

Conclusion
The conclusion of this study are:
1. The study area have hornblende hypherstyne
pumiceous tuff (Qhpt) and pumiceus tuff (Qpt) which
are critical by landslide event

The study area are classified by high landslide event.
The study area have wet climate and have > 4000 mm
rainfall.
Landslide fragile event need carefully for communityand need protected management of landslide event
mainly in heavy rain.

Reference
Saidi A, dan Asmar (2003) Kajian Sifat Fisik dan Kimia
Tanah di bawah beberapa jenis penggunaan Lahan diLereng Gunung Tandikat. Padang Pariaman. Seminar
HITI . Prosiding Seminar HITI. Padang:22-24,Juli 2003.
Saidi A(2010) Aspek Vegetasi dan penggunaan lahandalam hubungannya dengan degradasi lahan dan
peningkatan produktivitas tanah. Pidato Pengukuhan
pada Tanggal 28 Januari 2010 di Rapat Senat Luar
Biasa Unand Padang.
Dasrizal (2006) Analisis spasial distribusi dan tingkat
bahaya longsor di Gunung Padang Sumatera Barat.
Thesis Magister Sains pada Program Pascasarjana
Unand Padang.
Yunita M (2003) Kajian sifat fisik tanah pada beberapa
penggunaan lahan di daerah gunung tandikek
Kabupaten Padang Pariaman. Skripsi pada Fakultas
Pertanian Unand Padang.
Martayesa (2005) Pengakajian pengaruh kegiatan
penambangan batu bintang (Obsidian) terhadap
kandungan sedimen dan hara terangkut pada sub DAS
Kalulutan.Kabupaten Padang Pariaman. Skripsi pada
Fakultas Pertanian Unand Padang.
Kastowo GW, Leo S, Gafour, and Amin TC(1996)
Geological map of the Padang quadrangle, Sumatera.
Geological Research and Development Centre.
Bandung.
Zuidam C (1979) Terrain Analysis and Classification
Using Aerial Photograph. A GeomorphologicalApproach. ITC Texbook of Photo Interpretation Vol
7:2-23, Netherland.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 1 -General Issue and Solution-: 02

SOIL RESOURCE ISSUES IN INDONESIA○Komariah1 and Masateru SENGE2( 1 Soil Science Dept., Faculty of Agriculture, Sebelas Maret University, INDONESIA,
2 Faculty of Applied Biological Science, Gifu University, JAPAN)
SUMMARY Indonesia is a large archipelago country with more than 17,000 islands that spread
under tropical monsoonal climate. Indonesia, which lays between two continents (Asia andAustralia) and two oceans (Pacific and Indian) is facing the increasing population density andrapid industrialisation, which threat soil resource. The issues associate with soil resources inIndonesia include of deforestation, acid soil, soil degradation, soil erosion, greenhouse gas
emission, peat soil burn, land use conversion, land tenure and social-economic problems. The
problems mainly caused by anthropogenic factors such as intensive agriculture on steep slope
lands, open mining, industrial wastes, imbalanced fertilization etc. The technology to solve soil
problems is becoming main concern which is kept on developing to support the sustainable soil
resource. The implementation of terraces, cover crops, mulches and usage of materials to improve
infiltration and water holding capacity had been practiced widely. Water harvesting with farmreservoir has also been improved to minimize climate change on soil dryness and saturated soil.
Soil rehabilitation or reclamation programs shall be decided by discussing with surrounding
societies to formulate a bottom-up strategy.
Keyword: soil degradation, climate change, soil fertility, land management,
The Soil of Indonesia
Indonesia is an archipelago country of 17,504
islands, with total area of 1,913,578.68 km2(BPS, 2017). The big islands are, Sumatra,
Papua, Sulawesi and Java in that order; it isdivided into 34 provinces. The population is263,510,146, fourth after China, India andUS, with an annual increase of 1.12% (United
Nations, 2017).Although there are about
3,000 dialects, the national language isIndonesian. Indonesia lies between 6o08’ N
and 11o15’ S, and 94o45’ E and 141o05’ W. The
chain of islands from Sumatra, Java, Bali andNusa Tenggara appears to connect Asia with
Australia but the Wallace line, throughLombok strait between Bali and Lombok,
separates the fauna and flora of Asia fromthat of Australia (Nitis, 2006).
According to National Soil Classification
System which was introduced as PPT soil
classification
systemin
1978/1982,
Indonesian soil is distributed as Alluvials,
Andosols, Cambisols, Grumusols, Litosols,
Mediterranean,
Organosols,
Podzols,
Podzolics,
Regosols,
andRendzinas.
Meanwhile, according to USDA Soil
Taxonomy, the soil types in Indonesia isshown in the soil exploratory map ofIndonesia (Puslitanak, 1998) as presented inFig. 1.
Fig. 1 shows that soil types occupied inIndonesia are Alfisols, Andisols, Entisols,
Histosols, Inceptisols, Mollisols, Oxisols,
Spodols, Ultisols, and Vertisols.
Alfisols,

Inceptisols, Ultisols and Entisols are widelydistributed over almost entire
area.
Inceptisols cover 37.5% of Indonesian area,with total area approx. 70.52 million ha, andwidely employed for agriculture (Puslittanak,2000). Andisols cover areas with volcanic
mountains at Java, Bali, Sumatera and Nusa
Tenggara.
Oxisols is found mostly in
Sumatera, Borneo and Papua.
Ultisols
spreads at 25% of Indonesian lands (45.7
million ha), is mostly distributed in Borneo,
and also Sumatera, Papua, Selabes and Nusa
Tenggara (Subagyo et al., 2004). Histosols
known as peat soil, covers approximately 18
million hectares, which makes Indonesia as
the 4th peat soil coverage in the world after
Canada,RussiaandUnitedStates(Wahyunto et al, 2005).
Vertisols is
distributed commonly at Java and East Nusa
Tenggara.
The
topographicofIndonesia
ismountainous to flat. Approximately 27% of
the area has slope more than 30%, while hilly(15-30% slope) and undulating (8-15% slope)areas are 20, and 30%, respectively (Agus etal., 2015), with the annual rainfall of morethan 2,000 mm. Therefore, the topographic
and rainfall condition also dominate the soil
formation.
Since Indonesia is an archipelago country
which lays under monsoonal climate
condition and is included in the list of
volcanoes ring of fire, the formation of soil
had been influenced by parent material (geo-Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 1 -General Issue and Solution-: 02

morphology), rainfall and relatively highFig. 1 Soil Exploratory Map of Indonesia Scale 1:1,000,000 (Puslitanak, 1998)
tropical temperature. The parent materials of
Histosols is organic materials that had been
flooded for long period, while rock is theparent material of mineral soil. Histosols,
well-known as peat soil, is used for plantation,
especially oil palm in Sumatera and Borneo.
Over the geologic period, the peat land in
Borneo already converted into coal, so thatcoal mining is also extensive in Borneo.
Some mineral soil is developed well, suchas, Ultisols, Alfisols, Vertisols, Inceptisols, etc.
Ultisols originating from acids sedimentaryand volcanic rocks. Ultisols is widely used forplantation, and also for agriculture,
Vertisols, which is soil with high content ofexpansive clay known as montmorillonite
majorly distribute at dry areas, and thus
employ for upland farming system (Ma’shum
et al, 2008; Ispandi, 2003).
Alfisols, which is formed under ustic
climate with more than 3 months of drymonths and formation period of more 5,000
years (Buol et al., 1973), is majorly used forrice fields, sugar cane plantation and annual
plants.
Andisols
originatingfromintermediary volcanic and spreads onelevation higher than 600 m above sea level.
Since Andisols is formed with volcanic ash
sedimentation, the soil is fertile and thus
commonly used for agriculture farms lands.
Entisols is soil which does not show the
profile development but A-horizon, andwidely used for rice fields. The soil resourcesof all types are facing degradation problem, in
accompanied by land use change problem.

Recent Soil Degradation Problems inIndonesia
Soil degradation refers to reduction in thephysical, chemical or biological status, whichcauses land degradation in company withvegetation degradation (UNCCD, 2015).
Land degradation which also means a decline
in land quality caused by human activities,
has become a major global issue during the20th century and will remain highly on theinternational agenda in the 21st century. The
urgency of land degradation among global
issues is enhanced because of its impact onworld food security and quality of theenvironment.
Lindert (2000) reported in Fig. 2 that the
topsoil declined from 1940 to 1970, and rose
again thereafter but has not yet reached the1940 level. This appears to be the case for rice
field and upland, as well as the other uses.
Nitrogen probably followed the same trend.
There was a gain of around 44% in total
phosphorus over the same period, probably
due to fertilizer application. Potassium levels
may have also increased, around 28%, though
the trend is less distinct especially in the
upland and tree crop soils. It, too, may be due
to fertilizer application especially on foodcrops. The pH levels have varied as Indonesia
actualized liming applications and water
control. Since 1970, the pH has rather
increased at large range of farm lands.
The domination of steep and undulating
topographic, high annual rainfall and landProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 1 -General Issue and Solution-: 02

degradation lead to the increasing trend of
soil erosion in Indonesia. Lindert (2000) used
two approaches to observe erosion trends, one
chemical and one physical. The chemical
estimation refers to the assumption thaterosion carries away organic matter andnutrients, so one would expect their loss withsevere erosion. This did not occur in the
period since 1970 when Java andsurroundings transmigration areas wasundergoing agricultural intensification
associated with rapid population increases.
The physical estimation of erosion is based on
measurements of changes in the thickness ofthe topsoil layer. The manner in which topsoil
depth was measured, however, varied overtime. Even ignoring this, the trend wasinconclusive, and apparently there was no
dramatic change in topsoil depth.

Fig. 2 Change in Soil Characteristics by Landuse Type, Java and the outer island, 1940 to 1993
(Source: Lindert 2000)

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 1 -General Issue and Solution-: 02

Table 1 Land use change in Indonesia between 2000-2010 (Bappenas, 2011)

Besides the physical soil degradation,
land use/land cover change as an impact ofhuman activities also contribute to landdegradation through deforestation, removalof natural vegetation, and urban sprawl;
unsustainableagriculturallandusemanagement practices, such as use and abuseof fertilizer, pesticide, and heavy machinery;and overgrazing, improper crop rotation, poor
irrigation practices, and so forth (WMO,
2005). Major land use changes have been
occurred in Indonesia during the period of
2000-2010, as presented in Table 1. The total
area of forest decreased by more than 2
million hectares (1.7%), while the total areaof Shrubs, grasslands and sparsely vegetatedareas increased by 276,966.78 hectares or 3%.
The total area of cropland increased by
1,810,485.16 hectares or 2.7 %. There is nochange in wetlands and water bodies andartificial area during the period.
Climate Change Issues on Soil Resources
Climate change promotes precipitation
irregularity which sometimes lead drought
occurrences in Indonesia. Drought has long
been recognized as one of the most insidiouscauses of human misery. Recently drought isthe natural disaster which takes the mostvictims every year. Drought is a naturally
occurring phenomenon that can accelerate
desertification and land degradation (Nkonya
et al., 2011). Droughts normally occur during
long dry seasons in certain areas, especiallyin eastern Indonesia such as West Nusa
Tenggara, East Nusa Tenggara, and several
areas in Sulawesi, Kalimantan and Papua.
Drought, especially in semi-arid areas inIndonesia, is a serious problem that the
government have to concern, but undoubtedly
the main problem of Indonesia related withland degradation and its drivers isdeforestation.
The absolute rate of
deforestation in Indonesia is considered to beamong the highest on the planet, and has
been estimated to fluctuate between 0.7 and1.7 Mha yr-1 between 1990 and 2005 (Hansen
et al., 2009).
Forest and land use sectors, including
agriculture (land-based sector), have beenreported to be a significant source of global
GHG emissions, as shown in Fig 3. Figure 3
also presents a significant annual variationin GHG emissions and removals on forest andpeatlands across the whole country; reflecting
the impact of historical land management,
current practices and fluctuations in weather
conditions, particularly dry years with higher
incidences of fire. This sector has been themost dominant source of GHG emissions inIndonesia contributing to more than 60% of
the total GHG emissions (Indonesia Second
National Communication, 2010). This might
be a function of Indonesia having one of thelargest forest areas in the world, coupled withhigh rates of deforestation, forest degradationand large areas of drained peat lands.
Climate change and soil degradation not only
affect directly the declining of the
agricultural production but also increase theproduction cost and susceptibility of crop topest and diseases. Thus, the methods foraddressing the problem and ensuring thesustainability in all aspects is urgently
required, to ensure the national economic
stability and farmer’s household income.
Land Management Strategies for Soil
Restoration and Rehabilitation in Indonesia
Indonesian government concerns about thethreats on national land resources bydeclaring the National Action Program (NAP)
to combat land degradation (CLD). UNCCD(2015) reported that the NAP-CLD in
Indonesian context in particular, is therefore
defined as measures to prevent the landdegradation occurrences and to rehabilitate
degraded land on dry land with fullparticipation by local communities. The
purpose of NAP is to identify the factors
contributing to land degradation andpractical measures necessary to combat landdegradation and mitigate the effects ofProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 1 -General Issue and Solution-: 02

Fig. 3 Total annual net GHG emissions estimates in Indonesia for the period 2001 to 2012
from all pools (Bappenas, 2011)
drought. There are 13 Thematic Programs &Projects mentioned in the NAP, they are:Providing Enabling Conditions, Land
Degradation Inventory
and Monitoring,
Promoting of Agroforestry, Monitoring and
Mitigating the Impact of Drought, Preventionof Land Degradation, Rehabilitation of
Degraded Lands, Improvement of irrigation
facilities and Water Conservation, Sylvopastoral and Agro-pastoral Development,
Monitoring and Evaluating of Climatic
Variation,
Empowerment
of
Local
Communities
and
Local
Institutions,
Establishmentof
Sustainable
Land
Management, Providing Guidelines andManuals, and Creating and improving
market system.
Major impacts of land degradation on
production are sometimes not distinctly
performed in the yield. Land degradationeven on the hillslopes of Java has notmeasurably reduced yields or productivity
because of the 1. increasing and wide use offertilizers, 2. increased application of labor to
do SWC and other productivity enhancement
practices, and 3. government terracing
programs. Erosion on the other Islands,
however,hasmeasurably
reducedproductivity (UNCCD, 2015).
INCAS, Indonesian National Carbon
Accounting System (2015) reported that the
governmentofIndonesia(GOI)
hascommitted to reduce GHG emissions by up to
26 percent below ‘business as usual’ levels by
2020, and by up to 41 percent if international
assistance is forthcoming. Around 80 percentof these proposed reductions are expected tobe achieved through changes to the ways inwhich forest and peatlands are managed(Bappenas, 2011). Indonesian efforts are
expected to be enhanced through access tointernational finance that will support policy,
planning and on-ground activities to reduce
emissions from deforestation and forest
degradation, and the role of conservation,
sustainable management of forests andenhancement of forest carbon stocks,
commonly known as REDD+.
Conclusion
Indonesia with its specific soil characteristics
and topography under tropical monsoon
climate in accompanied with the impact ofclimate change, experience soil and landdegradation over period. The government
make an attempt to conserve and maintainthe sustainability by declare some national
programs and projects, such as National
Action Programme (NAP) to combat landdegradation (CLD) and REDD+.
Acknowledgement
Author acknowledges the United Graduate
School of Agriculture Science (UGSAS), Gifu
University, Japan for funding support.
References
Agus F, Wiratno and Suwardi (2015) Status ofIndonesian Soil Resources. Presentation in
Asian Soil Partnership Consultation
Workshop on Sustainable Management andProtection of Soil Resources: 13-15, May
2015,
Bangkok,Thailand.
http://www.fao.org/fileadmin/user_upload/GProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 1 -General Issue and Solution-: 02

SP/docs/asia_2015/Indonesia_F_Agus.pdf.
Bappenas [The Ministry of National
Development
Planning,
Republicof
Indonesia] (2011) National Action Plan for
Reducing GHG Emissions. Republic ofIndonesia, Jakarta.
BPS [The Indonesian Central Bureau of
Statistics] (2017) Total Area and Total
Islands of Each Province (in Indonesian)
2002-2015.
https://www.bps.go.id/linkTabelStatis/view/id/1366.
Hansen MC, Stehman SV, Potapov PV,
Arunarwati B, Stolle F and Pittman K(2009) Quantifying changes in the rates offorest clearing in Indonesia from 1990 to2005 using remotely sensed data sets.
Environmental Research Letters.
INCAS[Indonesian
National
CarbonAccounting System] (2015) National
Inventory of Greenhouse Gas Emissions
and Removals on Indonesia’s Forests andPeatlands. Ministry Of Environment andForestry Research, Development andInnovation Agency. Republic of Indonesia.
Ispandi A (2003) The application of P, K
Fertlizer and Application Period on
Cassava at Dry Land (in Indonesian).
Vol.10, 2: 35-50.
Lindert PH (2000) Shifting Ground: The
Changing Agricultural Soils of China andIndonesia. Cambridge, MA and London,
UK: Massachusetts Institute of Technology
Press.
Ma’shum M (2004) Soil Management andPlantation for Sustainable Productivity ofRain-fed Lands at South Lombok (inIndonesian). http://ntb.litbang.deptan.go.id/
Munir M (1996) Main Soils in Indonesia (inIndonesian). Pustaka Jaya: Jakarta
Nitis IM (2006) Country pasture/forage
resource profiles: Indonesia. Food andAgriculture Organization of the United
Nations, Rome, Italy.
Nkonya E, Gerber N, Baumgartner P, vonBraun J, De Pinto A, Graw V, Kato E, Kloos
J and Walter T (2011), The Economics ofDesertification, Land Degradation, andDrought Toward an Integrated Global
Assessment, ZEF- Discussion Papers on
Development Policy No. 150, Center for
Development Research. Bonn. pp. 184.
Puslittanak[Indonesian
SoilandAgroclimate Research Institute] (1998)
Atlas of Indonesian Exploration Soil
Resources (in Indonesian). Dept. ofAgriculture, Republic of Indonesia. Bogor.
Puslittanak (Indonesian Soil and Agroclimate
Research Institute) (2000) Land Resourcesof Indonesia and The Management (inIndonesian). Dept. of Agriculture, Republicof Indonesia. Bogor.
Subagyo HNS, and Siswanto AB (2004)
Agricultiral Lands in Indonesia (inIndonesian).
Tan KH (2008) Soils in the Humid Tropics
and Monsoon Region of Indonesia. CRC
Press. Georgia.
UNCCD (2015) Indonesia - Land Degradation
Neutrality National Report. Republic ofIndonesia, Jakarta.
United Nations. 2017. The 2017 Revisionof World Population Prospects. United
Nations
Population
Division|
https://esa.un.org/unpd/wpp/Download/Standard/Population/
Wahyunto, S. Ritung, Suparto, and H.
Subagjo. (2005) Peatland distribution and
its C content in Sumatra and Kalimantan.
Wetland Int’l –Indonesia Programme andWildlife Habitat Canada. Bogor, Indonesia
WMO (2005) Climate and Land Degradation.
World
MeteorologicalOrganization.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 01

Soil Carbon Stock and Sequestration after 29 Years of No-tillage in Sumatra, Indonesia○Muhajir UTOMO, Jamalam LUMBANRAJA, Tamaluddin SYAM and Fajri Taufik AKBAR(Faculty of Agriculture, University of Lampung, Indonesia）
SUMMARY
In the tropics, soil organic carbon (SOC) has important role on enhancing soil health and productivity, but easily
degraded by current soil management. The objective of this experiment was to determine the influence of long-term
no-tillage and N fertilization on soil C stock and soil C sequestration. The long-term experiment was initiallyestablished in February 1987, at experiment farm of Politeknik Negeri Lampung, Sumatra, Indonesia. The soil is
Udult, clayey, slope ranging from 6 to 9%, with elevation 122 m. The experiment was a factorial, randomized complete
block design, with 4 replications. Tillage treatments were no-tillage (NT), minimum tillage (MT) and conventionaltillage (CT); while nitrogen fertilization rates were 0 kg N ha-1 (N0) and 200 kg N ha-1 (N1). Soil samples were taken
in February 2016 at 0-20 cm depth for all treatments, but only combination treatments of NTN1 and CTN1 for the
representative profiles. It revealed that after 29 years of cropping, there were significantly influences of tillage and N
fertilization on soil C stock and C sequestration (P<0.05). Soil C stock of no-tillage at 0-20 cm depth was 35.4 Mg
C ha-1, or 12.8% higher than CT, but not difference than MT. While soil C stock in 0 kg N/ha treatment was 34.9
Mg C ha-1, or 7.7% higher than 200 kg N ha-1 treatment (P<0.05). In soil profile up to 60 cm depth, C stock under NT,
CT and reference site were 57.1, 55.6 and 47.9 Mg C ha-1, respectively. Soil C sequestration rate by NT was the highest(118.4 kg C ha-1yr-1), but not significantly different than MT (71.8 kg C ha-1yr-1). While in contrast, soil C sequestration
under CT was significanly the lowest (-20.7 kg C ha-1yr-1). Soil C sequestration rate by N fertilization was lower 14.3
kg C ha-1yr-1 than no N fertilization (98.7 kg C ha-1yr-1)

Introduction

2010; Triplett and Dick 2008) and yet in Indonesia

Concerns about climate change due to greenhouse gas(Utomo 2014). Rapid adoption of NT is due to the fact(GHG) emissions is currently receiving considerable

that it requires less cost and labor, sustains soil fertility

attention worldwide (Rastogi et al. 2002; Lal 2016;

and crop yield at least the same as CT (Lal 1997; Utomo

Utomo 2014). Depletion of soil SOC contents in soils

2014).

due to land use conversion and soil cultivation have been

Sá et al. (2015) reported that by the conversion ofcontributing to the increase of that GHG emission (Lal,native forest in tropical Brazil to a continuous use

2007; Sá et al. 2015). As a global initiative therefore, theplow-based CT agro-ecosystem had decreased SOC‘4 per mille Soils for Food Security and Climate’ aspires

sequestration. Significant differences in the SOC

to increase global soil organic matter stocks by 4 persequestrations

mille (0.4 percent) per year as a compensation for the

20-cm depth were observed with the rate of of

between NT and CT cropping systems at
-1

0.

-1

global GHG emissions by anthropogenic sources

48–1.30 Mg C ha yr . Similar trend was also reported(Chambers et al. 2016; Lal 2016; Minasny et al. 2016).

by Bayer et al. (2006). The soil C stocks at 0-20 cm

The strategy is to promote SOC sequestration throughdepth in no-till sandy clay loam Oxisol in Brazil was 2.4

implementing best management practices (BMPs) of C

Mg ha-1 higher thanconventionally tilled soil, with C

farming including conservation agriculture (Lal 2016).

sequestration rate of

0.30 Mg ha-1 yr-1. In the profile

Sequestration of SOC has been considered as a possible

sample, the soil C stocks were significantly higher forsolution to mitigate climate change (Chambers et al.

the minimum tillage (MT) treatment than NT and CT

2016; Minasny et al.., 2016; Lal 2016) with an additional

treatments (Andruschkewitsch et al. 2013). In NT,

benefit of enhancing ecosystem services (Lal 2013), andhowever, soil C accumulation increased with the increase

increasing soil productivity as well (Utomo et al. 2013;

in the input of biomass-C (Carvalho et al. 2016; Sá et al.

Utomo 2014).

2015). For an example, with 80 Mg ha-1 of sugarcane

With less soil surface manipulation and applicationof mulch,no-tillage (NT) is among BMPs thatbagasse, soil C stock and soil C sequestration under NT
after 5 years were

42.9 Mg C ha-1 and 2.8 Mg C ha-1

expected to have SOC sequestration and yield higher

yr-1, respectively. While under CT with no mulch, soil C

than that of conventional tllage (CT) (Lal 1997; Utomo

stock was only 29.4 Mg C ha-1 and C sequestration was2014). Due to those reasons, since about 1990, adoption

0.24 Mg C ha-1yr-1 (Utomo et al. 2017). In tropicalof NT has expanded rapidly worldwide (Derpsch et al.

agro-ecosystem however, there is a limited information

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 01

about soil C stock and soil C sequestration underrespectively. Analysis of variance and means test withlong-term NT plot. The aims of this research were to

Least Significance Different (LSD 0.05) were analyzed

determine the effect of long-term tillage systems and N

using the Statistical Analysis System package (SASfertilization on soil C stock and soil C sequestration after

Institute 2003).

29 years of corn-soybean crop rotation.
Result and Discussions

Material and Method
Experiment Site and Design
The long-term experiment that was established in

Soil Carbon Stock
After 29 years of cropping, it turned out that soil C stockand sequestration at 0-20 cm depth were affected by

February 1987 (Utomo et al. 1989), was located at thetillage (T) and nitrogen (N), but not affected by NTexperiment farm of Politeknik Negeri Lampung, Sumatra,interaction (Table1). Due to addition of crop residues each

o

o

o

Indonesia (105 13’ 45.5”-105 13’ 45.5”-105 13’ 48.0"E,ooseason (Utomo et al. 2013), soil C stock under NT was

05 21’19.6"-05 21’ 19.7"S) with elevation of 122 m

significantly (P<0.01) the highest (35.4 Mg C ha-1), whilefrom sea level (Utomo et al. 2013). Cropping pattern ofin contrast under CT was the lowest (31.4 Mg C ha-1)

this longterm experiment was cereal (corn or upland(Table 2). Soil C stock under NT was 12.7% and 3.8%rice)-legume (soybean, mungbean or cowpea)-fallow

higher than those of CT and MT, respectively.

(weed or bare soil) rotation.

This finding was similar to those that reported by

The experiment was arranged in a factorial,
randomized

completely

block

design,

with

four

replications. The plot size was four by six meters. The

Bayer et al. (2006), Carvalho et al. (2016), and Sá et al.
(2015).
Within the soil profile (0-60 cm),the trend of soil

first factor was tillage systems; those were conventional

C stock was consistent with that of 0-20 cm depth (Fig.

tillage (CT), no-tillage (NT), and minimum tillage, (MT).

2). Soil C stock under NT within soil profile throughWhile the second factor was nitrogen (N) treatment with

0-60 cm depth was the highest (57.1 Mg C ha-1), while

rates of 0 (N0) and 200 kg N ha

-1(N1) applied

under the reference profile was the lowest (47.9 Mg C

specifically for corn production. Nitrogen source for theha-1). It was 19.2% and 2.6% higher than those of

N fertilization was Urea 46% N. For initial soil C stock,reference and CT sites, respectively.

composite sample was taken prior to experiment in
February 1987 at 0-20 cm depth (Utomo et al. 1989;
Utomo 2014). While samples for soil C stock andsequestration were sampled in February 2016 at depth of
0-20 cm for all treatments, and at depth of 0-60 cm forrepresentative profiles of specific treatments. The soil C
stock was calculated from soil BD and the soil carbon
concentration as follow: soil C stock (g C cm-2) = [SOCx BD x D]/100, where C, BD and

D were SOC (%),

-3

soil bulk density (g cm ), and soil depth (cm),respectively. Soil C stock was then scaled up into per-1unit area of estimation (Mg C ha ). Finally, the soil C
sequestration rate after 29 years of cropping (Mg ha-1yr-1)=[C stock 2016–C stock 1987]/29. Those estimations

Table 1 Analysis of variances for soil C stock andsequestration at 0-20 cm depth
Treatments
C stock
Cseq
C seq rate
Till (T)******
Nitro (N)
*
*
*
T*N
ns
ns
ns
-1
-1
Note: N0= 0 kg N ha ; N1= 200 kg N ha
Table 2 Long-term (29 years) effect of tillage on soil
C stock and sequestration at 0-20 cm depth
Treatments
C stock
C seq
C seq rate
No-till
Min-till
Con-till(MgCha-1)(MgCha-129yr-1)(kgCha-1yr-1)

35.4 a34.1 a31.4 b3.4 a
2.1 a-0.6 b118.4 a71.8 a-20.7 bwere modified from Cerri et al. (2011); Galdos et al.
(2009); Khasanaha et al. (2015).
Statistical Analysis
The homoginity and additivity of the data were
determined

withBartlett’s

test

and

Tukey

test,

Table 3 Long-term (29 years) effect of nitrogen on
soil C stock and sequestration at 0-20 cm depth
C stock
C seq
C seq rate
(MgCha-1)(MgCha-129yr-1)(kgCha-1yr-1)

N034.9 a2.9 a98.7 aN1
32.4 b0.4 b14.3 bNote: N0= 0 kg N ha-1; N1= 200 kg N ha-1

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 01

accumulated in horizon A, but in horizon B was thelowest. This was because

in NT, there was anaccumulation of previous crop surface on the soil surface
with no soil surface disturbance, yielding in higher SOC
in A horizon, but lower SOC in B horizon (Fig. 3).
The strong long-term effect of NT on inducing SOC, wasreflected on higher soil C stock under NT if combinedwith any N treatment. On the other hand, with lower
SOC, CT had lower soil C stock (Table 2), resulted in alower soil C stock if combined with any N treatment (Fig.
1). Soil C stock under N0NT at 0-20 cm depth tended tobe the highest (37.1 Mg C ha-1), while under NTCT was
the lowest (29.6 Mg C ha-1) (Fig. 1). This was atributedby the higher

soil C stock under NT alone than othertillage treatments.
Fig. 1 Soil C stock after 29 years of cropping (0-20 cm)

Different from NT, long-term nitrogen application(200 kg N ha-1) reduced soil C stock. Soil C stock at 0-20
cm depth under N1 was 14.3 kg C ha-1yr-1 (Table 3),
while under N0 was 98.7 kg C ha-1yr-1 (P<0.5%).
Probably, this was

indirectly

due to N application had

induced SOC mineralisation, resulted in lower soil C
stock.
Soil Carbon Sequestration
The C sequestration rate (kg C ha-1yr-1) after 29 years ofcropping was calculated as [C stock 2016-C stock1987]/29. It is noted that initial carbon stock at 0–20 cm
depth in 1987 (when this long-term plot was established)was 32.0 Mg ha−1 (Utomo et al. 1989; Utomo 2014).
Therefore, during 29 years of cropping, NT had
Fig. 2 Soil C sock within soil profile after 29 years ofsignificantly sequestered SOC as much as 3.4 Mg C ha−1

cropping (0-60 cm)

29 yr-1, resulting in a soil carbon sequestration rate of
118 kg C ha−1yr−1. In contrast, IT had significantly
depleted SOC as much as -0.6 Mg C ha−1 29 yr-1,
yielding with carbon depletion rate of -20.7 kg C ha−1
yr−1 (Table 2).
Figure 3 shown the trend of combination effectbetweentillagesequestration rate.
rate

and

N

fertilization

on

soil

C

Under N0NT, soil C sequestration

was the highest (175.1 kg C ha-1yr-1) amongCsequestration rate under N1CT was depleted to -82.8

treatment

combinations.

In

contrast,

soil

kg C ha-1yr-1 (Fig. 3). Depletion of soil carbon with
repect to CT combined with any N fertilization was
mainly due to there was no crop residue addition and soil
erosion with respect to CT (Lal 1997; Utomo et al. 2013;
Fig. 3 Soil C sequestration rate after 29 years of cropping

Utomo 2014), and higher SOC mineralization with

(0-20 cm)

respect to N fertilization. Figure 3 also shown that

Different from others, most of soil C stock under NT was

combination nitrogen with any tillage treatments tended

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 01

to reduced soil C sequestration. It seems that nitrogen
had negative effect on soil C

sequestration. Comparedto with no nitrogen application, application of 200 kg N
ha-1 reduced soil C sequestration as much as 84.4 kg C
ha-1yr-1 (Table 3).
However compared to other reports in temperate region(Bayer et al. 2006; Sá et al. 2015), these soil C
squestration values were lower. This is because intropical ecosystem such as Indonesia, soil C pool issubjected to be decomposed much faster than temperateregion, resulted in a relatively lower soil C sequestration(Utomo 2014).

Conclusion
Long-term (29 years) no-tillage increased soil C stockand soil C sequestration rate at 0-20 cm depth. In
contrast,

conventional tillage depleted soil C stock andsoil C sequestration rate. This trend was consistent in soil
profile up to 0-60 cm depth.
Long-term nitrogen fertilization (200 kg N ha-1)
depleted soil C stock and soil C sequestration at 0-20 cm
depth.
These

findings

suggestthat

applicationofconservation agriculture such as no-tillage can bepromoted for implementation of the ‘4 per mille Soils for
Food Security and Climate’ global inisiative.

Acknowledgement
The research was financially supported by the
Research Institute of University of Lampung
through Hibah Profesor of University of Lampung
in 2016/2017, and partially supported by Yokohama
National University, Japan. Acknowledgements arehighly appreciated for those who have supported thislong-term no-tillage research.

Reference
Andruschkewitsch R, Geisseler D, Koch HJ and Ludwig
B (2013) Effects of tillage on contents of organic carbon,
nitrogen, water-stable aggregates and light fraction for
four different long-term trials. Geoderma, 192:368–377.
Bayer C, Martin-Neto L, Mielniczuk J, Pavinato A,
Dieckow J (2006) Carbon sequestration in two
Brazilian Cerrado soils under no-till. Soil & Tillage
Research, 86:237–245.
Carvalho JLN, Noguerol RC, Menandro LMS, Bordonal
RDO, Borges CD, Cantarella H and Franco HCJ(2016) Agronomic and environmental implications ofsugarcane straw removal: a major review. GCB
Bioenergy, 1-15.
Cerri CC, Galdos MV, Maia SMF, Bernoux M, Feigla BJ,

Powlson D and Cerri CEP (2011) Effect of sugarcane
harvesting systems on soil carbon stocks in Brazil: an
examination of existing data. European Journal of Soil
Science, 62:23–28.
Chambers A, Lal R, Paustian K (2016) Soil carbon
sequestration potential of US croplands andgrasslands: implementing the 4 per thousand initiative.
J. Soil Water Conserv, 71: 68A–74A.
Derpsch R, Friedrich T, Kassam A, Hongwen L (2010)
Current status of adoption of no-till farming in theworld and some of its main benefits. Int J Agric &Biol Eng, 3 (1): 1-25.
Galdos MV, Cerri CC, Cerri CEP (2009) Soil carbon
stocks under burned and unburned sugarcane in Brazil.
Geoderma., 153; 347–352.
Khasanaha N, van Noordwijk M, Ningsih H, Rahayu S(2015) Carbon neutral? No change in mineral soil
carbon stock under oil palm plantations derived fromforest or non-forest in Indonesia.
Agriculture,
Ecosystems and Environment., 211:195–206.
Lal R (1997) Residue management, conservation tillage
and soil restoration for mitigating greenhouse effectby CO2 -enrichment. Soil Tillage Res 43:81–107.
Lal R (2007) Soil carbon sequestration to mitigate
climate change and advance food security. Soil Sci,
32(12):943–956.
Lal R (2013) Enhancing ecosystem services with no-till.
Renewable Agriculture and Food Systems, 28(2);102–114.
Lal R (2016) Beyond COP 21: potential and challengesof the “4 per thousand” initiative. J. Soil Water
Conserv, 71: 20A–25A.
Minasny B, Malone BP, Alex B. McBratney, Angers DA,
Arrouays D, Chambers A, Chaplot V, Chen ZS,
Cheng K, Das BS, Fielda DJ, Gimona A, Hedley CB,
Hong SY, Mandal B, Marchant BP, Martin M,
McConkey BG, Mulder VL, O'Rourke S, Anne C.
Richer-de-Forges AC, Odeh I, Padarian J, Paustian K,
Pan G, Laura Poggio i, Savin I, Stolbovoy V,
Stockmann U, Sulaeman Y, Tsui CC, Vågen
TG,Wesemael BV, Winowiecki L (2016) Soil carbon 4
per mille. Geoderma, 292:59–86.
Rastogi M, Singh S, Pathak H (2002) Emission of carbon
dioxide from soil. Curr Sci, 82(5):510–517.
Sá JCD, Séguy L, Tivet F, Lal R, Bouzinac S,
Borszowskei PR, Briedis C, Santos JBD, Hartman
DDC, Bertoloni CG, Rosa J, and Friedrich T (2015)
Carbon depletion by plowing and its restoration by
no-till cropping systems in Oxisols of subtropical andtropical agro-ecoregions in Brazil. Land Degrad.
Develop, 26: 531–543.
SAS [Statistical Analysis System] Institute (2003)
TheSAS system for windows. Release 9.1. SAS
Inst.Inc. Cary, NC.
Triplett GB and Dick WA (2008) No-tillage crop
production: a revolution in agriculture. Agro J,
100:153–156.
Utomo M, H Suprapto and Sunyoto. 1989. Influence oftillage and nitrogen fertilization on soil nitrogen,decomposition of alang-alang (Imperata cylindrica)
and corn production of alang-alang land. In: J van der
Heide (ed). Nutrient management for food crop
production in tropical farming systems. Institute forProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 01

Soil Fertility (IB), 367-373.
Utomo M, Banuwa IS, Buchari H, Anggraini Y, Berthiria(2013) Long-term tillage and nitrogen fertilization
effects on soil properties and crop yields. J Trop Soils,
18 (20):21–30.
Utomo M 2014 Conservation Tillage Assessment for
Mitigating Greenhouse Gas Emission in Rainfed
Agro- Ecosystems. N. Kaneko et al.. (eds.),
Sustainable Living with Environmental Risks,

35:35-44.
Utomo M, Niswati A, Yusnaini S, Pamungkas DT, Diky
N, Haryani S, and Kaneko N (2017) Soil carbon
sequestration after five years of no-tillage and bagassemulching in sugarcane plantation. International
Conference on Organic Agriculture in the Tropics:
State of the Art, Challenges and Opportunities.
Yogyakarta, August 20-24, 2017.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 02

Soil Properties in Relation with the Incidence of Heart Rot Disease in Pineapple due
to Phytophthora sp. in Humid Tropical Climate of Lampung, Indonesia○Afandi*,P. Cahyono**, G.alang I. Jaya *, M.A.S. Syamsul Arif*, Ivayani*, and Auliana Afandi***（*Faculty of Agriculture, Lampung University, Indonesia**Research & Development PT. GGP, Indonesia***United Graduate School of Agricultural Sciences, Gifu University, Japan）

SUMMARY
This study examined the relationship between soil properties, especially pH and C-organic soil with the incidence ofheart rot disease due to phythophthora in pineapple plantation. The heart rot disease which was caused by Phytophthora
sp. was studied in small scale plot experiment. To simulate the amount of C-organic in soil as well as pH, theexperiment was done by applying compost with the following treatments: 0 t/ha, 100 t/ha, and 200 t/ha of compost with
5 replicate. Three months after planting, the incidence of disease was very severe in application of 200 t compost per ha,
and all the plants were nearly dead 5 months after planting in 100 and 200 t/ha of compost application. Application ofcompost increased C-organic soil and soil pH in, especially treatment 200 t/ha followed by the increasing disease
incidence due to phythophthora. The species of Phytophthora sp was identified as Phytophthora nicotianae.
Keywords: pineapple, compost, heart rot disease, phytophthora

Introduction(2014) also reported that sporangia of P. cinnamomi

The soil developed under humid tropical climate

grew well in temperatures were between 26 °C to 30 °C.

generally is characterized with low pH (acid soil), low

Afandi et al. (2016) reported that the heart rot diseasechemical fertility as well as poor soil physical properties.

due to phythophthora started attack at pH above 4.4 andFarming in such soil conditions have many obstacles,

soil organic matter above around 1%.

mainly getting high yield of agricultural crop and

The objective of this research is to investigate themaintaining the soil health.

Application of organic

relationship between soil properties, especially pH andmatter or compost and liming usually applied to

C-soil organic with phythophthora incidence in pineapple

encounter these problems. However, in pineapplein Lampung, Indonesia.

cultivation, increasing pH above 5 would promotedisease in the form of heart rot and root rot disease due

Material and Method

to Phytophthora sp. (Rohrbach and Johnson, 2003; Pegg,

Research conducted in pineapple plantation, Central

1993; Mite et al., 2010). On the other hand, if the pH is

Lampung, Lampung, Indonesia, from June 2016 untilvery low, the availability of macro nutrient will be

March2 2017 The

limited.

compost with the following treatments as follows :0 t/ha,

Understandingof

100 t/ha, and 200 t/ha compost with 5 replicate planted

Phythophthora sp. in pineapple could control thewith pineapple. The plot size was 3 mx 2.5 m withincidence

thisplanting distance 56 between rows and 20 cm in row.

In Hawai‘i, pineapple heart and root

Planting material of pineapple was sucker with clone

rots are most severe in high-rainfall areas and irrigatedGP3. Prior to planting, the base fertilizer were applied

soils with poor soil drainage (Green and Nelson, 2015).

with 100 kg Urea/ha, 150 kg KCl/ha, and 250 kg DAP/ha.

Corcobado et al., (2013) reported that the occurrence ofThe disease incidence were investigated 3, 4, 5 monthinfected trees by Phytophthora cinnamomi was higher inafter planting on January, February and March 2017.

soil low bulk densities, fine textured soils and in thickChemical soil properties, including in pH and C-organic

Ah horizons. Morgan and Shearer (2013) showed thatsoil were analyzed 5 months after planting.

of

microorganism.

thediseaseslivingwhich

environment

experiment was done by applying

causedbythe capacity of P.cinnamomi to sporulate and release

The soil used in this experiment was classified aszoospores significantly greater in the jarrah forest soil

Ultisols or Red Yellow Podzolic Soils with have theand Bassendean sand than the mining soils. Shearer

following soil fraction composition: sand 53.8%, siltProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 02

8.6%, and clay 37.6% and categorized as sandy clay in

Disease Incidence

USDA Soil Texture Classification. The initial chemical

The diseases incidence caused by phythophthora wasproperties of soil have the following values: pH 4.7,

characterized by the leaves which easily pulled from theC-organic 1.5, and CEC total 19.7 meq/100 g.

plant, with foul smell and the plant would finally be dead.

Compost consisted of 20% cow dung, 20% bamboo

Identification of the species in this location by Auliana

chops, and 60% of pineapple bagasse, which alreadyAfandi in Gifu University showed that the species ofcomposting and mature. The content of compost were as

Phytophthora is Phytophthora nicotianae.

follows: pH 7.2, C-total 21.59%, N-total 1.68%, C/N

The disease incidence which was observed from 3 after

ratio 12.89 and CEC total 56.48 meq/100 g.

months planting is shown in Fig 3.

Result and Discussions

incidence of disease was very severe in application of

Figure 3 showed that 3 months after planting, the
200 t compost per ha, and all the plants were nearly deadClimate condition

4 and 5 months after planting in 100 and 200 t/ha of

The average rainfall during 1981-2012 was aroundcompost application.

2452 mm per year. The dry season, which therainfall below 100 mm per month, occurred in June
until

September.

November

until

The

rainy

seasonApril.

The

monthlyon

pH, C-organic and disease incidence
Application of compost increased C-organic soil in,

rainfallespecially treatment 200 t/ha. Compost application also

start

distribution is shown in Fig.1.
The average air temperature as shown in Fig.2 wasooincreased pH. Increasing pH and C-organic were
followed by the increasing of disease incidence (Tablearound 22.5 C to 32.6 C throughout the year. The

1).

maximum temperature occurred in October, while theSince compost has high pH, the application of compost

minimum temperature occurred in July.

would increase pH in soil. In this experiment, theThis climate character was ideal with phytophthora
growth which high rainfall and warm temperature.

treatment with 0 t/ha of compost has already pH >5, theideal condition of the Phythophthora, so until five monthafter planting, the incidence of phytophthora disease wasaround 53%.

Combination of high pH and high organic

soil in treatment 100 and 200 t/ha compost made almost
the all pineapple plant died five months after planting.
Other experiment using 50 t/ha of compost, thedisease incidence was not significantly reduced thepineapple population as well as yield.

Fig.1 Monthly rainfall in Central Lampung

Fig.3 Disease incidence after planting

Fig.2 Monthly minimum and maximum temperatureProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 02

Table 1 Disease incidence and soil properties
CompostC-soil organic
pH
Disease(t/ha)(%)
incidence (%)
0
1.72a
5.47a
53a
100
2.35ab
5.71a
99b
200
3.16b
6.25b
98b
*) Means followed by same letters within a column do not differ
statistically(2013) Combined effects of soil properties andPhytophthora cinnamomi infections on Quercus ilex
decline. Plant Soil. 373:403–413.
Green J and Nelson S (2015) Heart and Root Rots of
Pineapple. Plant Disease July 2015 PD-106. College of
Tropical Agriculture and Human Resources, Universityof Hawai’i at Manoa:1-7.
Mite F, Espinosa J, and Medina L (2010) Liming EffectConclusion
Application of high dosage compost with high pH has
induced phythophthora attack in pineapple. Five monthafter planting, all pineapple plant (98-99%) almost diedon Pineapple Yield and Soil Properties in Volcanic
Soils. Better Crops Vol.94 (1):7-9.
Morgan, B.R., and B. L. Shearer. (2013): Soil type anddue to heart rot disease caused by Phytophthora

season mediated Phytophthora cinnamomi sporangium

nicotianae. Compost application below 100 t/ha andformation and zoospore release. Australasian Plant

liming application not more than until pH 5, is better for

Pathol. 42:477–483.
Pegg KG (1993). Diseases. In Pineapple Pest andpineapple.

Disorder (eds. R.H. Broadly, R.C. Wassman III and E.

Acknowledgement

Sinclair).

The authors thanked to PT. Great Giant Pineapple,
Central Lampung, Lampung, Indonesia, for facilitating
this research.

DPI Queensland:11-32.

Rohrbach KG and Johnson MW (2003) Pests, Diseases
and Weeds. In The Pineapple: Botany, production andUses (eds. D.P. Bartholomew, R.E. Paull and K.G.
Rohrbach), CAB International:203-252.

Reference
Afandi, Martin DAN, Suharjo R, Niswati A, Loekito S,

Shearer BL (2014) Time course studies of temperature

and Afandi A (2016) Soil Properties under Heart Rot

and soil depth mediated sporangium production by

Disease of Pineapple due to Phytophthora Incidence,

Phytophthora cinnamomi. Australasian Plant Pathol.

in

43:235–244.

Lampung,Indonesia.

Proceeding

The

5th

UGSAS-GU Roundtable & Symposium 2016:29–31,
August, 2016, Gifu, Japan.
Corcobado T, Solla A, Madeira MA, and G. Moreno.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 03

Changes of soil morphology and properties in long-term soil management under humid
tropical regions of Lampung, Indonesia○Didin Wiharso, Muhajir Utomo and Afandi(Faculty of Agriculture, Lampung University, Indonesia）
SUMMARY
The humid tropical climate was characterized by high rainfall and solar heat for most of the year, resulting in high rates
of soil weathering, soil losses, cations leaching, and oxidation of soil organic matter. The aim of this research was toobserve the changes of soil morphology and soil properties due to differences in soil management for 20 years. There
were three types of soil management, Intensive Tillage (IT), Minimum Tillage (MT) and No or without tillage (NT).
Basically, Minimum Tillage and No Tillage are the Conservation Tillage (CT). The results showed that the lower
content of organic matter in the upper layer of IT had caused the soil color become lighter, which was characterized byhigher chroma. Soil structure on the top layer of IT had changed from crumbs toward to the angular blocky. The topsoilon IT was more friable than two others, while the lower layer was more dense or compact. Generally, the chemical
properties of CT were better than IT, and NT was slightly better than MT.
Keywords: Intensive Tillage, Minimum Tillage, No-Tillage, Conservation Tillage

1. Introduction
Technically the major constraint for humid tropicalregions in producing food is the low quality of soil due tothe rapid rate of soil degradation, as a result of hightemperature and rainfall. Because of the large amountand high intensity of rainfall in the humid tropics, soil
erosion can potentially reach dramatic levels in thisregion (El-Swaify et al., 1982; Lal, 1990), therefore thesoil quality will decrease rapidly. Decrease in soil quality
both physically and chemically occurs at a high rate dueto the high rate of soil loss, soil organic matter, nutrients,
as well as damage to soil structure and compaction
process. The above conditions occur because in general
the existing agricultural cultivation or conventional
agriculture is less attention to soil conservation aspects
and this is not only happening on the farmland but also
occurs in plantation companies.
In order to minimize or reduce the rate of soil
degradation due to high rainfall and solar heat in thehumid tropics, alternative agricultural cultivation
technology is needed to pay more attention to soil
conservation aspects, among others by reducing soil
tillage or minimum tillage (MT) and another alternativeis that with no-tillage technology (NT). Both of thesecultivation technologies can be referred to as aconservation tillage (CT) or conservation agriculture
because they do not modify soil layers intensively,
therefore it will not alter or damage the soil structure.
Conservation tillage, the most important aspect ofConservation Agriculture, is thought to take care of thesoil health, plant growth and the environment (Busari etal., 2015).
Through conservation tillage technology, besides not
too damage soil structure at the top soil, residue of theharvest that is spread over the soil surface could befunction as a mulch. The presence of mulch above the soil
surface is expected to reduce soil damage due to splash
erosion and surface Run-Off. Plant residues fromprevious crop season which are used as mulch isimportant in CT practices. This is not only because its
effectiveness in reducing soil erosion, but also inconverting the substrate to microbial biomass carbon(Wright and Hons 2004; Smith and Collins 2007; Utomo
et al. 2010). In addition, the mulch covering the soil
surface is expected to restrain the effects of solar heat sothat the microclimate on the surface layer will notoverheat which will further reduce the rate of oxidation ofsoil organic matter. By using mulch, soil temperature at 5cm depth could decrease between 5-9 °C and could
increase soil moisture content (Kamara, 1986).
This study aims to determine the changes that occur inthe morphology and soil properties after the difference ofland management for 20 years.
2. Material and Method
This research was conducted on Reddish Brown Latosol(Udult) derived from andesitic volcanic rocks thatoriginating from Mount Betung in the Southern part of
Sumatra Island, Indonesia (Mangga et al., 1993). Soils
had been managed for 20 years since 1987 with 3 types ofmanagement, the first treatment was the intensive tillage(IT), the second was the minimum tillage (MT), and thethird was no-tillage (NT). The cereal-legume-fallow
rotation sequences were set each year. Plot size of thislong-term experiment was four by six meters (Utomo etal. 1989). In the IT plot, prior to planting, the soil was
plowed twice, while all weeds and previous crop residues
were removed from the plots. In the MT plot, soil wasplow lightly at a depth of 0-5 cm by using a hoe. In NT
plots, weeds were sprayed with glyphosate at a dose of
4.8 liters per hectare. In CT plots (MT and NT), all deadweeds and previous crop residues were used for mulch
covering the soil surface, while in IT plot, all weeds andprevious crop residues were removed from the plots(Utomo et al., 2013). Nitrogen source for the N treatment
was Urea 46% N. Nitrogen fertilizer application wasapplied as hand banding in the row close to the crop. A
week after planting, P and K fertilizers at rates of 100 kg
SP-18 ha-1 and 100 kg KCl ha-1 were applied as basal
fertilizers, respectively (Utomo et al. 2010).
Soil profile was dug in the middle of each plot, thensoil profiles were described and sampled according toProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 03

Soil Survey Division Staffs (1993). Soil color wasdetermined by Munsell Soil Color Charts (Macbeth a
Division of Kollmorgen Corporation, 1975). Disturbed
soil samples were taken for analyzing soil texture by
pipette method (Gee and Bauder, 1986) and soil
chemical properties. Soil chemical properties include
organic carbon content (Walkley and Black); total
nitrogen (Kjeldahl), pH in H2O with ratio of 1:2.5 (pHmeter); Exchangeable bases, soil CEC extracted by 1 N
NH4OAc. at pH 7.0, and exchangeable Al & H extracted
by 1 N KCl were measured by AAS. Undisturbed soil
sample was taken through sample ring with a 2 inches
diameter to analyze Bulk Density by the core method(Blake and Hartge, 1986). Soil strength in each soil layer
was measured using a pocket penetrometer (Unconfinedcomp. strength ELE).
3. Result and Discussions
3. 1

Soil Morphology

3. 1. 1 Soil Horizons
From soil surface to a depth of 150 cm, there is adifference in the number of soil horizons, IT pedon has 6
soil horizons, MT pedon has 5 soil horizons and NT has 4soil horizons. Differences are also found in the thicknessof the surface horizon where the surface horizon of the IT
pedon (18 cm) is thicker than that of both CT pedons (15cm). This happens because the soil plowing reaches adepth of 18 cm on the IT pedon.
3. 1. 2 Soil Color
There is a gradual difference in soil color on the surface
horizon where the soil color on the IT pedon (7.5 YR 3/4)
is slightly lighter than the CT pedon (7.5 YR 3/2) which ischaracterized by the higher chroma. Although there is adifference in the soil color, all of the three pedons havethe same class that is the dark brown color (Table 1). The
soil color difference on the surface horizon is due to thedifference in soil organic carbon (SOC) content, where
the SOC content on the upper layer of the IT pedon(1.42 %) is less than the two CT pedons (Table 3).
Between the two pedons CT, the soil C-organic content
on the surface horizon on the NT pedon (1.60%) was
higher than that of the MT pedon (1.53%) (Table 3).

soil aggregates will rupture become smaller. In the subsoil
horizon, soil consistency in the IT pedon has a thicker
layer of firmly soil consistence, while the NT pedon has
no firmly soil consistence (Table 1). The presence of alayer of soil that has a firm consistency will inhibit thegrowth and development of plant roots. The very
thickness of a firm layer of soil on the IT pedon will
inhibit the development of plant roots.
3. 2 Soil Physical Properties
3. 2. 1 Soil Texture
All three pedons have the same texture class that is clay.
The content of clay particles in the soil surface layers
ranges from 55-58%, while at the bottom layer ranges
between 80-88%. Differences in clay content is actuallyfound in the second soil layer, where the content of clayon pedon NT is much higher than the other two pedons.
This may occur because of the more open topsoil on the
IT pedon as a result of intensive soil tillage can promote
the leaching processes of clay particles running more
intensive than in NT pedon, therefore the clay content in
the second layer of IT pedon is the least.
In IT pedon, more open soil in the surface layer due
to low BD and without mulch cause the penetration ofrain water becomes higher. With such condition, it will
be conducive to the leaching of clay particles. In addition,
the opening of soil without mulch and higher macro porespace on the soil surface layer causes better aeration, sothat the exchange of air and heat from sunlight allow toenter the deeper layers of the soil. This condition could
cause the adhesiveness of granules become stronger,
consequently the consistency of the soil becomes more
firm (Tabel 1) and the BD value becomes higher (Table 2
and Fig 1).
3. 2. 3 Soil Strength
In line with the soil texture, BD and soil consistency, thehigher the clay content cause the BD value will increase
and the soil consistency will be stronger, then this willcause the soil strength is also stronger. Figure 2 showsthat the soil strength in the lower layer of IT pedon
stronger than pedon CT. The stronger the soil strength
will further inhibit the growth and development of plantroots.

3. 1. 3 Soil Structure
Soil structure on the surface layer of soil on the two CT
pedons have the same shape of structure that is Crumb,while the IT pedon has shown a change toward to theform of angular blocky (Table 1). The change is certainly
related to the reduced content of soil organic matter(SOM) (Table 3). According to Busari et al. (2015),
implying yearly practice of no-till system over a long
period of time, is beneficial to maintenance andenhancement of the structure and chemical properties ofthe soil, most especially the content of soil organic carbon.
3. 1. 4 Soil Consistence
The topsoil on the IT pedon has a more friableconsistency than both CT pedons (Table 1), because soil
plowing could dismantle the chunk of the soil, therefore

Fig. 1 Bulk Density distribution in the three pedonsProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 03

Fig. 2 Soil Strength of three pedonsFig. 4 Organic Carbon and Total Nitrogen of the threepedonshigher than the two CT pedons. Al cation is the soil
acidity potential that is able to release H + into the soil
solution consequently the soil becomes more acid.

3. 3. 2 Soil organic carbon and total nitrogen
Up to a depth of 100 cm, the soil organic-C content on the
IT pedon is lower than that of both CT pedons, while thetotal-N content of the IT pedon is lower to 60 cm from thesoil surface (Figure 4). The data of soil organic-C on thesurface horizons of the three pedons indicates that the CT
treatment is more capable to conserve the soil organic
matter content in the soil surface layer than the IT
Fig. 3 Soil pH, Exchangeable Al and H

treatment. Meanwhile, among CT treatments showed thatof the three pedons

NT treatment was more able to conserve the soil organic
matter content in the soil surface layer from loss through3. 3 Soil Chemical Properties

erosion, leaching, or from the oxidation processes.

3. 3. 1 Soil pH and potential soil acidity
The pH of the soil surface layer on the IT pedon is lower

Between the two pedons CT, the soil organic-C content
on the surface horizon on the NT pedon (1.60%) was

than that of the two CT pedons, while the soil pH on thehigher than that of the MT pedon (1.53%) (Table 3). The

NT pedon is less than the MT pedon (Figs. 3 and 3). This

presence of mulch as a soil cover could preserve the loss

is related to the exchangeable Al & H on the IT pedonof soil nitrogen either through evaporation,

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 03

3. 3. 3 Available Phosphate
Figure 5 shows that the available Phosphate of the NT
pedon higher than IT and MT pedons. As a static elementin the soil body, phosphates are generally more stable andis usually loss through surface runoff and soil erosion,
although water-soluble phosphates could be lost throughleaching process. The absence of destructive treatment tosoil surface layer causes NT system to better protect thesoil from phosphate loss through surface runoff, erosion,
Fig.5 Available Phosphate of the three pedonsor leaching process compared to IT or MT systems.
3. 3. 4 Soil CEC, Exch. Bases & Base Saturation
Figure 6 shows that the IT pedon has soil CEC, sum of
exchangeable bases and Base Saturation less than the CT
pedons. Both of the two CT pedons have the same Sum of
exchangeable bases, while the soil CEC of MT pedon ishigher than NT pedon, therefore the Base Saturation ofNT pedon is little higher than MT pedon. Natural weeds
can take nutrients from the deeper layers through theroots and brought to the canopy of the plant, then throughthe process of dead weed decomposition will releasenutrients to the topsoil. Through the nutrient cycles, thelonger it becomes, the higher the soil layer of nutrients
than the lower layers. Nutrient contribution through theweed cycle then could be utilized by the main plant.
Covering soil surface with natural weeds and its residues
in Coffee plantation had increased organic carbon content,
total nitrogen, soil pH, CEC, exchangeable calcium, as
well as decreased exchangeable Al and Al saturation insoil surface horizon (Afandi et al., 2003). Therefore, in
addition to the CT system can reduce the loss of soil and
SOM, it can also contribute plant nutrients andsimultaneously improve the soil chemical properties.
4. Conclusion
The results showed that the lower content of soil organic
matter in the upper layer of IT had cause the soil color
become lighter, which was characterized by higher
chroma. Soil structure on the top layer of IT changed
from crumbs toward to the angular blocky. The topsoil on
IT was more friable than two others, while the lower layerFig 6. Soil CEC, Sum of Exchangeable Bases and Base
Saturation of the three pedons

was more dense or compact shown by the higher BD,
stonger Soil Strength, and very thick firmly soil layer.
Generally, the chemical properties of CT were better thandecomposition of soil organic matter, or through leachingprocess.

IT, and NT was slightly better than MT, particularly at thesoil surface layer.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 03

5. References

Sidarto (1993) Geological Map of Tanjung Karang,

Afandi D, Wiharso, Senge M, Adawiah AJ, Oki Y andSumatera

Quadrangle,
Geological

Sumatera.

Adachi T (2003) The Change of Morphology in Red

1:1,250,000.

Acid Soil after Four Years Treatment of Cofee

Development Center, Bandung, Indonesia.

Scale

ResearchandPlantation with Different Weeds Management in a

Smith JL and Collins HP (2007) Management of

Hilly Area of Lampung, South Sumatra, Indonesia. J.

organisms and their processes in soils. In: EA Paul (ed).

Jpn. Soil Phys. No. 95: 55-62.

SoilMicrobiology, Ecology and Biochemistry. Third

Blake GR and Hartge KH (1986) Bulk density. In: A

Edition. Academic Press, Burlington, USA, 532 p.

Klute (ed.). Methods of Soil Analysis. ASA and SSSA.

Soil Survey Division Staffs (1993) Soil Survey Manual.

Madison, Wisconsin, USA:363-375.

USDA Handbook No. 18, Wahington DC.

El-Swaify SA, Dangler EW and Armstrong CL (1982)

Utomo M, Suprapto H, and Sunyoto (1989) Influence ofSoil erosion by waters in the tropics. University oftillage and nitrogen fertilization on soil nitrogen,

Hawaii, Research Extension Series 024, HITAHR,

decomposition of alang-alang (Imperata cylindrica)

College of tropical agriculture and human resources,

and corn production of alang-alang land. In: J van der

Honolulu, Hawaii.

Heide (ed.). Nutrient management for food crop

Gee GW and Bauder JW (1986) Particle size analysis. p.
383-411. In A. Klute (Ed.). Methods of Soil Analysis(Part I). Agronomy 9. Soil Sci. Soc. Amer., Madison,
WI, USA.

production in tropical farming systems. Institute forSoil Fertility (IB):367-373.
Utomo MA, Niswati, Dermiyati, Wati MR, Raguan AF,
and Syarif S (2010) Earthworm and soil carbon

Kamara CS (1986) Mulch-tillage effects on soil loss andsequestration after twenty one years of continuous

soil properties on an ultisol in the humid tropics. Soil

no-tillage corn-legume rotation in Indonesia. JIFS 7:

and Tillage Research. Volume 8, November

51-58.

1986:131-144
Lal R (1990) Soil erosion in the tropics: principles andmanagement. McGraw-Hill, New Yor.
Macbeth a Division of Kollmorgen Corporation (1975)
Munsell Color Soil Charts, 1975 Ed. 2441 North
Calvert Street, Baltimore, Maryland 21218.
Mangga SA, Amirudin T, Suwarti S, Gafoer, andUtomo M, Banuwa IS, Buchari H, Anggraini Y andBerthiria (2013) Long-term Tillage and Nitrogen
Fertilization Effects on Soil Properties and Crop Yields.
J. Trop. Soils, Vol. 18, No. 2, 2013: 131-139.
Wright AL and Hons FM (2004) Soil aggregation andcarbon and nitrogen storage under soybean cropping
sequences. Soil Sci. Soc. Am. J. 68: 507-513.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 03

Table 1 Soil Morphology of three pedons under diference
management
Typeof
Tillage

IT

MT

NT

Soil
Depth
(cm)
0-18

Soil
Horizon

Soil Color

Soil Structure

Soil
ConsistenceAp

7.5YR 3/4

Cr-Ab, vF, 2

vfr

18-27

AB

5YR 3/4

Ab, F, 2

fr

27-54

Bt1

5YR 4/4

Ab, M, 2

sf

54-82

Bt2

5YR 4/6

Ab, C, 2f82-128Bt3

5YR 5/6

Ab, M, 2f

128-147

Bw

5YR 5/8

Ab, M, 2

sf

0-15

Ap

7.5YR 3/2

Cr, vF, 2

fr

15-45

AB

5YR 3/4

Ab, F, 2

fr

45-82

Bt1

5YR 4/4

Ab, M, 2sf

82-112

Bt2

5YR 4/6

Ab, M, 2f

112-150

Bt3

5YR 5/6

Ab, F, 2

sf

0-15

Ap

7.5YR 3/2

Cr, vF, 2

fr

15-48

Bt1

5YR 4/4

Ab, M, 2sf

48-124

Bt2

5YR 4/6

Ab, M, 2sf

124-168

Bw

5YR 5/6

Ab, vF, 2

sfExpl.: Ab = angular blocky, Cr = Crumb, vF = very Fine, M = medium, vfr = very
frible, fr = friable, sf = slightly firm, f = firm

Table 2 Soil physical properties of three pedons under different management
Type ofTillage

IT

MT

NT

Soil
Depth
(cm)

Soil
Hor

Soil
Strength(Kgf.Cm-3)

Bulk
Density(g cm-3)

Soil Separates (%)
Sand

Silt

Clay

0-18
18-27
27-54
54-82
82-128128-147
0-15
15-45
45-82
82-112
112-150
0-15
15-48

Ap
AB
Bt1
Bt2
Bt3
Bw
Ap
AB
Bt1
Bt2
Bt3
Ap
Bt1

1.35
1.70
2.00
3.45
4.05
2.75
1.20
2.10
2.40
2.75
2.30
1.80
1.85

0.98
1.13
1.18
1.32
1.34
1.34
1.04
1.08
1.17
1.23
1.18
1.14
1.18

12.36
8.01
6.15
4.13
3.94
3.79
14.18
7.43
5.53
4.90
4.31
14.27
7.31

30.03
23.50
13.11
12.34
8.76
8.38
27.76
21.38
13.49
12.34
16.37
30.43
11.28

57.61
68.49
80.74
83.53
87.30
87.83
58.06
71.19
80.98
82.76
79.32
55.38
81.41

48-124

Bt2

2.75

1.24

4.17

10.55

85.28

124-168

Bw

1.95

1.16

3.90

8.43

87.67

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 03

Table 3 Soil Chemical Properties of the three pedons under difference soil tillage.

Avail. P
Type ofTillage

IT

MT

NT

pH H2O
(1:2.5)

OrgC (%)

Exch. Al
(cmol (+)

(cmol

.

kg-1)

(+) kg-1)

N (%)

Soil CEC-1

Total(ppm)

Sum

Exchangeable Bases

Exch. Hof(cmol (+) kg )BS
(cmol (+)

Exch.
Ca

Mg

K

Na

Bases

4.61

1.42

0.11

2.56

0.15

0.15

2.00

0.40

0.36

0.13

2.89

4.92

0.99

0.09

1.24

0.05

0.05

1.54

0.28

0.13

0.02

5.57

0.84

0.04

2.56

0.05

0.05

2.33

1.71

0.11

0.05

5.60

0.49

0.07

1.24

0.05

0.05

3.88

2.75

0.05

5.66

0.76

0.05

1.24

0.05

0.05

3.88

2.75

5.46

0.80

0.04

2.56

0.50

0.10

1.49

0.23

5.57

1.53

0.12

2.78

0.05

0.10

4.61

5.24

1.15

0.11

1.24

0.05

0.10

4.65

5.51

0.92

0.06

1.24

0.05

0.05

5.58

0.72

0.06

2.56

0.05

0.05

kg-1)

(%)

8.70

33.22

1.97

11.30

17.43

4.20

10.30

40.78

0.01

6.69

10.70

62.52

0.10

0.01

6.74

8.30

77.95

0.11

0.01

1.84

10.10

18.22

3.02

0.61

0.12

8.36

13.90

60.14

2.48

0.20

0.04

7.37

10.70

68.88

5.61

2.33

0.06

0.01

8.01

10.50

76.29

3.81

2.19

0.11

0.04

6.15

8.10

75.93

5.67

0.68

0.04

2.78

0.05

0.05

3.22

2.09

0.10

0.02

5.43

10.90

49.82

5.33

1.60

0.12

4.26

0.10

0.10

5.11

2.89

0.35

0.02

8.37

11.90

70.34

5.15

1.11

0.13

2.56

0.05

0.05

3.88

2.48

0.05

0.10

6.51

11.30

57.61

5.58

0.92

0.08

1.24

0.05

0.05

4.66

2.15

0.07

0.05

6.93

10.30

67.28

5.69

0.72

0.03

2.56

0.05

0.05

3.55

2.47

0.06

0.07

6.15

9.80

62.76

Expl.: BS = Base Saturation (%)

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 04

Application of bentonite to soil reclamation in drought areas of Ninh Thuan province,
Viet Nam○Nguyen Thi Hang NGA(Faculty of Water Resources Engineering, Thuy Loi University, Viet Nam)
SUMMARY
In this research, the potential of bentonite as a possible amendment for increasing nutrition and moisture retention of
sandy soils in Ninh Thuan province are investigated. The study was conducted with the pot experiments in thegreenhouse condition in 2016. Sandy soils were collected from grape cultivation areas in Vinh Hai, Ninh Hai District,Ninh Thuan province. After being dried at room temperature, they were mixed with bentonite in proportions of 0, 5, 10,
15 and 20% by dry weight. The soil mixtures were watered to field capacity (appro. 30,2% water) then soy bean planted
for 5 weeks without any additional water. The test results show that bentonite greatly affected the local soil
characteristic. Bentonite application increased the soil moisture retention and affected on pH, N, P, and K of soil. Sandy
soils amended with 10% or more bentonite were more moisture (approx. 15-18%) while they were 7,8-11,3% with the
mixtures containing less than 10% bentonite. Higher bentonite rates increased pH values to levels more suitable forgrapes (6,7-6,8). Application of bentonite up to 10% had no significant effect on soil N content. Extractable P increased
with addition of 5% bentonite for the soil. Bentonite application had no significant effect on the K content.

Introduction

the South of Viet Nam (approx. 350 million m3)

Ninh Thuan is located in south central coastal region of

Bentonite is a 2:1 clay mineral consisting mostly

Viet Nam where has been seriously affected by climateof montmorillonite, feldspar and crystalline quartz. Thechange leading to severe drought these days.

Water isspecial properties of bentonite are an ability to absorb

one of the most important factors for the growth of grape

large quantities of water, and a high cation exchange

crop,

area.

capacity, yet they have been effectively used forRepresentative soils in Ninh Thuan are acrisols (ultisols

agriculture parts, especially for physio-chemical soil

in USDA soil taxonomy) (Bat, L.T, 2000). Soils arecharacteristic improvement. Therefore, this research has

characterized by low pH, low fertility, and light sandy

been focused on examination of the potential of

texture, low content of clay, and low water holding

bentonite as a possible amendment for increasing

capacity (Bat, L.T,2000). Therefore, prolonged drought

nutrition and moisture retention of sandy soils in Ninhsituation has been caused huge damage to soil

Thuan province, Viet Nam.

a

main

agricultural

crop

of

the

characteristics, deﬁciency of nutrients and grape products
as well.

Material and Method

To improve the low water holding capacity of soil, some

The study was conducted with the pot experiments in thematerials have been applied. In a previous experiment,

greenhouse condition. Fine bentonite was provided from

Ramesh et al, 2008 added ﬂy ash to cultivated soil in

Binh Thuan Mining Company in Southern Viet Nam.

semi-arid tropical alﬁsols. Abdel-Fattah and Mohamed K

The materials were tested for pH, organic matter (OM),

2012

reclaiming

phosphorus, available K, P and N using standardusedgypsumandcompostinsaline-sodic soils in Egypt. Masazumi Kayama, 2015

methods (Okalebo et al., 1993). Soil samples wereassessed application of Bentonite, Charcoal and Corncob

collected from Tri Hai commune, Hai Ninh District,for Soil Improvement and Growth Characteristics ofNinh Thuan province (11°38'44.98" N, 109° 4'30.47" E)

Teak Seedling Planted on Acrisols in Northeast Thailand.

from the depth of 0-50 cm. Then they were air dried,

Chandraka, Jenne D, 2015 studied on using fly ash on

crushed and sieved through a 2-mm sieve and analyzed

soil reclamation in acidic alfisoil to increase corn yield.

for physicochemical properties. Properties of materials

Research results displayed that using fertilizer andand soils used in the study are presented in table 1 and 2.

natural minerals could be effective methods to improve

To study the effect of bentonite on the characteristics ofthe low pH and poor fertility of soil in Ninh Thuan.

soils as well soil water holding capacity, natural soil

However, there has been no research examining

were sampled at 0 to 50cm depth. The soil samples were

improvements water holding capacity of soil so far.

dried for 7 days at room temperature. Soil was thenBentonite, natural clay mineral resources are available inground and sieved through a 2 mm sieve and analyzed

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 04

for soil moisture, pH, organic matter (OM), phosphorus,

Result and Discussions

K+, N and particle size distribution using standard
methods (Okalebo et al., 1993).
In the greenhouse, 10 kg of air-dried soil were put in

Effects of Bentonite on soil moisture
The results indicated that there was appreciable change

experiment pots. Bentonite was added to the soils within water holding capacity of soil samples when bentonite

rate of: 0, 5, 10, 15 and 20%, respectively. After agitation,

was added (fig.1). Soil water content increased

deionized water (1 L) was added to each pot containing

significantly (P<0.05) with the amount of bentonite

the soil-bentonite mixtures, representing approximately

added to soil. Soils amended with higher than 10% of

30% moisture. The mixtures were left in a greenhouse at

bentonite received more moisture soil (approx. 15-18%)o

27 to 32 C for 5 weeks, and sampled every after one

while they were 8-11.3% with the mixtures containing

week (7 days). No more water was added to the mixturesless than 10% bentonite.

during the entire 5-week period. The samples were driedcapacity increased along the soil depth up to 45 cm andoSimilarly, the water holding

at 105 C for moisture determination. At the end ofthen decreased. The increase in water holding capacity inexperiment period, soil at each mixture pot was collectedsurface and sub-surface soil with bentonite combination

for determination of pH, OM, available P, K and N.

with soil in treated plots might be due to alter in soil
texture by having more silt and clay content, increase

Table 1
Fraction

micro-porosity and hence, improve the water-holding

Physic chemical characteristics of bentonite
Clay %(texture)

Fine

CoarseFine

Coarsesilt %

silt %

sand %

sand %

72.6

8.3

4.7

4.7

4.2

Elemental

Al2O3

SiO2

CaO %

MgO

Fe2O3

oxides

%

%

%

%

18.5

59.3

9.97

0.44

1.92

capacity (Jones CC and Amos DF, 1976); (Garg RN,
Kalra N and Harit RC, 2003).
Effects of Bentonite on soil chemical properties
Table 3 and fig.2-5 present the effects of bentonite
application on soil properties during the experimentperiod. Application of 5% bentonite significantly(P<0.05) increased the soil pH by 3.5-6. Higher

Table 2 Physical and chemical properties of the soils at
the initial stage

bentonite rates maintained higher pH values in the soils.
The increase in pH over bentonite application might be

Property

Soil

Soil

Soil

due to increase in basic cations. The CaO of bentonite

1

2

3

might have interacted with water in the presence of CO2

Clay

22.3

20.8

23.6

solution and the carbonates are precipitates. These

Silt

7.9

8.2

8.6

reactions and the presence of Na, would explain the high

Sand

69.8

71.0

67.8

pH value (Kuan, Y.H.; Liong, M.T, 2008); (Karanasios, E

Particle size distribution [%]:and produced hydroxyl and other ionic forms in the soil

Soil moisture characteristics [%]:

et al, 2012).

Saturation percent

59.4

58.6

59.1

Field capacity

30.4

29.8

30.1

Wilting point

13.2

12.6

12.8

Bulk density [Mg.m-3]:

1.62

1.58

1.61

Total porosity [%]

51.2

50.2

49.8

CEC (cmolc kg-1)

18.3

20.2

19.8

pH [Soil suspension 1:5]

6.3

6.2

6.2

Organic matter [%]

0.88

0.93

0.96

Available N-NH4+ (mgkg )

23.6

22.6

22.8

Available P (mgkg-1)

42.4

38.5

40.4

138.7

134.6

137.3

-1

-1

Available K (mgkg )Fig. 1

Effect of bentonite use on soil moistureProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 04

Table 3 The physical and chemical properties of soil at
the final stage
BentonitepH

added %OM

Avail.N

Avail. P

Avail.K%(mg/kg)(mg/kg)(mg/kg)

42.4

138.7

Soil 1
0

6.3

0.88

23.5

5

6.4

0.87

23.3

43.6

137.9

10

6.4

0.88

23

44.1

137.1

15

6.6

0.9

23.1

44.5

137.9

20

6.7

0.87

22.9

45.9

137.5

0

6.2

0.93

21.6

38.5

134.6

5

6.3

0.92

21.4

39.1

135.3

10

6.4

0.94

21.8

40.4

134.9

15

6.5

0.93

21.6

42.3

135.1

20

6.7

0.94

21.4

44.1

134.8

0

6.2

0.96

22.4

40.4

137.3

5

6.4

0.96

22.5

40.9

138.2

10

6.4

0.95

22.6

41.2

137.1

15

6.6

0.94

22.3

43.6

137.9

20

6.7

0.95

22.2

44.2

137.7

Soil 2
Fig. 4 Effect of Bentonite use on availble P in soil

Soil 3Fig. 5 Effect of Bentonite use on availble K in soil
Application of bentonite up to 10% had no significant
effect on soil N content. Higher rates of bentonite (15 &20%) slightly decreased soil nitrogen content (P<0.05).
There was a significant (P<0.05) increase in Mehlich III(Mehlich, 1984) extractable P with addition of 5%
bentonite for all soils. A further significant (P<0.05)
increase in Mehlich III extractable P was observed forhigher rates of bentonite applied (44.1-45.9 mg/kg).
Fig. 2 Effect of Bentonite use on soil pH

Bentonite application had no significant (P>0.05) effecton the K content of the soils even over 10 % bentonite
was mixture (Fig 3,4,5).

Conclusion
Bentonite has a high cation exchange capacity and would
be expected to have high water nutrient retention
capacity for agriculture. Application of bentonite brings
great benefits for sandy loam soil in Ninh Thuan, Viet
Nam. The test results show that bentonite greatly
affected

the

local

soil

characteristic.

Bentonite

application significantly increased the soil moistureretention and affected on pH, N, P, and K of soil. Sandy
Fig 3. Effect of Bentonite use on availble N in soil

soils amended with 10% or more bentonite were moremoisture (approx. 15-18%) while they were 7,8-11%

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 2 - Soil Science -: 04

with the mixtures containing less than 10% bentonite.
Higher bentonite rates increased pH values to levels
more suitable for grapes (6.7-6.8). Application of
bentonite up to 10% had no significant effect on soil N
content. Higher rates of bentonite (15 & 20%) decreased
soil nitrogen content. Extractable P increased withaddition of 5% bentonite for the soil. A further
significant in P content was observed for higher rates ofbentonite

applied.

Bentonite

application

had

no

significant effect on the K content of the soil. Thus
bentonite presents promising reclamation ability forsandy soils with low fertility in drought areas in climatechange condition in Viet Nam.

Acknowledgement
We thank Institute of Soil and Fertilizer, Viet Nam forhaving offered greenhouse experiments and also Mr. Vu
Huy Dung from Thuy Loi University for providing
bentonite material.

References
De Lucia B, Cristiano G (2015) Composted amendment
affects soil quality and hedges performance in the.

Mediterranean urban landscape. Compost Sci. Util., 23,
48–57.
Garg RN, Kalra N and Harit RC (2003) Fly ash
incorporation effect on soil environment of texturally
variant soils.
Jones CC and Amos DF (1976) Physical changes in
Virginia soils resulting from additions of high rates of
fly ash. In: Faber JH, Babcock AW, Spencer JD,
editors. Proceedings of the 4th international ash
utilization symposium US Energy Research
Development
Administration
MERC/SP-76-4,
Morgantown, WV; 1976.
Karanasios E, Papadi-Psyllou A, Karpouzas DG,
Tsiropoulos NG (2012) Optimization of biomixture
composition and water management for maximum
pesticide dissipation in peat-free biobeds. J. Environ.
Qual., 41, 1787–1795.
Kuan YH, Liong MT (2008) Chemical andphysicochemical characterization of agrowaste ﬁbrousmaterials and residues. J. Agric. Food. Chem. 56:
9252–9257.
Le Thai Bat (2000) Soil in Viet Nam, Association of Soil
Science of Viet Nam Publication.
Mehlich A (1984) Mehlich No. 3. Soil test extractant: A
Modification of Mehlich No. 2. Extractant. Commun.
Soil Sci. Plant Anal. 15:1409-1416.
Okalebo JR, Gathua KW, Woomer PL (1993) Laboratory
Methods of Soil and Plant Analysis: a Working
Manual. TSBF, Nairobi.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 01

The Evaluation of Watershed Condition of Sumani Based in Solok Regency
Based on Land Characteristic○Delvi Yanti，Khandra Fahmy, Isril berd, Fery Arlius(Faculty of Agriculture Technology, Andalas University, Indonesia）
SUMMARY
The functions of watershed have decreased from year to year as a results of environmental degradation.
Uncontrolled land use without regard to soil and water conservation leads to increase erosion and sedimentation,
decreases of vegetation cover, and accelerates of land degradation. This study was conducted at watershed of
Sumani, Solok Regency, West Sumatra. Analysis of watershed conditions used scoring and weighting methods. The
parameters used in this study referred to Regulation of the Forestry Ministry of Indonesia number .P.61 / Menhut-II /2014 including critical land, vegetation cover, and erosion index. The results of study show that watershed condition
based on 2016 data was very bad category, with the class for each parameter was very high (critical land), very bad(vegetation cover), and very high (erosion index). Watershed conditions are closely related to watershedmanagement systems. Increased demands on natural resources (water, land and forests), cause changes to thewatershed conditions.

Introduction

The data used in this study are secondary data

Watershed has a function to accommodate, store, andconsisting of Sumani watershed map, satellite image,drain of water from rainfall to the lake or to the sea

slope map of sumani basin, soil type map, soil solum

naturally. The functions of watershed from year to year

map, DEM / SRTM data, rainfall data (10 years) fromhave decreased, as a result of watershed environmental

each nearest station in DAS Sumani.

degradation. It was caused by significant change of land

The study was conducted by using scoring anduse, population growth, and lack of public awareness ofweighting method. Indicators and parameters forwatershed conservation.

watershed environmental sustainability of land criteria

Sumani basin which located in Solok experienced

based on Minister of Forestry Regulation No.P.61 /degradation of its function. The Lembang and Sumani

Menhut-II / 2014 including the critical land, erosion

are the rivers across this Basin which face the problem ofindex, and vegetation cover.

water shortage and low water quality due to the highsediment. It was occurred due to forest clearing forResult and Discussions

expansion of agricultural areas and vegetable plantations(Farida et al., 2005). It can be seen from the fluctuation

The Critical Land
The characteristics of land in Sumani Watershed of Solokof debit (flood or drought) in two rivers that cross theRegency (Table 1) were dominated by agricultural land

Sumani Basin.

(29.35%), rice field (25.72%), and mixed plantation

The condition of a watershed is closely related to thewatershed

management

system.

The(17.19%). Land use was closely related to people's

watershedlivelihoods. Based on the data of Solok District BPS in

conditions from land aspects can be seen from critical

2015, the population whose field of business inland conditions, vegetation cover and erosion rates. The

agriculture, forestry, hunting and fishery were 59.72% ofobjectives to be achieved were: to know the condition of

the total number of people in working age (15 years andthe Sumani Basin from the land aspect so that it can beabove).

assessed to the management system.

Based on Permenhut No. P. 61/Menhut-II/2014, thepercentage of critical land is the ratio of critical land area

Material and Method

to the width of the watershed, which the critical land isThis research was conducted at Sumani Basin of Solokcritical and highly critical land.

Regency with wide of 58,330 Ha. The location of theTable 1 shows that 30.85% of the total area of DAS

Sumani Basin is located at 100032'41 "EL- 100040'40"

was at a very critical land level around 17,996.76 ha, andEL and 0042'17 "SL-002'2" SL, which is located at anland in critical condition of 14.10% or around 8,222.14

altitude of 300-2500 m above sea level.

ha. The distribution of land criticality is also presented In

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 01

Figure 1, so that the percentage of Critical Land (PLK)

ArcGIS, the erosion value was 2,160,431,790 ton/year or

was 44.95%.

37,038.09 ton/ha/year. While the value of Tolerable Soil
Loss (TSL) obtained was 1,749,900 ton/year or 30 ton/

Table 1 Distribution Data of Land Critical Level ofha/year, then the value of erosion index was 1,234,603. It

Sumani Watershed in Solok District.

could be concluded that the erosion occurring in Sumani
District

of

Solok

Regency

was

to

very

high

classification.
Vegetation CoverClosure of vegetation on a land describes the use of theland. Data of vegetation cover with permanent vegetation
was obtained from secondary data of image identification,
the cover of vegetation cover of Sumani River Basin.
Permanent vegetation analyzed was annual crop, in theform of forest, shrub, and plantation. The area of
permanent vegetation in Sumani District of Solok
Regency was 23,905.14 ha, the percentage of Vegetation
Closure (PPV) is 40.98%, which was classified as amoderate.

Conclusion
Based on the analysis of Sumani Watershed condition of
Solok Regency was in very bad condition. Watershed
conditions are closely related to watershed management
Fig.1 Map Distribution of Land Critical Level on Sumani

systems. Increased demands on natural resources (water,

Watershed of Solok Regency

land and forests), cause changes to the watershed
conditions. The very poor watershed condition describes
the watershed management system was also in a very
bad category. It has been directly illustrated that theutilization of the Sumani River Basin of Solok regency
does not pay attention to soil and water conservation
rules, causing the increase of critical land, decreasing
vegetation cover, and increasing erosion hazard.

Acknowledgement
Thank you very much to Faculty of Agricultural
Technology, Andals University for supporting thisresearch.

Reference
Fig.2 Distribution of Erosion Danger Level of Sumani
Watershed in Solok Regency.
Erosion Index
The erosion occurring in Sumani Watershed of Solok
Regency varies from very mild to very heavy, as shownin Figure 2.
Based on the calculation of erosion result using

Arsyad, S. (2010). Konservasi Tanah dan Air. IPB Press
edisi kedua. Bogor.
Asdak, C. (2010). Hidrologi dan Pengelolaan Daerah
Aliran Sungai. Gajah Mada University Press Edisi
Kelima. Yogyakarta.
Farida et al. (2005). Penilaian Cepat Hidrologis:
Pendekatan Terpadu dalam Menilai Fungsi Daerah
Aliran Sungai (DAS). Bogor: Rewarding Upland Poor

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 01

for Environmental Services (RUPES) Program World

P.04/V-SET/2009 Tanggal: 05 Maret 2009 Tentang

Agroforestry Centre (ICRAF).

Pedoman Monitoring dan Evaluasi Daerah Aliran

Menteri Kehutanan. (2014). Surat Keputusan Menteri

Sungai. Jakarta

Kehutanan P. 61/Menhut-II/2014. Tentang Monitoring[BPS] Badan Pusat Staistik Kabupaten Solok. (2015).

dan Evaluasi Pengelolaan Daerah Aliran Sungai.

Banyaknya Penduduk 15 Tahun Ke Atas yang Bekerja

Jakarta.

Menurut Lapangan Usaha Tahun 2015. Solok.

Menteri Kehutanan. (2009). Peraturan Direktur Jenderal
Rehabilitasi Lahan dan Perhutanan Sosial Nomor:[https://solokkab.bps.go.id]

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 02

Wisdom Agriculture Application in Oil Palm Industry for Promoting Healthy Soil andEmission Reduction○Muhammad MAKKY1*，Delviyanti, Isril BERD
( 1Dept. of Agricultural Engineering, Andalas University, Indonesia)*
E-mail: muh_makky@yahoo.com
SUMMARY
Researches in bio-robotics fields have been done en-masse. Development in intelligence monitoring systems for
agricultural application have unfold the possibility to observe individual plant response upon receiving external stimuli.
In this study, artificial Bio-pores, 30 cm in diameter, were introduced to the ranges of oil palm trees in three commercial
plantations. Various applications methods of Bio-pores, in particular depths and numbers per plant were investigated.
The Bio-pores drilled around the root zone of the trees using an earth auger, and filled with chopped semi-decomposed
fronds and midribs from the plantation maintenance (pruning). A robotic quadcopter drone with 2.7K camera, operated
with pre-set flight-plan, employed to record the crown image of oil palm trees under observation. The drone flown at
the altitude of 23±0.1 meters above the crown, recording each crown individually. Focus and setting of drone’s cameras
was set to automatic, enabling unbiased image recording. The weather conditions (sun radiation, cloud covering, wing
speed) upon images recording were measured and recorded. When recording the images, the drone’s GPS-assisted
hovering system maintained its position in both axes (horizontal and vertical), producing identical image acquisition foreach crown. All plants’ crown was observed at 0, 30, 60, and 120 days after Bio-pores introduced. Image processing
software was developed to segment and extract vegetation index (Vis) information from the images. Plants’morphological conditions (height, radial, and new leaf) were measured and analyse by statistical methods to understandvarious Bio-pores applications influences to plants development. Crown images were processed, and its features
extracted and correlated with chlorophyll in leaves. Models developed to predict chlorophyll contents (A, B, and Total)
in crown and Vis analyses methods were used to compare individual plant responding to this external stimulus by meansof rotational-pivot charts. Results showed that intensive Bio-pores introduction promote plant’s radial development andthe emergence of new leaves. Furthermore, chlorophylls contents in leaves of plants with substantial Bio-pores
applications were greater compared to normal plants. Models showed that optical features extracted from crownimages obtained high coefficient of correlation (R2) with leaves chlorophyll contents. This study has paved the way for
wisdom agricultural application in Indonesian oil palm industry. The results may be integrated into the emission
reduction program in Indonesia.
Keywords:Oil Palm; Bio-Pores; Intelligent Plant Monitoring System; Vegetation Indices; Drone; Wisdom Agriculture.

Introduction

production

Palm oil and its derivative products are among

intensification of oil palm production, particularly

Indonesia's most profitable commodity. Since 2006, it

through increased crop productivity [5].

became the leading export products, replacing other

While new-breeds specific genetic-modified cultivars ofagricultural shipments [1]. Annual world consumption ofoil palm can yield up to 42 tons per hectare [6] whenoil products is growing, in particular from emerging

accompanied by excellent plant management, in general,

world economy (i.e. India and China) [2]. In order tomost of the aging oil palm trees in Indonesia are Marihat

maintain their world market share, Indonesian oil palm

cultivar, planted in early 1990s [7]. These trees required

industry exercising any plausibly action to expand theirmore luxurious application of fertilizers, to decelerate its

production.

declining productivity [8]. Nonetheless, application of

Despite this opportunity, the Indonesian government took

synthetic fertilizers has restrictions, and over-fertilizationa drastic more pro-environment policy, issuing a

inhibitfive-year moratorium on new oil palm plantation

contamination due to leaching and waste of resources

concessions, limiting any further expansion [3]. The[9].

policy aimed to promote more sustainable oil palm

Among recent innovative methods adopted by oil palm

production practices while at the same time reducing

industry in Indonesia, the utilization of plantations andglobal criticism on environmental issues in Indonesia [4].

mills solid wastes to complement the enormous

As a consequence, the only option to increase oil palm

requirement for expensive synthetic fertilization in

in

plant

Indonesia

growth,isandthroughrisk

sustainable

environmental

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 02

plantation is the most preferable solution opted.

high-resolution tool to map the health condition in

Traditional method by scattering the wastes around theindividual palm trees [15]. In this study, similar low-costtrees is not efficient. Materials will be washed by rains,system was developed to enable smart monitoringand only minuscule amount can be utilized by the plants.

application for oil palm plantation in Indonesia.

Introducing artificial Bio-pores [10] in the vicinity ofThis research aimed to understand oil palm treesroots provide better access to water and nutrients for themorphological responds to various artificial Bio-pores

plants and enhanced plant growth. Previous study

introduction. Moreover, an intelligent monitoring systemsuggests that large Bio-pores provide favourable

was developed to observe the trees crown, and quantified

environment for roots to grew better, and when it filledthewith decomposed organic materials would be benefits fornon-destructive manner. The study will pave the way forsecuring extra water and nutrients for the plants [11]. The

wisdom agriculture adoption in Indonesian oil palmchange of the environment influences different plant

industry.

chlorophyll

content

inits

leavesthrough

responds, (i.e. stomatal conductance, cell expansion, cell
division, and rate of leaf appearance) and in nature

Material and Method

attuned the growth and development of a plant [12].

The study performed at three oil palm plantations,

Altering soil conditions, by means of Bio-pores, may

located in West Sumatra, Indonesia. The first site locateddeliver various plants responds. The results may notin Kinali district (-0.0867332, 99.8860441), while thereadily be explained [12]. The implication of bio-poressecond and third location were in Bawan (-0.1703710,

influence is still not understandable, especially in terms

99.9493757), and Manggopoh district (-0.2824046,

of the ability of the plants to absorb nutrients and water.

99.9597891). The elevations in all location range

In common, this nature can be explained as feedforward

between 100 to 150 meter above sea level. On the firstreaction, and observable through the alteration in leaves

site, the soils are Alluvial, while the Andosols and Peatappearances. Abiotic stimulation produces immediatesoils present on the second and third locations

symptoms in leaves such as wilting or withering, andrespectively [16]. The trees samples were 8 to 20 years,

visually observed. Change of leaf colour is caused by the

represented equally as samples in all three location. The

chlorophyll breaks down, and subsequently followed bysamples cultivars are Marihat, produced by IOPRI [7].

other chemical changes. Chlorophyll play important roleAllin photosynthesis process. It is considered as the main

telecommunications technology networks (EDGE andvegetation indices to predict the productivity of plants

GPRS) [17].

[13].

The trees were cultivated according to the standard of oil

Chlorophyll content can be easily determined by means

palm plantation [18]. Fertilizer applied at minimum level,of non-destructive methods using device such as

half of normal application doze (Urea, KCL, Kieserite,demo-plots

coveredbywirelessmobileChlorophyll Content Meter. This device is accurate andSP-36,

reliable for in-situ measurements. In addition, it isMagnesium, Boron). The application done six months

proven for non-destructive

prior to the experiments.

chlorophyll

content

evaluation formeasurements,

in-situbesideBorax,

Sodium,Phosphorus,

Potassium,

its

The Bio-pores created by drilling the soil around theuser-friendly features. However, for tall trees, such as oil

perimeter of critical root zone, using an earth auger (MSpalm, the method is not practical and require much

520+

efforts. Mature oil palm trees can grow up to 20 meters

centimetres from the stems’ centre axis (Figure 1). Thishigh and provide great challenge for manual chlorophyll

distance is set according to the average half-way spacemeasurement using such device.

between two adjacent trees. The Bio-pores drilled at

On the other hand, development in intelligencevarious depth (30, 60, and 80 cm), representing upper,

monitoring systems for agricultural application havemiddle and lower root zone. The factors were setup in

unfold the possibility to quantify chlorophyll content inorder to see different plants respond. In addition, theplant. The system employed unmanned aerial vehicle

second factor in this study was set by differentiating the(drone) equipped with camera or other sensing devices

number of Bio-pores applied per tree (1, 2, and 4 holes),[14]. Other intelligence monitoring systems utilized

in order to observe how the plant, respond to different

airborne hyperspectral imaging to provide a sensitive andBio-pores density. After drilled, the holes were filled

300mm,

Tasso,

PRC),

approximately

450

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 02

with chopped semi-decomposed midribs and fronds,

The samples were placed according to the Randomized

obtained from the pruning process, with density of 0.6

Completekg.cm-3. These bio-material wastes normally placed

agricultural experiments. The field is divided into units

around the oil palm trees in oil palm plantation, andto account for any variation in the field. Treatments are

slowly decomposed naturally, allowing additional carbon

then assigned at random to the subjects in thestocks to the soils. In this study, the decomposition

blocks-once in each block.Prior to the Bio-poresprocess of the bio-materials performs naturally without

application, each individual tree’s crown was recorded,

any bio-activator addition. Each Bio-pores treatments

using ultra-high definition digital-camera, suspended

were replicated 5 times.

below a robotic quadcopter drone. It flown above the tree

In order to avoid interplay between plants and Bio-porescrown, positioned at the crown centre, and subsequently

treatments, each sample was punctuated by untreatedrecord the image, while the camera is set perpendicularly

trees. In total, 150 oil palm trees were used as samples intoward the ground. The drone's camera-view was set tothis study, and arranged according to Table 1. Control

cover the whole crown spread (from dripline to dripline),plants were specified at each study site, and selectedenable image recording for all parts of the crown. The

randomly, five trees per location (Table 1).

drone position upon recording is set at 23 ± 0.1 meter

Blockdesign,astandard

designforabove the ground. The drone equipped with a built-in
camera2.7k

withComplementary

Metal

Oxide

Semiconductor (CMOS) image sensor. The sensor iscoatedwith

Bayer-filter-mosaic

in

the

form ofcolour-filter array. The filter produces red-green-blue(RGB) colour picture, with resolution of 2704 by 1524
pixels [19]. The Bayer pattern filter mosaic-sensitive
4.5 m

4.5 m

utilized luminance and chrominance-sensitive elements

4.5 m[20]. The camera’s image sensor is layered with Ultra= 30 cm= 60 cm= 80cmViolet and infra-red filter glasses in order to avoid
false-colour image produce by the sensor.
The drone operated with the pre-set flight plan to record
the crown of trees under observation. Each plant’s crown

Bio pore(s)Crown of Oil Palm Tree

Fig. 1. Bio-pores application arranged in the demo-plot.
For each location, 5 demo-plots, with 36 samples plants
per plot, were setup. In total, there were 15 demo plots forthis study. The experiment was set up as a randomized
complete block design (RCBD) with five replications foreach object. In this study, artificial Bio-pores prepared inthree different depth; 30, 60, and 80cm.

recorded individually, using drone’s stabilized 3-axis
rotating camera. Upon recording, the location recordedby the drone’s Global Positioning System (GPS), withaccuracy up to ±0.1m (vertical) and ±0.3m (Horizontal)[21] the information included in the image as
geo-location data.
Focus and setting of the camera were set auto-mode, for
producing consistent image recording results. Auto whitebalance in camera’s sensor was set to compensate

Table 1 The randomized complete block design for thedifferent intensity and colour of sunlight during

bio-pores application in each location

recording. The setup enabling drone’s camera chromatic

Treatment Bio-Pores (30 cm Diam.) Number of Samples
Sites
Depth
Density(cm)(per plant)
1
2
3
-*
-*
Control
5
5
5
1
30
1
5
5
5
2
5
5
5
4
5
5
5
2
60
1
5
5
5
2
5
5
5
4
5
5
5
3
80
1
5
5
5
2
5
5
5
4
5
5
5
*
Assigned as control

aberration and lens distortion to be reduced by 56% and
36% respectively [22]. Each crown recorded three times,
and the best image produce among them was selected.
The drone controlled remotely using an Android™ based
mobile-phone (Asus, Zenphone 2, Taiwan). Android (Ver.
6.0.1) [23] mobile application software platform (DJI,
USA) in the phone provide live-view option, enables theoperator to directly observe the scenery viewed by thedrone’s camera. The image for each recorded crownProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 02transferred from the drone to the mobile phone through a

The leaves sampling used the 17th frond leaves of oil

wireless local area networking technology [24], based on

palm [41]. The selection of the 17th frond leaves for

the IEEE 802.11 standards [25-27]. The network uses 2.4

analysing the N status suggested due to its sensitivity togigahertz (12 cm) Ultra High Frequency (UHF) radio

indicate nutrient content [41]. Furthermore, the nutrient

bands [24]. The mobile phone itself can connect to thestatus in the 17th frond leaves provide better correlation

Internet via a wireless access point, mostly using

to oil palm production [42] compare to other leaves. The

wireless mobile telecommunications technology [28].

total chlorophyll content of the leaves samples

Using this connection, the crown images and its

determined using acetone extraction method describedgeo-information were uploaded to a cloud computing

by Arnon [43], Hiscox & Israelstam [44], andservice platform, whenever possible [28]. Using wirelessRichardson et al. [45].

and internet connection, remote access computer was set

The plants total chlorophyll content influences its

up to download these images. The retrieved file thenphotosynthesis rate [46], which correlated to theprocessed using a C# based programming to segment

productivity [47]. The chlorophyll content results fromobject and backgrounds in the image.

the measurements then compared with the leaf greenness

The surroundings conditions when the crown recorded

as observed by the drone camera.

are observed. The sun radiation was measured between

Plants morphological development was measured. Plant

16 and 17 MJ/m2. Climatic conditions relatively similarheight, stem diameter and number of fronds (leaves)in all locations, with precipitation measured between

measured and calculated every 30 days.

2372.3 mm and 3267 mm annually. All study locations

averaged over the replications for all measurements andaccommodated optimum growth conditions for oil palm

their mean were used in deriving relationships between

cultivation [29]. The wind speeds condition was

treatments. Duncan’s Multiple Range Test (DMRT;

measured between 2.5 and 3 m/s. While recording thep<0.05 and p<0.01) was used to detect significant

image, the GPS-assisted hovering system automaticallygrouping among treatments. The index of Plants

work to maintain drone flight position, both in horizontal

morphological development calculated based on the(±0.3m) and vertical (±0.1m) condition, thus image

differences of three morphological features observed inacquisition condition was similar for every crownthis study. The higher index indicating stronger positive

recorded.

influence on treatments to plants development, and

The trees crown recorded every 30 days for the next 120

selected as a reference for determining the best treatmentdays. The image recorded process with a developedon each study site.

Data weresoftware platform. The image processing softwaredeveloped

based

on

C#

programming

language,

Result and Discussions

segmenting object from the background, and extract

The plants growth was observed based on the changes ofvegetation indices information (RGB) from the images.

the leaves on the tree crown, stem radial increment, theThe vegetation indices selected based on the colour

stem high, and changes of the concentration of

response of the leaves, as observed by the drone camera,chlorophyll in the leaves. The oil palm trees arewhen recording the plants’ crown.

Arecaceae (Palmae), and its cylindrical trunk can growSeveral methods used for extracting and analysing

up to 75 cm in diameter, for old trees [48]. The tree canvegetation indices features in the image [30-31].

reach 25 m with ordinary increment up to 1 m.yr-1

Extractions and analyses methods [32-40] were used to[48-49].

compare every plant vegetation indices, from its crownIn this study, the trees morphological developments wereimages. A rotational-pivot chart created based on themeasured for 120 days. The observation to all samples

features data to explain the image texture for further

showed different plants responds according to theanalyses [33, 36-38]. The changes in crowns’ image

treatments (Table 2). In the first and second sites,

textures are used to understand how each individual plantsignificant stem growth (p <0.01) at 30 days after

copes with stimulation caused by the bio-pores

treatments were observed on plants with four 80 cm

introductions.

depth Bio-pores application. Significant growth also

For every crown, the leaves were analysed to estimate

observed in the first location when plants treated withchlorophyll content, corresponding to the plant N-status.

two 80 cm depth Bio-pores. However, in subsequentProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 02

observations, (days 60 and 120) the plants obtained

compared to the similar plants grown in Andosols andsimilar high with control. Thus, bio-pore application

Peat soils. Oil palm plants grown in both soils only

provided no significant influence to the plants height

produce 28.13% and 20% greater stem diameter growthincrement. According IOPRI [50] and Lubis [51], on

respectively compared to the control plants.

average,distinguished

In previous studies, stem radial growth in oil palm trees

morphological growth, and not necessarily influence tooccurred due to development of the meristem cells. This

the plants age (Table 3).

activity was more visible in their early development

In contrast to the stem growth, stem radial development

stages (age 6 to 9 yrs.) [41]. In this development stages,

has a strong correlation with the Bio-pores treatments

plants stem increased radially, in particular at the base

(Table 2). Bio-pores application promote acceleration ofsection. Previous studies suggested that the diameter ofradial stem increment in all sites. On the other hand,the stem can reach up to 60 to 100 cm [41, 50-52]. Thus,

density and depth of Bio-pores introduced to the sample

in this study, Bio-pores introductions on oil palm

plants failed to show a general trend. The acceleration ofplantations were able to stimulate an increase in radialradial growth can be observed at 30 days after

growth of the plants’ stems, up to 4.1 mm in 120 days,

application. In all experimental sites, most plants treatedequivalent to 123 mm per annum, 23% greater thanby bio pore(s) showed extended growth of stem diameter

average radial development of normal plants.

compare to control, with the exception of plants with

The oil palm belongs to the cocoideae species, and grows

single or two 30 cm deep bio-pores application in site 1.

actively throughout its life span. The leaves produced bydifferent

cultivars

have

Similarly, plants with single 60 and 80 cm deep

the plants every 12-14 days [41], from its primordial

Bio-pores, grow on the second site, did not produce

point. The spear-shaped leaves development requires twobetter radial increment compare to control. At 60 days,

years from initiation until fully grown. The healthy

most plants produce higher radial growth compare toleaves of the oil palm able to perform photosynthesis

controls, nevertheless, some plants only obtained similareffectively for 24 months, before it become degraded.

results to controls. Along with the observation time, theEach leaf is para-pinnate in form, and produced with aradial development was progressing. By the end of thisuniform

study, plants with higher density of deeper Bio-poresenvironmental factors, in particular precipitation and soil

produce significantly larger stem diameter, compare to

fertility, will determine the number of leaves developed.

all control.

In the most favourable environment, an oil palm canWhile the trend was consistent with the samples at

produce up to 48 new leaves annually [41]. For younger

location one and three, the treated plants at location twoplants (3-4 years), the new leaves emerge 20 to 30 fronds

were similarly responsive when applied by shallower

per year, and decreased along with the age of the plants.

Bio-pores, although Bio-pores density did not principally

On the adult trees, the number of new leaves decreased

determine the results. The results suggested that deeper

to 18 fronds per year [52]. Furthermore, in less

Bio-pores (80 cm) application is more suitable when

vapourable condition, the new leaves only emerge 16 -applied to the oil palm trees grown on Alluvial and Peat

18 per year.

soils, while for the Andosols soils, medium depth

In this study, the emergence of new leaves on oil palm

Bio-pores (60 cm) was enough to stimulate the plants totrees differed according to its bio pore(s) application

enhanced its radial development.

(Table2). Results suggested

On average, oil palm plants treated with deeper andintroduced, the new leaves development increase 23.33%

denser Bio-pores have their stem diameter increased byhigher than control plants. The rapid growth can be

2.2 mm after 120 days. While this was still lower thanachieved when the deeper and denser Bio-pores

the growth of stem diameters of treated plants at location

introduced to the oil crops grown in the alluvial soil (siteone (4.1 mm) and three (3.6 mm), but when compared1). Introduction of Bio-pores treatment also promotedwith the controls, plants in the location two have 57.14%

new-leave developments in second (Andosols soils) andlarger stem diameter growth in comparison to the plants

third location (Peat Soils). These obtained through quad

without Bio-pores introductions. The value suggested

80cm Bio-pores application per plant, with greaterthat oil palm plants cultivated in alluvial soils responds

results compared to controls.

better when introduced by more Bio-pores, when

numberon

eachvariety.

that,

However,

after Bio-poresProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 02

Table 2 Oil Palm Trees Morphological Growth According to Bio-Pores Introduction
Treatment

Location

Development of Plant Morphology**

1 Control (A)Bio-pores Volume*(cm3)

GrowthAverage Height Increment (cm)Average Radial Increment (cm)New Leaves Emergence

30

30 d

30 d

60

90

120

60 d

90 d

120 d

60 d

Index***

90 d 120 d

0 5.5 a 10.95 a 12.72 a 27.4 a 0.07 a 0.12 a 0.15 a 0.32 a

0.9 a 1.7 a 3.3 a 6.5 A

1

1_30 cm _1

84823 5.54 a 10.96 a 12.74 a 27.49 a 0.08 a 0.12 a 0.16 a 0.32 a

1.0 a 1.8 a 3.4 a 6.6 A

1

1_30 cm _2

169646 5.57 a 11.12 a 12.86 a 27.58 a 0.07 a 0.14 b 0.16 ab 0.32 a

1.1 b 1.9 b 3.3 a 6.7 A

1

1_30 cm _4

226194.7 5.59 a 11.01 a 12.92 a 27.44 a 0.08 b 0.14 b 0.17 b 0.33 a

1.0 ab 2.0 b 3.6 ab 6.7 A

1

1_60 cm _1

169646 5.62 a 10.99 a 12.74 a 27.51 a 0.09 b 0.13 a 0.16 ab 0.34 a

1.0 ab 1.8 a 3.4 a 6.6 A

1

1_60 cm _2

339292 5.63 a 11.28 a 13.07 a 27.66 a

0.11 b 0.16 b 0.19 b 0.35 b

1.2 b 2.1 b 3.4 a 6.7 A

1.667

1_60 cm _4452389.4 5.79 ab 10.97 a 13.09 a 27.51 a

0.11 b 0.14 b 0.15 a 0.37 b

1.0 b 2.0 b 3.4 a 6.6 A

1.667

1_80 cm _1

339292 5.71 a 11.23 a 12.82 a 27.55 a

0.11 b 0.14 b 0.18 b 0.32 a

1.0 ab 1.9 ab 3.4 a 6.9 ab

1.333

1_80 cm _2

678584 6.05 b

11.6 ab 13.16 a 27.76 a 0.13 b 0.16 b 0.19 b 0.35 ab 0.9 a 1.9 b 3.5 ab 6.6 A

1.333

1_80 cm _4

904778.8 6.38 b

11.3 a 13.11 a 27.6 a 0.13 b 0.20 b 0.24 b 0.41 b

1.6 b 2.7 b 3.4 a 7.3 B

2.333

2 Control (B)

0 5.83 a 9.083 a 14.99 a 26.62 a 0.03 a 0.05 a 0.07 a 0.14 a

0.9 a 2.1 a 3.8 a 6.0 A

12_30 cm _1

84823 5.89 a 9.115 a 15.08 a 26.71 a 0.04 b 0.05 a 0.08 ab 0.15 a

0.9 ab 2.2 a 3.9 a 6.0 A

12_30 cm _2

169646 5.85 a 9.261 a 15.15 a 26.65 a 0.04 b 0.05 a 0.09 b 0.15 ab 1.0 b 2.1 a 3.9 a 6.0 A

1.333

2_30 cm _4

226194.7 6.01 a 9.216 a 15.21 a 26.63 a 0.04 b 0.05 b 0.10 b 0.16 b

0.9 a 2.2 ab 4.0 ab 6.0 A

1.667

2_60 cm _1

169646 5.84 a 9.192 a 15.08 a 26.72 a 0.03 a 0.05 a 0.08 ab 0.16 b

1.0 b 2.2 ab 3.9 a 6.1 A

1.667

2_60 cm _2

339292 5.85 a 9.432 a 15.35 a 26.78 a 0.05 b 0.08 b 0.10 b 0.16 b

0.9 ab 2.4 b 4.1 ab 6.4 ab22_60 cm _4452389.4 5.84 a 9.568 ab 15.25 a 26.66 a 0.04 b 0.09 b 0.09 b 0.14 a

1.2 b 2.3 b 3.8 a 6.2 A

1

2_80 cm _1

339292 5.94 a 9.149 a 15.26 a 26.91 a 0.03 a 0.06 b 0.09 b 0.15 ab 1.2 b 2.4 b 3.8 a 6.0 A

1.333

2_80 cm _2

678584 6.22 ab 9.375 a 15.46 a 27.08 a 0.08 b 0.09 b 0.09 b 0.18 b

1.2 b 2.6 b 3.9 a 6.3 ab22_80 cm _4

904778.8 6.57 b 9.259 a 15.14 a 27.51 a 0.04 b 0.09 b 0.15 b 0.22 b

1.1 b 2.9 b 4.0 ab 6.6 B

2.333

3 Control (C)0 6.08 a 8.426 a 12.53 a 24.6 a 0.07 a 0.08 a 0.16 a 0.30 a

1.0 a 2.3 a 4.0 a 6.0 A

1

3_30 cm _1

84823 6.17 a 8.428 a 12.54 a 24.61 a 0.08 b 0.08 a 0.16 a 0.31 a

1.1 ab 2.4 a 4.1 a 6.1 A

1

3_30 cm _2

169646 6.17 a 8.582 a 12.69 b 24.76 a 0.09 b 0.09 b 0.17 a 0.31 a

1.2 b 2.5 ab 4.1 a 6.1 A

1

3_30 cm _4

226194.7 6.27 a 8.606 a 12.61 b 24.78 a 0.09 b 0.10 b 0.17 a 0.30 a

1.0 a 2.4 a 4.2 a 6.1 A

1

3_60 cm _1

169646 6.18 a

8.54 a 12.54 b 24.61 a 0.09 b 0.09 b 0.17 a 0.31 a

1.1 b 2.4 a 4.1 a 6.1 A

1

3_60 cm _2

339292 6.27 a 8.641 a 12.59 b 24.89 a 0.10 b 0.11 b 0.18 ab 0.31 a

1.2 b 2.6 b 4.3 ab 6.0 A

1

25 a 0.08 b 0.11 b 0.17 a 0.31 a

1.5 b 2.5 ab 4.5 b 6.4 ab

1.333

3_80 cm _1

339292 6.44 ab 8.525 a 12.62 b 24.63 a 0.08 b 0.08 a 0.18 ab 0.31 a

1.0 a 2.5 ab 4.0 a 6.3 A

1

3_80 cm _2

678584 6.61 ab 9.064 ab 13.08 b 24.87 a 0.14 b 0.15 b 0.23 b 0.35 b

1.3 b 2.7 b 4.4 ab 6.2 A

1.667

3_80 cm _4

904778.8 6.6 ab 8.694 a 12.81 b 25.29 a 0.13 b 0.15 b 0.22 b 0.36 b

1.3 b 2.4 a 4.4 ab 6.8 B

2.333

3_60 cm _4452389.4 6.44 ab 8.469 a 12.89 banonsignificant at the 0.05 probability level.
ab
Significant at the 0.05 probability level.
bSignificant at the 0.01 probability level.
*
Re-filled with chopped semi decomposed fronds and leaves of oil palm trees**
Within columns, means followed by the same letter are not significantly different according to Fisher’s LSD (0.05)***
Higher values indicating stronger positive influence to plants development
Table 3 Morphological Development of Oil Palm Trees at 12 Years [50]
Cultivar
Morphological
Dolok
Bah Marihat AVROS La
Yangambi Simalungun Socfindo(L) Socfindo(Y) SP-1
PPKS PPKS PPKS Langkat
Development
Sinumbah Jambi
Me
Dumpy 540 718 239
Height
65
65
53
68
58
70
75-80
50
50
40-55 7275
62.5 60-70
Increment(cm/annum)
Stem Diameter 98.37
97.72 98.37 106.30 98.37 98.53
n.a.
n.a.
n.a.
n.a.
n.a. n.a. n.a. n.a.
(cm)
New
Leaves 2.25
2.25 2.17
2.25
2.33 2.33
n.a.
2.58
2.67
n.a.
n.a. n.a. n.a. n.a.
(/Month)n.a.
data not available

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 02

Fig. 2 Image Processing Software Developed to Extract Distinguished Features from Crown Image and Modelled the
Chlorophylls Content Based on The Established Model
Results of this study provide different finding, when

their soil environment in ways that cannot readily becompared to others [51.53-54]. The average number of

explained, in terms of the ability of the roots to take up

new leaves emerging from the oil palm trees, cultivate inwater and nutrients.

peat soils, and treated with Bio-pores obtained better

conditions in its environment may produce theresults. Quad 80cm deep Bio-pores when applied to oil

acceleration signals to the shoots [56], stem [57] as well

palm plants, result in 22 new fronds per year, as

as to the leaves [58].

Roots that sense favourable

extrapolated from 120-day observations. This result

From this study, it was known that Bio-pores application

successfully promotes better plants growth condition, inalone

particular, when the cultivation located on peat soils [53development of the oil palm trees. Soil type and-54].

condition, depth of Bio-pores applications as well as the

According to the previous study [55], plants that grow indensity of Bio-pores play crucial role to the plants

soil that is too soft or in the which the roots are forced toresponses,

grow in very large pores can also induce certain

Nonetheless, in general, the introduction of Bio-poresconservative responses. The roots that grow in thisproduced positive responds from the plants in terms of

Bio-pores will produce stimulant signals that may

its morphological development.

influence stomatal conductance, cell expansion, cell

The results also suggest that plants condition may havedivision and the rate of leaf appearance [55]. Although

influenced by Bio-pores introductions. The Bio-pores

introduction of artificial bio pore(s) to plants had been

provide channels for deep roots to water and nutrients

studied, the nature the plants responding to these externaland ease the overall crop access to both abiotic needs.

stimuli is still believed as a complex probability of a

The density of Bio-pores, number of Bio-pores per unit

network of hormonal and other responses involved inarea, and proportion of Bio-pores occupied by roots were

attuning the growth and development of a plant to its

strongly enhanced the morphological development of aenvironment [55]. Most plants respond to the change inplant [11].

cannotwithsolelyimproveddifferent

influencesmorphological(Table2).

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 02

two aspects. First is the accelerate radial growth of thestem, and secondly is the more frequent emergence of
new leaf. While different bio-pores application produced
various responds to plants, the environment conditions,in particular the growth media, provide primary factor to
the plants response to the external stimuli. These
responds can be calculated into an Index, indicating how
strong a plant responding its morphological development
towards more favourable living conditions.
Fig. 3 Relationships of Chlorophylls Content and Primary
Color (RGB) of The Crown. The Crown Recorded by an
UAV and The Images Subsequently Processed to Extract
The Primary Color Features (RGB). Leaves Samples fromThe Crown Then Analized to Measured Its Cholorphyll
Concentration.

This study shown that, introducing artificial Bio-pores atthe critical perimetry of the root zone, and filled it withdecomposed plants wastes provide a feeding ground forthe roots, in particular to absorb nutrients resulting fromthe decomposing process of the wastes materials. In
addition, the holes filled by water during rainy days, act
as a temporal water storage that can be utilized by theplants for their growth.
Moreover, the Bio-pores can act as a micro climate
control to the root zone, enhancing aeration and ion
exchange, thus providing a luxurious condition for theroots to grow, and provide precious minerals forphotosynthesis process [13]. The process reacts the
carbon dioxide from air around the leaves, with water

Fig. 4 Relationships of Chlorophylls Content and The
Ratio of Normalized Primary Color (RGB) of The Oil
Palm Trees’ Crowns

absorb by roots, producing glucose, a form of sugar [46].
The glucose then used in respiration by plants, or in otherway converted into starch and stored [47]. The
photosynthesis process produced oxygen as a by-product.

Previous study [11] suggest that the percentage ofThis condition can maintain the water status in leaf at

Bio-pores occupied by roots increased along with thehigh [60-61].

size and depth of Bio-pores. Less roots grown in

Since the chlorophyll in the leaves plays important role

restricted Bio-pores (shallow and small), suggesting thatin the photosynthesis process [13], the concentration ofroots opt to enter sizeable bio pore(s) and remained in it

chlorophyll in leaves of the sample plants is measured in[11].

this study and compared with the electromagneticallyIn the sustainable agriculture studies, it is important toreflection of visible light from the leaves surface, as

identify plants that are efficient of utilizing artificial

recorded by camera. The plants’ crowns were recorded

Bio-pores for better economic and management systemusing camera, attached to a drone. The image thenin cultivation.

While in their natural habitat, plant’s

processed using a developed image processing software

conservative behaviour is likely to improve the plants’(Figure 2). The results showed that difference Bio-poreschances of success. In agriculture, the condition isapplication to oil palm trees produces different change inreverse. The plants choose to prioritized generativeplants’ chlorophyll content in their leaves. Three primary

results compare to their survival. Plants often transform

colours, namely red (R), green (G), and Blue (B) were

their natural behaviour in wild, to achieved better

extracted from each crown image, then correlated withproduction compare to their predecessor [59]. Frequent

the chlorophyll content of the corresponding leaves.

irrigation often required to increase yield, even whenAmong the mean brightness of three primary colours ofnormal water application is sufficient [59-60].

the leaves of plants, R have high correlation with theComparing to normal conditions, oil palm whichmeasured chlorophyll content (Figure 3), with negative

introduced to external stimuli in this study (i.e. artificial

coefficient. Furthermore, the correlation of the B and G

Bio-pores) produce better morphological development invalue with measured chlorophyll content was observed

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 02

to be poor and independent for each location. Similar tofrom aerial platforms such as satellite, airborne, andB, the average total mean brightness (RGB) haveunmanned aerial vehicles (UAV) have the potential for

medium R2 when correlate with the chlorophyll content,

evaluating the plant performance in much wider area.

with decreasing trend. Although it was poorly correlated

The low-cost system used in this study remove thewith chlorophyll content, the primary colour of G and B

limitations of these technologies for commercial use at

may have influenced, to certain degree, with Bio-poresindividual farmer’s field or household.

introduction. The results showed that R could be use as
one of primary variable to estimate chlorophyll content

Conclusionin oil palm leaves. Nonetheless, using a single-color

The study explained how the oil palm trees responded

component for determining the chlorophyll content in oilmorphologically to the disruption of its environment

palm plants leaves may not produce high accuracy, duecondition, through the introduction of artificial bio-pores.

to its R2 limitation.

The Bio-pores, 30 cm in diameter, and depth of 30, 60,

In various studies, image processing techniques haveand 80 cm arranged with different density (1, 2, and 4

been developed to monitor plant health using mainly theper plant). The treatments gave different effects on the

RGB (Red Green Blue) colour model [62]. Images ofconcentration of chlorophyll in the crown. Variations ofleaves under consideration were acquired by cameras,

soils as well as the density of Bio-pores applied on eachand the chlorophylls and nitrogen content of the plants

individual

were modelled according their RGB value. Adamsen et

between the treated and control plants. Deeper Bio-poresal. [63] stated that the relationships between G/R and(80cm) when administered with denser numbers (4 pores

SPAD were linear over most of the range of G/R and thisper plant) brought positive significant influence to theratio responded to chlorophyll concentrations. Finally,morphological growth, peculiarly the stem diameter and

Hu et al. [64] showed that the RGB colour indices of R,

the emerging of new leaves, when oil palm trees planted

G and R+G+B, R-B, R+B, R+G had significant

in alluvial and peat soils. However, when the trees

relationship with chlorophyll content.

planted in andosols soils, medium depth Bio-pores

Both methods [63-64] were tested in this study, and the(60cm) produce better results in term of morphologicalresults (Figure 4) suggested that the ratio of normalized gfeatures, when compared to control. The intelligent plant

and r (g/r) produce better R2 to the leaves chlorophyll

monitoring system developed in this study provide

plant

determinesignificant

differences

content, as contrast to other models [62-64]. The result

solution for real-time estimation of leaf chlorophyll

indicated that for crown-level observation, normalization

content,of colour model minimized the root mean square error

measurement using hand-held devices is not possible.

(RMSE) for chlorophyll concentration determination

The ratio of normalized primary colour from the image

model, thus promoting a new mean of non-destructive

produce better coefficient of correlation for real-timeevaluation method for oil palm intelligent monitoring.

estimation of chlorophyll concentration of the plants'

The plant monitoring system developed in this study may

crowns, with R2 of 0.7997 and 0.7835 for r/g and r+b

provide solution for real time estimation of leaf

respectively.

notablywheneverdirectchlorophylls

chlorophyll content, whenever manual measurement
using chlorophylls meter is not possible. The mentioned
cases already reported by Yadhav et al. [65] andKawashima and Nakatani [66], and the results indicatedthat RGB based image analysis was a useful tool for
chlorophyll estimation in regenerated plants.
Although several non-destructive methods alreadyavailable to estimate the Nitrogen in plants, andsubsequently provide the fertilizer recommendations,most of these methods are based on vegetation index
observation through manual assessment. This study open
the opportunity of aerial evaluation for remote sensing
and plants performance. The use of multiple sensors

Acknowledgement
The authors acknowledge substantial contribution fromAPKASINDO West Sumatera, Indonesia, in particular
Mr. Irman, Mr. Djasmir, Mr. Marlin, and Mr. Wali forlending their plantation plots for this experiment. The
study was funded by Andalas University BOPTN
research grant, based on the agreement of professorshipresearch cluster No.524/XIV/A/UNAND-2016, signed
on 9 May 2016.

Reference
1) KEMENTAN. 2014. Plantations Data Sub Sector Oil Palm:
Palm Oil Productivity by Province 2013-2017. Directorate
Generalof
Estate.
Website:http://www.pertanian.go.id/Data5tahun/Esti2017-BUN(pdf)/
208-Produksi-KelapaSawit.pdf J.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 022) Sime Darby. 2014. Palm Oil Facts & Figures. Sime Darby23) Karch, M. 2010. Android for Work: Productivity for
Plantation.
Website:Professionals. Apress. ISBN 978-1-4302-3000-7.
http://www.simedarby.com/upload/Palm_Oil_Facts_and_Fig
24) Muller, S. 2015. Upgrading and Repairing PCs (22nd ed.).
ures.pdf
Pearson Education. p. 898. ISBN 978-0-7897-5610-7.
3) Indonesia-Investments. 2016. Indonesia's Palm Oil25) Geier, J. 2016. Overview of the IEEE 802.11 Standard.
Moratorium
IncludesExisting
Concessions.
InformIT.
http://www.indonesia-investments.com/news/todays-headlin
26) 3.1.1 Packet format. 2012. IEEE Standard for Ethernet,
es/indonesia-s-palm-oil-moratorium-includes-existing-conce
802.3-2012 – section one. pp. 53.
ssions/item7017?
27) David J. G. 2005. 3G Cellular Standards And Patents.
4) Mongabay. 2016. Indonesia’s palm oil permit moratorium toIEEE Wireless com. Polytechnic Institute of New York
last
five
years.
University.
https://news.mongabay.com/2016/07/indonesias-palm-oil-per28) Lemstra, W., Hayes, V., Groenewegen, J. 2010. The
mit-moratorium-to-last-five-years/
innovation journey of Wi-Fi: the road to global success.
5) Hoffmann, M.P., Donough, C., Oberthür, T. Vera, A.C., Wijk,
Cambridge
University
Press.
p.
121.
ISBN
M.T.V., Lim, C.H., Asmono, D., Samosir, Y., Lubis, A.P.,
978-0-521-19971-1.
Moses, D.S., and Whitbread, A.M. 2015. Benchmarking29) Shofiyati, R., Las, I., and Agus, F. 2010. Indonesian Soil
Yield for Sustainable Intensification of Oil Palm Production
Data Base and Predicted Stock of Soil Carbon. Proc.of Int.
in Indonesia using PALMSIM. The Planter, 91 (1067). pp.
Workshop on Evaluation and Sustainable Management of
81-96. ISSN 0126-575X
Soil Carbon Sequestration in Asian Countries, Sept. 28-29.
6) Binasawit Makmur. 2017. DxP Sriwijaya Oil Palm Seeds:
Bogor, Indonesia.
Characteristics and Advantages. Products Detail. Binasawit30) Putra, B.T.W., and Soni, P. 2017. Evaluating NIR-Red and
Makmur.
NIR-Red-Edge external filters with digital cameras under
7) IOPRI. 2015. Clon Marihat: The advantage of using IOPRI’s
different illumination for assessing vegetation indices.
plant material Clones. Indonesian Oil Palm Research
Infrared Physics & Technology 81: 148–156.
Institute. Medan, Indonesia
31) Ali, M.M., Al-Ani, A., Eamus, D., and Tan, D.K.Y. 2012.
8) Manitoba Gov. 2013. Effects of Manure and Fertilizer on
A New Image Processing Based Technique to Determine
Soil Fertility and Soil Quality. Manitoba, Canada
Chlorophyll in Plants. American-Eurasian J. Agric. &9) USDA. 2017. Over-Fertilization of Soils: Its Causes, Effects
Environ. Sci., 12 (10): 1323-1328.
and Remediation. Agriculture - Commercial Horticulture.
32) Cherie, D., Herodian, S., Ahmad, U., Mandang, T. and
The center for Agricultural, Food, and the Environment.
Makky, M. 2015. Optical Characteristics of Oil Palm Fresh
University of Massachusetts Amherst
Fruits Bunch (FFB) Under Three Spectrum Regions
10) Stirzaker, R.J., Passioura, J.B., and Wilms, Y. 1996. Soil
Influence for Harvest Decision. International Journal on
structure and plant growth: Impact of bulk density andAdvanced Science, Engineering and Information Technology
Bio-pores. Plant and Soil 185(1):151–162
5(3): 104-112.
11) Nakamoto, T. 2000. The Distribution of Wheat and Maize
33) Makky, M. and Soni, P. 2013. Development of an
Roots as Influenced by Bio-pores in a Subsoil of the Kanto
automatic grading machine for oil palm fresh fruit bunches
Loam Type, Plant Production Science, 3:2, 140-144, DOI:
(FFBs) based on machine vision. Computers and Electronics
10.1626/pps.3.140
in Agriculture 93: 129-139.
12) Passioura, J. B. 2002. Soil conditions and plant growth.
34) Makky, M. and Soni, P. 2013. Towards sustainable green
Plant, Cell and Environment 25:311–318
production: exploring automated grading for oil palm fresh13) Haferkamp, M.R. 1987. Environmental Factors Affecting
fruit bunches (FFB) using machine vision and spectral
Plant Productivity. Proc. Fort Keogh Research Symposium.
analysis. International Journal on Advanced Science,Montana Agr. Exp. Sta., Bozeman.
Engineering and Information Technology 3(1): 1-7.
14) Aditya, K., Udupa, G., and Lee, Y. 2011. Development of35) Makky, M. and Soni, P. 2014. In situ quality assessment of
Bio-Machine Based on the Plant Response to External
intact oil palm fresh fruit bunches using rapid portable
Stimuli.
Journalof
Robotics
2011:1-7.
non-contact and nondestructive approach. Journal of Food
doi:10.1155/2011/124314.
Engineering 120: 248-259.
15) AISA. 2015. Oil palm mapping. Spectral Imaging Ltd.
36) Makky, M., Soni, P. and Salokhe, V. M. 2014. AutomaticOulu, Finland.
nondestructive quality inspection system for oil palm fruits.
16) FAO. 1999. Indonesia: Country Pasture/Forage Resource
International Agrophysics 28: 319-329.
Profiles. Udayana University, Denpasar, Bali, Indonesia.
37) Makky, M. 2016. A Portable Low-cost Non-destructive17) 3rd Generation Partnership Project. 2015. 3GGP
Ripeness Inspection for Oil Palm FFB. Agriculture andTS45.001: Technical Specification Group GSM/EDGE
Agricultural Science Procedia 9(1): 230 – 240.
Radio Access Network; Mobile Station (MS) - Base Station38) Makky, M. 2016. Multi-modal Bio-metrics Evaluation for
System (BSS) interface; Radio Link Control / Medium
Non-destructive Age States Determination of Tomato Plants
Access Control (RLC/MAC) protocol; section 10.0a.1 (Solanum lycopersicum). International Journal on Advanced
GPRS RLC/MAC block for data transfer.
Science, Engineering and Information Technology 6(3):18) Ditjenbun. 2013. Technical guidelines for Oil Palm
349-355.
Plantation Development. Directorate general of estates.
39) Makky, M. 2016. Trend in non-destructive quality
Ministry of Agriculture, Indonesia.
inspections for oil palm fresh fruits bunch in Indonesia.
19) DJI. 2016. Phantom 3 4K Camera Specification. Phantom
International Food Research Journal 23(Suppl): S81-S90
3 4K Documents and Manual. DJI. USA.
40) Makky, M., Santosa, Putri, R.E., and Nakano, K. 2017.
20) Vorlesungen.
2015.
GlobalComputer
Vision.
Nondestructive Evaluation of c.v. Simauang Paddy Grains
http://www.inf.fu-berlin.de/lehre/WS02/robotik/Vorlesungen/with Different Moisture Contents By Means ofVorlesung2/ComputerVision-2.pdf.
Spectrophotometry. AIP Conference Proc. 1813(1):1-10. doi:21) DJI. 2016. Phantom 3 4K Documents and Manual. DJI.
10.1063/1.4975940
USA.
41) Pahan I. 2006. Complete Guide for Oil Palm Cultivation.
22) Harry Ng, Y. M., and C. P. Kwong. 2003. Correcting the
Niaga Swadaya, 2006; ISBN 979489995X, 9789794899953.
Chromatic Aberration in Barrel Distortion of Endoscopic42) Yudhi, A.N. 2010. Study of Soil Nutrient Status and The
Images. Systemic, Cybernetics And Informatics 1(2):81-87
Oil Palm (Elaeis guineensis Jacq.) Tissue in the Palm

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 02
Plantation Center for Integrated Agricultural Research andPlant, Cell and Environment 25:311–318.
Development (BP3T) Tambang Ulang District, Tanah Laut
56) Davies W.J. & Zhang J. 1991. Root signals and theAgroscientiae. 2010; 17.
regulation of growth and development of plants in drying43) Arnon, D. 1949. Plant Physiology 24: 1- 15.
soil. Annual Review of Plant Physiology and Plant
44) Hiscox, J. D., and G. F. Israelstam. 1979. A method for the
Molecular Biology 42, 55–76
extraction of chlorophyll from leaf tissue without maceration.
57) Jackson M.B. 1993. Are plant hormones involved in root
Canadian Journal of Botany, 1979, 57(12): 1332-1334,
to shoot communication? Advances in Botanical Research 19,
10.1139/b79-163
103– 187.
45) Richardson, A. D., Duigan, S. P. and Berlyn, G. P. 2002.
58) Aiken R.M. & Smucker A.J.M. 1996. Root system
An evaluation of noninvasive methods to estimate foliar
regulation of whole plant growth. Annual Review ofchlorophyll content. New Phytologist, 153: 185–194.
Phytopathology 34, 325– 346.
doi:10.1046/j.0028-646X.2001.00289.x
59) Evans L.T. 1993. Crop Evolution, Adaptation and Yield.
46) Law, C.C., Zaharah, A.R., Husni, M.H.A., Siti, N.A.A.
Cambridge University Press, Cambridge.
2014. Leaf Nitrogen Content in Oil Palm Seedlings and60) Merrill S.D. & Rawlins S.L. 1979. Distribution and
Their Relationship to SPAD Chlorophyll Meter Readings.
growth of sorghum roots in response to irrigation frequency.
Journal of Oil Palm, Environment & Health 5(1):8-17.
Agronomy Journal 71, 738–745.
47) Sim, C.C., Zaharah, A.R., Tan, M.S., and Goh, K.J. 2015.
61) Garside A.L., Lawn R.J., Muchow R.C. & Byth D.E. 1992.
Rapid Determination of Leaf Chlorophyll Concentration,
Irrigation management of soybean (Glycine max (L.)
Photosynthetic Activity and NK Concentration of Elaies
Merrill) in a semi-arid tropical environment. II. Effect ofguineensis Via Correlated SPAD-502 Chlorophyll Index.
irrigation frequency on soil and plant water status and crop
Asian Journal of Agricultural Research 9 (3): 132-138. DOI:
water use. Australian Journal of Agricultural Research 43,
10.3923/ajar.2015.132.138
1019–1032.
48) Fauzi, Y., Y. E. Widyastuti, I. Satyawibawa, dan R.
62) Erickson, J.E.,
M.D.
Keziah,L.A. Nelson &Hartono. 2004. Palm oil: Cultivation, Utilization, Yield and
C. T. Young, 1988. Variation of colour of oil cooked Virginia
Waste, Business Analysis and Marketing. Penebar Swadaya,
type peanuts, Proceedings of the American Peanut Research
Jakarta.
and Education Society, 20: 45.
49) Wahyono, T., R. Nurkhoiry, and M. A. Agustira. 1996.
63) Adamsen, F.J., P.J. Pinter, E.M. Barnes et al. 1999,
Profile of Palm Oil in Indonesia. IOPRI. Medan, Indonesia.
'Measuring wheat senescence with a digital camera', Crop50) IOPRI. 2015. Bahan Tanaman PPKS. Varietas BenihScience, 39: 719-24.
Unggul PPKS. Indonesian Oil Palm Research Institute.
64) Hu, H., H.Q. Liu, H. Zhang, Jing-huanzhu, Xu-guoyao,
Medan, Indonesia.
Xiao-bin and Kee-zheng, 2010. Assessment of chlorophyll51) Lubis, A.U.. 1992. Oil Palm (Elaeis guineensis Jacq.)
content based on image color analysis, comparison with
Cultivation in Indonesia. IOPRI, Indonesia
SPAd-502', paper presented to the, The 2 International52) Mangoensoekarjo, S. and H. Semangun. 2003.
Conference on Information Engineering and Computer
Agribusiness Management of Oil palm. Gajah Mada
Science Proceedings, Wuhan, China, 25-26 December 2010.
University Press, Yogyakarta.
65) Yadav, S.P., Y. Ibaraki and S.D. Gupta, 2010. Estimation
53) Soehardjo. 1984. Vademecum of Oil Palm (Elaeisof the chlorophyll content of micro propagated potato plants
guineensis Jacq.). PTPN IV, Bah Jambi, Pematang Siantar,
using RGB based image analysis. Plant Cell Tiss Organ Cult,
Indonesia.
100: 183-8.
54) Sianturi, H. S. D.. 1991. The agronomy of Oil Palm
66) Kawashima, S. and M. Nakatani, 1998. An algorithm for(Elaeis guineensis Jacq.). Faculty of agriculture, North
estimating chlorophyll content in leaves using a video
Sumatera University, Medan, Indonesia.
camera. Annals of Botany, 81: 49-54.
55) Passioura, J. B. 2002. Soil conditions and plant growth.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 03

Soil and Water Conservation with Zero Runoff Model in Oil Palm Plantation○Eri Gas EKAPUTRA，Fadli IRSYAD(Faculty of Agricultural Technology, Andalas University, Indonesia）
SUMMARY
Soil and water conservation by infiltration through infiltration wells are very important. Because considering the land
use changes in the earth's surface as a consequence of the growth in population and economy, society. Infiltration wells
will decrease runoff and erosion rate. If the surface flow decreased, soils eroded and drift would be reduced. The
impacts are runoff and erosion will be small. This research was conducted in June to August 2016 in West Pasaman
PTPN VI. This study aims to determine the number of recharge wells, dimensions, distribution of recharge wells andreduce the volume of runoff that occurs. This research was conducted through the following steps: (1) Analysis ofIntensity Rain, (2) Determination of the coefficient of runoff, (3) Analysis of Spatial Hydrology, (4) Calculation ofVolume runoff, (5) Calculation of recharge wells needs, and (6) Distribution recharge wells. The secondary data used inthis research were the rainfall data, map of PTPN VI, and the SRTM data were used to analyze the volume of runoff.
The results of the analysis are obtained on Afdeling 1, where are 21 water catchment areas with runoff volume, and thenumber of wells required catchment different. So from 21 the catchment area takes 5200 recharge wells that can holdthe runoff volume of 23,400 m3 with areal extents section , 948.985 Ha, infiltration wells have dimension 1.5m ×1.5m
and height 2m

Introduction

groundwater in PTPN VI West Pasaman. This method is

Global climatic changing of the earth due to greenhouseone of the zero runoff model (Setiawan 2010). The

effect has impacts on weather conditions in every region

design of infiltration wells is necessary need to considerof Indonesia. Among the impacts are the increase ofclimatic factors, soil conditions and land use. Climatic

rainfall intensity, flash flooding (rob), local storm /factors to consider is the amount of rainfall, the greater

tornado,landslides.

the rainfall in an area means greater absorption wells

Indonesia region which lies on the equator gets sunlightrequired. Increased groundwater through the production

throughout the year and it has only two seasons, rainyof absorption wells needs to be done on a large scale,and dry seasons. The dominance of the two seasons

because of the ground really need the supply of water

greatly affects the availability of water. In dry season

through infiltration wells (Ihsan et al., 2016). Based on

shortage of water occurs and in rainy season there is an

the above, the authors conducted a study entitled "Oilincrease of runoff.

and Water Conservation with Zero Runoff Model in Oil

Rainfall that falls to the ground at first will wet the land,

Palm Plantation".

buildings, plants and rocks. When rain falls on the area

Material and Methodof porous it will seep into the ground as infiltration, theThis research was conducted in June to August 2016 inlonger the water will seep deeper until it enters the area

Oil Palm Plantation PT.PN VI Pasaman Barat andof the aquifer and eventually into the groundwater

Laboratory of Land and Water Resources Engineering.

(Robertus, 1999). Run off occurs when the land cannot

The tools were used in the implementation of this study,

longer infiltrate surface water because the land is alreadynamely: a set of computers; GPS, and stationery; a digitalin a state of saturation. Run off the main cause of erosion

camera for documentation retrieval. The materials used inin some areas in Indonesia.

this study were (1) Software ArcGIS 10.3, Global Mapper,

Absorption of surface runoff water into the ground canand Google Sketh Up 8; (2) Data precipitation last 10

be carried out by an eco-drainage system (Krebs et al.,years from 2006 to 2015; (3) Map the location of PTPN

1997).

VI Pasaman Barat; (4) Data SRTM 1 Arc-Second.

temperature,

droughts

andThis system can also reduce the erosion that

occurs, fill the soil aquifer, and prevent damage, and rain

The first procedure performed in this study was toharvest during the dry season (Contreras et al. 2013;

conduct a field survey to determine the condition of the

Papafotiou et al., 2015; Kumar et al., 2013; Afolayan et

field such as topography, land cover, and soil types. This

al., 2012; and Otti et al., 2013)

research was conducted through the following steps: (1)Application design of infiltration wells will be applied toAnalysis of Intensity Rain, (2) Determination of the

reduce the rate of runoff and ensuring the availability ofcoefficient of runoff, (3) Analysis of Spatial Hydrology,

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 03(4) Calculation of Volume runoff, (5) Calculation ofcontours of the land and the water flow visible research

recharge wells needs, and (6) Distribution recharge

location on the map with the help of ArcGIS 10.3

wells.

software by using the tools Flow Direction. The results

Rainfall were estimated with a specific return periodof the flow direction has been obtained and then used as(Bhim et al. 2012), were calculated by four methods ofa reference for determining the amount of the water

frequency distribution (Suripin 2014). namely:

catchment area (CA) using Extension Basin Hydrology,

1. Normal distribution

then each catchment area is calculated areas processed

2. Log Normal Distribution

using ArcGIS 10.3 software.

3. Log Pearson III distribution

According USSCS (1973), one of the

4. Gumbel distributioncommonly used to estimate the peak flow rate (discharge

methods

The frequency distribution is used to determine theplanning), the Rational method. Rational method was

relationship of the magnitude of extreme hydrologicaldeveloped based on the assumption that the rainfall has

events such as floods with a number of events that have

uniform intensity and evenly throughout the drainage

occurred so the chances of extreme events predicted timearea for at least equal to the time of concentration (tc),(Bhim, 2012). Data analysis was performed on all four ofthe mathematical equations Rational Method is asthese methods include the average, standard deviation,

following:

coefficient of variation, coefficient of skewness (heelingQ = 0.278. C. I. A

/ skewness) and kurtosis coefficients.

Placement location of Infiltration/recharge wells were

Rainfall intensity is expressed in high rainfall (mm/hr)

analyzed using a contour map PTPN VI West Pasaman,

per unit time, which occurs at a time duration, when rainfrom SRTM data will be processed on the Global

is concentrated. One common formula for calculating the

Mapper software to obtain contour in each catchment

intensity of the rain is the formula Mononobe.

area. The contour map is converted to raster data in
ArcGIS 10.3 software using Topo extension to raster,I

raster then will be cut in accordance with the

Runoff coefficient is the ratio between runoff andadministrative boundaries PTPN VI West Pasaman andprecipitation (Rajil, 2011). The runoff coefficient values

each catchment area in section 1 by using extension

based on land use factor is presented in Table 1 below.

extract by mask. Infiltration wells will be placed atTable 1points bevy of water that can be seen by a map of the

Runoff coefficient (C) for a rational method
Runoff coefficient (C)movement direction of flow of PTPN VI West Pasaman

Secondary dry forest

0.03

then recharge wells will spread all amounts have been

Thicket0.07

calculated and analyzed.

Primary Forest

0.02

Industrial Plantation Forest

0.05

Result and Discussions

Secondary swamp forest

0.15

PTPN VI has the areal extents 3549.16 hectares, andplantation

0.4

consists of four department. PTPN VI Ophir Business

Dryland Agriculture

0.1

Unit located in the border area between the province ofDryland Agriculture mixed

0.1

West Sumatra and North Sumatra Province.

Settlement

0.6

Paddy field

0.15

1. Rainfall plan (R24)
Determination of rainfall estimation to use the study

Tambak

0.05

Open land

0.2

Bodies water

0.05

Land use

shrub

Analysis of Spatial Hydrology to draw the direction of
runoff. It determined by topography. Topographic maps
can be created from SRTM data so that the resulting

site's average precipitation last 10 years (2006-2015)
were obtained from climatological station PTPN VI
Business Unit Ophir, Pasaman Barat. Rainfall data wereobtained and analyzed in order to extract statisticalparameters to

select theappropriate methodofdistribution of the rainfall, the results obtained from the
Log Pearson III method that meets the requirements foranalyzing the rain draft of the study sites. The value ofProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 03

the parameter and design rainfall were obtained in Table

Table 4 Analysis The rainfall intensity (mm / hour)

2 and Table 3 below:

Periode Ulang (Tahun)
CA
1

2

5

10

25

50

100

Table 2 Parameter Analysis Test statistic Distribution

CA 1

27

29

35

38

43

47

51

Log Pearson III

CA 2

28

30

35

39

44

48

52

Parameters

value

CA 3

25

26

31

34

38

42

45

The average CH

26.5

CA 4

19

21

24

27

30

33

35

Average - Average Log

1.410

CA 5

23

25

29

32

36

39

43

The standard deviation

Sx = 0.077

CA 6

35

37

43

48

54

59

64

The coefficient of variation

Cv = 0.0029

CA 7

24

26

30

33

37

41

44

The coefficient of skewness

Cs = 0.876

CA 8

21

22

26

29

33

36

39

Ck = 4.14

CA 9

31

33

39

43

48

52

57

CA 10

27

28

33

37

0

45

49

CA 11

22

23

27

30

34

37

40

Kurtosis coefficient

Based on the analysis of statistical parameters of rainfall
data of the past 10 years found the average value of
precipitation 26.051, then the average value of logs
obtained 1,410, the value of a standard deviation of
0.876 this shows the data more inclined to right because
it is positive, then obtained standard deviation or
standard deviation of 0.077, this value indicates the sizeof the statistical distribution of data or an average
distance of deviations of data points measured from theaverage value of the data. The value of rainfall eachspecific return period can be seen on Table 3.
Table 3 Maximum daily rainfall by return period.
Return Period (years)

Plan Rainfall (mm)

1

23

2

25

5

29

10

32

25

37

50

40

100

43

Based on the above data on the 1-year period, the valueof 23 mm rainfall. This means that the rain is expected tobe equaled or exceeded in any one year. Plan Rainfall isestimate that the rain if exceeded

k times in a long

period of years will have a value M k / M isapproximately equal to 1 / T.
2. Calculation of Rainfall intensity
The calculation of rainfall intensity within the return
period T years of daily rainfall data can be calculated byusing the Mononobe formula. According to the statement
Loebis (1992) that the rainfall intensity (mm/hour) canbe derived from daily rainfall data using equations
Mononobe.

CA 12

29

31

36

40

45

49

53

CA 13

32

34

40

45

50

55

59

CA 14

21

22

26

29

33

36

39

CA 15

16

17

20

22

25

27

29

CA 16

20

21

25

0

0

34

0

CA 17

14

15

18

20

22

24

26

CA 18

12

13

16

17

20

21

23

CA 19

12

13

15

17

19

21

23

CA 20

15

16

19

20

23

25

27

CA 21

11

12

14

16

18

19

21

In the table above can be seen the calculation results
obtained for the intensity of the rain that took place ineach catchment area (CA), each CA has a rainfall
intensity is different, because it is influenced by thelength of the flow that occurs in each catchment area
(CA), in Diversion rain into streams there are several
properties of rain is important to note, among others, isthe intensity of rainfall, rainfall depth and concentration
time (Soemarto, 1987).
Time of concentration (tc), is used to determine
the length of the rain water flows from upstream todownstream flow. Time of concentration (tc) is
calculated using the formula Kirpich (1940).
The length and slope flow CTA obtained byusing Geographic Information System (GIS), based on
the results obtained SRTM data processing flow that
occurs in each CA, so the length of the flow can bemeasured using a map. The length of the flow in the CA
is the length of the maximum flow from the upstream
point to a downstream point (Triadmojo, 2008).
Based on the results in Table 4 are the smallest rainfall
intensity on CA 21, this is due to the length of the flowthat occurred in the CA, causing streaming, a long timefrom a point upstream to downstream, and rainfall

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 03

intensity obtained small. In the CA 21 long stream

Runoff comes from the highest points and move toward

measured on a map that is 2,343 km, the tilt of 1.7%, andthe lower points in a direction perpendicular to thethe length of time streaming, 0.6 hours or 36 minutes,

contour lines.

and the largest rainfall intensity contained in CA 6, with

Map directions runoff that has been obtained can be seena length of 0.417 km flow, with a slope of 4, 3%, so time

toward the more dominant runoff moved south-west or

streaming, fast, ie 0.114 hours or 6.84 minutes.

seaward. Map directions runoff is then processed again
by the software ArcGIS 10.3 for later obtained the
distribution of water catchments in Afdeling 1.

3. Directions and Watershed Runoff (CA)Determining the direction of water runoff that occurs at

Based on the results of processing map directions runoff

the site of the research results from processing of data

generated 21 DTA in Afdeling1. The DTA is obtained

SRTM 1 arc-second which has a spatial resolution of 30

with an area of 158.231 hectares ie DTA 21 for themeters, the data is then carried out the process of the clip

smallest DTA DTA 1 with an area of 12.261 ha. Surface(cutting) by using software ArcGIS 10.3, after it and thenflow at Watershed occur in several forms: 1) the flow ofmade a topographic map by using software Global

runoff on the soil surface, 2) flow through through the

Mapper, so that the resulting map topography in research

ditch / sewer, 3) flow through streams, and 4) the flow

location.

through the main river. The flow of the land surface

Topographic maps that have been made visible

runoff occurred during or after rain in the form of runoff

topographical conditions in some parts of the corrugatedon the soil surface. The flow went into the ditch / sewer

region Afdeling 1, topographic high located towards thewhich then flows into the streams further into the flow innorth or towards the mountain Pasaman. Topographic

the main river. Hydrological characteristics of the

map is then used for processing with ArcGIS 10.3

catchment area is influenced by the length of the river /software for the resulting map directions runoff, contour

stream, shape, area, relief / topography, and drainage

lines are used to determine the direction of the runoff.

patterns of the catchment (Triatmodjo, 2008).

Table 5The Cathment Area (CA)4. Coefficient and Runoff debit

Catchment Area (CA)Luas (ha)Rational method runoff coefficients for the location of

Catchment area 1

12,261

research can be seen from land use, namely plantation.

Catchment area 2

14,695

Runoff coefficient value is 0.4 for plantation areas, canCatchment area 3

15,974be seen in Table 1.

Catchment area 4

18,128

Runoff discharge that occurs in the location study was

Catchment area 5

18,319calculated using a rational method for estimating theCatchment area 6

18,426peak discharge caused by heavy rains in the catchment

Catchment area 7

19,234(DAS) is small. A small catchment area is considered

Catchment area 8

19,816

uniform when the distribution of rainfall in space andCatchment area 921,757

time, and duration of rainfall normally exceeds theCatchment area 10

22,699concentration time. Some experts view that theCatchment area 1122,880catchment area of less than 2.5 km2 can be considered aCatchment area 1232,367

small watershed (Ponce, 1989). After calculation, it can

Catchment area 13

41,152be seen in Table 6 runoff discharge that occurs in theCatchment area 14

41,272

respective DTA with a specific return period.

Catchment area 15

42,716

Based on the calculation results table above can be seen

Catchment area 16

46,454

runoff discharge, discharge runoff obtained is affected by

Catchment area 17

85,011

1) catchment area, 2) runoff coefficient, and 3) Intensity

Catchment area 18

93,740of Rain. Catchment area are the main parameters that

Catchment area 19

98,524influence the outcome of the discharge, the discharge ofCatchment area 20

105,329

runoff largest found in DTA 21, it can be seen theCatchment area 21

158,231influence of the area of comprehensive DTA 21
compared with the DTA other, the DTA 21 is the area'sProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 03

Table 6
CA

Discharge of Runoff (m3 / sec)

Table 7

Periode Ulang (Tahun)

The Volume of Runoff (m3)Periode Ulang (Tahun)

1

2

5

10

25

50

100

CA 1

0.4

0.4

0.5

0.5

0.6

0.6

0.7

CA 2

0.5

0.5

0.6

0.6

0.7

0.8

CA 3

0.4

0.5

0.5

0.6

0.7

CA 4

0.4

0.4

0.5

0.5

CA 5

0.5

0.5

0.6

CA 6

0.7

0.8

CA 7

0.5

0.5

CA
1

2

5

10

25

50

100

1

216

231

272

300

338

368

398

0.8

2

256

274

322

356

401

436

473

0.7

0.8

3

298

319

375

414

466

507

549

0.6

0.7

0.7

4

382

409

481

531

598

651

705

0.7

0.7

0.8

0.9

5

351

376

442

488

550

598

648

0.9

1.0

1.1

1.2

1.3

6

290

311

365

403

454

494

535

0.6

0.7

0.8

0.9

0.9

7

364

390

458

506

570

620

672

CA 8

0.5

0.5

0.6

0.6

0.7

0.8

0.9

8

400

428

503

556

626

680

737

CA 9

0.7

0.8

0.9

1.0

1.2

1.3

1.4

9

364

389

457

506

569

619

671

CA 10

0.7

0.7

0.8

0.9

1.0

1.1

1.2

10

407

436

512

566

638

693

751

CA 11

0.6

0.6

0.7

0.8

0.9

0.9

1.0

11

454

486

571

631

710

773

837

CA 12

1.0

1.8
2.5
1.6

1.9
2.7
1.8

594

698

771

869

945

1,024

671

719

845

933

1,051

1,143

1,239

1.0

1.6
2.3
1.5

13

CA 14

1.4
2.0
1.3

555

1.5

1.3
1.8
1.2

12

CA 13

1.1
1.6
1.0

14

835

894

1,051

1,162

1,308

1,422

1,541

CA 15

0.7

0.8

0.9

1.0

1.2

1.3

1.4

15

996

1,067

1,254

1,386

1,560

1,697

1,838

CA 16

1.0

1.1

1,342

1,511

1,643

1,780

1.3

1.4

CA 19

1.3

1.4

CA 20

1.7

1.8

CA 21

2.0

2.1

1.9
2.5
2.4
2.5
3.2
3.6

1,214

CA 18

1.7
2.3
2.2
2.3
2.9
3.4

1,033

1.4

1.6
2.1
2.0
2.1
2.7
3.1

965

1.3

1.4
1.9
1.8
1.9
2.4
2.8

16

CA 17

1.3
1.7
1.6
1.7
2.2
2.5

17

2,081

2,227

2,618

2,893

3,258

3,543

3,838

18

2,454

2,627

3,087

3,412

3,842

4,178

4,526

19

2,594

2,777

3,264

3,607

4,062

4,417

4,785

20

2,534

2,713

3,188

3,523

3,968

4,314

4,674

21

4,358

4,665

5,483

6,059

6,823

7,420

8,038

largest, while to discharge runoff smallest one is on DTA

with an area DTA 1, which is the smallest catchment area

1, which is the catchment area with the smallest area.

of the region.

5. Volume of Runoff
The volume of runoff is the number of accommodated

6. Dimensional Recharge wells
Design dimensional infiltration wells using the volume

runoff catchment area that occurred during the drainageof runoff with a return period of 2 years, seeing antime (tc), then from the discharge runoff we can calculate

opportunity rains that occurred 50% and a prediction of

the volume of runoff in the respective catchment areas,rain events are not too short and too long, if using awhere each of the catchment area has a drainage time (tc)return period of 1 year, the time is too short, if the return

dif- different. Here are the results of calculations eachperiod of 5 years, the odds of a small 20% and thecatchment runoff volume at a certain return period.

predicted long time. In this study dimensional diffusion
well defined with a size of 1.5 meters x 1.5 meters highBased on the above calculation can be seen the volume

on its side and infiltration wells 2 meters, so that theof runoff largest located in the region DTA 21, it can be

storage volume that is generated for the recharge wells isseen from the large catchment areas in the region,

4.5 m3. In the table below the results can be seen in thecausing the volume of runoff, if seen from the intensity

number and volume of each pitcher infiltration wells ofof rain DTA 21, the rain intensity smallest, is caused bywater catchment areas.

the length of time streaming but for the volume of runoff

In table 8 above can be seen, the number and volume of

can be seen are the main factors influencing thecatchment runoff each DTA vary, the DTA 1, the volume

magnitude of the extent of the catchment area and theof runoff that occurs 231.143 m3, so it takes 52 pieces oflength of time jetting, for the smallest runoff volume

recharge wells to accommodate runoff that occurs, andobtained in the area DTA 1, this results in accordance

the volume catchment runoff by recharge wells are 234

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 03

Table 8 Number and volume of runoff catchment
RunoffCA

Volume3

NumberRechargeof wells

Volume(m3)Numbersediment runoff so that it does not fit into the wells to
reduce the volume of catchment it.

of

1

231

52

234

4

7. Distribution Infiltration Wells in location research
Based on the number and map directions runoff, can be

2

274

61

275

4

determined placement of recharge wells, recharge wells

3

319

71

320

4

would be made at the meeting point of water and in areas

4

409

91

410

5

of ramps / flat (not steep), so that water flowing from the

5

376

84

378

5

high point to the sloping area and can get into recharge

6

311

70

315

4

wells optimally , Infiltration wells will be deployed on

7

390

87

392

5

the DTA by considering the density of the contour lines

8

428

96

432

5

in accordance with their respective amounts so as to

9

389

87

392

4

absorb runoff that occurs every DTA.

10

436

97

437

4

11

486

108

486

5

(m )

wells/ha

12

594

132

594

4

13

719

160

720

4

14

894

199

896

5

15

1,067

238

1071

6

16

1,033

230

1035

5

17

2,227

495

2228

6

18

2,627

584

2628

6

19

2,777

618

2781

6

20

2,713

603

2714

6

21

4,665

1037

4667

7

Conclusion

23,363

5200

23400

104

1. On Afdeling 1 PTPN VI West Pasaman based on theFig.1 3D Cathment area 1 and Distribution
Recharge wells

direction of flow generated 21 Watershed eachm3, as well as other DTA, such as DTA 21, which isthelargest runoff volume needed recharge wells on thecatchment area runoff discharge occurs different
when it rains.

acreage in 1037 with an area of 158.231 hectares to

2. In section 1 PTPN VI Pasaman Barat with areal

4664.795m3

extents 948,985 Ha be required 5200 recharge wells(appendix 14), when seen needs infiltration wells in an

or 5 recharge wells per Ha to accommodate thearea of 1 Ha also varies every DTA no need 4, 5 and 6 ofvolume of runoff that occurs at 23.363,437 m3 based

absorption wells in 1 Ha, even on DTA 21 extents areon the 2 year period used in the design.

accommodate

therunoffvolumeofmost in need of 7 infiltration wells in 1 Ha, on the

3. Based on the concept of zero run off pitcher volume

volume of runoff that is in great need of recharge wells

resulting from 5200 recharge wells as 23.400 m3 so itthat are so much in keeping with the area large

can accommodate the volume of runoff that occurs incatchment area.

section 1 PTPN VI.

Infiltration wells are designed with the type ofsquare-shaped with dimensions that have been set, theReferencesquare shape selected because it is easily made in thefield and volume of reservoirs produced greater than acylindrical shape, making it more suitable for the appliedfield, construction design recharge wells consisting ofwall infiltration wells and around recharge wells on thesurface of the ground made a small ditch filled withempty oil palm bunches, it serves as a filter so that water
seeped into clean and can accommodate sediments due toRegional Environmental Management Agency (2003)
Final report of coordination of catchment wellinventory in DKI Jakarta Province. Jakarta (ID):BPLHD.
Kuesnaidi (2000) Infiltration wells for Urban and Rural
Settlements. Penebarswadaya. Jakarta.
Contreras SM, Sandoval TS, and Tejada SQ (2013)
Rainwater harvesting, its prospects and challenges in
the uplands of Talugtog, Nueva Ecija, Philippines.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 03

International Soil and Water Conservation Research.
1:56-67.
Papafotiou E, and Katsifarakis KL (2015) Ecologicalrainwater management in urban areas. Preliminary
considerations for the city of Corinth, Greece. Journalof Agriculture and Agricultural Science Procedia.
4:383-391.
Setiawan BI, Saptomo SK, Saleh E (2010). Developmentof water control for tropical wetland agriculture.IPB
Press. Bogor
Kumar R, Thaman S, Agrawal G, and Poonam S (2011)
Rain water harvesting and ground water recharging inNorth Western Himalayan Region for Sustainable
Agricultural Productivity. Journal of Environmental
Research and Technology. 1(4):539-544.
Afolayan SO, Makinde AA, Shuaib M, Idris BA,
Yaduma JJ, and Yau MG (2012) Rainfall harvesting, asustainable water management alternative for foodsecurity in Nigeria. Journal of Agricultural Research &Management. 2012(136):1-8.
Ihsan M, Setiawan BI, Pandjaitan NH (2016) Design ofZero Runoff System at IPB Darmaga Campus, Bogor,West Java. Civil and Environmental Engineering
Journal 1 (1) : 1- 9.
Otti VI, and Ezenwaji EE (2013) Enhancing
community-driven initiative in Rainwater Harvestingin Nigeria. International journal of Engineering andTechnology. 3(1):73-79.
Suripin (2004) Sustainable Urban Drainage Systems.
Yogyakarta: Andi.
Bhim S, Deepak R, Amol V, and Jitendra S (2012)
Probability analysis for estimation of annual one day
maximum rainfall of Jhalarapatan area of Rajasthan,India. Plant Archives 12(2): 1093-1100. ISSN:
0972-5210.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 04

Conservation Analysis of Kuranji Watershed using SWAT Application○Fadli IRSYAD, Eri Gas EKAPUTRA(Faculty of Agricultural Technology, Andalas University）
SUMMARY
Land degradation is a major cause of high runoff compared to other factors. Changes in land use occurring in an area
cause a change in the catchment area conditions and may cause changes in runoff. If runoff occurs during minor rain
and infiltration of water into large soil, then water is first stored in soil that will increase ground water availability. The
Kuanji watershed is one of the watersheds in Padang City with an area of 202.7 km2 and consists of 5 sub-catchments.
This research was conducted on Kuranji watershed which geographically located at 100o20'31.20 "- 100o33'50.40" E
and 00o55'59.88 "- 00o47'24" S. This research was conducted in March - June 2013. This study has used ArcSWAT 12
application. Initial stages in this research are data collection, SWOT analysis in Kuranji watershed, and determination ofconservation area of Kuranji watershed. Results of research using ArcSWAT for Kuranji watershed were more than3000 HRUs. The largest runoff was 84 mm with an area of 75.195 ha, and spread in four sub-districts (Pauh, Padang
Utara, Nanggalo, and Koto tengah). The recommended conservation areas are Limau Manih (81.56 ha), Lambung Bukit(42.27 ha), Gunung Sarik (86.32 ha), Kuranji (60.20 ha), and Lubuk Minturun (64.45 ha)
Introduction

chemical transport of agricultural land and other uses inLand use changes that occur in a region has impacts on

the management of a watershed over a period of time.

condition of the catchment area directly or indirectly

This study aims to analyze the critical areas of Kuranji(Poyatos et al., 2003; Turkelboom et al., 2008).

watershed for reference by government and related

Furthermore, these condition cause changing in surface

agencies in conducting conservation activities. Soil andflow, this influence to the condition of the river (outlet)

water conservation activities in the Kuranji watershedon the watershed (Baker et al., 2013; Ghaffari et al.,can minimize runoff and erosion occurring in the2010; Niehoff et al., 2002). Land use change is the main

watershedcause of high runoff compared to other factors. If theforests within a watershed were converted into asettlement, the peak river flow will increase from 6 to 20

Material and Method
The SWAT (Soil and Water Assessment Tool) application

times. The number depends on the type of forest and theis a model to analyze a river or basin condition,

type of settlement (Kodoatie et al., 2008). The land slope

developed by Dr. Jeff Arnold for USDA, Agricultural

factor, soil type and vegetation above contribute in

Research Service (ARS). SWAT was developed todetermining the amount of runoff and water that can bepredict the impacts of land management practices on

stored into

water, sediment and chemical yields in watersheds withthesoil through infiltration process(Turkelboom et al., 2008).

different types of soil, land use and management over

The Kuanji watershed is one of the watersheds in Padanglong periods of time (Neitsch et al., 2004).

2

City with an area of 202.7 km and consists of 5
sub-catchments. According to Arsyad (2006), the slopeof the land is closely related to the erosion. The higher

SWAT Simulation on Kuranji Watershed
SWAT model allows performing a partial watershed

the slope, the infiltration of rainwater into the soil

analysis. SWAT model describes the interaction of eachbecomes smaller, so the surface runoff and erosion

smallest element of the watershed that is in the form of

becomes larger. In this study, a conservation simulation

HRU (Hydrological Response Unit). The HRU describesof watershed discharge was conducted using SWAT

the hydrological response occurring in one unit area. The

Application

Geographic

division of HRU is based on overlay of soil

information system (GIS) data are analyzed using thecharacteristics, land use, and land slope. The SWAT

Arc-GIS application Arc Interfaces software for Soil andmodel analyzes the overall HRU in the watershed, to

Water Assessment Tool (Arc-SWAT 12). The application

describe the watershed condition thoroughly but can

can calculate the influence of climate parameters on theanalyze the watershed conditions from the smallest

amount of discharge from a stream, sedimentation,

element of HRU. The stages in SWAT analysis are as(Arnoldetal.,1994).

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 04

follows:

large soil, then water is first stored in the soil that will

1.

Watershed delineation

increase groundwater availability. If the infiltration rate

The Kuranji River Basin was made by Automaticis small then surface flow will increase, this may result in

Watershed

SWAT

increased erosion, increase rapid river discharge, andapplication. The DEM map of the Kuranjirising energy damaged of water. So the focus of thewatershed area with a resolution of 30 m x 30 m

conservation effort in the Kuranji watershed is thewas used as input to present the elevation difference

increase of water storage into the soil.

from each point to see the direction of surface water

In this activity there were several alternatives to increase

flow. The flow of the formed river will form awater storage ability, but not to eliminate thewatershed.

hydrological function. The effort is an appropriate

Hydrological Response Unit (HRU)

targeted reforestation. Tree planting should be targeted in

The hydrological region was formed by theorder to affect the condition of Kuranji watershed. The

manufacture of Hydrological Response Unit (HRU)

location of HRUs that has a large influence on runoff andin SWAT applications. Input data in the form arehigh water damage has been used as a working area inland use maps, soil map and the slope of the land.

land conservation scenarios in terms of landuse, slope,

The slope used in determining the HRU is divided

soil, channel, and others.

2.

Delineation

methodininto several divisions according to Arsyad (2006) ie< 3; 3-8; 8-15; 5-30; 30-45; > 45. The threshold of

Result and Discussions

the percentage of total area used for land use (10%),soil type (5%), and Slope (5%) has a percentage of3.

4.

area smaller than the threshold specified to be

1. Geographical Condition of Kuranji Watershed
Kuranji is geographically located at 100o20'31.20 "-ignored.

100o33'50.40" East Longitude and 00o55'59.88 "-SWAT simulation

00o47'24" South Latitude. Kuranji watershed has an area

At this stage the input data used is the simulation

202 km2 with a main river length of 32.41 km and a

period of 2010-2015. The data files include climate

river density of 1.36 / km. This watershed has several

station data (.txt), daily rainfall data files (*.pcp),

sub-basins, among others: (1) Kuranji Sub-basin (Andaily temperature (*.tmp) and weather generator

area of 19.86 km2, the main river length of 14.66 km);files (*.wgn) files.

(2) Belimbing sub-basin (An area of 62.64 km2 with the

Visualization of simulation results.

main river length 17.08 km) ; (3) Air Sungkai sub-basin

At the stage of visualization the desired output(An area of 6 km2 with length of main river 3.63 km);parameters can be displayed in ArcSWAT, in the(4) Padang Janiah

form of color gradations.

with a main river length of 18.86 km); And (5) Limau

Sub-Basin (An area of 82.26 km2

SWAT model on Kuranji watershed can be used as a

Manih sub-basin (an area of 31,93 km2 with length ofguideline for conservation. Because the simulation

main river 16,42 km).

results will illustrate the condition of HRU from Kuranji
watershed related to runoff, erosion, evapotranspirationand ground water recharge that happened. Thus can be

2. Climate Condition
Climatic conditions in the Kuranji watershed is an area

determined area / HRU that need to be done to minimize

with tropical climatic conditions where rainfall is highthe conservation of runoff, erosion and destructive power

enough between 3500-4000 mm/year of climaticof water. The simulation result also aims to determine theconditions in the Kuranji

location / area of the watershed that needs to be

Table 1.

watershed can be seen inconserved.
Kuranji River Conservation Area Analysis
The land slope, soil type and vegetation factor in an

3. Soil Condition
Soil characteristics for Kuranji watershed are grouped

HRU are instrumental in determining the amount of

into 4 types of soils based on FAO 1974 (in Neitsch,

runoff that occurs and the amount of water that can be2005) (Table 2).

stored into the soil through infiltration process. If runoff
occurs during minor rain and infiltration of water intoProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 04

4. Land Use
Land use in Kuranji watershed has changed significantly.
Based on the data of land use obtained from Rupa Bumi
Indonesia in 2014, the land use condition as in Table 3 isobtained.
5. SWAT Simulation
Watershed delineation
The depiction of the watershed requires DEM data in its
processing. In this study the DEM data used had aresolution of 30 x 30 m.

Fig. 1 Kuranji Watershed

Table 1 Climate Condition in Kuranji WatershedThis is intended for SWAT processing in a more detailed

RH
(%)
83,5

Rainfall(mm/m)
31,04

ET(mm/m)
110,0

Wind
(m/s)
2,1

Radiation(Mj/m2)14,6kuranji watershed and closer to real conditions in the

Jan

Temp
(oC)
26,5

Feb

26,3

84,7

30,42

101,2

2,1

14,2

Automatic Watershed Delineation method. The results of

Mar

26,6

83,5

34,40

123,0

2,1

16,3

Kuranji River Basin depiction can be seen in Figure 1.

Apr

26,9

83,1

29,62

119,0

1,8

16,1

May

27,0

82,8

25,88

121,3

1,5

16,0

June

26,6

81,6

29,27

109,8

1,6

15,1

July

26,3

79,9

34,58

122,8

1,7

16,2

August

26,3

78,7

26,35

132,0

1,7

17,5

Hydrological Response Unit (HRU)

Sep

26,7

78,0

27,00

136,3

1,7

18,6

The hydrological region is formed by the manufacture of

Oct

26,9

79,0

19,98

136,3

1,8

18,0

Nov

26,8

80,8

20,57

120,4

1,9

16,4

Dec

26,6

82,2

29,87

113,0

2,1

15,4

Month

field. The delineation of watershed was done by

Based on the delineation result, the total watershed area
is 21795.364 ha with five sub-catchments.

Hydrological

Response

Unit

(HRU)

in

SWAT

applications. The threshold of the percentage of total areaused for land use (10%), soil type (5%), and Slope (5%)

Table 2.

Soil characteristics of kuranji watershed

has a percentage of area smaller than the thresholdspecified to be ignored. The results of this process forSoil TypeArea (ha)Perscentage (%)

Vertisol

12146,756

54,09

Phaeozem

6778,852

30,19

Andosol

1708,922

7,61

SWAT Analysis Results
At this stage the input data used was the simulation

Ferralsols

1822,707

8,12

period of 2015. The data files include climate station

Total

22065,269

100

data (.txt), daily rainfall data files (.pcp), daily

Kuranji watershed were 2034 HRU.

temperature (.tmp) and weather generator files (.wgn)
Table 3

Land use condition

Land use
airportPrimary Dryland Forest

files.
Area (ha)118,78

6. Analysis of Kuranji Watershed Conservation

12128,61

Water Body

63,34

Using SWAT Applications
SWAT model on Kuranji watershed can be used as a

Secondary Dryland Forests

124,08

guideline

Field

for

conservation. This is because

the

0,1

simulation results will illustrate the condition of HRU

Mixed Forest

1542,07from Kuranji watershed related to runoff, erosion,

Settlement

1542,72

evapotranspiration and ground water recharge that

Rice fields

5318,57

happened. Thus can be determined area / HRU that needShrubs1162,11

to be done to minimize the conservation of runoff,

Total

22000.38

erosion and destructive power of water. The simulation
result also aims to determine the location / area of thewatershed that needs to be done conservation, so that

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 04

conservation is done on target (Irsyad, 2011).

Table 4 Conservation site in Kuranji Watershed

Based on the simulation results in Kuranji watershed,

Sub-District

Area (ha)the location with high runoff distribution, this can be

Limau Manih

81,56

seen in Figure 2.

Lambung Bukit

42,27

The result of simulation for erosion in Kuranji

Gunung Sarik

86,32

watershed is obtained by several locations with a

Kuranji

60,20

relatively large erosion level with the distribution can be

Lubuk Minturun

64,45

seen in Figure 3.

Total

334,80

Reforestation / tree planting should be targeted so thatconservation is done correctly affect the condition of

The location of HRUs that has a large influence on

Kuranji watershed.

runoff and high water damage has been used as aworking area in land conservation scenarios in terms ofland use, slope, soil, channel, and others. The result of
location determination based on slope and landuse thatneed to be done reforestation obtained some location in
middle part of DAS. The location of reforestation can beseen in Figure 4.
The location of conservation activities is located inseveral sub-districts in Kuranji watershed. This can beseen in Table 4. The location has a slope of> 45 and has
open land cover, grass and shrubs, the location is also

Fig. 2 Runoff distribution based on HRU in
Kuranji Watershedvery risky due to landslides resulting from runoff andcarrying capacity Land to low surface slides.
Conclusion
The Kuranji watershed has a total basin area of
21795,364 ha with five sub-catchments. SWAT analysis
result for Kuranji watershed was obtained by DAS HRU
as much as 2,034 HRU. The largest runoff is 84 mm withan area of 75.195 ha, and spread in four sub-districts(Pauh, Padang Utara, Nanggalo, and Kototengah). The
recommended conservation areas are Limau Manih(81.56 ha), Lambung Bukit (42.27 ha), Gunung Sarik

Fig. 3 Erosion distribution based on HRU in
Kuranji Watershed

Fig. 4 Conservation site in Kuranji watershed(86.32 ha), Kuranji (60.20 ha), and Lubuk Minturun(64.45 ha).
Reference
Arnold JG, Williams JR, Srinivasan R, King KW andGriggs RH (1994) SWAT (Soil and Water Assessment
Tool) User Manual. Agricultural Research Service,
Grassland. Soil and Water Research Lab. US
Department of Agriculture.
Arnold JG. Allen PM, and Bernhardt G (1993) A
Comprehensive Surface-Groundwater Flow Model.
Journal of Hydrology 142: 47-69.
Arsyad S (2006) Soil and Water Conservation. Bogor:
IPB Press
Irsyad and Fadli (2011) Cidanau discharge analysis using
SWAT Application. Thesis: Institut Pertanian Bogor.
Bogor.
Kodoatie RJ, Sjarief R (2008) Integrated Water
Resources Management. Yogyakarta: Penerbit Andi.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 3 - Watershed Management -: 04

Neitsch SL, Arnold JG, Kiniry JR, Srinivasan R, andWilliams JR (2004) Soil and Water Assessment Tool,
Input/Output File Documentation Version 2005. Texas:
Texas Water Resources Institute.
Neitsch SL, Arnold JG, Kiniry JR, Srinivasan R, andWilliams JR (2005) Soil and Water Assessment Tool,
Theorical Documentation Version 2005. Grassland
Soil and Water Research Laboratory, Agricultural
Research Service, Blackland Research Center-Texas
Agricultural Experiment Station. USA.
Poyatos R, Latron J, and Liorens P (2003) Land Use andLand Cover Change After Agricultural Abandonment“The Case of a Mediterranean Mountain Area (Catalan
Pre-Pyrenees)”. Mountain Research and Development
23 (4):362-368.
Turkelboom F, Poesen J, G Trébuil (2008) The multiple
land degradation effects caused by land-use
intensification in tropical steeplands: A catchment

study from northern Thailand. Catena 75: 102–116.
Baker TJ and Miller SN (2013) Using the Soil and Water
Assessment Tool (SWAT) to assess land use impact onwater resources in an East African watershed. Journalof Hydrology 486: 100–111.
Ghaffari G, Keesstra S, Ghodousi J, and Ahmadi H(2010) SWAT-simulated hydrological impact ofland-use change in the Zanjanrood Basin, Northwest
Iran. Hydrological Processes 24: 892–903.
Niehoff D, Fritscha U, Bronstert A (2002) Land-use
impacts on storm-runoff generation: scenarios ofland-use change and simulation of hydrologicalresponse in a meso-scale catchment in SW-Germany.
Journal of Hydrology 267 : 80–93.
Pfister L, Kwadijk J, Musy A, Bronstertd A, And
Hoffmann L (2004) Climate Change, Land Use
Change And Runoff Prediction In The Rhine–Meuse
Basins. River Research And Applications 20: 229–241.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 01

Phytoremediation of Soil Contaminated by Chromium (Cr) of Industrial Waste Using
Mendong Plant (Fimbrystilis globulosa) in Its Combination With Agrobacterium Sp.I3 or
Organic Matter○Pungky Ferina, Supriyadi, Retno Rosariastuti*(Soil Science, Faculty of Agriculture, Sebelas Maret University, Indonesia)*) corresponding author: retnobs@yahoo.co.id

SUMMARY
Chromium (Cr) is one of the most dangerous heavy metal for environment, especially chromium hexavalent.
Many characteristics of chromium hexavalent are soluble, toxic, carcinogenic, etc. Soil contaminated bychromium is dangerous to be planted by food crop, because Cr will be uptaken by plant and can come into
nutrient cycle, so it must be remediated. Bioremediation is a way to degrade, move and change Cr (VI) into Cr(III), using microorganism or plant (Phytoremediation) as bioremediation agent. Organic Matter (compost) also
can be used in heavy metal bioremediation, because it can chelate the metal. Mendong in its association with
Agrobacterium Sp.I3 or compost used in this research. The result showed that mendong plant effective asbioremediator of soil contaminated by Cr. Soil Cr which has highest decreased and effectiveness offitoremediation reached of 58,39% on treatment combination of artificial fertilizer, Agrobacterium Sp.I3
and Mendong Plant. Chromium uptaken by roots less than Cr uptaken by shoot of plant. Bioremediation has
also affected in decreasing soil pH, and increasing soil cation exchange capacity (CEC) and total soil bacterialcolonies. Mendong plant has good growth and good condition during the bioremediation process.

Introduction
Karanganyar Regency, (near Solo City) is one ofregency in Central Java Province, Indonesia, which
has many industrial activities, especially textile
industries and also agricultural activities. Many
agricultural lands here have been irrigated byindustrial waste water. Textile industrial waste
contains toxic material that are harmful to theenvironment, water, soil, andhuman health.
According of the Ministry of the Environment (2010),
many of heavy metals that are produced by the textile
industry are Ag, Cu, Cr, Pb, Cd, Hg, Ni, and Zn. Oneof the dangerous heavy metals is Chromium (Cr).
Jaten and Kebakkramat subdistrict of Karanganyar
Regency are suspected to be polluted by chromium
above quality standart.
Soils in Jaten containedof Cr between 0.531-3.99 ppm (Widyastuti et al.,2003). In general, standart quality of chromium insoils that is allowed by the Indonesian Givemment is
2.3 ppm (Ministry of Environment 2013).
Technology for recovering quality of soil
contaminated by heavy metal that is now being
developed is bioremediation. Bioremediation is a way
to degrade, move, and change harmful compounds
into more simple and harmless (Kamaludeen et al.
2003). Bioremediation that uses plants asbioremediation agent, called Phytoremediation.
Phytoremediation is a technology for reducing,degrading, and isolating polluters of the environment
using plant (Pramono et al., 2013). Plant that can beused as a hiperaccumulator is a plant that has highdurability, rapid growth, ability to do phytoextractionof heavy metal, and it is not a food crop. Mendong
plant is a non food plant for human or animal
consumption, has characteristics : rapid growth,easily cultivated, survive in flooded condition, andhigh economic value of craft materials. So
Mendong plant can be selected as a plant inphytoremediation.
Other technique that can be employed to clean
up soils contaminated by heavy metals is
Rhizoremediation. Rhizoremediation is a process thatinvolves the association of mutualism rizosphere
plants with microorganisms, which can releaseexudate and oxygen into the soil to decrease
chromium (Pramono et al., 2013). Bacterias used in
the remediation of chromium resistant to chromium
and survive in the environmental contaminated bychromium. One of the bacteria that is resistant to theenvironmental contaminated by heavy metals isAgrobacterium sp I3. This bacteria has been isolatedby Rosariastuti. This bacteria can increase theuptake of Cr and translocate it to the shoot ofplant. Addition of Agrobacterium sp I3 isolate canincrease the growth of Rami plant (Rosariastuti etal., 2013). The purpose of this study was to explore
the ability of Mendong plant in absorbing chromiumof chromium contaminated soil, by combined itwith Agrobacterium sp I3 or compost (because
compost can be used as chelating agent of heavy
metal), and its
influence
in decreasing Cr
soils.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 01

Material and Method
This study was carried out on the paddy fields
contaminated by chromium in Waru village,
Kebakkramat subdistrict, Karanganyar regency ofCentral Java Province, from May to October 2016.
This study has factorial patern, consisted of threefactors (treatments), i.e. artificial fertilizers (P),chelator (Agrobacterium sp I3; or compost) (B),
Plant
(T). Twelve treatment (Table 1) werearranged in
Randomized
Completely Block
Design as the based design with 3 replications.

Table 1 Treatments
No.

Treatments

Explanation

1.

P0B0T0Without artificial fertilizers, without chelators, without Mendong plant (control)

2.

P0B0T1

Without artificial fertilizers, without chelators, with Mendong plant

3.

P0B1T0Without artificial fertilizers, with Agrobacterium sp I3, without Mendong plant

4.

P0B1T1

Without artificial fertilizers, with Agrobacterium sp I3, with Mendong plant

5.

P0B2T0Without artificial fertilizers, with compost, without Mendong plant

6.

P0B2T1

Without artificial fertilizers, with compost, with Mendong plant

7.

P1B0T0With artificial fertilizers, without chelators, without Mendong plant (control)

8.

P1B0T1

With artificial fertilizers, without chelators, with Mendong plant

9.

P1B1T0With artificial fertilizers, with Agrobacterium sp I3, without Mendong plant

10.

P1B1T1

With artificial fertilizers, with Agrobacterium sp I3, with Mendong plant

11.

P1B2T0With artificial fertilizers, with compost, without Mendong plant

12.

P1B2T1

With artificial fertilizers, with compost, with Mendong plant

Preparation of Bacteria Carrier
Carrier materials used for this study were 7.5 kg brancompost, 750 mL EM-4, and 15 L of water. The
materials were mixed well and then incubated for 2
months, than sterilized using presto pan.
Preparation of Agrobacteriumsp spI3 Inoculum
Replication of Agrobakterium sp I3 inoculum wasstarted with preparation of the LB (Luria Bertani)
medium with the composition of 10 g tripton, 10 g
NaCl, 5 g yeast extract, 100 mL destilled water,
15-20 g, NA (Nutrient Agar) medium with thecomposition of 10 g beef extract, 10 g pepton, 5 g
NaCl, 1000 mL destilled water, and 15 g agar/L.
After obtaining pure isolate, purification was donein Luria Bertani liquid in Erlenmeyer and mixed up
to gain density of 1010 cells/mL. Carrier was thenenriched with squirted Agrobacterium sp I3 to sterile
carrier. The comparison was 600 mL Agrobacterium
sp I3 for 2 kg of the carrier.
Implementation of the Study
This study used compost with dose to Mendong
plant was 5 t/ha, while the dose of NPK fertilizer for
Mendong plant was 400 kg/ha (Darini 2012). The
dose of compost applied for Mendong plant treatment
was 0.75 kg/plot of land. The dose of compost
applied for the control treatment (without Mendong

plant) was 1.125 kg/plot of land. Artificial fertilizers
applied for Mendong plant treatment were 19.59 g
Urea/plot of land, 25 g of SP-36/plot of land, and 15
g KCl/plot of land. Artificial fertilizers applied forcontrol treatment (without Mendong plant) were
19.56 g Urea/plot of land, 18.75 g SP-36/plot of land,and 11.25 g KCl/plot of land. Application of compost
and artificial fertilizers was done 1 day before
planting of Mendong plant.
The size of plot of land was 1.5 m x 1 m.
Each plot planted by 6 (six) seeds of Mendong
with planting space 50x50 cm. Field observations
were plant height of one time in a week and plant
dry weight after harvesting. Plant dry weightconsisted of parts of the root and the shoot of
Mendong plant. Harvest was carried out at 30 days
Mendong planted and applicated byafter
Agrobacterium sp I3 isolate.
Analysis of the content of chromium in soil,roots, and shoots of mendong plant was done using
wet destruction method with AAS (Atomic
Absorption Spectrophotometer). Soil characteristics
parameters analyzed were CEC (Amonium Asetat
Saturation), C-Organic (Walkley and Black), pH H2O(Electrometric), and total bacterial colonies (plate
count). Datas were analyzed by statistical analysis
using Anova at 5 % level , continued with test of
Duncan at 5 % level, and correlation test.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 01

Result and Discussions
The result of laboratory analysis of Soil Characteristics were in table 2 below:
Table 2 Soil Characteristics
No. Treatments Soil pH

Initial Soil
P0B0T0(control)
2.
P0B0T1
3.
P0B1T04.
P0B1T1
5.
P0B2T06.
P0B2T1
7.
P1B0T08.
P1B0T19.
P1B1T010.
P1B1T111.
P1B2T012.
P1B2T1
Source: Primary
1.

Soil CEC(cmol(+).kg-1)

7.55
6.96bc19.61430.22ab

6.59a
6.76abc
7.02c
6.88abc
6.90bc
6.59a
6.68ab
6.88abc
6.81abc
6.69ab
6.59a26.43ab32.24b
21.67a22.39ab23.91ab29.98ab22.79ab25.73ab24.97ab26.79ab24.21abBioremediation were decreasing pHfrom pH of
initial soil and control, and increasing CEC from
CEC of initial soil, also almost all of total Soilbacterial colonies from total Soil bacterial colonies
of initial soil. Bacterial inoculation treatment
increasing soil C organic and total soil bacterialcolonies higher than compost treatment.
Soil Chromium
Soil chromiums are in Table 3 below.
Table 3 Soil Chromium
No
Treatment

Soil
Chromium
mg.kg-1
2.460
2.438b
1.737ab1.853ab1.714ab2.155ab1.423ab1.782ab1.554a1.762ab1.023a1.750ab1.550aInitial1.
P0B0T02.
P0B0T1
3.
P0B1T04.
P0B1T1
5.
P0B2T06.
P0B2T1
7.
P1B0T08.
P1B0T19.
P1B1T010.
P1B1T111.
P1B2T012.
P1B2T1
Source: primary
Bioremediation decreased soil chromium
content in all treatments, from initial soil chromiumand control. Before bioremediation, initial soil
chromium was 2.46 mg.kg-1 which was above thestandard quality of
2.3 mg.kg-1 (Ministry of

SoilC-organic
(%)
3.31
2.91a

Total Soil Bacterial Colonies(Log 10 CFU.g-1)
12.62
12.65a2.99a12.18a3.28a16.18b
3.72a16.85c
3.11a
12.66a4.14a12.88a2.85a14.54a2.71a12.98a3.47a
14.54a3.05a
14.57a3.23a12.24a3.32a12.10aEnvironment 2010). Decreasing soil chromium wascaused by decreasing of soil pH. High H+ ionsincreased the solubility of chromium (Cr(VI)), so
chromium become available and easy to be taken
up by plant. Artificial fertilizers were decreasing soil
pH because it has soluble properties in water orhigroskopis that can cause soil H+ ions become high.
High H+ ion in water increasing the solubility ofhexavalent chromium, so it becomes easy uptakenby plants (Yunilda 2008).
Compost treatment
reduced soil pH value, because compost contains freemineral acids.
Plant treatment is decreasing soil chromium.
Low Molecular Weight Organic Acid (LMWOA),
such as sitric acid, oxalic acid, malic acid and acetic
acid, produced by plant and microorganism, arenatural organic chelating agents. They will make acomplex compound with metal in low to medium
stability (Souza et al. 2013). Nacimento et al.
(2006a) and Freitas et al. (2009) said that naturalorganic chelating agents make the phytoextraction
process more efficient than synthetic chelating agent.
Bhargawa et al. (2012) and Taiwo et al. (2016)
said that organic matter, such as compost, andmicroorganism can increase the solubility, mobility
and availability of metal for plant and have an
importantrole in maximizing
contaminanttransport from root to shoot.
Treatment with Mendong plant (T1) had
chromium content in the soil that was lower than
without Mendong plant (T0). Treatment with
Agrobacterium sp I3 or compost had chromium
content in the soil that was lower than control
treatment (P0B0T0). It is proven by the increase ofC-organic after bioremediation. High C-organic in theProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 01

soil cause nutrient elements high availability that has
an impact on the growth of higher Mendong plant.
The compost on P1B2T1 treatments could decrease
Cr content was 1.55 µg/g.
Results of Anova showed that the treatmentsof artificial fertilizers, Agrobacterium sp I3, compostand Mendong plant have significantly effect indecreasing soil chromium. The lowest decrease of Cr
soil was in control (P0B0T0 = 2.438 mg.kg-1 =0.89%) and the highest decrease of Cr soil is in
P1B1T1 treatment (1.023 mg.kg-1 = 58.39%). Basedon the correlation tests, soil chromium has positively
correlated to soil pH, and negatively correlated tototal soil bacterial colonies, soil CEC, and C-organic.
Mendong plant can increase CEC. The
process of bioremediation make Cr6+ cations areexchanged by other cations, Cr in the soil areexchanged by other cations then Cr were uptakenby plants, so Cr soil could be reduced.
Agrobacterium sp I3 acted elaborate compost into thenutrient elements ready to be uptaken by the plant(Hanafiah et al 2009).
Treatment combinations ofartificial
fertilizers, Agrobacterium sp I3 with Mendong plantdecreased soil chromium. Agrobacterium spI3
treatment made a symbiosis with root of Mendong
plant. Root of Mendong produced exudates
containing nutrient for Agrobacterium spI3.
Agrobacterium spI3, also produced nutrientfor
plant. Bacteria and plant produced LMWOA, which
would chelate metal, and metal became more soluble,
mobile and available for plant (Souza et al. 2013). So
thissymbiosis
could
decreasechromium
concentration in soil. Agrobacterium spI3 has hightolerance to hexavalent chromium (Rosariastuti et al.
2013).
In
phytostabilization
mechanisms,
Agrobacterium sp I3 helps Mendong plant toaccelerate chromium in rhizosphere areas or
chromium uptaken by root but it cannot be toxic forroot of Mendong plant.
Total soil bacterial colonies in all treatments
increased, except on the P0B0T1. Agrobacterium sp
had total bacterial colonies more thanI3 treatment
compost treatments. Treatment with highest total soil
bacterial colonies of 16.85 Log 10 CFU.g-1 was theP0B1T1 treatment. Application of Agrobacterium sp
I3 increased the total soil bacterial colonies. The
resilience of bacteria can be seen from the number ofcolonies. If number of total soil bacterial colonies
before bioremediation is low, and become high after
bioremediation, it means that Agrobacterium spI3
proved capability of adapting and good tolerance inthose plots.
Result of correlations analysis was that therelationship among soil pH, soil CEC, soil C organic,
Total Soil Bacterial Colonies and soil chromium is
not strong (r < 0,5).
Only these four soil
characteristics have relatively strong relationship,

they were C organic has negative relationship with C
pH (r = -0.311). it means that increasing C
organic will decreasing pH. Total bacterial colonies
has positively relationship with C organis (r = 0.427).
It means that increasing of total bacterial colonies
will increasing C organic. Soil Cr
has positively
relationship with soil pH and soil CEC, but has
negatively relationship with soil C organic and plant
dry weight.
Removal effectivity/phytoremediation effectivenes
Mendong plant ability in decreasing soil chromium. It
can be calculated to detect the effectiveness as
phytoremediator from removal effectivity. Removal
effectivity/phytoremediation effectiveness is the
successfull of Mendong plant in uptaking chromium
in different concentration. Removal effectivity can beseen from removal effectivity value (Prayudi et al.,2015).
Removaleffectivity/phytoremediation
effectiveness can be calculated using the following
formula:RE(%)=
Table 4 Chromium Removal Effectivity
No Treatment
Removal Effectivity(%)
1.
P0B0T00.87
2.
P0B0T1
29.37
3.
P0B1T024.65
4.
P0B1T1
30.32
5.
P0B2T012.38
6.
P0B2T142.15
7.
P1B0T027.55
8.
P1B0T136.98
9.
P1B1T028.38
10.
P1B1T158.39
11.
P1B2T028.84
12.
P1B2T1
36.98
Source : Based on the Result of Calculation
Removal effectivity of soil contaminated bychromium was high in the treatment of Mendong
plant with artificial fertilizers, and Agrobacterium sp
I3 (P1B1T1) of 58.39 %. Whereas other treatment
combinations using Mendong plant had chromium
removal effectivity more than without Mendong
plant.
Mendong plant was effective as abioremediator agent of soil contaminated bychromium when it was combined with artificial
fertilizers, Agrobakterium sp I3, or compost.
Mendong plant treatment without
artificial
fertilizers and chelators could only decrease soil
chromium by 29.37 %. So, a better strategy forbioremediation of Cr contaminated soil
is a

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 01

combination treatment that can
Plant Characteristics

maximize theabsorption of chromium.

The Result plant characteristics analysis can be seen at Table 5 below.
Table 5 Plant Characteristics
No.

Treatments

1.
2.
3.
4.
5.
6.

P0B0T1P0B1T1P0B2T1
P1B0T1P1B1T1P1B2T1

Dry Weight
g.
Root
9.36b
7.33ab
6.82ab
8.32ab
8.33ab
2.65a

Shoot
4.60a
7.07ab
6.79ab
7.14ab
8.39b
5.29a

Total
13.957ab14.403ab13.609ab15.460ab
16.725b7.943aCr Content in Plant
µ.g-1
Root
1.491a0.450b0.649a1.782a1.123a0.450aSource : Based on the Result of Calculation
Dry Weight of Mendong Plant
Table 5 showed that the P1B2T1 treatment had thelowest dry weight, means had the lowest growth.
Highest dry weight was 16.725 g on plant with
P1B1T1 treatment. Based on Anova, chelators
significantly influencing the dry weight. Based on
the correlations analysis, plant dry weight positively
correlated to root chromium content, root chromium
uptake,pH and CEC, but negatively correlated
to shoot chromium content and shoot chromium
uptake, C organic and soil Cr. Hiperaccumulator
plant can be tolerance against heavy metals atleast 10-20 times of normal plant and still produce
high biomass (Baker et al., 1994).

Chromium Content and Uptake by Mendong
Plant
Chromium content in roots was
lower thanchromium content in shoot of Mendong plant.
Mendong plant with control treatment (P0B0T1) had
the lowest chromium content inshoot of plant.
Treatment of compost application (B2) had thehighest chromium content in the shoot.
Based on the Anova, chelator significantly
influencing chromium content in shoot of Mendong.
This indicated that addition of compost improve
C-organic to soil. The high content of C-organic insoil will increasing chromium uptake by plant,
because C-organic affected chromium uptake
processes in plant roots and shoot. Bhargawa et al.
(2012) and Taiwo et al. (2016) said that organic
matter, such as compost, and microorganism canincrease the solubility, mobility and availability ofmetal for plant and have an important role inmaximizing contaminant transport from root toshoot.
Root Cr content and root Cr uptake of
Mendong was lower than in shoot. It indicated that Cr
was translocated from root to shoot. This process
called phytoextraction. The highest Chromium uptake

Shoot6.082a8.020a30.259a6.162a4.841a26.639aTotal
3.004ab4.352ab15.423c3.805ab2.988a17.892c

Cr
Uptaken by Plant
µ
Root
Shoot
Total
13.96c27.98a41.93a3.30ab
56.68ab 62.68b
4.43ab 205.46c 209.89c
14.83c44.00ab 58.82ab
9.36b
40.62ab 49.97ab
1.19a
140.92b 142.11bc

in shoot of Mendong plant was 209.8 µg (P0B2T1).
Based on the Cr uptake, Mendong plant can beconsidered as a Cr hiperaccumulator plant. A plantcan be considered as hiperaccumulator if it can
uptake more than 100 ppm for Cd, Cr, Pb, and Co(Baker et al., 1994). Control treatment had the lowest
total Cr uptaken by plant.
Primarily, the uptake Cr process occurs in root,
where Cr will accumulated in root cells. The root
cells are closely related to soil CEC. Soil CEC
increased during the bioremediation process, so ahigh soil CEC caused the high chromium uptake inthe root. Hexavalent chromium gets into the root
from epidermis, then crosses a series of cells andbreaks through the endodermis to xylem shoot of
the plant.
Based on the Anova, chelator treatment
significantly influencing total Cr content and total
Cr uptaken by plant. Based on correlations analysis,
total Cr content has positively relationship to shoot Cr
content, shoot Cr uptake, shoot Cr uptake by plant(total), CEC and Corganic. Total Cr uptaken by plant
has positively relationship to shoot Cr content, shootCr uptake, CEC, C organic and soil Cr. It means that
increasing soil Cr will increasing total Cr uptaken byplant.

Conclusion
The Mendong plant effective as a phytoremediator ofsoil contaminated by chromium and can be used asplant hiperaccumulator of chromium,
where Crwas uptake to root than translocate to shoot(phytoextraction). Chromium uptake in root was lessthan Cr uptake in shoot of plant. Bioremediation
decreased soil pH, increased soil CEC, soil C-organic,
and total soil bacterial colonies.
Both chelator (agrobacterium spI3
andcompost) can decrease soil Cr, but
the most
effective combination treatments in decreasing soil
chromium was Mendong plant in combination
treatmentwithartificial
fertilizer
andProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 01

agrobacterium spI3 (P1B1T1). This treatment had
highest phytoremediation effectivity: 58.39%,
42.15% in P0B2T1 treatment, and 36.98 % in
P1B0T1 treatment.
Removal effectivity of chromium in treatmentusing Mendong plant was higher than without
Mendong plant. Artificial fertilizers, Agrobacterium
sp I3 and compost increased the growth of Mendong
plant. The growth of Mendong plant was in a goodcondition during the bioremediation process.

Acknowledgement
1. Pungky Ferina and tim whose helping me in doing
this study
2. Dr. Ir. Supriyadi, MP, lecture of Agriculture
Faculty of Sebelas Maret University, my partnerin doing this study.
3. Department of Research and Development ofCentral Java Province goverment as the donor ofthis study.

References
Baker AJM, Reeves RD, and Hajar ASM (1994)
Heavy Metal Accumulation and Tolerance inBritish Population of the Metallophyte Thlaspi
caerulescens and Brassicaceae. New Phytologist
Trust127: 61-68.
[Balittan] Balai Penelitian Tanah (2009) Analisis
Kimia Tanah, Tanaman, Air, dan Pupuk. Bogor :Balai Penelitian Tanah Press.
Bhargava A, Carmona FF, Bhargava M, Srivastava S(2012) Approaches for enchanched phytoextractionof heavy metals. Journal of Environmental
Management 105: 103-120.
Darini Maria (2012) Kajian Jarak Tanam dan Dosis
Pupuk NPK Terhadap Sifat Agronomi Tanaman
Mendong Fimbristylis globulosa Serta Intensitas
Kompetisi
Gulma.
SkripsiAgroteknologi.
Universitas Sarjanawiyata Tamansiswa Yogyakarta.
Freitas EVD, do Nascimento CWA, Silva AJ, Duda
GP (2009) Citric acid enhances lead phytoextraction
from a soil contaminated by automotive batteries.
Revista Brasilleira de Cien cia do Solo 33: 467-473.
(In Portugese with abstract in English).

Hanafiah, Sabrina T, and Guchi H (2009) Biologi dan
Ekologi Tanah. Fakultas Pertanian Universitas
Sumatera Utara, Medan.
Kamaludeen S, Arunkumar K, Avudainayagam S(2003) Bioremediation of chromium contaminatedenvironments. Indian Journal of Experimental
Biology, 41 (9) : 972–985.
Ministry of Environment Indonesia (2010)
Kementrian Lingkungan Hidup. Himpunan
Peraturan Lingkungan Hidup. Ekojaya : Jakarta.
Nacimento CWA, and Xing B (2006) A review onenhanced metal availability and plant accumulation.
Scientia Agricola; 63: 299-311.
Pramono A, Irfan D, Ngadiman., Rosariastuti R(2013) Bacterial Cr (VI) Reduction and Its Impact.
Jurnal Ilmu Lingkungan 11 (2) : 120-131.
Prayudi MTA, Ahmad Z, Iskandar M (2015)
Fitoremediasi Tanah Tercemar Logam Cr dengan
Tumbuhan Akar Wangi pada Media Tanah
Berkompos.
SkripsiTeknikLingkungan.
Universitas Hasanuddin Makasar.
Rosariastuti R, Prijambada ID, Ngadiman,
Prawidyarini GS, and Putri AR (2013) Isolation
and Identification of Plant Growth Promoting andChromium Uptake Enhancing Bacteria from Soil
Contaminated by Leather Tanning Industrial Waste.
Journal of Basic and Applied Sciences, 9 :243–251.
Souza LA, Piotto FA, Nogueirol RC, Antunes R,
Azeveda(2013)
Review:
Useof
non-hyperaccumulator plant species for thephytoextraction of heavy metals using chelating
agents. Sci.Agric. V.70, n.4:290-295.
Taiwo AM, Gbadebo AM, Oyedepo JA, Ojekunie ZO,
Alo OM, Oyeniran AA, Onalaja OJ, Ogunjimi D,
Taiwo OT (2016) Bioremediation of industriallycontaminated soil using compost and planttechnology. Journal of hazardous
materials
304: 166-172.
Widyastuti E., Retno Rosariastuti M.M.A., JauhariSyamsiyah. 2003. Pengaruh macam bahan Organik
Terhadap Kelarutan dan Kadar Cr Tanaman Jagung(Zea mays L) Di Tanah Entisol yang tercemar
limbah cair industri tekstil batik. Seminar Nasional
Pengelolaan Lingkungan.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 02

Potency of rhizobiota consortium as biofertilizer inoculants
to inhibit basal rot and increase yield○Sudadi1, Hadiwiyono2 and Sumarno1
2)(1) Soil Science Department, Faculty of Agriculture, Universitas Sebelas Maret, Indonesia
Agrotechnology Department, Faculty of Agriculture, Universitas Sebelas Maret, Indonesia)
Abstract

Shallot is one of important vegetable commodity in Indonesia. Its production is often lower than consumption.
Low soil nutrients status and plant disesase maybe make it productivy low. Indeed, rhizosphere occupied byvarious rhizobacteria potentially has ability to increase available nutrient and inhibit growth of Fusarium
oxysporum f.cepae which cause basal rot disease. Research aims to study the potential of rhizobacteria
consortium as biofertilizer inoculants to inhibit basal rot disease and increase yield. Rhizobacteria were isolated
from rhizosphere of both healthy and suffer grow in Vertisol, Entisol and Andisol soils. Isolates taken thanevaluated their potential to solubilize P and K, and to oxidized So in agar plate as well as liquid media. Selectedisolates with high potential then evaluated their ability to inhibit growth of Fusarium oxysporum f. cepae in agar
plate media and consortium of them used as biofertilzer inoculant applied to plant in pot experiments. Resultshow that some isolated rhizobacteria solubilze P and K, and oxidize So also inhibit Fusarium growth in agar
plate media. Inoculation with rhizobacteria isolate consortium increase P-uptake and decrease basal rot diseaseintensity of shallot.
Key words: basal rot; P-solubilizer; K-solubilizer; So-oxydizer
Introduction
Nutrient deficiencies such as nitrogen (N),phosphorus (P), potassium (K) and sulfur (S) as
well as plant disease are two factors that often leadto decreased production and crop failure of onion(Allium ascalonicum L.). Deficiencies of P and S
nutrients can also degrade the production quality(Anonymous, 2009). Onion is one of importantvegetable in Indonesia and is consumed as aseasoning. This plant can grow in the lowlands andhighlands. Onion is an agricultural commodity thathas high economic value and its development has
the potential to improve the welfare of farmers inIndonesia. The interest of farmers to onion is highbut in concession still encountered various
obstacles. Improper control of pests and diseases
can have serious and detrimental consequences.
Basal rot or so-called "Moler" disease is one of thediseases that often lead to a reduction in onion
production in Indonesia (Ramadhan et al., 2015).
Moler Disease of (MDS) caused by the fungus ofFusarium oxysporum is characterized by thesymptoms of wilted fast plants, root rot, yellowing
and curling leaves, at the base of the stem grows
white fungus colonies, the plants become collapsed
and eventually die. Domestic onion production has
not been able to meet the increasing needs fasterthan its production.
Therefore, it is needed to provide nutrient andtoo control disease continuously during plant
growth to increase it productivity. Nitrogen, P, andK deficiencies have long been a major topic of soil
fertility management in Indonesia. Similarly, sulfur
deficiency has long been happening in Indonesia

with an increasingly widespread distribution area.
Elements of N, P and K are primary macro while S
is secondary macro nutrients to plants. Nitrogenand sulfur are the component of proteins, whilephosphorus is a constituent of nucleic acids (DNAand RNA) and high energy storage (ATP)compounds in plants. Potassium is a cytoplasmic
compound and cofactor of various enzymes.
The nutrients supply and protection against rootrot disease during plant growth can be met throughthe use of biofertilizers which microbial inoculants
isolated from plant risosphere. It has long been
known that plant rhizosphere is the most highly
populated part of the soil by various microbes (Pauland Clark, 1989; Coyne, 1999; Thies andGrossman, 2006) which have a range of functional
capabilities in increasing nutrient availability andin suppressing the growth of microbial cause’s
disease (Lopez-Real and Hodges, 1986; Keel et al.,1990). Similarly, microbes play crucial roles insustainable agriculture systems (Lopez-Real and
Hodges 1986; Rӧmheld and Neumann, 2006).
Especially for onions, the rhizosphere is occupied
by various fungi and bacteria have potential tocontrol basal rot disease (Bernadip et al., 2014) andto provide nutrients (Sudadi et al., 2013a,b;
Hadiwiyono et al., 2014). This study aims to
examine the potential of the risosphere's microbialconsortium as an inoculant of biological fertilizer
to suppress basal rot disease and improve onion
yield.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 02

Bacteria isolate number

12
BawangHealthymerah sehat

10

Suffer merah sakit
Bawang8
6
4
20
BantulNgargoyosoTawangmangu
Local Origin

Palur

Fig. 1 Isolate number of rhizobacteria fromrhizosphere

Isolate antagonize to Fusarium

4.5

BawangHealthymerah sehat
BawangSuffer merah sakit

4
3.5
3
2.5
2
1.5
1
0.5
0
BantulNgargoyosoTawangmangu

Palur

Local origin

Fig.2 Number of rhizobacteria isolates inhibits
growth of Fusarium oxysporum
12
Fungal Isolates number

Material and Method
The research was conducted from April to
November 2013. Experiments and analyzes werecarried out at the Lab. of Soil Biology andBiotechnology and Lab. of Chemistry Soil andFertility, Faculty of Agriculture UNS Surakarta.
Microbial
inoculants
includingFusarium
oxysporum fungi, were isolated from therhizosphere of onion plants both healthy and sufferfrom Moler using Potato Dextrose Agar (PDA)
medium for fungi and Nutrient Agar (NA) for
bacteria, from Palur Village, Mojolaban Sub
District, District of Sukoharjo, Central Java withsoil order of Vertisol, from Tawangmangu Area,
District of Karanganyar, Central Java with order ofAndisol and from Kretek area, Bantul, Yogyakarta
Special Region with Entisol order.
Fungal pure culture was store in potato dextrose
agar (PDA) while for bacteria in nutrient agar
medium (NA). Qualitative test of fungi andbacterial solubilize phosphate using Pikovskaya
media, fungi and potassium solubilizing bacteriausing Alexandrov medium, fungi and sulfur
oxydizing bacteria using Czapex-dok + sulfur
medium and non-symbiotic nitrogen-fixing bacteria(Azotobacter) using Jensen medium. Isolates
indicating high potency were further tested for theirability to inhibit the growth of Fusarium
oxysporum on agar medium. Isolates that
demonstrated a high ability to inhibit the growth ofFusarium oxysporum were selected for further
testing in dissolving P, K and oxidized So in liquidmedium and in soil, and in decreasing basal rot
disease in a pot experiment at greenhouse.
Variables observed include the ability to provide P,
K and S. Statistical analysis using F test followedby Duncan's multiple-range test 95% confidence
level.

BawangHealthy merah sehat
Bawangmerah
sakit
Suffer from
moler

10
8
6
4
2
0
BantulNgargoyoso Tawangmangu

Palur

Local origin

Fig.3 Number
rhizosphere
10
Isolate antagonize toFusarium

Result and Discussion
From the isolation that has been done
from four areas namely Tawangmangu, andNgargoyoso, with the order of Andisol, from Palur,
Sukoharjo with Vertisol order and from Bantul, DI
Yogyakarta with Entisol soil order obtained 40
bacterial isolates and 41 isolates of fungus,
including Fusarium oxysporum fungus isolatecausing moler disease in onion. The isolates
obtained maybe are a small portion of the
population of bacteria and fungi present in therhizosphere of healthy and suffer onion from moler
disease. Isolation was done gradually and thefungal and bacteria classifying according to theirmorphological similarity and colony color.

8

offungalisolatedfrom

Ngargoyoso Tawangmangu

Palur

BawangHealthymerah
plant sehat
BawangSeverelymerah
plant sakit

64
20
Bantul-2

Local origin

Fig. 4 Isolates number of fungal inhibit tousarium oxysporum growth

F2D1

F2D2

F1D2

10.00

F1D1

15.00

F1D0

20.00

19.71

25.00

25.99

30.00

15.20

NPK

F3D2

F3D1

F3D0

F2D0

F0D2

0.00

F0D1

5.00
F0D0

Soil available-P, ppm

Fig. 6 Qualitative test on the ability of somerhizobacteria isolates to solubilze P and tooxydize So

17.86

Treatments combination
Fig. 7 The effect of rhizobiota consortium
formula and organic fertilizer dosages on soil
available-P of Alfisols
Basal rot disease intensity, (%)% isolate antagonize to Fusarium

Kind of fungsional bacteria

20.36

30.95

S-oxydizer S
Pengoksidasi

Pelarut P
P-solubilizer

10.61

28.57

NBH TBK 3
12

19.39

40

0.4

PBH
17

12.94

40.48

PBH PBH 7 TBH
17
18

11.93

50

0.5

12.47

60

0.83

0.8

17.38

57.14

1

8.82

70

1.7

1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0

13.11

In general, the population of bacteria in therhizosphere of healthy onion is higher than on thesick onion plants. This is because healthy plants orhealthy soils are characterized by high diversity
and microbial density. The same thing is found in
total fungus that is also higher in the environmentof roots of healthy onion roots. In line with the
population density, the number of bacterial isolates
from the roots of healthy plants more than the sickplants (Fig 1). This means that the diversity ofbacteria in the rhizosphere of healthy onion plants
is higher than in sick plants. The rhizosphere ofhealthy plants inhabited more bacteria that have theability to inhibit the growth of Fusarium
oxysporum (54.17%) compared to the rhizosphereof onion that are attacked by root rot disease(38.46%) (Fig.1, 2).
Similarly, the number of fungal isolates that havethe ability to inhibit the growth of Fusarium
oxysporum is higher in healthy onion rhizosphere(70.59%) than onion that is suffer from Molerdisease (66.67%) (Fig.3, 4). In this case thepopulation of antagonistic bacteria and fungi
dominating the onion roots environment and able tosuppress the growth of Fusarium oxysporum so thatplants grow healthy.
Figure 1-4 shows that microbials fromrhizosphere, both bacteria and fungi have thepotential as source of inoculum of biological agentsto control basal rot disease caused by the Fusarium
oxysporum. Basal rot disease (moler disease) is oneof the main diseases that often decrease productionof s in Indonesia. A number of fungal and bacterial
isolates antagonistic to Fusarium also demonstrate
their capability to dissolve P, dissolve K or oxidize
S (Fig. 5 and 6).
This suggests that the rhizospheric microbes
potentially decrease the incidence of basal rot
disease (moler disease) and increase yield whenused as inoculum of biofertilizer which has
capability as biological control agents of Molerdisease of.

Diameter of clean zona, cm

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 02

90
80
70
60
50
40
30
20
10
0

63.83442.62227.249

NOBF

BF1

BF2

Rhizobiota consortium Formula

30

Fig. 8 The effect of rhizobiota consortium
formula on basal rot disease intensity of

20
100
Pelarut P
P-solubilizer

Pelarut K
K-solubilizer

Pelarut P Nonpelarut
Non-solubilizer
P,K-solubilizer
dan K

P dan K

Fig. 5 Percentage of Fusarium antagonist fungal
isolates able to solubilize P and K

F0D0
F0D1
F0D2
F1D0
F1D1
F1D2
F2D0
F2D1
F2D2
F3D0
F3D1
F3D2
NPK

22.63

15.70

0.0

13.17

20.0

11.33

40.0

65.53
50.87

60.0

40.17

54.77

80.0

67.17

81.10

64.50

100.0

16.33
15.97

Bulb fresh weight, gplant-1

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 02Treatment combination
Fig. 9 The effect of rhizobiota consortium
formula and organic fertilizer dosages to yieldon Alfisols
The potency of rhizobiota consortium to increase
yield also indicated by their capability to increasesoil nutrients, for example available-P. Bothconsortium formula and organic fertilizer dosages
increase soil available-P of Alfisols (Fig.7). This,because the rhizobiota consortium content someisolates of P-solubilizing microbe, both bacteria
and fungus.
Inoculation of shallot with rhizobiota consortium
also decrease basal rot disease intensity (Fig.8). As
well as the capability to solubilize P, the capabilityof formula 2 (BF2) to reduce basal rot intensity ishigher than formula 1 (BF1). Formula 1 (BF1)
consist of P-solubilizing, K-solubilizing, Soxydizing and N-fixing microbes. Formula 2 (BF2)
consist of P-solubilizing, K-solubilizing, Soxydizing, without N-fixing microbes. While
formula 3 (F3) consist of organic matterdecomposer microbes without capability to inhibit
growth of Fusariumoxysporum.
Inoculation of rhizobiota consortium alone did
not increase shallot yield but their interaction withorganic fertilizer increase significantly (Fig. 9).
This is maybe because of low organic matter
content of the soil. Heterotrophic microbes needorganic carbon to build their body and take energy
for their activities.
Conclusion
The results showed that more than 50% isolates offungi and bacteria isolated from rhizosphere of red
onion showed the capability to inhibit growth ofFusarium oxysporum, fungus causes basal rot(Moler) disease on shallot. More than 28% isolatesof fungi and bacteria have capability to oxidize S or
dissolve P and K, also have the capability to inhibit
growth of Fusarium oxysporum. Inoculation ofshallot with rhizobiota consortium increaseavailable-P, decrease basal rot disease intensity andincrease shallot yield in pot experiment, so they
have potency to use as inoculum of biofertilizer
with capability as biological control agents of basal
rot disease to enhance shallot yield.

Acknowledgement
We highly to appreciate to The Director of DP3M
Directorate General of Higher Education Republicof Indonesia who has given us the research grant.
Thank a lot address to our students for their helped
along the research: Aghata Eka Satriana, Claudia
Sandy Sofani, Dhani Dhyana Ciptasari, Bayu
Rahmad Bernadip, Rohman Ashuri, Andhika
Wahyu Nugroho and Nunik Iriyanti Ramadhan.
References
Anonim. 2009.
http://id.wikipedia.org/wiki/bawang_merah.
Bernadip BR, Hadiwiyono and Sudadi (2014) Diversityof Fungi and Bacteria of Rizosphere Against Moler
Pathogen. Sains Tan.ah – Journal of Soil Science andAgroclimatology 11 (1): 52 -60.
Coyne MS (1999) Soil Microbiology : An Explanatory
Approach. Ch.12. Soil as a Microbial Habitat:139 2157. Delmar Publisher. Albany.
Hadiwiyono, Sudadi and CS. Sofani (2014) Psolubilizing Fungi as Biological Control Agents toIncrease Growth and Prevent Moler Disease on Red
Onion. Sains Tan.ah – Journal of Soil Science andAgroclimatology 11 (2) : 130 -138.
Lopez-Real JM and Hodges RD (1986) Preface. In :Lopez-Real and
Hodges,
The role ofmicroorganismes on a sustainable agriculture. A B
Acad. Publisher. Great Britain. p. v.
Keel, C., B. Koller and G. Defago. 1990. Plant GrowthPromoting Rhizobacteria. Progress and Prospect. The
Second International Workshop on Plant GrowthPromoting Rhizobacteria. Interlaken, Switzerland, Oct
14 - 19, 1990.
Paul, E.A. and F.E. Clark. 1989. Soil Microbiology andBichemestry. Ch. 5. Occurrence and Distribution of
Soil Organisms. Acad. Press Inc. San Diego,
California. p. 74-90.
Ramadhan, N.I., Hadiwiyono and Sudadi.2015.
Rhizobacteria as Biocontrol Agents of “Moler”
Disease of . Sains Tanah – Journal of Soil Scienceand Agroclimatology, 12 (1) , 2015, 26-31
Rӧmheld, V and G. Neumann. The rhizosphere :Contribution of the soil-root interface to sustainablesoil systems. In: Uphoff et al., Biological Approaches
to Sustainable Soil Systems. Taylor & Francis Group,
LLC. Boca Raton, FL.p. 91 - 108.
Sudadi, I. Ernawati, Sumarno, WS Dewi, and H.
Widijanto. 2013. Study on The Potency of Soil
Microbes Isolated from Andisols of Dieng, Central
Java, as S-Oxidizing Biofertilizer Inoculant. Sains
Tanah–Journal of Soil Science and Agroclimatology
11 (2) : 130 -138.
Sudadi H, Widijanto and L. Habsari Efendi Putri (2013)
Isolation of Indigenous Phosphate Solubilizing
Microbia from Andisols Dieng and Its Potency as
Inoculum of Phosphate Solubilizing Biofertilizer).
Sains Tanah–Journal of Soil Science andAgroclimatology 10 (2): 1 -10.
Thies JE and Grossman M (2006) The soil habitat andsoil ecology. In: Uphoff et al., Biological Approaches
to Sustainable Soil Systems. Taylor & Francis Group,
LLC. Boca Raton, FL:59-78. ix + 418 p.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 03

BIOCHAR AND AZOLLA FOR SUSTAINABLE RICE SOIL MANAGEMENT○Widyatmani Sih Dewi1 and Masateru SENGE2(1Soil Science Study Program, Faculty of Agriculture, Universitas Sebelas Maret, Indonesia,
2
Faculty of Applied Biological Sciences, Gifu University,Japan)
Summary
Paddy (Oryza sativa L.) is a strategic food commodity in the world as it is the food for the majority of world's
population. Indonesia is one of the largest harvesting areas in Southeast Asia, both irrigated (6,154,000 ha) anddryland (4,015,000 ha). Some challenges and constraints of paddy fields nowadays are decreasing harvests area
and rice yields, the less of 2% soil organic matter content, low nutrients, the limited availability of water, andgreenhouse gasses emission. The management of soil organic matter is one of the key strategies to maintain thesustainability of paddy fields. Biochar is a soil ameliorant, which is by-product of various organic waste
pyrolysis. Some researchers report that biochar applications into paddy soils can improve the physical, chemical,
and biological properties of the soil, as well as crop productivity. Biochar contains stable C, which has a longmean residence time, so C remains sequestered in the soil for long periods. The application of biochar ispotential to increase water holding capacity, a refuge for beneficial soil microbes, as well as mitigate greenhousegas emissions. However, unwise use of biochar has a temporary negative effect because it can fix Nitrogen andPhosphorus that plants need. Therefore, the addition of biochar into paddy soil needs to be accompanied by
Azolla. Azolla is a symbiosis between water spikes with Anabaena azolla that can fix N from the atmosphere.
Azolla usually cultivated with rice plants as dual cropping. Azolla can provide nutrients especially N for rice
crops, and other nutrients if Azolla incorporated in paddy fields. The provision of nutrients by Azolla is slow
release thus preventing loss of N nutrients through leaching or loss in the form of N2O. This paper is a review ofsome literature that will reveal the importance of biochar management on paddy soil, its positive and adverse
effects, and why its application needs to be accompanied by Azolla as a strategy to conserve paddy fields.
Keywords: biochar, Azolla, paddy field, management
a. Paddy soil in Indonesia, some challenges andconstraints
Rice (Oryza sativa L.) is a strategic foodcommodity in the world, which is the primary foodfor more than half of the world’s population, andaffect the livelihoods and economies of several
billion people (Redfern et al., 2012). The highest
global rice consumption in China amounted toabout 144 million metric tons in 2016/2017, while
the global use of rice per capita amounted to about
54.24 kilograms in that year (Statista, 2017).
Indonesia is the third largest rice consuming
country in the world, which is 37.6 million metrictons per year (Statista, 2017), with average percapita food use of milled rice approximately 126139 kilograms per year (Setiawan et al., 2014;
Zaini, 2016). Population growth drives demand forfood, accordingly, at least agricultural production
must be increased following the rate of population
growth, otherwise, there is a need to import food tofulfil those demands (Setiawan et al., 2014). FAO
predict that farmers will have to produce twice asmuch food as they do today as to feed the expected
9.2 billion global population by 2050 (Abubakar etal., 2015).
FAOSTAT (2012) reported that approximately
88% of the global rice harvested were in Asia (137
million ha), and 31% of which (48 million ha) were
harvested in Southeast Asia. Indonesia is one of thelargest harvesting areas in Southeast Asia, both
irrigated (6,154,000 ha) and dryland (4,015,000 ha)(Redfern et al., 2012). The greatest levels of

productivity are found in irrigated rice, where morethan one crop is grown per year and yields are high(approximately 5-12.5 tons/ha/year) compared with
2.5 tons/ha/year for rainfed rice (Mutert andFairhurst, 2002; Redfern et al., 2012).
In Indonesia, which has the world’s fourthlargest population, rice remains the most importantcrop (Zaini, 2016). It is estimated that 14.2 million
Indonesian farming households directly obtain theirlivelihood from rice. Rice production in Indonesia
in 2015 amounted to 75.4 million tons (Badan
Pusat Statistik, 2017). The Indonesian government
targeted to increase production by 3% a year toreach 82.1 million tons by 2019 with aims to
reduce rice imports and achieve rice selfsufficiency (Zaini, 2016).
Wetland is a significant area in Indonesia
because it is the primary natural resources in riceproduction. The total area of wetland in Indonesia
in 2013 was 8.11 million ha, of which 3.23 million
ha were in Java, 2.24 million ha in Sumatra, and1.07 million ha in Kalimantan, and the rest are inBali and Nusa Tenggara. Of this area, irrigatedwetland is the largest land that is about 4.81 million
ha. The total area of irrigated rice fields continues
to decline from 2009 to 2013, with the average
decrease in the period was 113,204.22 ha/year(Center for Agriculture Data and Information
System, 2014). Until now lowland paddy remain
the backbone of national rice production, which isrelated to the level of soil fertility, availability ofwater, and better infrastructure compared with

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 03other agroecosystems. Therefore, the program toincrease rice production is more directed to theirrigated paddy. However, at present some of the
paddy fields have decreased productivity, as
reflected by the slower rate of paddy production(Sanny, 2010).
Paddy soil is used or potentially used to growpaddy, either continuously throughout the year or
take turns with crops. Hardjowigeno and Rayes(2005) classified rice field problems in Indonesia
into two groups that are: (a) reduced land area dueto the conversion of paddy fields to nonagricultural, and (b) the existence of levelling off inrice production. The result of research by IAARD(2006) shows that about 65 percent of the 7.9
million ha of paddy fields in Indonesia have low tovery low organic content (C-organic less than 2%)(Setyorini et al., 2010). Some challenges andconstraints of paddy fields nowadays are
decreasing harvests area and rice yields, the less of
2% soil organic matter content, low nutrients, thelimited availability of water, climate variability andclimate change, and greenhouse gasses emission.
Farmers need to intensify agricultural production in
the face of declining availability of water andagricultural land, lower productivity, due tounsustainable practices such as overuse of agrochemicals (Abubakar et al., 2015).
Currently, the presence of fertile soil isthreatened due to the increasing land conversion for
non-agriculture. In the period 1981-1999, about 1.6
million ha of productive paddy fields (62.5% inJava) converted to residential, industrial andcommercial areas, offices, or roads. Paddy field
conversion from 1999-2002, approximately
188,000 ha per year, of which 70% outside Java.
This land conversion will be accelerated if there areno concrete steps to control (Irawan, 2006).
Rice cultivation in Indonesia is done intensively
using excessive inorganic fertilizers and pesticide,
and without returning the residue plant or applying
organic fertilizer. The practice continues for
decades. When crops are harvested, or residues
burned, organic matter is removed from the system(Bot & Benites, 2005), which lead depletion of soilorganic matter content; even many places hasreached the level of vulnerability. The practice ofintensive rice cultivation using agrochemicalmaterials continuously causes paddy soil toaccelerate the decline of soil fertility and soil
quality degradation (Supriyadi et al., 2017).
Puddling and flooding of rice fields without thereturn of organic materials can increase bulk
density and decrease water retention. Suntoro(2003) reported that about 60% of the rice fieldarea in Java has less than 1% organic matter
content. Meanwhile, the agricultural system can besustainable if the soil organic matter content ismore than 2% (Loveland 2001). If the soil humus
content decreases gradually, the soil will become

hard, compact and clumped and become lessproductive.
Rice cultivation is one source of greenhouse gas(GHG) emissions. GHG emissions and climatechange are important issues related to rice, as theyaffect rice production and affect concentrations ofgreenhouse gases in the atmosphere (Paustian et al.,1997). Climate change, GHG, food insecurity, andsoil degradation have a very close and complicatedrelationship (Lal, 2014).
Climate variability and climate change in the
future will be one of the greatest challenges inaffecting the successful increase in rice production(Las et al., 2011). Rice production system, strongly
influenced by variability and climate change,
especially rainfall and seasonal patterns andextreme climate events. The most dominant
impacts of climate variability and climate change
are growing season, extensive planting andharvested area that leads to decreased riceproductivity and production. The analysis showsthat climate change has potential to decrease 14%of the planted area in El-Nino year compared to theexisting or normal condition, but can increase theplanting area by 10% in La-Nina, especially in thefirst dry season. Therefore, it is necessary to havean appropriate strategy supported by various
technologies which are adaptive to climate
variability and climate change. Efficient land andwater management technologies that are suited toclimatic conditions are needed for adaptation toclimate variability and climate change. The
challenge will be for farmers to intensify paddy
field production in a sustainable way while meeting
the increasing demand for food at present and in
the future (Abubakar et al., 2015).
According to decreasing of the productive landarea and the complexity of rice field problem, it isnecessary to maintain the sustainability of paddy
soil function. This paper will discuss the role ofbiochar and Azolla for sustainable paddy land
management.
b. Biochar as a soil ameliorant
Flooded rice soil has a unique profile. The
oxidation and reduction layers will form during therice growing season. In paddy fields, the organic
material decomposes anaerobically to produce CH4gas, while in aerobic condition produce CO2. Gas
N2O is potentially produced in anaerobic condition.
There is some issue related GHG in wetland rice:methane (CH4), dinitro oxide emission (N2O),
carbon dioxide (CO2) emissions, and soil carbon
storage (C storage) (Gathorne-Hardy, 2013).
Therefore, understanding how GHG emitted frompaddy fields is important to find a proper strategy
to mitigate. Efforts to solve these problems should
apply integrated technology that has been shown tolead low-emission farming practices (Lal, 2014).

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 03

Flooded rice is a significant source of emissionsof N2O and CH4 (Xing et al., 2009). The
agricultural sector contributes to a 20% increase ingreenhouse gases per year, mainly in the form of
CH4 and N2O gas emitted from the soil (Paustian etal., 1997). CH4 gases emitted from rice fields range
from 20 to 100 Tg/year, with an average of about
60 Tg/year (IPCC 1996; Redfern et al. 2012). Ricefields in Indonesia contribute to CH4 emissions ofabout 2.2 to 6.2 million tons of CH4/year or
equivalent to 46.2 to 130 million tons of CO2e
(GHG Research Team, 2011). Estimated CH4
emissions from paddy fields in Sukamandi, West
Java, are between 8.7 to 20.2 mg/m2/hr or about 19- 44 g/m2 per season (IPCC, 1996).
One promising approach to lower atmospheric
CO2 and suppress N2O emissions is biochar(Lehmann, 2007, Cayuela et al., 2014; Case et al.,2015). Biochar potential for stabilizing biomass C
in soils with a maximum mitigation potential of 1.8
Pg CO2–C equivalent per year (Woolf et al., 2010),
and improving soil health (Khura et al., 2015).
Biochar is a product of the pyrolysis of biomass.
It can be made from various agricultural wastes
such as wood chips, coconut shells, palm oilbunches, corn cobs, rice husks, livestock manure,straw, peanut shells, barks, and others. The term
biochar is often interchangeable with activatedCarbon and charcoal, but all three have differences.
Activated carbon is also called activated charcoal
which is 'activated' charcoal using a series oftechnical processes to increase the internal micro
porosity of carbon-rich originating material. All'activation' processes take individual C atoms andcreate proper angles and crevices on the carbonrich material, which serve as adsorption sites. So
activated carbon is intended for adsorbents toremove something, especially organic compounds
from liquids or vapours. Charcoal is fuel forcooking and generating heat. Charcoal made frombiomass heating, especially wood, in low oxygen
conditions. It burns heater and produces less smoke,
so is often used to heat mineral ores. Biochar ismade in the same manner as charcoal but is used as
an adsorbent or soil ameliorant. The fundamental
difference between biochar and charcoal is the end
utilization of both materials, coal as fuel whilebiochar for the adsorbent. So the nature of biochar
is similar to activated carbon and charcoal but has
some unique differences from both (McLaughlin,2016).
Biochar has an aromatic C structure so that it isrelatively slow to decompose, persistence in thesoil, and can act as a carbon sequester (C sequester).
Biochar also has a high nutrient holding capacity ascompared with other organic materials (Lehmann,2007). Biochar is particle-shaped, so it has a large
surface area. Biochar have unique properties
include low densities so providing additional voids
and aeration in the soil, high adsorption and cationexchange capacity, and the ability to promoteliving soil microorganisms, and improving soil
food web (McLaughlin, 2016).
Application of biochar to the soil lead increasewater holding capacity. Biochar can be useful as asoil ameliorant and building soil organic matter.
Based on these characteristics, the application ofbiochar into the paddy soil can have a beneficial
effect, i.e., (1) improve carbon storage and soilorganic matter, (2) mitigation of greenhouse gases,(3) improving soil properties and soil fertility, (4)increase filtration of percolating soil water and (5)reducing environmental pollution. Biochar isincreasingly used on agricultural soils to enhance
productivity and to sequester carbon (Ajayi et al.,2016). The potential use of biochar for sustainablesoil management and its impact on global climate
presented in Figure 1.
Figure 1 shows inputs, process, outputs,
applications, and impacts on global climate. The
height/width of the coloured fields shows therelative proportions of the components of eachcategories. CO2 from the atmosphere converted toyield biomass through photosynthesis. Agriculture
and agroforestry wastes and crops residue throughpyrolysis is converted to bio-oil, syngas, process
heat, and biochar. The bio-oil and syngas aresubsequently combusted to yield energy and CO2.
This energy and the process heat are used to offset
fossil carbon emissions. Biochar stores carbon for asignificantly longer period compared with if theoriginal biomass had been left to decay, it would
increase soil carbon storage, control of methaneand nitrous oxide emissions. Biochar has thepotential for even greater impact on climate
through its enhancement of the productivity ofinfertile soils and its effects on soil GHG fluxes(Woolf et al., 2010).
Application of biochar in the sandy loamy silt
soil improve the pore structure and increase thesaturated hydraulic conductivity, and produces
better soil–plant–water environment. The beneficial
effects of biochar on pore structure, aggregationand stabilization depend on the amount of biochar,
the texture of the original soil material and thenumber of wetting and drying cycles (Ajayi et al.,2016).
A review of 261 studies, both in laboratories
and in the field, during 2007 - 2013, shows thatbiochar can reduce N2O emissions by 49 ± 5%. The
effect of biochar application in the field led tolower N2O emission (28±16%) when comparedwith laboratory studies (54 ± 3%) (Cayuela et al.,2015). Biochar raw materials, pyrolysis conditions,and C/N ratios are key factors influencing biocharon N2O emission reductions (Cayuela et al., 2014),
as well as the degree of polymerization andaromatics of biochar (Cayuela et al., 2015).
The biochar application on fertile and almost
water-saturated soil conditions, suppresses theProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 03

average N2O cumulative production by 91%, while
the mean cumulative denitrification is reduced byabout 37% (Case et al., 2015). In Zimbabwe,application of 3.5 ton biochar/year (equivalent≥
63% C) could use storage 2.2 ton/year of soil C.
Biochar can be used to absorb various
contaminants or soil pollutants (Khura et al., 2015).
The reasons for the reduction of methane andNOx emissions are still not very clear. In general,biochar can reduce N2O emissions by 10% -41%
and charcoal can reduce CH4 emissions by 14% -

70% (Fungo et al., 2014). The use of biochar as asoil enhancer affects pH increase in various
locations and climate variations in China, thusincreasing the availability and uptake of Si by rice
plants (Liu et al., 2014). Silicate (Si) is a nutrientthat affects rice resistance against pest and diseaseattacks. The application of straw biochar 22.5
ton/ha to paddy fields, without urea, could increaserice production by 19.8% to 21.6%, and N retention(Dong et al., 2015)

Figure 1 The illustration of the sustainable biochar concept (Woolf et al. 2010)
c. Azolla as source of organic nutrient
Intensive, conservative and environmentallyfriendly rice cultivation practices and use ofrenewable resources are essential, such as Azolla,
to maintain the sustainability of soil functions.
Azolla is a symbiotic complex of floating
pteridophytes
withendophytic
N-fixing
cyanobacteria Anabaena azollae Strasburger lives
within the leaf cavities (Wagner, 1997; Bocchi &Malgioglio, 2010). The endosymbiont, which isnitrogen-fixing, provides sufficient nitrogen forboth itself and its host. The fern, on the other hand,provides a protected environment for the alga andalso supplies it with a fixed carbon source (Wagner,
1997).
Paddy field is suitable environment for growthof Azollae. The symbiosis of Azolla-Anabaena ismarvellous due to its high productivity combinedwith its ability to fix nitrogen at high rates (Wagner,
1997). Azolla can be used as biofertilizer, ananimal feed, human food, medicine, a water
purifier, production of biogas, control of weeds &mosquitoes, and the reduction of ammonia
volatilization which accompanies the application ofchemical
nitrogenfertilizer.
Besides
environmentally viable, for farmers who cannot
afford chemical fertilizers, Azolla applications canminimize costs but can improve yields (Wagner,
1997). Azolla can be used as fertilizer in the formof fresh (as dual cropping with rice plant), dried orcompost. 100 kg fresh weight Azolla produces 4-6
kg dry weight Azolla. 10 tons fresh weight Azolla
equivalent to 100 kilograms of ZA or 50 kg of Urea
(Khan, 1988).
Rice requires macro essential nutrients
especially N, P, K. Azolla can be utilized as
biological fertilizer and nutrient source for rice
plants. Azolla contains 0.2-0.3% N of fresh weightwith C/N ratio of 15-18:1. Azolla also contains
crude fat 24-30%, dissolved sugar 3.4-3.5%, starch
6.54%, chlorophyll 0.34-0.55%, P 0.5-0.9%, Ca 0.4-1.0%, K 2.0-4.5%, Mg 0.5-0.6%, Mn 0.11-0.16%,
Fe 0.06-0.26% and 10.5% ash. Dry weight ofAzolla production ranged from 10.8 to 24.4 tons
ha-1 with N yields 575-1,500 kg ha-1 year-1 inmonoculture (Khan, 1988).
Azolla is a green manure that is often used forrice fertilization and to suppress CH4 emissions(Bharati et al., 2000), but not all farmers inIndonesia use it. Azolla can be applied before
planting rice or in combination with rice plants by
dual-cropping. It also can be utilized as compost(compa-zolla). The beneficial effect of Azolla
application in rice cropping is: (1) inhibit
evaporation and conserve moisture soil content, (2)quickly growth of Azolla covering surface water toinhibit weed growth, (3) water filter from heavy
metal pollution, and (4) improve available plant
nutrients.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 03Dual cropping Azolla with rice plants from the
beginning of rice planting equivalent of 30 kg N
plus 30 kg urea can reduce CH4 emission by 89.29
kg CH4 ha-1(Bharati et al., 2000). Applications ofAzolla inoculum can reduce CH4 emissions in theorganic rice system by 52.91%. Optimum doses of
Azolla in 'minapadi' systems can suppress CH4 gas
emissions and increase fish and paddy yields from
2 to 4 tons ha-1 (Mujiyo et al., 2011). Applying
Azolla equivalent to 120 kg N ha-1 can increase theavailability of NH4+-N and NO3--N soil followed byincreasing dry grain yield at harvesting by 7.09
tons ha-1, compared to control (6.47 tons ha-1).
Application of 10 tons of organic fertilizer plus 2
tons ha-1 Azolla can increase production of Mentik
Wangi rice and reduce the emission of CH4(Nungkat et al., 2015).
d. Integrated organic management using
biochar and azolla for sustainability paddy
soil fuctions
The achievement of sustainable agriculture was
the target of Agenda 21 declared at UN Conference
on Environment and Development (UNCED) heldin Rio de Janeiro in 1992. It relates to serious
issues of agricultural sustainability and agricultural
impacts on the global and local environment. Some
serious environmental problems related toagriculture are rapid deforestation, biodiversity
degradation, irreversible soil degradation due tosoil erosion, GHG from agricultural land, water,
and air pollution, and toxic chemical compounds
used for agriculture (Kyuma, 1995).
The main characteristic of lowland paddy
cultivation is waterlogging. It creates the soil
environment becomes anaerobic because the rate ofoxygen diffusion into the water is prolonged.
Biologically, when oxygen is lost from the soil, andaerobic microorganisms die, the anaerobic microbe
becomes dominant for some time. When anaerobic
conditions continue the organisms will gradually be
replaced by strict or obligate anaerobic (Kyuma
1995). Changes in reductive oxidative condition
will significantly affect the nutrient dynamics andresponse of rice crops, which will ultimately affect
the growth and yield of rice, and GHG emitted.
The biochemical processes of submerging soil
related concerning the decomposition of organic
matter, and oxidation and reduction, which arecontrolled by several factors, such as pH, soil
temperature, and oxidizing and reducers agents.
The oxidizing agents in submerge soil are O2, NO3,
Mn oxide, Fe oxide, and SO2, while reducing
agentsareorganic(especiallyreadily
decomposable) materials. The performance of thesefactors depends on the type of soil (Inubushi et al.,1984).
Currently, the carbon content of the majority of
paddy soil in Indonesia is already below 2%, andsome are already below the critical threshold(Atmojo, 2003), so the management of soil organic
matter (SOM) is one of the key strategies tomaintain the sustainability of paddy soil. SOM is
the key to healthy soil because the variety of soil
microorganisms depends on SOM to provides avariety of functions and services in the below
ground ecosystem (Bot & Benites, 2005). The
improvement of SOM content will also improve thechemical, and physical soil properties led
sustainable soil function to support plant growth.
SOM must be kept above the minimum limit toprevent or minimize the irreversible degradation ofsoil properties. Loveland et al. (2001) stated thatthe soil could be used sustainably if the soil organic
Carbon (SOC) content is minimum 2% orequivalent to soil organic matter (SOM) 3.4%. The
quality of litter or organic residue is essential indetermining the availability of nutrients or building
SOM when incorporation to the soil. Organic
materials with C/N less than 20 are easy to be
decomposed and provide nutrients for the plants sothat if the application time is not synchronized withthe plants need, its potential loss N. Organic
materials with C/N more than 25 will build soilorganic matter, but less provide nutrients. The
quality of organic materials applied to the soil also
affects GHG emissions. Organic materials with low
C/N emit more N2O than natural materials thathave high C/N (Baggs, 2001). Therefore, themanagement of organic matter must be wise
concerning its quality to prevent or reduce its
adverse effects.
Azolla is one of the most suitable N sources tobe developed on paddy fields, either dual cropping
or being immersed in the soil. C/N ratio of Azolla
is less than 20, so it is easy to be decomposed ormineralized into N-inorganic, which is very labileand easily lost from waterlogging paddy soil. The
addition of Azolla cannot build soil organic matter,
only increase the availability of nutrients. Biochar
has C/N ratio more than 25, so slowly decomposed,
and its application into the soil can build soilorganic matter, but little provide soil nutrients.
Both organic materials are reported to be able tosuppress GHG emissions. Azolla and biochar eachhave advantages and disadvantages, so if only
Azolla or biochar is applied, then the effect on thesoil is not as good if both are given together. Ninorganic from azolla mineralization can be bonded
by biochar thus protect loss of N from paddy soil,
soil organic matter builds up, and reduce GHG
emissions.
Acknowledgement
The author would like to thank the Ministry of
Research, Technology, and Higher Education,
Republic of Indonesia that support funding throughINSENTIF RISET SINAS for fiscal year 2015.
RefferenceProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 03

Abubakar ALM, Ketelaar JW and Minamiguchi N(2015) FAO’s Regional Rice Initiative:
Sustainable Management of the Multiple Goods
and Services derived from Rice Production
Landscapes in Asia. In Program and Abstract of
the MARCO Symposium.
Ajayi AE, Holthusen D, and Horn R (2016)
Changes in microstructural behaviour andhydraulic functions of biochar amended soils.
Soil & Tillage Research 155: 166–175.
Atmojo SW (2003) Peranan bahan organikterhadap
kesuburan
tanah
dan
upaya
pengelolaannya. Pidato Pengukuhan Guru Besar
Ilmu Kesuburan Tanah Fakultas Pertanian
Universitas Sebelas Maret. Surakarta:1-36.
Badan Pusat Statistik (2017) Produksi Padi
Menurut
Provinsi(ton),
1993-2015.
https://www.bps.go.id/linkTableDinamis/view/id/865
Baggs EM, Millar N, Ndufa JK and Cadisch G(2001) Effect of Residue Quality on N2O
Emissions from Tropical Soils. In: Rees RM,
Ball BC, Campbell CD, and Watson CA (Eds.).
Sustainable Management of Soil Organic Matter.
CAB International. UK:120-125.
Bot A and Benites J (2005) The importance of soilorganic matter Key to drought-resistant soil andsustained food production. Food and Agriculture
Organization of The United Nations. p.95, ISBN
92-5-105366-9.
Case SDC, McNamara NP, Reay DS, Stott AW,
Grant HK, and Whitaker J (2015) Biochar
suppresses N2O emissions while maintaining N
availability in a sandy loam soil. Soil Biology
and Biochemistry, 81(2):178–185.
Cayuela ML, van Zwieten L, Singh BP, Jeffery S,
Roig A, and Sánchez-Monedero M (2014)
Biochar’s role in mitigating soil nitrous oxide
emissions: A review
andmeta-analysis.
Agriculture, Ecosystems andEnvironment,
191: 5–16.
Center for Agriculture Data and Information
System (2014) Statistics of Agricultural Land2009-2013. Secretariat General – Ministry ofAgriculture. Jakarta. Indonesia. Pp. 185.
FAOSTAT(2012)(available
at:www.faostat.fao.org/).
GHG Research Team (2011) IndonesianExperience on GHG Emission Measurement in
Paddy Rice and Experience in Development ofSecond National Communication for GHG
inventory in Agricultural Sector. In EPOCHALTSUBUKA, Tsubuka International Congress
Hall
Gathorne-Hardy A (2013) Greenhouse gas
emissions from rice. doi:10.1021/bk-20111072.ch005l
Hardjowigeno S, Rayes ML (2005) Tanah sawah:
Karakteristik, kondisi, dan permasalahan tanahsawah di Indonesia. Bayu Media, Malang.

Inubushi K, Wada H, and Yasuo Takai Y (1984)
Easily decomposable organic matter in paddy
soil: IV. Relationship between reduction process
and organic matter decomposition. Soil Sci.
Plant Nutr., 30 (2), 189-198.
IPCC (1996) Methane Emissions from Rice
Cultivation?: Flooded Rice Fields. In Revised
1996 IPCC Guidelines for National Greenhouse
Gas Inventories: Reference Manual. Pp. 53–75.
Irawan (2006) Multifungsi Lahan dan Revitalisasi
Pertanian. Suara Pembaruan, 23 Juni 2006.
http://www.litbang.pertanian.go.id/artikel/one/14
6/pdf/Multifungsi%20Lahan%20dan%20Revitali
sasi%20Pertanian.pdf
Khan MM (1988) Azolla agronomy. IBS – UPLB –SEAMO – Searca. Phillipine.
Kyuma K (1995) Ecological Sustainability of The
Paddy Soil-Rice System In Asia. International
Seminar on the Appropriate Use of Fertilizers.
Taiwan ROC, November 6-14 1995. Pp. 9.
Lal R (2014) Climate Strategic Soil Management.
Challenges (vol. 5). doi:10.3390/challe5010043
Las I, Pramudia A, Runtunuwu E, and Setyanto P(2011) Antisipasi perubahan iklim dalammengamankan
produksi
beras
nasional.
Pengembangan Inovasi Pertanian, 4(1): 76-86.
Lehman J (2007) Bioenergy in the black. Frontiersin ecology and the environment, 5:381-387.
Loveland PJ, Webb J, and Bellamy P (2001)
Critical Levels of Soil Organic Matter: theEvidence for England and Wales. In: Rees RM,
Ball BC, Campbell CD, and Watson CA (Eds.).
Sustainable Management of Soil Organic Matter.
CAB International. UK. :23-33.
McLaughlin H (2016) An Overview of the current
Biochar and Activated Carbon Markets.
Biofueldigest.com. p. 3.
Mutert E and Fairhurst TH (2002) Developments inrice production in Southeast Asia. Better Crops
International Vol. 15, Special Supplement, May
2002.
Paustian K, Andren O, Janzen HH, Lal R, Smith P,
Tian G, Tiessen H, Van Noorwijk M, andWoomer P (1997) Agricultural soils as a sink tomitigate CO2 emission. Soil Use andManagement, 13:230-244.
Redfern SK, Azzu N, and Binamira JS (2012) Ricein Southeast Asia: facing risks andvulnerabilities
torespondtoclimatechange. Build Resilience Adapt Climate Change
Agri Sector, 23: 295-314.
Sanny L (2010) Analisis produksi beras diIndonesia. Binus Business Review, Vol.1 No.1
Mei 2010: 245-251
Statista (2017) Rice consumption worldwide in
2016/2017, by country (in 1,000 metric tons).
https://www.statista.com/statistics/255971/topcountries-based-on-rice-consumption-20122013/

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 4 - Soil Biology & Microbiology -: 03

Setiawan Y, Rustiadi E, Yoshino K, Liyantono, andEffendi H (2014) The seasonal dynamics of theJava’s paddy field using MODIS satellite images.
ISPRS Int. J. Geo-Inf., 3:110-129.
Setyorini D, Rochayati S, Las I (2010) Pertanianpadaekosistem lahansawah.
Dalam:
Suradisastra K, Pasaribu SM, Sayaka B, Dariah
A, Las I, Haryono, Pasandaran E (Eds.).
Membalik Kecenderungan Degradasi Sumber
Daya Lahan dan Air. Badan Penelitian dan
Pengembangan Pertanian Kementerian Pertanian.
IPB Press.
Supriyadi S, Purwanto P, Sarijan S, Mekiuw Y,
Ustiatik R, and Prahesti RR (2017) The
Assessment of Soil Quality at Paddy Fields in

Merauke, Indonesia. Bulgarian Journal of
Agricultural Science, 23 (no.3): 443-448.
Wagner GM (1997) Azolla: A Review of its
Biology and Utilization. The Botanical Review.
vol. 63 January-March no. 1. p. 25.
Woolf D, Amonette JE, Street-Perrott FA, Alayne
F, Lehmann J, and Joseph S (2010) Sustainablebiochar to mitigate global climate change. 2010.
Nature Communications 1:56, p.9.
Zaini Z (2016) Indonesia and IRRI. www.irri.org
Xing G, Zhao X, Xiong Z, Yan X, Xu H, Xie Y,
and Shi S (2009) Nitrous oxide emission frompaddy fields in China. Acta Ecologica Sinica,
29(1): 45–50.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 5 - Soil Chemistry -: 01

Emissions of CH4 and N2O and the relationships with soil properties
under different irrigation methods and nitrogen treatments○Fusheng Li(College of Agriculture, Guangxi University, China）
SUMMARY
To investigate the emissions of CH4 and N2O in paddy field and their relationships with soil properties under different
irrigation methods and nitrogen treatments, two field experiments of early rice and late rice had designed threeirrigation methods, i.e. conventional irrigation (CIR), “thin-shallow-wet-dry” irrigation (TIR) and alternate drying andwetting irrigation (DIR), and two ratios of urea-N to pig manure-N, i.e. 100% urea-N (FM1) and 50% urea-N and 50%
pig manure-N (FM2), so as to understand the mechanism of CH4 and N2O emissions from the paddy soil and obtainproper irrigation method and nitrogen management for reducing CH4 and N2O emissions. Compared to CIR, TIR
increased N2O emission slightly but reduced CH4 emission, and DIR increased N2O emission but reduced CH4 emission.
Compared to FM2, FM1 reduced global warming potential of CH4 and N2O under TIR and DIR. CH4 emission wasclosely correlated with the reducing substances content, microbial biomass carbon, methane oxidizing bacteria andinvertase activity in soils. And soil N2O flux had positive correlations with ammonia-oxidizing bacteria, potential
nitrification rate, hydroxylamine reductase activity and the number of nitrifying bacteria, but negative correlation with
reducing substances content. Thus TIR and DIR methods with single application of urea can reduce the CH4 and N2Oemission from the paddy field.

Introduction
CH4 and N2O emissions from paddy field play animportant role in increasing the global warming trend.
Rational application of irrigation method and nitrogen
management can reduce CH4 and N2O emissions frompaddy fields. The aim of this study was to investigate theemissions,
globalwarming
potential(GWP),
comprehensive emission intensity (CEI) of CH4 and N2Ofrom paddy field, and some soil factors under different
irrigation methods and nitrogen (N) treatments, and thenthe relationships between the CH4 and N2O emission flux
from the paddy fields and some soil factors wereanalyzed, so as to understand the mechanism of CH4 andN2O emissions from the paddy soil and obtain rational
irrigation method and nitrogen management for reducing
CH4 and N2O emissions.

Materials and Methods
In 2015 and 2016, the field experiments of early rice andlate rice were carried out at Nanning Irrigation
Experimental Station, Guangxi. Two-season experiments
had designed three irrigation methods, i.e. conventional
irrigation (CIR, keeping the water layer (10-20 mm)
during turning green stage, maintaining 20-40 mm fromtillering stage to the maturing stage except drying thefield in the late tillering stage, and naturally drying at thematuring stage), “thin- shallow -wet- dry” irrigation (TIR,keeping water layer of 15-20 mm at the transplanting
stage, 20-40 mm at the regreening stage, 90% of soil
saturated moisture content (θs) to 10 mm at early tillering
stage, field drying (60%θs-20 mm) at the late tillering
stage, 10-40 mm at the jointing to booting stages, 90%θs
to 10 mm at the milky stage, and naturally drying (50%θs)
at the mature stage. In addition, field water layer canincrease 10-30 mm after a rainfall), and alternate drying
and wetting irrigation (DIR, keeping the water layer of
10-20 mm within 10 days after transplanting (DAT), andthe starting DIR method after 10 DAT. The tension
meters were installed to monitor the soil water potential.
When shallow water layer in the field was naturally
drying to the soil water potential of -15 kPa, irrigated to
20 mm, and then naturally drying to the soil water
potential of -15 kPa, such circulation ended to thematurity stage of rice), and two ratios of urea-N to pig
manure-N, i.e. FM1: 100% urea-N (135 kg N/hm2) and

50% urea-N (67.5 kg N/hm2) +50% pig manure-N (67.5
kg N/hm2). There were six treatments, i.e. CIR-FM1,
TIR-FM1, DIR-FM1, CIR-FM2, TIR-FM2 andDIR-FM2. CH4 and N2O fluxes during the rice-growing
seasons were collected (Sampling from the regreeningstage, sampling once a week in 9:00 to 11:00 am. Totallythe number of sampling was 12 and 10 times for earlyand late rice seasons) using static closed chamber
method and determined using a gas chromatography.
Accumulative emission and GWP of CH4 and N2O were
calculated and CEI of CH4 and N2O was the ratio of
GWP of CH4 and N2O to rice yield. The rice yields fordifferent treatments were observed at the harvest. Soil
temperature, pH, Eh, the contents of water, reducing
substances, organic carbon (SOC), easily oxidizedorganic carbon (LOC), microbial biomass carbon andnitrogen (MBC and MBN) and inorganic N, the numberof methane oxidizing bacteria (MOB), ammoniaoxidizing bacteria, nitrifying bacteria and denitrifying
bacteria, the activities of nitrate reductase (NR), nitrite
reductase (NiR) and hydroxylamine reductase (HyR),
invertase, amylase and cellulose, mineralization oforganic carbon (MC) and potential nitrification rate, atthe tillering, booting, milky and maturing stages of earlyrice and late rice were also measured. The relationships
between CH4 or N2O flux and soil properties at the
sampling days were analyzed.

Results and Discussion
Compared to FM1, FM2 increased the early rice yieldand total yield of both seasons by 18.8 and 17.7% under
DIR, respectively. Compared to the CIR method, the TIR
and DIR methods increased the yield of early rice by
20.9 and 37.4%, respectively, and the DIR method
increased total yield of both seasons by 21.5% underFM2. The CH4 emission fluxes of both seasons indifferent treatments were high at the early growth stage
and low at the late growth stage (Fig. 1). During therice-growing period, the TIR and DIR methods had
lower accumulative CH4 emission from the paddy field
than the CIR method, and FM1 had significantly lower
accumulative CH4 emission from the paddy field thanFM2. The N2O emission flux was negative or low at theearly growth stage, and the N2O emission from the paddy
field was mainly concentrated during the dramatic waterProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 5 - Soil Chemistry -: 01
100

Late rice

CIR-N2

TIR-N1

TIR-N2

DIR-N1

DIR-N2

100

80

F

80

60
)
•h
(m
/
g
m
x
u
l
F

Late rice120

CIR-N1

)
•h
m
(/
g
m
x
u
l
F
4
H
C

F

2

2

40

4

H
C

60

F
40

D
20

D

F
20

0
12d

20d

42d

48d

54d

69d

62d

76d

83d

92d

0
12d

20d

42d

48d

54d

62d

69d

76d

83d

92d

Days after transplanting-20

Days after transplanting

-20

100

Early rice

F

120

CIR-N1

Early riceF

CIR-N2

TIR-N1

TIR-N2

DIR-N1

DIR-N2

100

80
D
80
60
)
•h
(m
/
g
m
x
lu
F

)
•h
m
(/
g
m
x
u
l
F

D

2

2

40

F

4

H
C

4

H
C

F
60

40

20
20

0

0
10d

19d

27d

34d

41d

48d

61d

68d

76d

83d

90d

97d

10d

Days after transplanting

19d

27d

34d

-20

41d

48d

61d

68d

76d

83d

90d

97d

Days after transplanting-20

F: Topdressing, D: Drying.

Fig. 1 Dynamic changes of CH4 flux during early riceand late rice growing seasons for different treatments

Late rice

Late rice

CIR-N1350

CIR-N2300

TIR-N1

TIR-N2
DIR-N2

DIR-N1
300

250

250
200
)]
•h
m
(/
g
µ
[
x
u
l
F
O
2
N

)]
•h
(m
/
g
[µ
x
lu
F
O
2
N

200

2

2

150
D

100

F

150

100

F
D

F

50

50

F
0

0
12d

20d

42d

48d

-50

54d

62d

69d

76d

83d

12d

92d

Days after transplanting

350

20d

42d

48d

Early rice300

CIR-N1

54d

62d

69d

76d

83d

Early rice

CIR-N2
TIR-N2

TIR-N1300

92d

Days after transplanting-50

DIR-N1

DIR-N2250

increase and decline relationship of CH4 and N2Oemissions from the paddy field in different treatments.
The contribution of CH4 emission to the GWP of CH4
and N2O was more than 99% and the contribution of
N2O emission was less than 1%. FM1 decreased molewarming potential CH4 or N2O, GWP and CEI of CH4
and N2O if compared to FM2, and the TIR and DIR
methods reduced GWP and CEI of CH4 and N2O whencompared to the CIR method (Table 1).
CH4 emission flux from early and late rice fields
positively correlated with the content of reducing
substances (r=0.34* for two seasons, n=48), MOB(r=0.63** and 0.52* for early and late rice seasons,n=24), MBC (r=0.40* and 0.52** for early and late rice
fields, n=24) and invertase activity (r=0.44* and 0.64**
for early and late rice seasons s, n=24), but negatively
correlated with soil cellulose activity (r=-0.42* and-0.45* for early and late rice seasons, n=24).
N2O emission flux from early and late rice fields had
significantly positive correlations with the number ofammonia-oxidizing bacteria (r=0.48* and 0.54** forearly and late rice seasons, n=24), potential nitrification
rate (r=0.59** and 0.41*, n=24), MBN (r=0.624** forlate rice season, n=48), the number of nitrifying bacteria(r=0.542** and 0.541** for early and late rice seasons,n=24) and HyR activity (r=0.455* and 0.431* for earlyand late rice seasons, n=24), but negative correlation
with reducing substances content (n=-0.37* for two
seasons, n=48) and NR activity (r=-0.324* for two seasons,+n=48). In addition, soil NH4 -N content had significantly
positivecorrelationswiththenumberofammonia-oxidizing bacteria and potential nitrification
rate, so soil NH4+-N content affected the N2O emission
indirectly.

Conclusions

Table 1 Global warming potential of CH4 and N2O
and comprehensive emission intensity (CEI) in earlyand late rice seasons for different treatments

TIR increased N2O emission slightly but reduced CH4
emission from paddy field, and DIR increased N2Oemission but reduced CH4 emission. Single applicationof urea reduced global warming potential of CH4 andN2O under TIR and DIR. CH4 emission was closely
correlated with the reducing substances content,
microbial biomass carbon, methane oxidizing bacteria
and invertase activity in soils. And soil N2O flux had
positive correlations with ammonia-oxidizing bacteria,
potential nitrification rate, hydroxylamine reductase
activity and the number of nitrifying bacteria, but
negative correlation with reducing substances content.
Thus TIR and DIR methods can reduce the CH4 and N2Oemission from the paddy field under single application ofurea.

Treatment

Acknowledgements

250

200
200
)]
•h
(m
/
g
[µ
x
lu
F
O
2
N

2

)]
•h
(m
/
g
[µ
x
u
l
F
O
2
N

F

2

150
D

100
F

50

F

150
D

100
F

50

0

0
10d

19d

27d

34d

41d

48d

61d

68d

76d

83d

90d

10d

97d

19d

27d

34d

41d

48d

61d

68d

76d

83d

90d

97d

-50

-50

Days after transplanting

Days after transplanting
-100

-100

F: Topdressing, D: Drying.

Fig. 2 Dynamic changes of N2O flux during early riceand late rice growing seasons for different treatments

CDE(CH4)(CO2 kg / ha)

CDE(N2O)
TCDE
CEI(CO2 kg(CO2 kg(CO2 kg
/ha)
/ha)
/t)
CIR-N134094.04ab
30.23c34124.27ab
2059.4ab
TIR-N1
26186.47bc
59.67b26246.14bc 1525.94bc
DIR-N113653.28d
244.4b13897.68d815.75d
CIR-N238379.21a106.56b38485.77a
2249.97a
TIR-N230414.75ab
97.43b30512.18ab 1782.95ab
DIR-N220265.59cd
358.43a20624.02cd 1161.26cd
Note: Different letters at the same column mean significant
difference at P<0.05 level.

change period, such as re-watering after field drying anddrying at the ripening period (Fig. 2). DIR method hadsignificantly higher accumulative N2O emission from the
paddy field than CIR method, and FM1 had lower
accumulative N2O emission than FM2. There was an

I am grateful for the fund support from the National
Natural Science Foundation of China (51469003) andour research group members (Yanfang Dong, Kai Wang,
Jingwen Liu, Zetao Fang) for their technical assistances.

References
Hou H, Peng S, Xu J, Yang S, Mao Z (2012) Seasonalvariations of CH4 and N2O emissions in response towater management of paddy fields located inSoutheast China. Chemosphere, 2012, 89: 884-892.
Liang Y, Li F, Nong M, Luo H, Zhang J. (2016)
Microbial activity in paddy soil and water-use
efficiency of rice as affected by irrigation method andnitrogen level. Communications in Soil Science andPlant Analysis, 47(1): 19–31.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 5 - Soil Chemistry -: 02

Methane Emissions in Paddy Field
and Its Mitigation Options for Win-Win Solution○Mujiyo1, Ken HIRAMATSU2 and Takeo ONISHI2(1 Soil Science Department, Faculty of Agriculture, Sebelas Maret University, Indonesia,
2

Faculty of Applied Biological Sciences, Gifu University, Japan）

SUMMARY
The effective absorption of infra-red radiation leads methane gas (CH4) play a direct role as a green house gas (GHG) in
our global climate. Methane accounts for about 15% to the current commitment to global warming. The global warming
potential (GWP) CH4 is 11 times the GWP of CO2. Methane emissions from paddy field soil is influenced by somefactors: soil properties (reduction-oxidation potential, organic matter, nutrient status, mineralogy, pH, texture, and soil
temperature), climate (rainfall, temperature), plant (variety), and cultural practices (tillage, planting method, fertilization,
irrigation, weeding, harvesting). This review studies on CH4 emissions from paddy fields, giving special attention to
mitigation options from the view-point of their feasibility on the field scale. The field management of paddy fields is
primarily not only to obtain suitable rice yield, but also has physical, chemical, and biological effects on CH4 emissions.
Therefore, some management practices such as water management; application of mature organic matter; and the use of
Azolla in the dual cropping system can be win-win options that sustain rice yield and mitigate CH4 emissions as these arean effective practice in rice yield sustainable and decreasing CH4 emissions.
Keywords: paddy field, management, methane mitigation

IntroductionThe

28 times higher than CO2.

Indonesian

Agencyfor

Meteorological,

In agriculture activities, paddy field takes a role as a2012)source of the methane emissions. Methane is produced inreported that the effect of global warming in Indonesia is

paddy fields after the sequential reduction of O2, nitrate,

Climatological,

andGeophysical(BMKG,

0increasing of the average of air temperature 0.01 C permanganese, iron and sulphate, which serves as electron

year during 1978 – 2010. In the dry season, the El-Nino

acceptors for oxidation of organic matter into CO2.

phenomenon (the increasing air temperature in Pacific

Strictly anaerobic condition and availability of readily

Ocean) causes drought and fires, crop failure, anddecomposable organic substrates are essential for the

shortage of water. In the wet season, the La-Nina

process of CH4 production in the soil (Nieder and Benbi,

phenomenon (the decreasing air temperature in Pacific2008). The series of the decomposition process of

Ocean) causes high rainfall, typhoon, floods, andorganic matter through oxidation-reduction process end

landslide.

with the formation of CO2 and CH4 (Le Mer and Roger,

The GHG concentration gives contribution to the2001; Nieder and Benbi, 2008).

global warming as in the atmosphere it can absorb andOn the other hand, paddy field in the Asia region has

re-emit some of the infrared solar radiation in allimportant contribution to the source of staple food. The

direction then warming the earth’s surface and the lower

projected increase in methane emissions is primarily

atmosphere layer. Methane is one of the GHG besides

attributed to the increasing demand for rice due toCO2, N2O, HFCs, PFCs and SF6 which contributes byexpected population growth in rice consuming countries

around 16% to the total GHG production (IPPC, 2014).

like China, India, Thailand, Indonesia, Vietnam, andNieder and Benbi (2008) stated that CH4 has the ability

Myanmar (USEPA, 2006). Therefore the paddy field

to radiate heat 21 times higher than CO2. Also IPPC

management must be based on the effort to reduce(2013) stated that methane’s global warming potential ismethane emissions without effecting the rice production.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 5 - Soil Chemistry -: 02

Material and Method

Factors which affecting the amount of methaneThis paper was made by reviewing some similar writings

production

in

paddy

field

are

soil

properties

to find a paddy field management which gives a win-win(reduction-oxidation potential, organic matter, nutrient

solution between rice production and methane emissions.

status, mineralogy, pH, texture, soil temperature);

The author's experiences and objectives in conducting

climate (rainfall, air temperature); plant (variety); andsimilar theme of research are also used as a comparison

cultural practices (tillage, planting method, fertilization,material with findings by other researchers.

irrigation, weeding, harvesting) (Yagi et al., 1990; Li,2007; Changseng, 2007). The main factor of methane

Result and Discussions

production in paddy soil is reduction-oxidation potential(Eh) as methanogen bacteria can only perform a

Paddy Field as a Source of Methane Production

metabolism and active in condition without oxygen or at

Looking at the total source of greenhouse gases, atvery low value of Eh. Li (2007) stated that the Ehthe moment CO2 contributes 76%; CH4 about 16%; N2O

optimum for the methane production is around -150 toabout 6% and the combined F-gases about 2% (IPPC,-350 mV. Hou et al. (2000) presented that the methane2014). Atmospheric methane reached a new high ofemissions from wetland are observed under Eh conditions

about 1.819 parts per billion (ppb) in 2012, or 260% of

below -100 mV. Bharati et al. (2000) mentioned that in

the pre-industrial level, due to increasing emissions fromunfertilized paddy field produced the Eh is -109.75 mV

anthropogenic

and resulted methane emissions around 94.94 kg CH4/ha.

sources.

The

World MeteorologicalOrganization (WMO, 2013) reported that since 2007
atmospheric methane has been increasing again after aRegulation

temporary period of levelling-off.

ManagementofMethaneEmissions

by

Water

Methane is the second most important long-lived

Various cultural practices in paddy field affectgreenhouse gas. Approximately 40% of methane ismethane emissions which defined aeration periods toemitted into the atmosphere by natural sources (e.g.,

reduce it (Neue et al., 1997). Yagi et al. (1997) and Yagi

wetlands and termites) and about 60% comes from(2006) stated that drainage in the middle of the growing

human activities like cattle breeding, rice agriculture,season is an effective strategy to mitigate the CH4

fossil fuel exploitation, landfills and biomass burningemissions in rice cultivation, but it will increase the cost

(WMO, 2013). The U.S. Environmental Protectionof labor and the possibility of causing the production of

Agency (USEPA, 2006) stated this section presents

N2O. Setyanto and Bakar (2005) resulted that pulse

global methane emissions for 1990 to 2020 for theirrigation gave 58.9% reduction in seasonal CH4

following agricultural sources: enteric fermentation, rice

emissions as compared with continuous flooding, while

cultivation, manure management, and other agriculturalintermittent and saturated irrigation resulted 27.2% andsources (including savanna burning, field burning of

48.6%, respectively. Plant growth parameters (dry matter

agricultural residues, open burning from forest clearing,weight of straw and filled grain) among the water

agricultural soils). Around 78% of methane emissions

treatments was not significantly different. Total grain

produced in Indonesia, China, India, Thailand, Vietnam,

yield was not affected by water treatments. Emissions ofand Myanmar originated from rice cultivation. While,

CH4 could be reduced by intermittent or pulse irrigation,

Reddy and DeLaune (2008) stated that the global CH4

whereby saving water which is a scarce resource foremissions were 500 Tg/year as rice fields contributed forfarmers.

around 50 Tg/year or 10% of it.

The soil with high, moderate and low C-organic

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 5 - Soil Chemistry -: 02reached the maximum average of CH production atal., 2016). Farmyard manure 4 tons/ha + Azolla 2 tons/ha

various times after flooding, i.e. on day 20, 15, and 10,

resulted dry grain harvest 6.78 tons/ha and methane

respectively (Mujiyo et al., 2017). Soil with highemissions 3.55 kg CH4/ha. Both are compared with

C-organic has enough C substrates to produce highhabits of farmers by the use of farmyard manure 8

amounts of CH and it will reach a longer peak

tons/ha which resulted dry grain harvest 7.04 tons/ha andproduction period. Meanwhile, soil with low C-organic

methane emissions 9.03 kg CH4/ha. Azolla increases thehas less C substrate will produce lower amount of CH

4content of NO2-, NO3-, and NH4+ in the floodwater.

and show faster peak production periods than the others.

Azolla is fixing N gas then the excess of N elements will

Based on this finding, Mujiyo et al. (2017) suggested

be released into the media in the form of NH4+ (Hamdi

that mitigation option can reduces CH emissions from1982; Arifin 1996) and will be partially converted into

organic rice fields and leads to drainage every 10–20

NO2- and NO3- (Sanchez, 1976; Vance, 1999). Accordingdays before reaching the maximum CH production.

to Slonczewski (2009) and Ettwig et al. (2010), NO2- and

4

4

4

4

NO3- are oxidizing agent for CH4, which is known as theRegulation of Methane Emision by Combined the Use

phenomenon of nitrite/nitrateoxidation of CH4

of Mature Organic Fertilizer and Azolla(Raghoebarsing et al., 2006; Thauer et al., 2008).

The use of organic fertilizer in the paddy field

Azolla in “mina-padi” (fish-rice cultivated together)appears to increase the methane production (Le Mer andsystem can suppress CH4 emissions and increase theRoger, 2001; Nieder and Benbi, 2008) by providing C

yield of fish and rice (Sasa and Syahromi, 2006).

sources and decreasing the amount of Eh (Hou et al.,Prasanna et al. (2002) found that the use of Azolla

2000; Li, 2007). The high amount of C-organic in the

microphylla able to reduce CH4 emissions from paddy

soil leads to the high amount of CH4 production (Jouliansoil with Azolla mechanisms that stimulate the oxidation

et al., 1996; Oelbermann and Schiff, 2008; Liu et al.,of CH4. Bharati et al. (2000) stated that the increasing in

2011; Brzezińska et al., 2012).

dissolved oxygen and reduction-oxidation potential in

Studies at the International Rice Research Institutethe soil followed by a decreasing in CH4 emissions.

shows that soil and added organic matter are the sources

Azolla reduces CH4 emissions by the release mechanism

for initial methane production as the addition of riceof oxygen into the soil. Azolla will increase the dissolved

straw can enhance methane production (Neue et al.,oxygen concentration at the soil–floodwater interface1996). Paddy fields that used rice straw (high C/N ratio)

then oxygen oxidized CH4 become CO2 and H2O. Azolla

produce higher methane production than the one that

thus also improves grain yield, which is not significantly

used green manure leaves (low C/N ratio) (Agnihotri etdifferent from the use of Urea.

al., 1999). Based on that understanding, if a paddy fieldOn the other hand, Ying et al. (2000) found that Azolla

uses Azolla as a green manure, so that the CH4 emissions

increases methane emissions through growing Azolla as

keep remain low because Azolla has low-medium in C/Na dual cropping with rice plant. Azolla could mediate

ratio and low provision C for CH4 forming. Mujiyo et al.

CH4 transport by the way it served as an additional(2016) found that the use of Azolla as green manure

pathway from the floodwater into the atmosphere. It was

resulted methane emissions which is not significant

also found that due to the presence of Azolla, chemicaldifference compared with the use of mature farmyard

soil properties could be developed, stimulating CH4

manure.

production, promoting CH4 availability and CH4

Azolla (applied in dual cropping with rice plant)

diffusion into the overlying water and by the fact that

effects in reducing CH4 emissions by 60.69% (Mujiyo etAzolla served as an additional pathway for CH4 transportProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 5 - Soil Chemistry -: 02

Fig.1 The schematic figure showing the combination of intermittent irrigation, the use of mature organic fertilizer andAzolla (Source: Setyanto and Bakar, 2005, with modification)
into the atmosphere.

mature organic fertilizer, and the use of Azolla in the dual

Suggestions for the Win-Win Practical Methods

cropping system is the effective practice in rice yield

The best combined of water management, use of maturesustainable and also decreasing CH4 emissions. Paddy

organic fertilizer and Azolla can decrease methane

field must not flood continuously. Intermittent irrigation

emissions and increase rice yield. The only one problem

aims that the soil is not too reductive, so this conditionof drainage in a rice field is suitable condition for weed

can inhibit the activity of methanogenic bacteria forming

growth. But, if there present of Azolla in the field

CH4. Application of mature organic fertilizer (low C/N)

suppresses the weed (Satapathy and Singh, 1985;

can decrease methane emissions. This is possible

Lumpkin and Plueknett 1985). Shin et al. (1996) foundbecause the methanogenic bacteria have not adequacythat the management of the paddy field with alternative

source of C-organic to produce methane. Azolla canirrigation and the use of straw composts, which become areduce the concentration of CH4 in the floodwater, so it

habit of farmers in Korea, is able to effectively reduce

will reduce CH4 emitted into the atmosphere.

methane emissions.
Adopted from Setyanto and Bakar (2005) there is aschematic

Acknowledgements

figure the combination of intermittent

The writing of this paper was supported by Gifu

irrigation, the use of mature organic fertilizer and Azolla

University under the staff exchange program 2015 and(Fig.1). The application of mature organic fertilizer isSebelas Maret University Surakarta under the researchdone 3 days before transplanting. This organic fertilizer

grant PNBP UNS 2017. We would like to thank Citra

is given to the soil after the plowing and then mixed

Recha Sari for her participation in the paper preparation.

evenly with the soil together with the renewal. Theintermittent irrigation received irrigation 5 cm waterlevel since the early growth stage (0 days after
transplanting/DAT). Azolla as a dual cropping wasapplied 5 DAT, and then after growing and covering theland, 75% of them can be immersed into the soil twice at
10 DAT and 25 DAT along with weeding. Draining of
the water was conducted twice at 15-20 DAT and 30-35
DAT. Within the 20-30 DAT periods the field weretotally flooded. After 70 DAT until harvest periods thefield were totally drained.
Conclusion
The combination of water management, application ofReference
Agnihotri S, Kulshreshtha K and Singh SN (1999)
Mitigation strategy to contain methane emission fromrice-fields.
Environmental
Monitoring
andAssessment, 58: 95-104.
Arifin Z (1996) Azolla, cultivation and utilization in rice.
Jakarta, Penebar Swadaya Publisher. (in Indonesian)
Bharati K, Mohanty SR, Singh DP, Rao VR and Adhya
TK(2000) Influence of incorporation or dual croppingof Azolla on methane emission from a flooded
alluvial soil planted to rice in eastern India.
Agriculture Ecosystems and Environment, 79:73–83.
BMKG (2012) Global Warming in Indonesia. The
Indonesian
Agencyfor
Meteorological,
Climatological, and Geophysical. Available at
http://www.bmkg.go.id/ (In Indonesian, accessed
February 20th, 2015)
Brzezińska M, Nosalewicz M, Pasztelan M andProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 5 - Soil Chemistry -: 02

Włodarczyk T (2012) Methane production andconsumption in loess soil at different slope position.
The Scientific World Journal, 2012: 1–8.
Ettwig KF, Butler MK, Le Paslier D, Pelletier E,
Mangenot S, Kuypers MMM, Schreiber F, Dutilh BE,
Zedelius J, de Beer D, Gloerich J, Wessels HJCT, van
Alen T, Luesken F, Wu ML, van de Pas-Schoonen KT,
Op den Camp HJM, Janssen-Megens EM, Francoijs
KJ, Stunnenberg H, Weissenbach J, Jetten MSM andStrous M (2010) Nitrite-driven anaerobic methane
oxidation by oxygenic bacteria. Macmillan Publishers
Limited, Nature, 464:543-548.
Hamdi YA (1982) Application of nitrogen-fixing systems
in soil improvement and management. FAO Soils
Bulletin, Food and Agriculture Organization of The
United Nation, Rome. 182 p.
Hou AX, Chen GX, Wang ZP, Van Cleemput O andPatrick WH Jr. (2000) Methane and nitrous oxide
emissions from a rice field in relation to soil redox
and microbiological processes. Soil Science Societyof America Journal, 64: 2180–2186.
IPCC (2013) Climate Change 2013: The PhysicalScience Basis. Contribution of Working Group I to
the 5th Assessment Report of the Intergovernmental
Panel on Climate Change. Stocker TF, Qin D,
Plattner GK, Tignor M, Allen SK, Boschung J,
Nauels A, Xia Y, Bex V and Midgley PM (eds).
Cambridge, New York, Cambridge University Press.
IPCC (2014) Climate Change 2014: Mitigation of
Climate Change. Contribution of Working Group III
to the 5th Assessment Report of theIntergovernmental Panel on Climate Change.
Edenhofer O, Pichs-Madruga R, Sokona Y, Farahani
E, Kadner S, Seyboth K, Adler A, Baum I, Brunner S,
Eickemeier P, Kriemann B, Savolainen J, Schlömer S,
von Stechow C, Zwickel T, Minx JC (eds).
Cambridge, New York, Cambridge University Press.
Joulian C, Olliver B, Neu HU and Roger PA (1996)
Microbiological aspects of methane emission by aricefield soil from the Camargue (France): 1.
Methanogenesis and related microflora. European
Journal of Soil Biology, 32: 61–70.
Le Mer J and Roger P (2001) Production, oxidation,
emission and consumption of methane by soils: A
review. European Journal of Soil Biology, 37: 25–50.
Li C (2007) Quantifying greenhouse gas emission fromsoils: Scientific basis and modeling approach. Soil
Science and Plant Nutrition, 53: 344–352.
Liu DY, Ding WX, Jia ZJ and Cai ZC (2011) Relation
between methanogenic archaea and methane
production potential in selected natural wetland
ecosystems across China. Biogeosciences, 8: 329–
338.
Lumpkin TA and Plueknett DL (1985) Azolla, a low costaquatic green manure for agricultural crops.
Lumpkin: Department of Agronomy and Soil Science.
College of Tropical Agriculture. University of Hawaii.
Plueknett: Consultative Group on International.
Agricultural Research. World Bank. Washington, D.C.
Congress of the U.S. Office of Technology
Assessment, Chapter II: 107-124.
Mujiyo, Sunarminto BH, Hanudin E, Widada J andSyamsiyah J (2016) Methane emission on organic

rice experiment using azolla. International Journal ofApplied Environmental Sciences, 11: 295-307.
Mujiyo M, Sunarminto BH, Hanudin E, Widada J,
Syamsiyah J (2017) Methane production potential ofsoil profile in organic paddy field. Online firstarticles in Soil and Water Research (SWR).
Available at
http://www.agriculturejournals.cz/web/swr.htm?type=article&id=58_2016-SWR(accessed July 14th, 2017)
Neue HU, Wassmann R, Kludze HK, Bujun W and
Lantin RS (1997) Factors and processes controlling
methane emissions from rice fields. Nutrient Cyclingin Agroecosystems, 49: 111-117.
Neue HU, Wassmann R, Lantin RS, Alberto CR, Aduna
JB and Javellana AM (1996) Factors affecting
methane emission from rice fields. Atmospheric
Environment, 30:1751-1754.
Nieder R and Benbi DK (2008) Carbon and Nitrogen in
the Terrestrial Environment. Berlin, Springer Science+ Bussines Media B.V.
Oelbermann M and Schiff SL (2008) Quantifying carbon
dioxide and methane emissions and carbon dynamics
from flooded boreal forest soil. Journal ofEnvironmental Quality, 37: 2037-2047.
Prasanna R, Kumar V, Kumar S, Yadav AK, Tripathi U,
Singh AK, Jain MC, Gupta P, Singh P K and
Sethunathan N (2002) Methane production in ricesoil is inhibited by Cyanobacteria. MicrobiologicalResearch, 157:1-6.
Raghoebarsing AA, Pol A, van de Pas-Schoonen KT,
Smolders AJP, Ettwig KF, Rijpstra IC, Schouten S,
Damste JSS, Op den Camp HJM, Jetten MSM andStrous M (2006) A microbial consortium couples
anaerobic methane oxidation to denitrification.
Macmillan Publishers Limited, Nature, 440:918-921.
Reddy KR and DeLaune RD (2008) Biogeochemistry ofwetlands: Science and applications. Boca Raton,
London, New York, CRC Press, Taylor & Francis
Group.
Sanchez PA (1976) Properties and management of soils
in the tropics. New York, London, Sydney, Toronto, A
Wiley-Intersscience Publ, John Wiley and Sons.
Sasa JJ and Syahromi O (2006) Rice-fish system inperspectives of land productivity, farm income, andenvironmental conservation. Indonesian Agency for
Agricultural
Research,
25(2):135-143.
(In
Indonesian)．
Satapathy KB and Singh P K (1985) Control of weeds by
Azolla in rice. Journal of Aquatic Plant Management,
23:40-42.
Setyanto P and Bakar RA (2005) Methane emission frompaddy fields as influenced by different water regimesin Central Java. Indonesian Journal of Agricultural
Science, 6(1): 1-9.
Shin YK, Yun SH, Park ME and Lee BL (1996)
Mitigation options for methane emissions from rice
fields in Korea. Ambio, 25: 289-291.
Slonczewski J (2009) Nitrate/nitrite methane oxidation.
(ed.) BIOL 238 Microbiology, Kenyon College.
Available athttps://microbewiki.kenyon.edu/index.php/Nitrate/nit
rite_methane_oxidation (accessed December 23th,2013).

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 5 - Soil Chemistry -: 02

Thauer RK, Kaster, AK, Seedorf H, Buckel W and
Hedderich R (2008) Methanogenic archaea:
Ecologically relevant differences in energy
conservation. Nature Reviews Microbiology,
6:579-591.
USEPA (2006) Global Antropogenic Non-CO GHG
Emission:
1990–2020.
Washington,
USEPA.
Available at http://www.epa.gov (accessed August
29th, 2013).
Vance DB (1996) Redox reactions in remediation.
Environmental Technology, 6:24-25. Available at
http://2the4.net/redox.htm (accessed December 12th,2013)
WMO (2013) Greenhouse gas concentrations in
2

atmosphere reach new record. World MeteorologicalOrganization.
Geneva.
Availableat
http://www.wmo.int (accessed February 25th, 2015).
Yagi K (2006) Methane emission in rice, mitigation
options for. In Encylopedia of Soil Science. Second
Edition. Volume 2. Edited by Rataan Lal. New York,
Taylor & Francis Group.
Yagi K, Tsuruta H and Minami K (1997) Possible
options for mitigating methane emission from ricecultivation. Nutrient Cycling in Agroecosystems, 49:
213-220.
Ying Z, Boeckx P, Chen GX and Van Cleemput O (2000)
Influence of Azolla on CH4 emission from rice fields.
Nutrient Cycling in Agroecosystems, 58: 321-326

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 5 - Soil Chemistry -: 03

Solutions for nutritional zinc management in paddy soils in the Red River Delta of
Vietnam (Tien Lu region, Hung Yen province)○Dinh Thi Lan Phuong1, Nguyen Thi Hang Nga2
(1Faculty of Environment, Thuy Loi University, Vietnam，2

Faculty of Water Resources Engineering, Thuy Loi University, Vietnam)

SUMMARY
Zinc was recognized as essential element for synthesizing nucleic acids, proteins and phosphorus, hence without
zinc leads to darkly reduce rice yield and quality. Alluvial soils of Vietnam’s Red River Delta commonly arelack of micronutrient zinc due to traditional flood irrigation. Therefore, managing water to protect nutrient zincin agricultural soil in the Red River Delta of Vietnam is very necessary. This study was conducted in Tien Lu
district, Hung Yen province, the middle region of Red River Delta, Vietnam during four rice seasons from 2015
to 2016. Soil properties has characteristics of neutral alluvial (pH around 6.9), mobile zinc 0.6829±0.0060
mg/100 gram soil (gs), total zinc 8.4082±0.2575 mg/100 gs, organic content 1.1 %, total nitrogen 0.9 %, CEC 14
meq/100 gs. Irrigation methods were traditional flooded irrigation (FI) with keeping water over 6 cm fromsurface and saving water irrigation (SWI) with controlling water level 2÷3 cm from surface with common KD18
rice variety. The SWI included wet irrigation in 10 days alternating 3 dry days and keeping 7÷10 dry days at theend stage. The study results showed that SWI contributed to maintain nutrient zinc in paddy soil more than FIwith mobile zinc decreased slightly (0.0371 mg/100 gs) while reduced significantly 0.5684 mg/100 gs by FI. In
addition, SWI saved approximately 25% of the irrigation water but unchanged rice yield. Therefore, SWI is theeffective solution to zinc management in paddy soil of Red River Delta of Vietnam at this moment.
Keywords: alluvial soil, nutrient soil zinc, paddy soil, zinc management.

Introduction

Lan Phuong, Tran Viet On, 2015).

Rice is the major consumer of irrigated water in the
agricultural aspect in Vietnam. Therefore, watersave irrigation (WSI) seems to be an useful solution
to adapt climate change toward lower carbon
economy and sustainable agricultural production
currently. Although WSI (controlling the surface
water and drying times). Has been applied in
Vietnam since 2003, it has been only deployed onsome regions in Red River Delta of Vietnam, suchas Phu Xuyen (Ha Noi), Ba Vi, Ha Noi, Nam Sach(Hai Duong), Thuong Tin (Ha Noi), in Mekong
Delta as An Giang, Can Tho. Besides, Vietnam’s
traditional irrigation technology (FI) for rice
requires continuous ﬂood and needs large water
inputs with the surface water lever from 5÷7 cm
even above 10 cm in the rainy season and lowland.
Flood soil leads to reduce redox potential (Eh) toform some sulfide toxins (H2S, HS-, S2-) in soil
(Yoshida.S & Chaudhry.M.R, 1979; Hafeez. B,
Khanif.M.Y, Saleem. M, 2013), consequently, zincmicronutrients in the rice soil significantly
decreases (F.N. Ponnamperuma, 1985).

Zinc is a very important element for rice growth,
however flood irrigation reduces mobile zinc for
Vietnam’s paddy soil causing zinc deficiency insoil. Until now there are few studies about nutrient
zinc protect for paddy soils in Vietnam has been
conducted. This study focuses on changing zinc
nutrition when applying water save irrigation andflood irrigation technology on alluvial agriculturesoils in Vietnam’s Red River Delta. From that,management solutions to micronutrients zinc in
paddy soils in the Red River Delta are proposed
aims to use agriculture soil sustainablly underclimate change condition in Vietnam.

Researching of WSI in Vietnam indicated that
irrigation water saved 794.5 m3/ha total water
demand (Tran Viet On, 2016), and controlled
methane emission 10-11% (Nguyen Viet Anh,2009), reduced toxic Fe2+ and Mn2+ (Tran Thi Minh
Nguyet, 2013) and sulfides HS-, S2-, H2S (Dinh Thi

With FI treatment, water level was controlledusually from 5 to 7 cm and up to 7÷10 cm in rainy.
The fields were dried for 15 days before havestingand did not use zinc fertilizers. WSI treatment, thelower water level was applied (3 to 5 cm). The
fields were dried for 4 to 5 days after 15th and theMaterials and methods
The study conducted field experiments in Tien Lu
district, Hung Yen province with location at
20°40'57.47"N, 106° 6'8.67"E. Two main
experiments treatments were included water save
irrigation (WSI) and continuous flood irrigation(FI). Traditional KD18 variety was chosen by thisstudy. Experiment time lasted 2 years 2015-2016.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 5 - Soil Chemistry -: 03

Table 1 Properties of experimental soil
Properties
CEC
Organic content
Nitrogen content
pHH2O
pHKCl
Total zinc
Mobile zince

Value
14 meq/100 gs
1.1%
0.9%
6.7-6.9
6.82÷6.94
8.4082±0.2575 mg/100 gs
0.6829±0.0060 mg/100gs

last stage was dried for 7 days and then continuous
dried during 15 days before harvesting. This
treatment, zinc fertilizers were not also used.

Table 2 The difference change of mobile zinc
(mg/100gs) in FI and SWI
FI
Sampling
time[Zn2+]

Standard
deviation

1
2
3
6
7

0.64500.61920.58500.47900.16890.00160.00350.00290.00410.0029

SWI
Standard2+[Zn ]deviation0.6569 0.0027
0.6302 0.0042
0.6457 0.0040
0.6314 0.0109
0.6198 0.0072

P (Ttest)

0.07260
0.01151
0.008470.001830.00056

In order to compare mobile Zinc in flooded
irrigation regimes and dried-wet alternative regime,
field experiments were designed. Monitoring
indicators were regular including Eh, pH, waterlevel and [Zn2+]. Observation times were in 5
growth stages of rice including irrigate a field(stage 1), take root (stage 2), last branching (stage
3), blossom (stage 4), flourish (stage 5).
Soil samples were taken at a depth of 10 cm, well
mixed, dried naturally, crushed and passed througha 1 cm sieve. The redox potential Eh and pHH2O
were measured by ORP/pH meter at 5-10 cm undersurface.
To assess the relationships between water level,
redox potential and mobile zinc without consuming
nutrient zinc of rice, the laboratory experiments
were designed as continuous flood soil (FS) withconstantly water level of 4-5 cm, andnoncontinuous flood soil (NFS) with level of 4-5
cm from the beginning then to be dried naturally.
The study was designed in the system of pots with
30 cm in diameter, 50 cm deep. An observation
time was 1, 2 or 3 weeks since planting. Monitoring
parameters were included Eh, pH, water level and[Zn2+].
[Zn2+] in soil was analyzed according the methodof soils Analysic published by the American
Society of Agronomy in Madison, Wisconsin(1982) with the anodic stripping voltammetry
method.
All experiment results were assessed based on
static analysis, dependent sample t-test for means
was calculated. A 5% significance level was
adopted for identifying significant treatment effects
and 2013 excel software was used.

Result and discussions
Field experiments
The field studies showed the different change ofmobile zinc in the lowland and aerobic soil under
different water regimes of FI and WSI. Mobile zincdecreased significantly under anaerobic condition(FI), however was improved by aeration condition(WSI). Table1 and Fig.1 indicated different mobile

Fig.1 Mobile zinc in FI and SWI experiments
zinc in two experiments.
Average water levels determined about from
6.6÷8.5 cm in experimental stages, FI indicated thatflood time correlated inversely with mobile zincconcentration. Average mobile zinc was reduced
strongly from 0.5283 mg/100 gs down to 0.3948
mg/100 gs/crop (R2 0.71÷0.80). Conducting
independent T-Test analysic between average
results in two continuous sampling stages to obtain
most values p < 0.05 showed that surface water
lever affects on mobile zinc.
However, controlling surface water of the WSI
from 3÷5 cm results mobile zinc was not affected
because of low water level. Although nutrient zinc
was consumed by rice, mobile zinc in the WSI only
slightly decreased. Times of 5-days and 7-days
dried increase [Zn2+] in the paddy soil (from 0.6302
to 0.6457 mg/100 gs in stage 2 to stage 3,
respectively). Results of low water and drying field
in a long time was cracking surface to lead toaccelerate diffusion speed of oxygen gas into therood regions to increase the redox potential. In thiscondition, zinc and sulfate are released from sulfide
precipitate by the oxidation reaction of aerobic
microorganism (Yoshida.S & Chaudhry.M.R, 1979;
Hafeez. B, Khanif.M.Y, Saleem. M, 2013). Zincand sulfate increased during the drying fields
between irrigation periods. So, WSI has maintained
mobile zinc while FI dramatically reduced the zinc
nutrient for rice.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 5 - Soil Chemistry -: 03

2ZnS + 3O2 + 2H2O ⇌ 2Zn2+ + 2SO42- + 4H+

Most of the values p < 0.05 (Table 1) fromindependent variance analysis (T-test) showed thatthe effects of water level on mobile zincconcentration was significant. These data suggestthat the influence of flood irrigation on mobile zinclevel were significant for two spring crops and two
season crops from 2015 to 2016 in this study.
Test of independent T-test analysis of average[Zn2+] between FI and SWI: except stage 1 (p =0.0726) was not significantly difference. However,almost p values under 0.05 revealed significant
change of mobile zinc concentration because ofdifferent irrigation level.

P(Ttest)With lower average water levels of NFS (5 –3.44 – 2.3 – 0 – 0 cm might limit to form sulfide
zinc (ZnS), so mobile zinc was only slightly
decreased 4÷10 % with content of 0.6481 to 0.5346
mg/100 gs in second week and slightly increasing
to 0.5826 mg/100 gs at the third week. Appearanceof small cracks in land face after drying in the 6th
week led to increasing oxygen gas in the soil, hence
Zn2+ ions released from sulfide precipitates (at thisstage [Zn2+] riced up to 0.6238 mg/100 gs). The
oxidation occurred strongly when the soil was more
dried after the 8th week, [Zn2+] rose to 0.6734
mg/100 gs (more than 1.62±0.05 % from the firstweek).

0.001202
0.046976
0.000185
5.13.10-8
4.44.10-8

From T-test analysis, a significant difference (p <0.05) showed that p values (from 0.0035 to 0.0052)
were under 0.05. Therefore, shallow water levelwith dry fields is favorable condition for aerobic
microorganisms to transfer indigestible zinc (ZnS)
into the digestible form (Zn2+).

Laboratory experiments
On the other hand, the studies in Lab for two
formulas including continuous flood soil (FS) andnoncontinuous flood soil (NFS) showed that mobile
zinc strongly reduced in longtime wetlands. The
overall effects of water levels on mobile zinc in the
SF and the NFS are showed in Table 2.
Table 3 The mobile zinc content in the FS and the
NFS formula (mg/100 gs).
NFS

FS

Flood
time
(week)

2+[Zn ]Standard
deviation

[Zn ]

1
2
3
6
8

0.64810.53460.47770.43920.11450.00570.00670.00270.00450.0034

0.66280.55000.5826
0.62380.67342+Standard
deviation
0.00500.00230.01060.00450.0002

between continuously sampling periods from
0.0006÷0.0023 indicated that the mobile zincchange under flood regime were significant.
Reducing mobile zinc was high due to theanaerobic respiration of reducing sulphate bacteria(desulfovibrio) transforming sulfate to sulfides (H2S, HS- or S2-): 4H2 + SO42-  H2S + 2H2O + 2OH(Yoshida.S & Chaudhry.M.R, 1979). Sulfide
precipitates are formed by the bonding reacts ofsulfides with zinc ions: HS- + Zn2+  H+ + ZnS↓;S2- + Zn2+  ZnS↓ (Yoshida.S & Chaudhry.M.R,
1979; Hafeez. B, Khanif.M.Y, Saleem. M, 2013).
As such, wetland was the cause of reducing amountmobile zinc.

Conclusion
The study was conducted in Tien Lu district, HungYen province, a soil zone is located in the Red
River Delta in Vietnam, indicated that water leveland surface water regimes affected [Zn2+] in soil.
The deeply water level in the FI decreased [Zn2+] so
FI for rice on the Vienam’s Red River Delta not
only uses more irrigation water but also reduces
important nutrients such as SO42- and Zn2+. The
mobile zinc status in the soil is improved when
dried fields. Nevertheless, agriculture soils wherezinc deficiency occurs, the useful way to improve
nutrient zinc is aerobic soil maintain. Using WSI
saves irrigation water, increases Eh and maintains
nutrient zinc in paddy soil. From the viewpoint ofenvironmental protection, water save irrigation isbenefit solution to protect soil zinc nutrition in the
Red River Delta of Vietnam.
Fig. 2 The mobile zinc content in the FS and the
NFS formulas.
Mobile zinc in the FS when high water level was
continuously flooded in 8 weeks decreased from
0.6829 - 0.1145 mg/100 gs. Correlation coefficients
R2 from 0.82÷0.85. Values p (T-test analysic)

Acknowledgement
We thank Prof. Tran Viet On from Thuy Loi
University, Vietnam for his support to review thisarticle.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
SESSION 5 - Soil Chemistry -: 03

References
Alloway (2008) Zinc in Soils and Crop Nutrition,
Second edition, published by IZA and IFA Brussels,
France.
Nguyen Viet Anh (2009) “Studying the suitablesurface water regime to reduce methane gas
emissions in rice fields in the lowland sludge
area in the Red River delta", PhD thesis,
Vietnam.
F.N. Ponnamperuma (1985), “Chemical kinetics ofwetland rice soils relative to soil fertility”,
Wetland soils: characterization, classification,and utilization (workshop of The International
Rice Research Institute.
Jal Vymazal, Lenka Kröpfelová (2008) Wastewater
Treatment in Constructed Wetlands with
Horizontal Sub-Surface Flow, Czech.
Shouichi Yoshida & M.R. Chaudhry (1979) “Sulfur
nutrition of rice”, Soil Science and Plant
Nutrition, 25(1): 121-134.
Tran Minh Nguyet (2013) “Study on the effects ofagroforestry irrigation regime on Mn and Fe
metabolism in wetland rice soil”, PhD thesis,
Vietnam.

-PART 2UGSAS-GU & BWEL JOINT POSTER SESSIONON AGRICULTURAL
AND BASIN WATER ENVIRONMENTAL SCIENCES

2017
POSTER PRESENTATIONSORGANIZERS:
THE UNITED GRADUATE SCHOOL OF AGRICULTURAL SCIENCE,
GIFU UNIVERSITY&
GIFU UNIVERSITY REARING PROGRAM
FOR BASIN WATER ENVIRONMENTAL LEADERS

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P01

Research on cause of dam failure under view point of hydraulic fracturing– Case study KE 2/20 REC dam failure in Vietnam
Tran Duy Quan1, Shinichi Nishimura2, Masateru Senge2 and Fumitoshi Imaizumi3
1. The United Graduate School of Agricultural Science, Gifu University, Japan.
2. Faculty of Applied Biological Sciences, Gifu University, Japan.
3. Faculty of Agricultural, Shizuoka University, Japan.

INTRODUCTION
Much research in recent years has focused on explaining
dam failures due to concentrated leakage. Hydraulic fracturing
is considered as one of potential causes leading toconcentrated leakage especially at the first filling soon after
dam completion. The risk of hydraulic fracturing might
become higher than when normal stress in fill dam is reduceby arching effect and reservoir water level rises up. Past
researches pointed out that dam failures in Hyttejuvet,
Balderhead, Stockton, Wister, Teton dams… during the first
impounding were caused to hydraulic fracturing.
This study introduces KE 2/20 REC dam failure that will be
used as a case study. This dam was started to construct in
October, 2006 in central area of Vietnam and was put into
operation in 2008. Just after 1 year, the main dam was broken
at location of culvert in completely normal condition. Past
research conducted by NGUYEN Chien and HO Sy Tam(2009) indicated that the dam failure was resulted from thepiping mechanism. Although the conclusion might explain
somewhat the cause of failure in KE 2/20 REC dam, theresearch has not clearly explained what happened prior to theseepage formed.
This research aims to explain the dam failure under
viewpoint of hydraulic fracturing by using finite element
method (FEM) analysis. A build-up analysis using FEM
model with successive 12 layers of fill soil was conducted tosimulate stress-strain state in longitudinal section of the dam
which includes cross section of culvert as well. Results fromthis analysis indicated that, normal stresses at both side of pipe
culvert are reduced by arching effect and to be lower waterpressure. Therefore, it can be concluded that, reason of thedam failure is due to hydraulic fracturing phenomenon.

MATERIALS AND METHODS
Overview of case study—KE 2/20 REC dam is located incentral area of Vietnam. The dam’s initial purpose was tocreate a reservoir that will supply irrigation water for a part offarmland (about 30hectare). Beside the reservoir also supplies
domestic water for many households toward downstream area.
KE 2/20 REC headwork consists of a main dam (withmaximum height of 12.5m), a saddle dam, a spillway (withwidth of 11.2m) and a culvert (with design flow of 0.037m3/s).
In June, 2009, the main dam was broken at location of culvert
in completely normal condition without earthquake, rain andwater level of reservoir was approximately normal water level+30.5m.
Observations after dam failure showed that a segment of
culvert was broken at the middle of the segment, after that,water flow eroded deeply into foundation which had
dimensions with approximating 8.5m length of water flow
direction and 3.5m depth of erosion. There was also no sign of
seepage from shoulder of the dam. At the same time, thebroken segment and a part of dam body close to the culvert
were also swept toward downstream. Real image of the dam
failure is demonstrated in picture 1.

Picture 1: KE 2/20 REC dam failure
Results of in-situ surveys and experiments after the dam
failure pointed out that slope of excavation at the left side of
culvert was rather steep. Observed slope in reality was just
1:0.5 (vertical and horizontal direction respectively), even lessthan (as in picture 1), although required value in design was
1:1. Fig.1 shows longitudinal section of the dam that was
idealized from design section and in-situ observations.
According to geological description, culvert and dam were put
on firm foundation that was cracked and weathered rock – akind of argillaceous slate. Elastic modulus of foundation ismuch higher than the value of filled soil. Physical propertiesof filled soil and foundation that were taken from previous
researches on the dam and were listed in Table 1. In addition,
in-situ test of filled soil after dam failure pointed out thatembankment was not compacted carefully. Real relative
compaction (90.4%) had not reached to required value (95%).
Cross sections of culvert and the dam are demonstrated in
Fig.2. It can be seen that the culvert was reinforced concrete
circular conduit and put on a foundation bed with 0.4m depth.
Physical parameters of culvert materials are also summarizedin Table 1.
Table 1: Material properties
a. Filled soil
Total density (ρ):
2.018 Mg/m3
Dry density (ρd):
1.673 Mg/m3
Soil cohesion (c):23.0 kPa
16o47’
Angle of internal friction (ϕ):
Coefficient of permeability (k):6.247×10-5 cm/s
Elastic modulus (E):16800 kPa
Poisson’s ratio (ν):
0.3
b. Reinforced concrete
Total density (ρ):
2.45 Mg/m3
Elastic modulus (E):
2.4×107kPa
Poisson’s ratio (ν):
0.2
Numerical analysis—In recent years, numerical analyses
using finite element method has been widely applying ininvestigation of stress-strain distribution as well as seepage indams. In this research, a build-up analysis by FEM withsuccessive 12 layers of fill soil is performed to analyze
deformation and stress in longitudinal section of the dam
which includes cross section of culvert as well. The build-up
model allows for better simulation of influences during

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P01
construction. Due to elastic modulus of foundation is alsomuch higher than embankment’s, for sake of simplicity, thismodel just simulates dam body. Coordinates of 11 main nodal
points on boundary are showed in Fig.1. The coordinates ofother nodal points were calculated from coordinates of 11
main nodal points.
35.00

Finite element mesh consists of 641 elements and 2121
nodal points. All elements are eight-node quadratic
quadrilateral elements and elements adjacent to culvert havesmaller dimension than the others in order to improveaccuracy and detail of stress distribution around the culvert.
The model is also assumed to be restrained at the foundation.
A

Crest of parapet wall +33.0m

1(0,32.2)

Dam crest +32.2m

30.00

2(28.96,30.68)
3(36.70,27.59)

25.00

4(95,25.77)
Original ground surface

20.00

5(101.2,19.17)

15.00

1.0
9(144.41,23.19)
0.5
Bottom trench10(150.5,23.19)

6(109.7,16.74)

8(138.2,18.51)
7(130.65,16.61)

Foundation

A

10.00

Foundation

Y

5.00
0.00

11(155.01,32.2)

Normal water level +30.5m

X
O

0.4m

Fig. 1: Longitudinal section and data of nodal points on boundary in numerical model
Pipe culvert by reinforced concreteStress—Fig.3 indicates relationship of subtraction between
inner diameter 0.6m
normal stress (σθ)and water pressure (W) around pipe versus
outer diameter 0.8m
theta angle (θo) with sign convention of theta as in Fig.4. It is
clear
that normal stresses at both side of the culvert wereConcrete
1.0
reducedand much lower than the stress at the top of the pipe.
0.5
Moreover, when theta angle was smaller than about 96.0o andhigher than about 248.7o, normal stress was really exceeded bywater pressure. From these observations, it can be concluded
0.35m 0.50m 0.35m
0.5m
1.2m
that hydraulic fracturing might have occurred at these regions.
These result is consistent with inferences of this research
Fig.2: Cross section of culvert
early.

RESULTSDISCUSSION
Displacement—Results from this research pointed out thatmaximum vertical displacement occurred nearly mid-height ofembankment. This is consistent with some past researches
using build-up model. However, it seems dissimilar to resultsthat was obtained from research conducted by NGUYEN
Chien and HO Sy Tam (2009). Because that study concluded
maximum displacement was at the dam crest. Furthermore,vertical displacement of fill soil column at both sides of pipe
were higher than in the column of fill soil above the crown of
the pipe. These differential displacements induce archingaction adjacent to the pipe culvert.

Past research conducted by NGUYEN Chien and HO Sy
Tam (2009) concluded that cause of this dam failure was due
to piping mechanism. However, results from build-up analysis
in this research pointed out that under arching effect, normal
stress at under part of the pipe culvert was considerable
reduced and much lower than water pressure, and therefore,hydraulic fracturing might have occurred at these regions. This
research also indicated that shape of culvert have significant
effect to formation of arching action. Besides that, slope
excavation and properties of foundation also contributearching effect to be more serious. Future work will propose
some countermeasure to reduce risk of hydraulic fracturing indam.

REFERENCES

Fig.3: Graph of subtraction between normal stress (σθ)
and water pressure (W) versus theta angle (θo)

Fig.4: Convention of theta angle (θo)

Ngambi, S., Nakano, R., Shimizu, H. and Nishimura, S.
(1997) Cause of leakage along the outlet conduit underneatha low fill dam with special reference to hydraulic fracturing,
JSIDRE, No.188, pp.93-102.
Ng, K. L. and Small, J. C., 1999 A case study of hydraulicfracturing using finite element methods. Can. Geotech. J.
36: 861-875.
Nishimura, S. Shimizu, H. (2004) A study of the measurementof fracture toughness in cohesive soil – relationshipbetween the size of initial crack and diameter of specimen.
Paddy Water Environ (2004) 2:27–32.
Rajesh Khanna, Chitra, R. (2016) Hydraulic fracturing in coreof earth and rockfill dams. International Journal ofEngineering Innovation & R esearch, Volume 5, Issue
1:136-142.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P02

Data mining the efficiency of auction in origin market based on random
forest-A case study of ATSUMI AREA, AICHI Prefecture Ning Li and Shigenori Maezawa
The United Graduate School of Agricultural Science, Gifu University

INTRODUCTION
Over the next decades, structure change in the eating habitsof Japanese nationals combined with pressure of Agricultural
population decrease are expected to have significant effects on
distribution of domestic vegetables. Particularly in some
agricultural products specified origin where less adaptable, In
the process of agricultural products trading, the decentralized
and complex traditional circulation mode still dominates. A
sustainable improvement of regional agricultural economy
requires better structure planning of agricultural products
distribution systems and of Business models in various
markets. However, structure reform of these areas are subject
to several constraints such as distribution bodies are isolated
from each other, Market size dispersion, Business model
differences etc.
In view of this situation, many agriculture-related
researchers wait to learn if agricultural industries can become“Smart” agricultural enterprises. In recent years at theinternational level, “Green Data Revolution” was born fromthe optimism that Big Data can and will deliver benefits toagricultural industries and global society. In japan in a similar
way the Green Revolution sparked an increase in agricultural
productivity. Everingham et al. (2015) reported the benefits
that a modern data mining method offers over contemporary,time-honored methods like stepwise linear regression
modelling. The key advantage of the random forest technique
is it can investigate nonlinear and hierarchical relationships
between the predictors and the response using an ensemble
learning approach. Consequently, random forests have been
applied in a number of agricultural related applications.
Matsui et al. (2014) developed factor analysis and prediction
model of abandonment cultivated land of Japan in regional
scale. Their research shows that the best machine learningalgorithm to predict the cultivation abandonment in Japan was
RF algorithms and it could detect major factors under regional
specific situations. YAMAYA et al. (2017) presents cropclassification using satellite data to establish a mapping
method in place of the existing ground survey and assessed theaccuracy of classification performed by machine learningalgorithm “Random Forest”. The results of their study
confirm that crop classification with the lower cost will
become possible.
If industry practices can be shaped to suit the size of theforthcoming demand for domestic cabbage, a number ofbenefits to both regional agriculture revitalization and national
agricultural product self - sufficiency rate can be realized.
Given the advantages offered from early and accurate
predictions of Cabbage auction price deviation and the abilityof data mining techniques to extract patterns in large andcomplex data sets, the objective of this paper is to determine
how accurately the random forest data mining method canestimate Cabbage auction price deviation in Cabbage specified
origin in the pursuit of advancing industry sustainability.

MATERIALS AND METHODS
1)Study Area

ATSUMI AREA is a peninsula in southern Aichi
Prefecture, central Honshū, Japan. Due to the influence of thewarm current (Kuroshio) flowing offshore, it has a mild
climate even in winter, the sunshine hours and the fine days
are top nationwide, with the geographical conditions suitable
for agriculture. Especially after the completion of the
Toyokawa water project, agriculture developed greatly, it
became one of Japan's representative agricultural zone ofvegetables, particularly, the production and shipment volume
of winter cabbage is highest in Japan. Furthermore, during theprocess of formation of cabbage production area, activities ofOrigin Merchants that have horizontal competitive
relationship with JA Group have become remarkable and havea significant effect on the local distribution network. Origin
merchants in this region show a unique presence when
promoting vegetables distribution that commensurate with theagricultural productivity as a main body. By utilizing thecharacteristic of Co., Ltd to correspond to vegetables
distribution, currently, 26 companies that are all in this area
are forming into one big cooperative, and have established 6
origin markets where trade-in the total amount of cabbage byauction. In addition, by focus on the target that producers who
are not linked to Kyohan system of JA Group, entire of Origin
Merchants are exerting power to pick up almost the same
share of cabbage trade-in amount.
This research focusses on Origin Market A that trading-in
maximum amount of winter cabbage in ATSUMI area. The
Auction data used consisted of that collected in Origin Market
A acquired from January 2011 to April 2015.
2) Building the Optimized Random Forest Classifiers
RF is an ensemble learning technique that generates amultitude of random decision trees that are then aggregated tocompute a classification. In many studies, the RF classifier has
been found to be stable and relatively efficient, to involve few
user-defined parameters and to yield overall accuracy levels
that are either comparable to or better than other classifiers
such as maximum likelihood and conventional decision trees,
AdaBoost decision trees and neural networks, and support
vector machines. RF uses a bagging-based approach (random
sampling with replacement) to build a forest of classification
trees. Observations of the original dataset that are not found ina bootstrap sample are referred to as out of bag observations(OOB). The OOB of error is calculated using a one-third
portion of the data that was randomly excluded from theconstruction of each of the 500 classification trees andcorresponds to the rate of misclassified samples.
Consequently, the classification accuracy is estimatedinternally and does not require an independent validation set.
“Random forest” has improved performance over single
decision trees, and it is much more efficient than traditional
machine learning techniques, e.g. artificial neural networks,
especially when the dataset is large. Random forest can handle
up to thousands of explanatory variables, can be used to rank
variables importance when the R package “random forest” isimplemented.
Variable importance sorting model is based on Random
Forests of Data Mining to study the important attributes, thus
providing a reference for price forecasting. One of theproperties of RF is that it can naturally provide variableProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P02
importance (i.e. feature ordering) in the learning process, theprocess is as follows:
A. Given the input sample, set D𝑛𝑛 = {(𝑥𝑥𝑖𝑖 , 𝑦𝑦𝑖𝑖 )}𝑛𝑛𝑖𝑖=1 , Set the
number of decision trees in RF to 𝑛𝑛𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 , and thenumber of candidate variable on each leaf node to
𝑚𝑚𝑡𝑡𝑡𝑡𝑡𝑡 .
B. Random picks with returned (bagging) 𝑛𝑛1 samples
from D𝑛𝑛 , then will get training set 𝑥𝑥𝑖𝑖 , Each decision
tree that not used in the training process be called as an
OOB (out of bag) sample.
C. Construct RF, test the OOB accuracy rate of the J-tree
and get 𝐴𝐴𝑗𝑗0, j = 1,2, ⋯ , 𝑛𝑛𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 .
D. For the i-th feature, on the j-th tree, the values of all
OOB samples on this variable are randomly substituted
and calculate the accuracy of the OOB sample.
E. The importance of the i-th variable is calculated
according to the following formula:𝑛𝑛𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡

𝑠𝑠𝑖𝑖 = 1�𝑛𝑛𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 � �𝐴𝐴𝑗𝑗0 − 𝐴𝐴𝑗𝑗𝑖𝑖 �
𝑗𝑗=1

Sort these scores by sorting from big to small, get{𝑆𝑆𝑑𝑑1 , 𝑆𝑆𝑑𝑑2 , ⋯ . 𝑆𝑆𝑑𝑑𝑑𝑑 }, then {𝑑𝑑1 , 𝑑𝑑2 , ⋯ 𝑑𝑑𝑛𝑛 }is the desired featuresin order of importance.

RESULTSIn the process of the price formation of the auction, thevariables that are relevant to the auction price are analyzed inimportance by using RF method. Details about the calculationof these indices can be found in Table 1. Of results generated
via the RF approach, the mean decrease in accuracy (MDA)
for a variable allows one to assess the importance (the degree
to which a variable is discriminant) of each variable used forclassification. The more the accuracy of the RF decreases dueto the exclusion (or permutation) of a single variable, the more
important that variable is. Consequently, higher values of
MDA indicate variables that are more important to theclassification.
Table 1: MDA results for each predictor variables
supplied to the random forest classification
Name

MDA

Size

7.6

Quantity/per

9.2

Week

10.1

Scale
(Producer)

10.2

Quantity-Day
sum

12.5

Details
The size of winter cabbage. Including L,
M, S,2L,3L,4L,5L,2S,3S
The quantity of winter cabbage (numberof case) in an auction
The week number of year that
production to be wend.
Calculated based on the delivery
volume of each producer. （Divided intolarge, medium and small）
Daily shipments. （Including all
producers’ productions）

The accuracy evaluation was performed through theinternal RF validation procedure that makes use of all thesample polygons in the database. The performance of theresulting optimized classifiers was estimated from confusion
matrices provided through the RF results via the calculation of
two measures: the overall accuracy, which corresponds to thetotal number of correctly classified objects divided by the total
number of test objects [43,44]. (Table 2)
Table 2: Output result with "Target within 15 yen"
Correct
58,33762.45%
Wrong

35,07337.55%

total

93,410100.00%DISCUSSION
Faced with problems and challenges encountered in the
traditional auction in Japan’s origin market and given theopportunities created through the development of data mining
technology, we have developed a classification workflow
based on multisource data. The method developed involves theuse of Random Forest, which has already proven to beefficient over many agricultural related fields.
In our approach, take advantage of the transaction
characteristics of the product to build the learning database
based on assumptions that: The classification model generated
by RF technology can effectively shorten the time cost of
auction. These assumptions are well validated in theevaluation of the effect of the model. In table 3, we can seethat the use of RF model to classify agricultural products caneffectively shorten the auction time by nearly 21% without
affect to final price.
Table 3: The calculated value of the impact of the RFclassifier on the auction time

Separate
Separate& PoolNumber of
auctions

Single time
consumingTime
consuming Ratio

93410

5

467050

1

73443

5(8)

3672150.79

In conclusion, based on the analysis and learning of
historical data, the model can give a more objective
assessment of the price classification of Agricultural products,
what can reduce the time and labor cost of the auction and thehuman factor. The results of the analysis on the actual
collection of auction datasets of cabbage show that the
proposed methods and models have objective and accurate
evaluation results, can be used as an auxiliary classification
model for vegetable auction.

ACKNOWLEDGMENTS
The authors would like to thank Staff in Origin Market A
for their assistance to the market surveys, Chuanpeng Zhang ,Hanyuan Zhang for providing logistical support in GIFU. andprofessor Maezawa for providing guidance on the research
approach.

REFERENCES
Takanori
MATSUI,
Tetsu
UGATA,
Takashi
MACHIMURA(2014) A development of factor analyzing
and predicting model of abandoned agricultural land withmachine learning algorithms. Journal of Japan Society of
Civil Engineers, Ser. G. Vol70, No.6, 42,131-139.
Everingham YL, Inman-Bamber NG, Sexton J, Stokes C(2015) A dual ensemble agroclimate modelling procedure toassess climate change impacts on sugarcane production inAustralia. Agric Sci. doi:10.4236/as.2015.68084
Yuki YAMAYA, Rei SONOBE, Hiroshi TAN, Xiufeng
WANG,
Nobuyuki
KOBAYASHI,
Kan-ichiro
MOCHIZUKI(2017), Crop Classification by Random
Forest Using TerraSAR-X Data, Memoirs of the Research
Faculty of Agriculture, Hokkaido University,34(2),1-11.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P03

Study of plant pathogenic genes of a soft rot disease causing bacterium,
Dickeya dadantii
Dina Istiqomah1 and Naoto Ogawa2
1. Science of Biological Resources, United Graduate School of Agricultural Sciences-Gifu University, Japan
2. The United Graduate School of Agricultural Sciences-Gifu University; Faculty of Agriculture-Shizuoka University, JapanINTRODUCTION
Soft rot disease causing bacteria is the most importantdisease than any other bacterial disease. This bacterial
pathogen causes more crop loss worldwide by damaging all of
the part of the plants, such as tubers, fruits, leaves, stems,
bulbs in nearly all plant family. The soft rot occurs bydegradation of pectate molecules in plant cells. Pectinases,
cellulases and proteases are the cell degradation enzymes ofthis bacteria and caused symptoms involving soft rot ofprogeny tubers, stolon end and or lenticellular rots, initial
wilting of top leaves, desiccation of foliage, external
darkening vascular system at stem base and internal necrosis
and hollowing of vascular tissues (Barras et al. 1994).
A number of Dickeya species cause soft rot disease. They
are divided into several pathovar based on host specifity i.e.
chrysanthemi(now
namelydadantii),
dianthicola,
dieffenbachia, paradisiaca, parthenii, zeae and solani (Lelliot
and Dickey 1984). Dickeya zeae is pathogen in warmer
countries, while Dickeya dianthicola spreading in Europe.
Among them, Dickeya dadantii has many host plants and themost widely distributed (Samson et al. 2005).
D. dadantii is one of the top 10 plant pathogenic bacteria, as
the result of survey by the association of bacterial pathologists(Mansfield 2012). The pathogenecity of D. dadantii isdetermined by their secreted molecules to colonize the planttissue. Thus, its virulence is very related with the presence of
pectinases, cellulases and proteases which play a role as cellwall degrading enzymes (Barras et al. 1994).
Expression of genes required for degradation of plant cellwall could be affected by the presence of many signals.
Several regulatory proteins have been reported to be involvedin controlling complex network of many bacterial phenotypes
either in positive or negative manner.

SOFT ROT BACTERIA
The main types of bacteria that cause soft rot are from themember of Enterobacteriaceae i.e.
Dickeya species,
Pectobacterium carotovora subspecies
carotovora and
Pectobacterium atrosepticum (Lojkowska and Kelman 1994;
Samson et al. 2005). Dickeya were initially establish in warm
tropical regions but in recent years, it occurs in temperate,
subtropical and tropical regions and attack various hosts. In
Europe, they caused severe damaged to potato (Czajkowski etal. 2011). The occurence of the species of Pectobacterium thatcause soft rots are vary depending on climatic conditions andgeographical location (McGuire and Kelman 1983; Peltzer andSivasithamparam 1985; Bain and Pérombelon 1988; Snijderand van Tuyl 2003). P. carotovora subspecies carotovora
occurs both in temperate and warm climates (Abo-Elyousr et
al. 2010) and P. atroseptica is restricted to temperate climatesregion (Perombelon 2000).
Dickeya are common in most soils and ground water as
epiphytes or as saprophytes until they encounter susceptible
plants. They are strong competitive bacteria that can inhibit
other microbes by mechanisms involving type V and type VI

secretion systems (Aoki et al. 2010; Koskiniemi et al. 2013).
Dickeya can also infect insects, which then act as
dissemination vectors (Grenier et al. 2006). Mild temperaturearound 30ºC with high humidity and less of oxygen conditionease the occurence of the disease (Lebeau et al. 2008)
The Dickeya species are dominant worldwide and haveability to infect maize, Chrysanthemum species, banana,
potato, Dianthus species and tomato. D. dadantii which
former name are Erwinia chrysanthemi biovar 3 (some strains)then change to Pectobacterium chrysanthemi biovar 3 (somestrains), able to infect wide range of plant species including
economically important crops such as Pelargonium,
pineapple, potato, Dianthus spp., Euphorbia, sweet potato,banana, maize, Philodendron and Saintpaulia (Samson et al.
2005)

VIRULENCE GENES OF D.dadantii
The virulence of D. dadantii is known with its ability tosynthesize and secrete pectinase (Pel) enzymes which act asplant cell wall degrading enzymes. Therefore, pel genes
encoding pectinases are the main virulence genes in D.
dadantii. (Collimer et al. 1986; Duprey et al. 2016).
Reverchon et al. (2016) reported that there are twenty-one
genes encoding pectinases in D. dadantii including nine endopectate lyases (PelA to E, PelI, PelL, PelN and PelZ), two exopectate lyases (PelX nad PelW), five polygalacturonases(PehV,
PehW,
PehX,
PehK
and
PehN),
onerhamnogalacturonate lyase RhiE, two pectin methylesterases(PemA, PemB), two pectin acetylesterases (PaeX, PaeY) andtwo feruloyl esterases (FaeD, FaeT).
The endopectate lyases of D. dadantii releaseoligogalacturonides as the product of pectinases activity withdifferent sizes. PelA, PelD and PelE are among the mostimportant Pels for virulence on Saintpaulia. Then, among thepel genes, pelD expression is most strongly affected by pectinderivatives, which makes it a key element in the induction of
D. dadantii virulence (Boccara et al. 1988; Hugouvieux et al.
1992).
However the contribution of each pel gene to virulence
depends on the host plants (Jiang et al. 2016). The synthesis ofpel genes depends on environmental or metabolic signals, suchas the presence of pectic compounds, oxidative and acidic
stresses (Jiang et al. 2016). Pectin contains a complex
structure of polysaccharide that is major component of cell
walls and intercellular tissues of all terestrial plants. Pectin
itself has three species which vary in the abundances andchemistries of their respective monosaccharides subunit i.e.
rhamnogalacturonan
I,rhamnogalacturonanIIandhomogalacturonan (Abbot 2008). It is assumed that themultiplicity of pectinases probably causing the evolutionary
adaptation of the bacteria to use various plant hosts.
Besides Pels, there are other genes in D. dadantii which are
identified encode enzymes as virulence factors in plant
pathogenesis. Fis is required for the efficient translocation of
the Pels in the growth medium and to preserve the moderately
supercoiled forms, protecting the DNA from shifts towards thestrongly relaxed or highly negatively supercoiled extremes ofProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P03
the topological spectrum (Dillon et al. 2010; Travers 2005).
Pir and Fur act to control induction by plant extracts and ironstarvation mediation (Franza et al. 1999). ExpR is a quorumsensing regulator that moderately participates in themodulation of pel genes expression in response to N-acylhomoserine lactones (Nasser et al. 1998). cAMP–CRP
complex genes as catabolic repression which acts as the main
activator of the pel gene expression (Nasser et al. 1997). PecS
may respond to phenolic compounds or reactive oxygen
species produced by the plant defence reactions (Reverchon etal. 1994). H-NS plays to respond the changes in environmental
conditions, and in particular to nutritional stress and variationin temperature (Nasser et al. 2001).
In the bacterial adaptation, there is a complex transcriptional
control system coordinating the expression of virulence genes
ensures efficient expression. Initially, the signals feed into thetranscriptional regulatory system of the bacterial cells, thencontinue to lead the physiological and morphologicalalterations which facilitate bacterial adaptation and affective
survival. There are some regulators potentially involved inbacterial survival under particular stress conditions. The
positive regulators (activator) are including cyclic AMP
receptor protein (CRP) (Tsuyumu 1979; Reverchon et al.
1997), plant inducible regulator (Pir) (Nomura et al. 1998),
ExpI-ExpR (Nasser et al. 1998), ExpM (Anderson 1999);
while KdgR (Nasser et al. 1992), PecS (Reverchon et al.
1994), RsmA (Cui et al. 1995), and Fur (Franza et al. 1999)
are reported to be negative regulators (repressor).
We are studying a gene which potentially plays a role as a
new transcriptional regulator involved in the expression ofvirulence factors and pathogenicity of D. dadantii in negative
manner called ltRWe will presemt preliminary results inrelation to analysis of this gene.

REFERENCES
Abbot, D. W., and Boraston, A.B., (2008). Structural Biologyof Pectin Degradation by Enterobacteriaceae. Microbiology
and Molecular Biology Reviews 72(2): 301-316.
Aoki, S.K., Diner, E.J., de Roodenbeke, C.T., Burgess, B.R.,
Poole, S.J., Braaten, B.A., Jones, A.M., Webb, J.S., Hayes,
C.S., Cotter, P.A., and Low, D.A. (2010). A Widespread
Family of Polymorphic Contact-Dependent Toxin Delivery
Systems in Bacteria. Nature 468(7322):439-442.
Bain, R.A., and Pérombelon, M.C.M. (1988). Methods ofTesting Potato Cultivars for Resistance to Soft Rot ofTubers Caused by Erwinia Carotovora Subsp. atroseptica.
Plant Pathology 37(3):431-437.
Barras, F., Van Gijsegem, F., and Chatterjee, A. K. (1994).
Extracellular Enzymes and Pathogenesis of Softrot Erwinia.
Annual Review of Phytopathology 32:201-234.
Boccara, M., Diolez, A., Rouve, M., and Kotoujansky, A.
(1988). The Role of the Individual Pectate Lyases of
Erwinia Chrysanthemi Strain 3937 in Pathogenicity on
Saintpaulia Plants. Physiological Molecular Plant Pathology
33:95-104.
Collmer, A., and Keen, N. T. (1986). The Role of Pectic
Enzymes in Plant Pathogenesis. Annual Review of
Phytopathology 24:383–409
Czajkowski, R., Pérombelon, M.C.M., van Veen, J.A., van derWolf, J.M. (2011). Control of Blackleg and Tuber Soft Rotof Potato Caused by Pectobacterium and Dickeya species: A
Review. Plant Pathology 60(6):999–1013.
Dillon, S.C., and Dorman, C.J. (2010). Bacterial NucleoidAssociated Proteins, Nucleoid Structure and Gene
Expression. Nature Reviews Microbiology 8:185–195

Duprey, A., Muskhelishvili, G., Reverchon, S., and Nasser, W.
(2016). Temporal Control of Dickeya dadantii Main
Virulence Gene Expression by Growth Phase-Dependent
Alteration of Regulatory Nucleoprotein Complexes.
Biochimia et Biophysica Acta 1859:1470-1480.
Grenier, A.M., Duport, G., Pages, S., Condemine, G., andRahbe, Y. (2006) The Phytopathogen Dickeya dadantii(Erwinia chrysanthemi 3937) is A Pathogen of the Pea
Aphid. Applied and Environmental Microbiology 72:1956–
1965.
Hajri, N.M., Malfatti, P., Pedron, J., Gaubert, S., Reverchon,S., and Gijsegem, F.V. (2011). Pecs is an Important Player
in the Regulatory Network Governing the CoordinatedExpression of Virulence Genes During the Interaction
Between Dickeya dadantii 3937 and Plants. Environmental
Microbiology 13(11): 2901-2914.
Hugouvieux-Cotte-Pattat, N., Dominguez, H., and RobertBaudouy, J. (1992). Environmental Conditions AffectTranscription of the Pectinase Genes of Erwinia
chrysanthemi 3937. Journal of Bacteriology 174:7807-7818.
Jiang, X., Zghidi-Abouzid, O., Oger-Desfeux, C., Hommais,F., Greliche, N., Muskhelishvili, G., Nasser, W., andReverchon, S. (2016). Global Transcriptional Response of
Dickeya dadantii to Environmental Stimuli Relevant to the
Plant Infection. Environmental Microbiology 00(00): 00–00.
Koskiniemi, S., Lomoureux, J.G., Nikolakais, K.C., T’Kint de
Roodenbeke,C., Kaplan, M.D., Low, D.A., and Hayes, C.S.
(2013). Rhs Protein From Diverse Bacteria Mediate
Intercellular Competition. Proceedings of the National
Academy of Sciences United States of America 110:7032–
7037.
Lebeau, A., Reverchon, S., Gaubert, S., Kraepiel, Y.,SimondCote, E., Nasser, W., and Van Gijsegem, F. (2008). The
GacA Global Regulator is Required for the Appropriate
Expression Oof Erwinia chrysanthemi 3937 Pathogenicity
Genes During Plant Infection. Environmental Microbiology
10:545–559.
Lelliott, R.A., and Dickey, R.S., (1984). Genus VII. Erwinia
Winslow, Broadhurst, Buchanan, Krumwiede, Rogers andSmith 1920, 209AL. In: Krieg NR, Holt JG, eds. Bergey’s
Manual of Systematic Bacteriology 1:469–76.
Mansfield, J., Genin, S., Magori, S., Citovsky, V.,
Sriariyanum, M., Ronald, P., Dow, M., Verdier, V., Beer,
S.V., Machado, M.A., Toth, I., Salmond, G., Foster, G.D.
(2012). Top 10 Plant Pathogenic Bacteria in Molecular Plant
Pathology. Molecular Plant Pathology 13(6):614-29.
Peltzer, S., and Sivasithamparam, K. (1985). Soft-rot Erwinias
and Stem Rots in Potatoes. Australian Journal of
Experimental Agriculture 25(3):693-696.
Reverchon, S., Muskhelishvili, G., and Nasser, W. (2016).
Virulence Program of a Bacterial Plant Pathogen: The
Dickeya Model. Progress in Molecular Biology andTranslational Science 142: 52-83.
Samson, R., Legendre JB, Christen R, Fischer-Le Saux M,
Achouak W, Gardan L (2005). Transfer of Pectobacterium
chrysanthemi (Burkholder et al., 1953) Brenner et al. (1973)
and Brenneria paradisiaca to the Genus Dickeya gen. nov.
as Dickeya chrysanthemi comb. nov. and Dickeya
paradisiaca comb. nov. and Delineation of Four Novel
Species, Dickeya dadantii sp. nov., Dickeya dianthicola sp.
nov., Dickeya dieffenbachiae sp. nov. and Dickeya zeae sp.
nov. International Journal of Systematic and Evolutionary
Microbiology 55(4):1415-1427.
Tsuyumu, S. (1979). “Self-catabolite repression” of pectate
lyase in Erwinia carotovora. Journal of Bacteriology
137:1035-1036

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P04

Augmentation of nuclease resistance and gene silencing by synthesizing
3’-end nucleoside base modified small interfering RNAs
Akash Chandela1 and Yoshihito Ueno1, 2
1.
2.

The United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan
Faculty of Applied Biological Sciences, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japanof 1.0 cm and a 3.0 mM duplex concentration. The sample
temperature was increased by 0.5˚C/min.
INTRODUCTION

RNA interference (RNAi) is a conserved self-defense
mechanism found in most eukaryotes where small doublestranded RNA (dsRNA) triggers a series of biochemical
events and results in sequence-specific suppression of gene
expression [1,2]. These small interfering RNAs (siRNAs) areshort (21-22 nucleotides in length), double-stranded regulatory
RNAs that contain two signature characteristics: a two
nucleotide 3’-end overhang and a phosphorylated 5’-end [3].
The functional strand, referred as guide strand, interacts
directly with the multi domain AGO proteins to form RNA
induced silencing complex (RISC). The RISC recognizes
messenger RNAs that contain sequences complementary to theguide strand and cleaves the mRNA. This eventually leads toinhibition of protein expression of the target mRNA.
AGO protein, a key molecule, has four domains: the Nterminal (N), Piwi/Argonaute/Zwille (PAZ), middle (MID),
and P-element-induced wimpy testis (PIWI) domains [6]. The
PAZ domain recognizes the 3’-end of guide strand whereas 5’end is recognized by MID domain. The PIWI domain
possesses endonuclease activity which helps in cleaving themRNA. The PAZ domain has also been reported to harbor the
nucleotides of the 3’-dangling end in its hydrophobic pocket[5], which forms basis of our research.
Previously reported problems encountered in this field are
nuclease degradation of siRNA, low cellular uptake andinefficient endosomal escape. On these lines, several groups
have performed various chemical modifications of siRNA toachieve long lasting effects and to prevent the degradation ofsiRNAs by RNases [7].

12Fig. 1. Structure of nucleoside analogs.

Partial digestion of ONs by SVPD
Each ON (600 pmol) labeled with fluorescein at the 5’-end
was incubated with SVPD (0.075 unit) in a buffer (150 μL)
comprising 0.1 M Tris-HCl (pH 8.0) and 20 mM MgCl2 at
37˚C. After 0, 1, 5, 10, 30, 60, 120, or 240 min, an aliquot(5 μL) of the reaction mixture was mixed with the loading
buffer (15 μL), comprising Tris-borate-EDTA (TBE) buffer
and formamide. Each sample was analyzed by 20% denaturing
PAGE at room temperature for 2 h at 20 mA. The gel was
visualized by use of a Luminescent Image analyzer LAS-4000(Fujifilm).
Dual-luciferase reporter assay
Twenty-four hours before transfection, cells (4 x 104/mL)
were transferred to a 96-well plate (100 µL/well). Cells ineach well were transfected with the indicated amounts ofsiRNA, and Lipofectamine RNAimax (1.5 µL) in Opti-MEM I
Reduced-Serum Medium (Invitrogen), and incubated at 37˚C.
Transfection without siRNA was used as a control. After 1 h,
MEM (100 µL) containing 10% BS was added to each well,and the whole was incubated at 37˚C. After 24 h, solution ineach well was removed and the plate was incubated at -80˚C.
After more than 4 h, activity of firefly and Renilla luciferases
in cell were determined with a dual-luciferase assay system(Promega) according to a manufacturer's protocol. The results
were confirmed by at least three independent transfection
experiments.

RESULTS
Synthesis
The synthetic route used to synthesize phosphoramidites 1617 of analogs 1-2 is shown in Scheme 1. Glycosylation of
trifluoroethanol (4) with 1-O-acetyl-2,3,5-tri-O-benzoyl-β-Dribofuranose (3) , was done to form the β-anomer 6.

Based upon this background information and earlier work
done by our group [4], our current work is focused upon
nucleoside base modifications at the 3’-overhang of siRNA toenhance nuclease resistance and gene silencing activity. So, in
this study we have substituted the base with trifluoroethyl andtrichloroethyl analogues respectively (Fig.1). The purpose is toutilize the interaction of the bases with the hydrophobic pocketof PAZ domain. Subsequently, the effect of thesemodifications on the nuclease resistance and gene silencing
has been monitored.

METHODS
Thermal denaturation study
The thermally induced transition of each mixture wasmonitored at 260 nm on UV-Vis spectrophotometer fitted witha temperature controller in quartz cuvettes with a path length

Scheme 1. Reaction scheme for phosphoramidite

Compound 6 was debenzoylated in the presence of a catalytic
amount of NaOCH3 in CH3OH, and subsequently, the primaryhydroxy group of 1 was protected by 4,4’-dimethoxytrityl(DMTr) group to produce the 5-O-DMTr derivative 10.
Silylation was performed with TBDMSCl to produce the 3-OTBDMS and 2-O-TBDMS derivatives 12 and 13 respectively.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P04
Compound 13 was phosphitylated by the standard method toyield corresponding phosphoramidite 16.
Solid support synthesis was performed by converting
derivative 12 to corresponding succinate, which was linked tocontrolled pore glass (CPG) to generate 18 as shown in
Scheme 2. In the similar manner, phosphoramidite and solid
support were also synthesized for trichloroethyl derivative (2).
Solid support based oligonucleotide (ON) synthesis was
performed with DNA/RNA synthesizer.

observations is that the sense strand modified withtrichloroethyl analogue also exhibited equivalent activity likethe native.

Fig. 3. Luciferase activity ratios for gene silencing activity ofsiRNAs (Concentration in nM)

Scheme 2. Reaction scheme for solid support

Synthesis and Thermal stability of siRNAs
Oligonucleotides
weresynthesizedbystandard
phospharamidite method. siRNAs 1-7 were prepared with thesynthesized ONs to produce modification in duplex, sense orantisense strand respectively. Analogues 1 and 2 slightly
decreased the thermal stability. Melting temperature (Tm) andchange in melting temperature with respect to native (ΔTm)
has been indicated in Table 1.

DISCUSSION
With the goal to synthesize nuclease resistant siRNAs withelevated silencing activity, modifications were performed atthe 3’-end to exploit the interaction with the PAZ domain of
AGO protein. Also, the thermal stability of these ONs wasfound to be in close agreement with the native but higher
nuclease resistance than latter. The silencing activity using
luciferase reporter assay revealed comparable results to thenative with duplex and sense strand modification. Whereas,
the guide strand modified siRNAs showed lower activity,
which could be due to the formation of hydrogen bonds withresidues at PAZ domain. Hence, we could design these novel
siRNAs with enhanced resistance and silencing activity.
Further studies will provide more fruitful solutions in thisdirection.

REFERENCES
1.
Table 1. Sequences of siRNAs and their Tm values

Nuclease resistanceIn order to estimate the nuclease resistivity, the modified
oligonucleotides were treated with exonuclease. The
trifluoroethyl analogue exhibited higher resistance incomparison to the trichloroethyl analog and the native.

2.

3.

4.

5.

6.
7.
Fig. 2. 20% PAGE of ONs hydrolyzed by SVPD.
(F denotes a Fluorescin)

Silencing activities of siRNAs
The duplex modification yielded silencing activity
comparable to the native whereas modification only in theguide strand showed lower activity. This kind of phenomenon
could be attributed to hydrogen bonding of the base withresidues in hydrophobic pocket of PAZ. One important

Elbashir, S. M. et al. Duplexes of 21 ± nucleotide RNAs
mediate RNA interference in cultured mammalian cells.
Nature 411, 494–498 (2001).
Fire, A. et al. Potent and specific genetic interference by
double-stranded RNA in Caenorhabditis elegans. Nature
391, 806–811 (1998).
Frank, F., Sonenberg, N. & Nagar, B. Structural basis for
5’-nucleotide base-specific recognition of guide NA byhuman AGO2. Nature 465, 818–822 (2010).
Inada, N., Nakamoto, K., Yokogawa, T. & Ueno, Y.
Synthesis of small interfering RNAs containing acetaltype nucleoside analogs at their 3'-ends and analysis of
their silencing activity and their ability to bind to the
Argonaute2 PAZ domain. Eur. J. Med. Chem. 103, 460–
472 (2015).
Lingel, A., Simon, B., Izaurralde, E. & Sattler, M.
Structure and nucleic-acid binding of the Drosophila
Argonaute 2 PAZ domain. Nature 426, 465–9 (2003).
MacRae, N. T. S. and I. J. The Crystal Structure of Human
Argonaute2. 336, 1037–1040 (2013).
Manoharan, M. RNA interference and chemicallymodified small interfering RNAs. Curr. Opin. Chem. Biol.
8, 570–579 (2004).

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P05

Maintenance of oligosaccharides content during soybean sprout cultivationby controlling temperature conditions
Daimon Syukri1, Manasikan Thammawong2 and Kohei Nakano1
1. The United Graduate School of Agricultural Science, Gifu University
2. Faculty of Applied Biological Science, Gifu University

Soybean sprout is one of soy-based food that produced bycultivation process from soybean. Cultivation process canenhance the nutritional value of soybean seed. Soybean
sprouts known as the healthy vegetable due to its highnutritional compounds such as isoflavones, amino acids,
vitamin and soya saponin (Kim et al, 2013). Unfortunately,
during soybean sprouts cultivation process, there is a reductionof another nutritional compound that cannot be avoiding i.e.
oligosaccharides
degradation.
The
degradationofoligosaccharides hypothesized to provide energy source forsprouts
growthbycellular
respiration
process.
Oligosaccharides are degraded during germination process ofsoybean seeds and disappear when sprouts are formed.
Growing process is influenced by various environmental
factors such as temperature, light and salinity. Particularly,
temperature is a major limiting factor (Huang et al. 2003; Tlig
et al. 2008). Moreover, Dahal et al. (1995) mentioned that
cellular respiration is sensitive with temperature and has
proportional correlation with growing speed. However, there
is little information on relationship between cultivation
temperatures and the behavior of oligosaccharides degradation
in soybean sprout.
Therefore, in this study, we investigated theoligosaccharides degradation of soybean sprout during
cultivation under different temperatures for discussing how to
produce soybean sprouts with high amount ofoligosaccharides. The results can guide the manufacturer toproduce soybean sprout with high amount of nutritional
compounds including oligosaccharides.

mobile phase was 0.8 mL/min. The charged aerosol detector
was used for oligosaccharides detection.
RESULTS
Figure 1 indicates the germination period of soybean sprout
under various temperature conditions. The germination andgrowth of soybean sprouts occurred in all temperature
conditions tested. The germination period that the soybean
sprouts reached 2 cm, 5 cm and 10 cm in radicle lenght weredifferent for each cultivation conditions. The cultivation
condition at 20 °C, 25 °C and 30 °C show similar growthtendency, however, the condition at 15 °C and 10 °C, thegrowth tendency become very slow. The germination period
three times and six times longer than 30 °C as the highest
temperature tested, respectively.

108
Leght (cm)INTRODUCTION

10°C
15°C
20°C
25°C
30°C

6
4
2
0
0

.
MATERIALS AND METHODS
Materials
Soybean seeds ‘cv. BS501’ were used in this study as
sample material. A 10 g soybean seeds was dipped into 70 °C
of water for 10 s to sterilize. Then the seeds were soaked to
30 °C of water and left for 8 h in order to stimulate thegermination. After soaking, the seeds were separated andmoved to each germination chamber at 10°C, 15 °C ,20 °C ,25 °C and 30 °C with 70-80 % RH. The seeds were wateredby 100 mL of water, twice a day (10 am and 4 pm).
Germinated sprouts were sampled daily until 5 days ofgermination and devided into 2 groups; cotyledon andhypocotyl.

The measurement of oligosaccharides
The oligosaccharides in the lyophilized soybean sprout
samples were extracted by 70% (v/v) of ethanol and analyzed
using a HPLC system. A 10 µL sample was loaded onto anamino bond column (Shodex, Asahipak NH2P-50 4E, 250 x
4,6 mm id.,5 µm) through an auto-sampler. The mobile phasewere water (solution A) and acetonitrile (solution B). The
programmed elution was performed in linear gradient of A
againts B from 35:65 to 70:30 in 20 min. The flow rate of

200
400
Germination period (h)600Fig. 1: The changes of sprouts radicle length during
cultivation under various temperature conditions
Figure 2 indicates the changes of oligosaccharides during
soybean sprouts cultivation at various radicle length undervarious cultivation temperature conditions. In soybean seed,
the oligosaccharides represent as raffinose and stachyose withconcentration approximately 4 mg·g-1 and 16 mg·g-1,
respectively. The levels of these oligosaccharides in cotyledon
were decreased during cultivation process of soybean sprouts
until 10 cm of radicle length. While in hypocotyl, there is no
oligosaccharides were detected. At early cultivation period, toreach 2 cm of radicle length the degradation ofoligosaccharides both raffinose and raffinose was different
among cultivation temperature tested. The cultivation
condition at 30 °C degraded the lowest amount ofoligosaccharides compare to other conditions. However at 5
cm and 10 cm of radicle length the amount of remained
oligosaccharides were similar for each temperature condition
tested.
Figure 3 indicates the remained oligosaccharides inharvested soybean sprouts with 10 cm in length of radicle.
Cultivation condition at 30 ºC induced the highest amount ofProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P05
oligosaccharides during cultivation process followed by 10 ºC,
25 ºC and 15 ºC. Cultivation condition at 20 ºC could maintainthe oligosaccharides content in harvested soybean sprouts in
the highest amount compare to other conditions.

Raffinose (mg·g-1 )

5
4

10°C
15°C
20°C
25°C
30°C

3
2
1
0
0

2

4
6
Length (cm)

8

10

0

2

4
6
Length (cm)810Stachyose( mg·g-1 )

20
16
12
8
4
0

Fig. 2: The changes oligosaccharrides level in soybean
sprout parts during cultivation under various
temperature conditions

Oligosaccharides (mg·g-1 )

1.6
1.2
0.8
0.4
0
10
15
20
25
30
Germination condition (°C)

Fig. 3: The comparison of oligosaccharides in
cotyledon part of soybean sprouts under various
cultivation temperature conditions (10 cm hypocotyl
length).

DISCUSSION
According to Botha et al (1992), sprouts cultivation process
began with an increasing of metabolic activity which indicatedby high O2 uptake and CO2 release during cellular respiration
process. Our results indicated that temperature affected to themetabolic activity of soybean sprouts germination process.
The increasing of temperature condition might induce themetabolic activity for accelerating in development of the newtissue, therefore at high temperature condition the cultivation
period become shorter than low temperature condition. During
cultivation process, oligosaccharides were used as sugar
source to support the respiration process (Pazur et al. 1962;
Labaneiah and Luh., 1981). Oligosaccharides degradation
caused by the α-galactosidase activity. To reach 2 cm inradicle length of soybean sprouts at early time of cultivation
process under various cultivation temperature conditions, thedifferent tendency of oligosaccharides degradation wasobserved. Low oligosaccharides degradation at hightemperature condition probably due to short cultivation timecompare to the lower condition. However, at 5 cm of sprouts
radicle in length, the requirement of oligosaccharides forsupporting the respiration process might be need in samevalue. It suggested there is a different requirement ofoligosaccharides at early time of soybean sprouts cultivation
process and the subsequent process. Finally, at harvested
soybean sprouts, the differences of remained oligosaccharides
has related to its degradation process during cultivation.
Therefore, the clarification of behavior of oligosaccharides
during soybean sprouts cultivation process must be conductedfurther.
ACKNOWLEDGEMENT
Soybean seeds sample was kindly provided by Salada
Cosmo Inc, Japan.
REFERENCES
Kim, S., J. Lee, Y. Kwon., W. Kim., G. Jung., D. Kim., C.
Lee., Y. Lee, M. Kim., Y. Kim., T. Hwang, and I. Chung.
2013. Introduction and nutritional evaluation of germinatedsoy germ. Food Chem. 136:491-500.
Huang, Y., X. Zhang., G. Zheng, and Y. Gutterman. 2003.
Influence of light, temperature, salinity and storage on seedgermination of Haloxylon ammodendron. J. Arid Environ.
55:453-464.
Tlig, T., M. Gorai, and M. Neffati. 2008. Germination
responses of diplotaxis harra to temperature and salinity.
Flora. 203. 421-428.
Dahal, P., N. S. Kim, and K. J. Bradford. 1996. Respirationand germination rates of tomato seed at suboptimal
temperatures and reduced water potential. J. Exp. Bot. 47:
941-947.
Botha, F.C., Potgieter, G.P., Botha, A.M. 1992. Respiratory
metabolism and gene expression during seed germination.
Plant Growth Regul. 11, 211–224.
Pazur, P.H., Shadaksharaswamy, M., and Meidell, G.E. (1962)
The metabolism of oligoshaccarides in germinating soybean,
Glycine Max. Archive of Biochemistry and Biophysic 99:
78-85.
Labaneiah, M.E.O. and Luh, B.S. (1981) Changes of starch,
crude fiber, and oligosaccahrides in germinating dry beans.
Cereal Chems 58(2): 135-138.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P06

Effect of temperature on flavonoid metabolism in citrus juice sacs
in vitro
Witchulada Yungyuen1,2, Gang Ma1, Lancui Zhang1, Kazuki Yamawaki1, Masaki Yahata1, Satoshi Ohta3, Terutaka Yoshioka3
and Masaya Kato1*
1.

Department of Biological and Environmental Sciences, Faculty of Agriculture, Shizuoka University, 836 Ohya, Suruga,
Shizuoka 422-8529, Japan
2. The United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
3. Department of Citrus Research, NARO Institute of Fruit Tree Science, Okitsunakacho, Shimizu, Shizuoka 424-0292,
Japan
Flavonoid determination—Flavonoid content wasmeasure by HPLC in three replications for each sample. 20 µL
INTRODUCTION
of aliquot was injected to HPLC system (Jasco) with YMCUltraHT Pro C18 column. The eluent was monitored by
Flavonoids are a large family of low molecular weight
UV/VIS detector (MD-2010/2015).
polyphenolic compounds that are widespread throughout plant
kingdom. The consumption of flavonoids provides a number
RNA extraction and real-time quantitative RT-PCR—of benefits to human health. One of the most beneficial effects
Total RNA was extracted in accordance with the methodof flavonoids is their antioxidant activity, which is reported todescribed by Ikoma et al. (1996). Total RNA was purified by
reduce the risk of atherosclerosis diseases and some cancers
RNeasy Mini Kit (Qiagen, Hilden, Germany). Real-time(Keys, 1995). Flavonoids are divided into six classes;
quantitative RT-PCR was performed in three replications forflavones, flavanones, flavonols, isoflavones, anthocyanidins,each sample. TaqMan MGB probes and set of primers forand flavanols. Citrus fruits accumulated a large amount offlavonoid biosynthetic genes (CitCHS1, CitCHS2, CitCHI,
flavonoids. Four types of flavonoids are observed in citrus
and CitFNS) were used for real-time quantitative RT-PCR.
fruits; flavanones, flavones, flavonols and anthocyanins, andflavanones are mainly existed among citrus species (Nogata et
RESULTS AND DISCUSSION
al. 2006).
Temperature had a strong influence on the accumulation
The effect of environmental factors on flavonoidof flavonoid in various plants. Low temperature did not only
accumulation has been received much attention for a longpromote plant growth and development, it also increased thetime. The sensitivity to temperature changes of flavonoid was
accumulation of chemical compositions including flavonoid
observed in several fruits and flowers (Jaakola and Hohtola,(Koshita 2015). In apple and grape, the level of anthocyanin
2010). However, a little is known about the effect ofcontent was higher at low growing temperature than hightemperature on flavonoid metabolism in citrus. In the present
growing temperature (Bakhshi and Arakawa 2006; Yamane etstudy, the results were corresponded with the previous studies
al. 2006).
in other plants that low temperature increased the level of
In citrus fruits, the regulatory mechanism of flavonoid
flavonoid content. In citrus, the accumulation of flavonoid
biosynthesis in response to temperatures has not been clearly
was induced at 10°C, but it was not affected at 30°C in theunderstood. The studies designed to evaluate the effect ofjuice sacs of three citrus varieties. The previous study oftemperature on metabolic reaction in citrus fruits during
Yamada et al. (1988) revealed that 10°C was an optimal
ripening are limited due to the difficulty in controlling field
temperature for flavonoid accumulation.
temperature. Therefore, in vitro culture system was used in the
The gene expression results found that at 10°C, thepresent study to control undesirable factors throughout theenhancement of flavonoid accumulation was correlated withexperimental period. Flavonoid content and their biosynthetic
the expression of flavonoid biosynthetic genes in the three
genes were investigated in juice sacs of Satsuma mandarin,
citrus varieties. In Satsuma mandarin, the expression of
Lisbon lemon, and Valencia orange, which showed a different
CitCHS1, CitCHS2, CitCHI, and CitFNS genes was
flavonoid accumulation profiles using in vitro culture system.
significantly higher at 10°C. In Lisbon lemon, the expression
The objective of this study was to evaluate the regulatoryof CitCHS2, CitCHI, and CitFNS genes was also significantly
mechanism of flavonoid biosynthesis in response to different
higher at 10°C. In Valencia orange, only the expression oftemperatures in citrus juice sac in vitro.
CitCHS1 and CitCHI genes was slightly higher at 10°C. The
former study reported that the modification of structural genes
MATERIALS AND METHODS
in flavonoid biosynthetic pathway could enhanced flavonoid
content (Schijlen et al. 2004). By this way, the flux throughIn vitro culture system and treatments—Three varieties
the biosynthetic pathway was induced, which led to increaseof fruits were cultured in vitro in accordance with the method
the level of specific flavonoid or even total flavonoid content.
described by Zhang et al. (2012). The juice sacs were cultured
From the present results, it might be suggested that thefor two weeks under the same condition at 20°C, and theninduction of flavonoid accumulation at 10°C in citrus juice
were cultured under different temperatures at 10, 20, and 30°C
sacs was regulated at transcriptional level.
for another two weeks. The temperature treatment at 20°C
To conclude, temperature treatment at 10°C induced
throughout the experimental period was used as the control.
flavonoid accumulation in the three varieties of citrus juice
Then, the juice sacs were harvested and immediately frozen insacs. The higher expression of flavonoid biosynthetic genes
liquid nitrogen and kept at -80°C until used.
was responsible for the higher level of flavonoid content at

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P06
10°C. The understanding in flavonoid regulation in response
to different temperatures during the fruit ripening process will
be helpful for enhancing flavonoid content and make anapproach to molecular breeding of flavonoid biosynthetic
pathway in citrus fruits in future research.
aTotal flavonoids(mg g-1 DW)bc

Temperatures
Fig. 1: Flavonoid accumulation in juice sacs of Satsuma
Mandarin (a), Lisbon lemon (b), and Valencia orange (c)at different temperatures in vitro. The results shown are
the mean ±SE for triplicate samples. Means denoted by
the same letter was not significant different at P ˂ 0.05
according to Tukey’s HSD test.

REFERENCES
Keys, A. (1995) Mediterranean diet and public health:
Personal reflections. American Journal of ClinicalNutrition 61:1321–1323.
Nogata, Y., Sakamoto, K., Shiratsuchi, H., Ishii, T., Yano, M.,
and Ohta, H. (2006) Flavonoid Composition of Fruit
Tissues of Citrus Species.Bioscience, Biotechnology,
and Biochemistry 70 (1): 178-192.
Koshita, Y. (2015) Effect of Temperature on Fruit Color
Development. In Abiotic, Stress Biology in
Horticultural Plants, edition no.;Yoshinori, K., Alexey,
K., Eds.; Publisher: Springer, Japan, p 47-58.
Bakhshi, D., and Arakawa, O. (2006) Induction of phenolic
compounds biosynthesis with light irradiation in the fleshof red and yellow apples. Journal of Applied Horticulture
8:101–104.
Yamane, Y., Jeong, S.T., Goto-Yamamoto, N., Koshita, Y.,
and Kobayashi, S. (2006) Effects of temperature on
anthocyanin biosynthesis in grape berry skins. American
Journal of Enology and Viticulture 57:54–59.
Zhang, L., Ma, G., Kato, M., Yamawaki, K., Takagi, T.,
Kiriiwa, Y., Ikoma, Y., Matsumoto, H., Yoshioka, T., andNesumi, H. (2012) Regulation of carotenoid accumulationand the expression of carotenoid metabolic genes in citrus
juice sacs in vitro. Journal of Experimental Botany
63:871-886.
Ikoma, Y., Yano, M., Ogawa, K., Yoshioka, T., Xu, Z.C.,
Hisada, S., Omura, M. and Moriguchi, T. (1996) Isolationand evaluation of RNA from polysaccharide-rich tissues infruit for quality by cDNA library construction and RTPCR. Journal of the Japanese Society for Horticultural
Sciences 64:809-814.
Jaakola, L., and Hohtola, A. (2010) Effect of latitude on
flavonoid biosynthesis in plants. Plants, Cell andEnvironment 33:1239-1247.
Yamada, H., Hamamoto, K., Sugiura, A., and Tomana, T.
(1988) Effect of controlled fruit temperature on maturationof apple fruits. Journal of Japan Society of Horticultural
Science 57:173–177.
Schijlen, E., Ric de Vos, C.H., Tunen, A., and Bovy, A.
(2004) Modification of flavonoid biosynthesis in crop
plants. Phytochemistry 65:2631-2648.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P07

Bioconversion of AHX to AOH by Buttiauxella gaviniae A111
Panyapon Pumkaeo, Ayaka Kikuchi and Shinji Tokuyama
Department of Applied Biological Chemistry, Graduated School of Integrated Science and Technology, Shizuoka University,
Shizuoka

INTRODUCTIONRESULTS

A compound that stimulates the growth of bentgrass, 2azahypoxanthine (AHX), was isolated from a mushroom,
Lepista soldida. AHX is metabolized to 2-oxohypoxanthine(AOH) in rice. (Fig.1) Both compounds show plant growthpromoting activity and are present in rice at levels similar to
those of plant hormones. AOH also imparts drought stress
tolerance and cold stress tolerance to Arabidopsis thaliana.
AOH has been synthesized from AHX by enzymatic
method because it is difficult to synthesize AOH by achemical method. At first, AOH was synthesized by xanthineoxidase (XOD) from buttermilk. The commercially available
XOD is not suitable for large-scale preparation of AOH
because the enzyme is very expensive and the concentration ofsubstrate, AOH is very low (70 mg/L). In the previous study,
we found that Burkholderia contaminas CH-1 converted from
AHX to AOH at 2 g/L but this strain was not enough toprepare AOH in a large scale.
In this study, to develop effective bioconversion method of
AHX to AOH in a large scale, we screened for
microorganisms that show higher conversion activity andshowed properties of the conversion enzyme.

Four strains (A13, A82, A111 and A112) isolated from soil
showed high AOH conversion activity at 2 g/L of AHX in
resting cell reaction for 4 hours (Fig.2). Among these strains,
strain A111 was selected as a strain showing the highest AOH
conversion activity. Although strain CH-1 converts 2 g/L of
AHX to AOH for 24 hours, strain A111 completely converts
AHX to AOH at 2 g/L within 4 hours. Strain A111 canconverts 5 g/L of AHX to AOH by the resting cell reaction
within 24 hours in 10 litter jar fermenter. The yield of thisreaction is 92.8%. (Fig.3) Conversion activity of strain A111
is 8-10 times higher than B. contaminas CH-1. Strain A111 ispresumed as Buttiauxella gaviniae by 16S rDNA analysis.
Most of the xanthine-oxidizing enzymes from microorganisms
are xanthine dehydrogenases. AOH conversion enzyme from
B. gaviniae A111 shows a xanthine oxidase activity.
80
Conversion rate ( % )

70
60
50
40
30
20
10
0
CH-1

A13

AOH

Fig1. Fairy chemicals
MATERIALS AND METHODS
The soil sample were isolate at 30 ºC. The isolate was
growth in TSB incubate at 30 ºC, 150 rpm for 16 hr. The
conversion of AHX to AOH by resting cells were carried out
in PBS (pH 7.4) at 30 ºC in various conditions. AHX andAOH were analyzed by HPLC (Develosil C30-UG-5 column,
0.02% TFA, 30ºC, 254 nm.)For cell extraction, the strain was grown in TSB medium.
The cultures, which were incubated on an orbital shaker (130rpm) at 30°C. Biomass was harvested after about 16 h ofcultivation by centrifugation at 10000 rpm for 10 min. The cellwere suspended in 50 mM phosphate buffer pH 7.0. The cells
were disrupted with sonication using a Kubota Insonator 201
M
For XOD and XDH assay. Mix sample or enzyme solution
the substrate (xanthine, 50 μM final concentration), andphosphate buffer (pH 7.0, 50 mM), total volume 1.0-3.0 mL,
in a cuvette. Record the time-dependent increase in theabsorbance at 290 nm during incubation of the reaction (10min) mixture at 30°C. Determine XHD activity in a sample byadding NAD+ (1mM final concentration) to the reaction
mixture. One unit of XOD/XDH activity is defined as thevelocity of the formation of 1µmol uric acid per minutes.

A82

A111
A111

A112

StrainsFig2.Conversion of AOH by isolated bacteria. The
concentration of AHX was 2 mg/ml. The strains were
inoculated for 8 hrs. Culture volume: ×1. Resting cells wereincubated at 30℃ and 90 spm for 2 hrs.

120
AOH conversion rate (%)

AHX

100
80
60
40
20
0
0

10

20
Time ( hrs )Fig3. Conversion of AHX to AOH by strain A111.
Reaction: 6 L

30

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P07

DISCUSSIONACKNOWLEDGMENTS

For AOH preparation the resting cell of A111 showed highability than milk xanthine oixdas and resting cell of strain CH1. Buttiauxella gaviniae A111 shows the conversion activity
which 8 times higher than Burkholderia contaminans CH-1.
To investigate whether the enzyme that produced AOH from
AHX in the crude extract of A111 was XOD/XDH or not. The
crude extract from strain A111 were measure the XOD/XDH
activity. The XOD/XDH was found in crude extract of
A111.The structure of AHX was analogous of hypoxanthine.
Previous study was investigated the plants produced
AHX/AOH though a pathway similar to the chemical
synthesis of novel purine metabolism. (Fig.4) It’s possible thatthe conversion enzyme maybe XOD/XDH.

I would like to express sincere thanks to Japanese Government(MEXT) Scholarship for chance and financial support
throughout the course of Master degree study.

Xanthine dehydrogenase
H O + NAD+2

Hypoxanthine

H O+O
2

2

NADH

HO
2

2

H O + NAD+

NADH

2

Xanthine

H O+O
2

2

HO
2

2

Uric acid

Xanthine oxidase
Fig 4. The metabolic pathways catalyzed by XOD/XDHREFERENCES
Choi J-H, Kikuchi K, Pumkaeo P, Hirai H, Tokuyama S &Kawagishi H.(2016) Bioconversion of AHX to AOH byresting cells of Burkholderia contaminans CH-1.Bioscience,
Biotechnology, and Biochemistry.10:2045-2050
Hettrich, D., Lingens, F. (1991) VIII. Xanthine dehydrogenasefrom a quinolone utilizing Pseudomonas putida Strain.
Biol.Chem.Hoppe-Seyler 2: 203-211

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P08

The characteristics of screened particle with different pulverization process
and drying condition
Arif Delviawan1, Shigehiko Suzuki2, Yoichi Kojima2 and Hikaru Kobori2
1. Department of Agriculture, Graduate School of Integrated Science and Technology, Shizuoka University
2. Faculty of Agriculture, Shizuoka University, JapanINTRODUCTION
Wood has been widely used in human daylife, for example
as building materials, furniture, paper, tools, fuel resources,
and more. However increasing deforestation becomes theimportant issue which causes the limited fulfillment of wood
raw materials. Global ecological concern has resulted inrenewed interest in natural materials. Natural organic fibers
from renewable natural resources offer the potential to act as abiodegradable reinforcing material alternative. Wood plastic
composite (WPC) has the advantages, such as easy tomaintain, high durability or longtime service life, as thesustainable product caused can make from recycled materials,
and we can put several additives (anti-UV, anti-oxidant, etc.)
to improve the properties.
Wood flour, particles or fibers are combined with thethermoplastic materials on specific heating and pressure to
produce WPC. The main applications of the WPC are interior
and exterior building products, such as poolside, slate, floor,
decking, door, window profiles, balconies and decorative
trims.
Many researchers investigated the factors that can affect thephysical and mechanical properties of the WPC. English andFalk has invetstigated those factors in 2008. Bledzki et al.
(1998) and Nourbakhsh et al. (2010) investigated that themechanical and physical properties of the WPC could be
improved by selecting proper coupling agents. Maldas et al.
(1989) investigated the influence of wood species on theproperties of WPC. Stark and Rowlands (2003); Zimmermann
et al. (2014) and Bouafif et al. (2008) investigated the effectsof particle size and fiber characteristics on the mechanical andphysical properties. These results suggest that thecharacteristics of wood flour as a raw material are important in
the manufacture of WPC. The quality and functionality of
WPC products should be improved in order to meet the publicdemand that increased continuously.
As we know that the different time of ball milling process
influences the size of wood flour. However, there is noquantitative investigation about the relationship between ball
milling time and particle size distribution. The aim of thisstudy is to investigate the characteristics of screened woodflour as the materials to make the WPC, with different
conditions of the drying process and different time ofpulverization process.

MATERIALS AND METHODS
Wood flour of Pinus densiflora was produced by rotor mill
(Pulverisette 14, Fritsch, Germany) with 20,000 rpm. Then
13.5 g of wood flour was milled with 200 ml of water by a ballmill (Pulverisette 5, Fritsch, Germany). The speed 200 rpm
was applied and the wet milling times were 0, 10, 20, 30, 40,
60, and 120 minutes.
Two kinds of drying conditions were applied. Seven days offreeze drying by a freeze dryer (FDU-1200, Eyela, Japan) and24 hours of heat drying by an oven dryer (SOFW-450S, Ettas,

Japan) at a temperature of 80 °C. After drying, wood flour was
fibrillated for 1 minute by a blender (IFM-800DG, Iwatani,
Japan). Vibrational acceleration ± 20 G was applied for 30
minutes by a compact vibrating shaker (VSS-50D, Tsutsui,Japan) to separate the wood flour by their particle size asfollows; >425 µm, 180-425 µm, 90-180 µm, 53-90 µm, 32-53µm, and <32 µm.
The particle analysis and micro structure of wood flour
were investigated through scanning electron microscope(JSM-6510LV, JEOL, Japan) test. Particle size distribution ofwood flour for before drying and after fibrillation was
analysed by a laser diffraction particle analyzer (LA-950S2,
Horiba, Japan).

RESULTS
Figure 1 shows the amount of dried wood flour after
screening process obtained with freezed drying condition.
The highest amount for 0 minutes wet milling time is thelargest size of the particle (more than 180 µm). It decreased
with increasing the time of wet milling time. However theamount of wood flour increased for 180 to 425 µm rapidly
from 30 minutes to 40 minutes wet milling time. The smaller
particle (90-180 µm, 53-90 µm, 32-53 µm, and <32 µm) wereincreased with increasing the wet milling time until 30
minutes. From that time the amount of wood flour decreased
until 60 minutes, and increased again from 60 minutes to 120
minutes wet milling time.

Fig. 1: The amount of dried wood flour obtained withfreezed drying condition. The time (minutes) of wet millingis on the X-axis, and the amount by weighing in unit gramper 8 pots is on the Y-axis.
Figure 2 shows the particle size distribution of wood flour
after ball milling process. The highest intensity for the largest
particle size was observed for 0 minutes wet milling time. At
that condition, the avarage of particle size was about 809 µm.
As the increasing time of pulverization proccess, particle size
decreased. However, from 60 minutes to 120 minutes wet
milling time the avarage particle size was increased from 124µm to 258 µm.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P08
time of ball milling process is too long (longer than 40
minutes), it can increase the aggregated large of wood flour.
Both SEM images and particle analysis clearly show theexcess time of ball milling will cause the aggregation of woodflour. Concerning the amount of wood flour in this study,
most of all condition increases after 30 minutes of wet milling
time. The increasing of the average particle size of wood flour
after pulverization process was found in the condition from 60
to 120 minutes, and in the case of fibrillation process particle
size increases from 40 to 60 minutes wet milling. This result
indicates that the optimum time for ball milling process is lessthan 30 minutes, because an aggregation of wood flour will
occur longer than that.
Fig. 2: The particle analysis after pulverization by a ballmill. The particle size of wood flour in µm is on the X-axis,
and the intensity of particle size (%) is on the Y-axis.
Figure 3 shows the particle distribution after the fibrillation
process. As the increasing of wet milling time, particle size
decreased. The highest intensity of particle was in unmilledwood flour (0 minutes wet milling time) with the average
about 632 µm. However, the average particle size wasincreased from 197 µm to 299 µm at 40 until 60 minutes wet
milling time, and decrease again when the time was 120
minutes.

Fig. 3: The particle analysis after fibrillation process.
The particle size of wood flour in µm is on the X-axis, andthe intensity of particle size (%) is on the Y-axis.
SEM images of wood flour for different pulverization time
were shown in Fig. 4. As can be seen in Fig. 4 (A), there wasan intact single particle. However in Fig. 4 (B), there wasfibrillated particle and also there was aggregated particle.
A

B

Fig. 4: The SEM image of heat drying wood flour with
100 times magnification and >425 µm by size. A) 0 minutes
wet milling time conditions; B) 60 minutes wet milling time
conditions;DISCUSSION
Increasing the time of pulverization decreases the particle
size and will produce the smaller wood flour. However if the

ACKNOWLEDGMENTS
The authors are grateful to the Toclas corp. for supportingand providing the materials for this research.

REFERENCES
Bledzki, A. K., Reihmane, S., Gassan, J. (1998)
Thermoplastics Reinforced with Wood Fillers: a Literature
Review. Polym Plast Technol Eng; 37(4):451–68.
Bouafif, H., Koubaa, A., Perre, P., Cloutier, A. (2008) Effectsof Fibre Characteristics on The Physical and Mechanical
Properties of Wood Plastic Composites. The 9thInternational Conference on Flow Processes in Composite
Materials, Canada.
English, B. W., Falk, R. H. (1995) Factors that Affect the
Application of Woodﬁber–Plastic Composites. In:
Proceedings of the Woodﬁber–plastic Composites
Conference, Madison, Wisconsin; 183.
Maldas, D., Kokta, B. V., Daneault, C. (1989) Thermoplastic
Composites of Polystyrene: Effect of Different Wood
Species on Mechanical Properties. J Appl Polym Sci;
38(3):413–39.
Nourbakhsh, A., Karegarfard, A., Ashori, A., Nourbakhsh, A.
(2010) Effects of Particle Size and Coupling Agent
Concentration on Mechanical Properties of ParticulateFilled Polymer Composites. J Thermoplastic Composite
Materials; 23:169.
Stark, N. M., Rowlands, R. E. (2003) Effects of Wood Fiber
Characteristicson
Mechanical
Properties
ofWood/Polypropylene Composites. Wood Fiber Sci;
35(2):167–74.
Zimmermann, M. V. G., Turella, T. C., Santana, R. M. C.,
Zattera, A. J. (2014) The Inﬂuence of Wood ﬂour Particle
Size and Content on The Rheological, Physical, Mechanicaland Morphological Properties of EVA/Wood Cellular
Composites. Materials and Design; 57:660-666.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P09

Isolation, semi-synthesis of Costunolide from Saussurea lappa and their
TNF-α inhibition
Siwattra Choodej1, Khanitha Pudhom2 and Tohru Mitsunaga1
1. The United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, 501-1193 Gifu, Japan
2. Department of Chemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330 Thailand
Extraction and isolation
The air-dried rhizomes of S. lappa (5 kg) were powdered
INTRODUCTION
and extracted three times with MeOH at room temperature.
Evaporation of the solvent under reduced pressure provided
The rhizomes of Saussurea lappa Clarke (Compositae) is
the MeOH extract. The MeOH extract was suspended in H2O
well-known as folk medicinal plant and popularly named as
and then partitioned with n-hexane to yield a hexane extract
costus and Kuth root. Since ancient times, its rhizomes have
(70 g) and an aqueous phase. The aqueous phase was extracted
been used in various traditional medicine such as Indianwith EtOAc to give EtOAc extract (30 g).
Ayurvedic and Chinese traditional system for the treatment of
The hexane extract (70 g) was subjected to normal-phaseabdominal pain, distention, stop vomiting, allergy and cancer.
silica gel column chromatography eluted with gradientIn addition, in Southeast Asia, it is used to reduce fever,condition of n-hexane/EtOAc (10:0-0:10) to give 16 fractions
headache and to treat diarrhea. The rhizomes extract is also
(Fr.1-16). Fr. 8 was recrystallized using n-hexane/EtOAc (9:1)
used to relieve syphilis in Japan.
to give costunolide (1). The other fractions were fractioned by
In previous reported, sesquiterpene and sesquiterpene
silica gel column chromatography and further purified bylactones are large chemical constituents of this plant, which
preparation HPLC [Inertsil ODS-3, 20 mm Փ x 250 mm] withhave been shown broad biological activities including antigradient condition, MeOH:H2O (7:3-10:0 v/v), to obtain costic
tumor, anti-ulcer, antibacterial and anti-inflammatoryacid (2), rupestonic acid G (3), dehydrocostus lactone (4),activities. For example, two main sesquiterpene lactones fromdehydrodihydrocostus lactone (5) and triterpene, betulinic
the rhizomes as costumolide and dehydrocostus lactone,
acid.
displayed potent nitric oxide (NO) and tumor necrosis factor
The EtOAc (30 g) extract was also subjected to normal(TNF)-α inhibition.
phase silica gel column chromatography (n-hexan/EtOAc,
Tumor necrosis (TNF)-α is one of the major mediators in
10:0-0:10) to give 10 fractions (Fr. 1-10). Fr. 2 was separated
inflammation process. The secretion can be activated by many
over sephadex LH-20 using MeOH and then purified by semicytokines or microbial pathogens such as lipopolysaccharide
preparative HPLC [VertiSep UPS C18, 10 mm Փ x 150 mm,(LPS) through binding with Toll-like receptors (TLRs). Theregradient condition, MeOH:H2O (7:3-10:0 v/v)] to afford αare several of evidence indicated that the high TNF-αcyclocostunolide (6), β-cyclocostunolide (7), arbusculin A
expression has been linked to acute and chronic inflammatory(8), arbusculin E methyl ester (9) and cnicothamnol (10).
diseases including rheumatoid arthritis, proliferation andAll structures were elucidated by using NMR spectroscopic
cancer diseases. Thus, the compounds that suppress or blocktechniques: 1D (1H and 13C), and 2D (1H-1H COSY,
TNF-α production might be useful in the treatment of
NOESY, HMQC and HMBC), and MALDI-TOFMS data. The
inflammatory diseases.
NMR data were compared with previously reported in the
We investigated 10 isolated sesquiterpenes from the nliterature.
hexane and EtOAc extracts of S. lappa rhizomes on LPSinduced TNF-α production in macrophage RAW 264.7 cells.
Moreover, 16 semisynthetic were synthesized to establish the
RESULTS and DISCUSSION
structural requirements for this activity, a structure-activity
relationship was studied here.
In preliminary screening, we found that the n-hexane and
EtOAc extracts of S. lappa rhizomes showed significant antiinflammatory activity by measuring their inhibition of TNF-α
MATERIALS AND METHODS
level in supernatant media of LPS-stimulated RAW 264.7
cells. The n-hexane and EtOAc extracts potently inhibited
General experimental procedures
TNF-α production at IC50 values of 0.5 and 1.0 μg/ml,
NMR spectra were measured in chloroform-d using JEOL
respectively.
EC600 M Hz NMR (JEOL, Tokyo, Japan). Matrix-assisted
Isolation of the n-hexane and EtOAc extracts using
laser desorption/ionization TOFMS (MALDI-TOFMS) spectra
chromatographic techniques including normal-phase silica gel,were determined on Shimadzu AXIMA-Resonancereverse-phase C18 and Sephadex LH-20 column
spectrometer (Kyoto, Japan). Preparative HPLC (Shimadzu
chromatography obtained the 10 known compounds 1-10 (Fig.
LC-6AD) was performed using an Inertsil ODS-3 column (201). The structures were identified by spectroscopic techniquesmm Փ x 250 mm; GL sciences, Tokyo, Japan) and semi(NMR, MALDI-TOFMS) and confirmed by comparison of 1H
preparative HPLC used VertiSep UPS C18 (10 mm Փ x 150
and 13C chemical shifts with previous reported.
mm; GL sciences, Tokyo, Japan). Silica gel (BW-200,
All 11 isolated sesquiterpenes were evaluated their potential
Chromatotex, Japan) and Sephadex LH-20 (18-111 µm, GE
anti-inflammatory activities, which costunolide (1),Healthcare), were used for open-column chromatography.
dehydrocostus lactone (4) and α-cyclocostunolide (6)Analytical thin layer chromatography (TLC) was performed
significantly inhibited of TNF-α values with the IC50 at 2.05,
on pre-coated silica gel 60 F254 glass plate (Merck, German).
2.06 and 5.33 µM, respectively. The previously, several
discussion reported that the presence of α-methylene-γ-lactone
Plant materials
moiety has enhanced cytotoxicity as costunolide. Although it
The rhizomes of S. lappa were purchased from the local
showed strongly TNF- α inhibitory effect (tested dose at 1.25market of Mea Sot, Tak in Thailand as herbal medicine store
5 µM), also showed 50% cell viability at a low concentrationin August 2015.
of 10 µM.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P09
Thus, 16 semisynthetic sesquiterpenes were synthesized todescribe the importance functional group in germacranolide
and eudesmanoline-type sesquiterpene and evaluated their
TNF-α inhibition. The major compound, costunolide (1) as agermacranolide-type was modified by chemical reactions. To
confirmed, α-methylene-γ- and lactone ring is required,compound 11 and 12, which did not show inhibitory activity.
In addition, epoxide product 13 moderately inhibited with IC50
value of 8.91 µM, it suggested that both of epoxide rings
decreased inhibitory activity.
Next, to get further information, the effect ofeudesmanolide-type was synthesized and investigated. A
natural compound, γ-cyclocostunolide (16) was synthesized
together with α- and β-cyclocostunolide. Compound 16
significantly inhibited TNF-α production with a very low IC50
value of 1.99 µM (tested dose at 1.25-5 µM), which also at 10µM showed 50% cell toxicity. Thus, samtamarin (14) andreynisin (15) as the natural eudesmanolide sesquiterpenes
were synthesized, which displayed potent TNF-α inhibition
with IC50 values of 6.64 and 5.19 µM, respectively. Whereas
the inhibitory effect of acetylation (14a, 15a) and oxidation(14b, 15b) of the hydroxyl group at C-1 position weredecreased.
Moreover, epoxide products were studied, which epoxidering at endocyclic double bond more effective than exocyclic
at C-4 position. Among the tested including isolated andsynthesized compounds, epoxidation of 6 as compound 6a not
only showed the most potent TNF-α inhibition, but the cell
toxicity was also decreased (96 and 50% cell viability of
tested dose at 10 and 25 µM, respectively). The relative
configuration of 6a at the epoxide ring was confirmed by
NOESY experiment. The NOESY cross-peaks between Me14/H-3, Me-14/H-6, Me-15/H-3 and Me-16/H-6, these
correlations indicated that their protons present on the sameside of the molecule.

ACKNOWLEDGMENTS
The first author greatly acknowledges MEXT(MONBUKAGAKUSHO) scholarship provided by theJapanese Government for conducting research in the United
Graduate School of Agricultural Science, Gifu University.

REFERENCES
Jang, M.K., Sohn, D.H., Ryu, J., 2001. A curcuminoid andsesquiterpenes as inhibitors of macrophage TNF-α releasefrom Curcuma zedoaria. Planta Med. 67, 550-552.
Hoffmann, H.M.R., Rabe, J., 1985. Synthesis and Biological
Activity of α-Methylene-γ-butyrolactones. J. Angew. Chem.
Int. Ed. Engl. 24, 94-110.
Madhuri, K., Elango, K., Ponnusankar, S., 2012. Saussurea
lappa (Kuth root) : review of its traditional uses,
phytochemistry and pharmacology. Orient. Pharm. Exp.
Med. 12. 1-9.
Zhao, F., Xu, H., He, E.Q., Jiang, Y.T., Liu, K., 2008.
Inhibitory effects of sesquiterpenes from Saussurea lappa on
the overproduction od nitric oxide and TNF-α release in
LPS-activated macrophages. J. Asian. Nat. Prod. Res. 10,1045-1053.
Wei, H., Yan, L., Feng, W., Ma, G., Peng, Y., Wang, Z., Xiao,P., 2014. Research progress on active ingradients andpharmacologic properties of Saussurea lappa. Curr. Opin.
Complement. Alternat. Med. 1, 1-7.
Jain, S.K., 1991. Dictionary of Indian folk Medicine andEthno Botany. Deep Publications, New Delhi.
Sun, C.M., Syu, W.J., Don, M.J., Lu, J.J., Lee, G.H., 2003.
Cytotoxic sesquiterpene lactones from the root of Saussurea
lappa. J. Nat. Prod. 66, 1175-1180.
Cho, J.Y., Baik, K.U., Jung, J.H., Park M.H., 2000. In vitro
anti-inflammatory effects of cynaropicrin, a sesquiterpene
lactone, from Saussurea lappa. Eur. J. Pharmacol. 398, 399407.

Fig. 1 Isolated compound from S. lappa

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P10

Protein-based functional analysis of renin and (pro) renin receptor genes inhypertensive and diabetic Bangladeshi population: Pursuing theenvironment-induced molecular traits

Jobaida Akther1, A. H. M. Nurun Nabi2, Tsutomu Nakagawa3, Fumiaki Suzuki3 and Akio Ebihara3
1.
The United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan2.
Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka 1000, Bangladesh
3.
Department of Applied Life Science, Faculty of Applied Biological Sciences, Gifu University, 1-1 Yanagido, Gifu 5011193, Japanof the selected polymorphisms was carried out using a PCR
based allelic discrimination method (KBiosciences, UK).
INTRODUCTION
Statistical and Bioinformatics analysis
Genotype frequencies of all SNPs were tested in control
Diabetes mellitus is one the most leading diseases at present
subjects for deviation from Hardy-Weinberg equilibrium
all over the world including Bangladesh. In 2015, there wereusing Pearson’s X2 test. The association among hypertension,
7.1 million cases of diabetes in Bangladesh and number ofdiabetes and genotype of the polymorphisms was evaluated bydeaths in adults due to diabetes was 129,312 (IDF diabetes
odds ratios (OR), 95% confidence intervals (CI) and P values,
atlas. 7th ed. 2015). The renin-angiotensin system has beenusing logistic regression. The estimate of linkage
found to be related to the pathogenesis of diabetic retinopathy
disequilibrium between the polymorphisms in Bangladeshi
through several studies (Satofuka et al. 2009, Deinum et al.
cases and controls combined was performed using SNP tool1999). There is substantial overlap between diabetes andpackage.
hypertension in etiology and disease mechanisms (Cheung etWestern blottingal. 2009). Animal model studies have clearly demonstrated
Two antibodies [α-Histidine conjugated to horseradishthat development of hypertension is associated with theperoxidase (HRP) enzyme and α-(P)RR (R&D) conjugated tovariations in renin gene (Rapp et al. 1989). In a Japanese
glucose oxidase (GOx) enzyme] were used to detect twocohort, (pro)renin receptor gene was found significantly anddistinctive regions of recombinant (pro)renin receptor protein.
independently related to ambulatory blood pressure in men
H2O2 produced by GOx is used by HRP for developing visible(Hirose et al. 2009).
color.
Other than genetic make-up, environmental factors are
Ang I-ELISA
considered as the key determinants of hypertension andRecombinant ovine angiotensinogen (oANG) was prepareddiabetes. Exposures to arsenic, lead, cadmium, pollutant
using E.coli cells (Yamashita et al. 2016). The rate ofgases, solvents, and pesticides have also been linked toangiotensin-I (AI) generation was determined by AI-ELISA
increased risk of cardiovascular disease (Brook et al. 2004).
(Suzuki F et al. 1990). Different concentrations of this oANG
Long-term complications of diabetes mellitus are associatedwere incubated with human renin for enzyme kinetics.
with various oxidative reactions, increased free radical
Measurement of thiobarbituric acid reactive substances
generation, and subsequent increase in oxidative stress(TBARS)
level(Giacco et al. 2010). In our previous study with tannery
TBARS value was determined according to the method ofworkers, we found higher TBARS (thiobarbituric acid reactive
Yagi (1998), and TBARS value is expressed as MDA
substances) level in the study subjects due to higher chromium
equivalent per mL of plasma.
exposure (Akther et al. 2016).
Measurement of TAS (total antioxidant status)
Both renin and (pro)renin receptor [(P)RR] proteins as well
The TAS levels of the sera were determined using an
as their genetic variations have been found to be associatedautomated measurement method described by Erel (2004).
with the risk of hypertension and diabetes; and no extensive
The results are expressed in mmol Trolox equivalents/L.
study has been performed so far in Bangladeshi population
regarding renin and (pro)renin receptor. In addition,
RESULTSenvironmental factors, which are sometimes imposed to
Bangladeshi workers, can make a large influence on theplasma levels of renin and (P)RR. Their effects can be
Polymorphism data of (P)RR and REN SNPs- Data for single
observed as environmental-induced molecular traits. Thus,
nucleotide polymorphism (SNP) of rs3112298, rs2968915 ofthis study aims to develop the following methods(pro)renin receptor gene and rs61827960, rs11571079 and1. Developing western blot method with high specificity
rs3730102 of renin gene were obtained. According to
2. Better ELISA for measuring plasma renin
association study, it is found that genotype of rs3112298 ofconcentration (PRC) and soluble (P)RR [s(P)RR](P)RR gene, is associated with hypertension. For the SNP
3. Storage of proteins in solid state using pullulan (ars2968915 of (P)RR gene, allele is associated with
polysaccharide polymer) and their activity checkhypertension. rs61827960 of renin gene is associated withhypertension. Both genotypic variation and alleles of renin
gene have been found to be associated with type 2 diabetes
MATERIALS AND METHODS
with regard to rs11571079. Allelic variations with regard to
rs11571079 of renin gene are also associated with type 2
Genotyping and sequencing of single nucleotide
diabetes related hypertension. Both genotypic and allelicpolymorphism (SNPs) within REN and (P)RR genes
variants of renin gene with regard to rs3730102 SNP have
The selection of the polymorphisms in order to fine map the
been found to be highly associated with the risk of type 2
renin gene and (P)RR gene was done using data on the Asian
diabetes and type 2 diabetes related hypertension.
population from HapMap database. Polymorphisms with a
TBARS level in the study subjects-The average TBARS in theminor allele frequency ≥0.10 were identified using tagger
healthy controls (300) was 0.97 ± 0.26 nmol/mL. The highest
program in Haploview using a minimum r2 of 0.8. GenotypingProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P10
level was found in hypertensive (169) patients (1.82 ± 1.11
nmol/mL) compared to the diabetic (288) patients (1.31 ± 0.31
nmol/mL) and patients (156) with diabetic related
hypertension (1.14 ± 0.21 nmol/mL).
Developing western blot method with high specificity –Recombinant (pro)renin receptor [(P)RR] protein was detected
specifically in the mixture containing FBS and DMEM
(Dulbecco's Modified Eagle's Medium) using α-His-HRP
antibody and α-(P)RR antibody that was conjugated toglucose oxidase (GOx). As two antibodies were used against
a single protein, the detection was more specific.
12

3

Lanes-2 to 4 contained 100 ng ofrecombinant (P)RR and 5% FBS
containing DMEM
Lane-1: protein marker
Lane-2: α-(P)RR antibody (R&D)
Lane-3: α-His-HRP antibody
recombinant Lane-4: GOx conjugated α-(P)RR(P)RR
antibody (R&D) and α-His-HRP
antibody*##

Fig.1: Detection of recombinant (pro)renin receptor in
FBS containing DMEM (Dulbecco's Modified Eagle's
Medium) specifically using GOx-HRP coupled reaction.
* Non-specific bands detected by α-His-HRP Ab# (P)RR fragments
Production of ovine angiotensinogen (oANG) using E.coli
cells- About 350 μL of 122 μM oANG was obtained from500 mL of E.coli cell culture. This preparation is amenable for
PRC assay which is performed in presence of an excess
amount of ANG added exogenously.
2

3

We know that, individuals with different genotypes areaffected differently by exposure to the same environmental
factors, and thus gene-environment interactions can result indifferent disease phenotypes. After establishing assay systems
at Gifu university to measure biochemical traits, I want to
combine the previous SNP data with the study results ofbiochemical traits in the collected samples and find correlation
with the environmental factors.

REFERENCES

4

*

1

DISCUSSION

4

5

6

7
Lane-1: supernatantLane-2: blankLane-3: after affinity
chromatography
Lane-4: after ion exchange
chromatography
Lane-5: after gel filtration
Lane-6: after concentratingoANG (1/10x diluted)
Lane-7: protein marker

Fig.2: Purification of oANG expressed in E.coli cells
Formation of oANG tablets using pullulan- We used pullulan(produced by Aureobasidium pullulans) for solidifyingoANG. Now we are trying to observe if there is any change in
the activities after solidification over months.
oANG tablet made using
pullulan

Fig.3: Tablet of oANG made using pullulan.

Akther, J., Ebihara, A., Nakagawa, T., Islam, L. N., Suzuki,F., Hosen, M. I., ... & Nabi, A. H. M. (2016) Analyses ofGenetic Variations of Glutathione S-Transferase Mu1 andTheta1 Genes in Bangladeshi Tannery Workers and
Healthy Controls. BioMed research international.
Brook RD, Franklin B, Cascio W, … & Tager I. (2004) Air
pollution and cardiovascular disease: a statement
forhealthcare professionals from the Expert Panel on
Population and Prevention Science of the American Heart
Association. Circulation 109: 2655–2671
Cheung, B. M. Y., & Li, C. (2012) Diabetes andHypertension: Is There a Common Metabolic Pathway?
Current Atherosclerosis Reports 14(2), 160–166.
Deinum J, Tarnow L, van Gool JM, de Bruin RA, Derkx FH,
SchalekampMA, Parving HH (1999) Plasma renin andprorenin and renin gene variation in patients with insulindependent diabetes mellitus and nephropathy. Nephrol Dial
Transplant 14: 1904-1911.
Erel, O. (2004). A novel automated direct measurement
method for total antioxidant capacity using a newgeneration, more stable ABTS radical cation. Clinicalbiochemistry, 37(4), 277-285.
Giacco, F., M. Brownlee and A.M. Schmidt (2010) Oxidative
stress and diabetic complications. Circulation Research
107: 1058-1070.
Hirose T, Hashimoto M, Totsune K, .… & Imai Y. (2009)
Association of (pro)renin receptor gene polymorphism withblood pressure in Japanese men: the Ohasama study.
American Journal of Hypertension 22:294–299.
International Diabetes Federation (IDF) (2015) [Internet].
Country estimates table 2011. IDF diabetes atlas. 7th ed..
Rapp JP, Dene H, Wang SM (1989) Restriction fragment
length polymorphisms for the renin gene in Dahl rats.
Journal of Hypertension 7: 121-126
Satofuka S, Ichihara A, … & Ishida S. (2009) (Pro)renin
receptor–mediated signal transduction and tissue reninangiotensin system contribute to diabetes-induced retinal
inflammation. Diabetes 58: 1625– 1633
Suzuki, F., Yamashita, S., Takahashi, A., Ito, M., Miyazaki,S., Nagata, Y., & Nakamura, Y. (1990) Highly sensitive
microplate-ELISA for angiotensin I using 3, 3′, 5, 5′tetramethylbenzidine.
ClinicalandExperimental
Hypertension. Part A: Theory and Practice, 12(1), 83-95.
Yagi, K. (1998). Simple assay for the level of total lipid
peroxides in serum or plasma. Free radical and antioxidant
protocols, 101-106.
Yamashita, S. et al. (2016). Escherichia coli-based productionof recombinant ovine angiotensinogen and its
characterization as a renin substrate. BMC biotechnology,
16(1), 33.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P11

The budding yeast Saccharomyces cerevisiae requires Vitamin B1(Thiamine) for acetaldehyde tolerance
Annisyia Zarina Putri, Madoka Kubota, Haruka Matsuyama, Tetsushi Takagi, Mizuho Inagaki, Masaya Shimada, Takashi
Hayakawa and Tomoyuki Nakagawa
Faculty of Applied Biological Sciences, Gifu University, 1-1 Yanagido, Gifu, JapanRESULTSINTRODUCTION
The budding yeast Saccharomyces cerevisiae, has been
widely used in several industries, such as alcohol
fermentations, making breads, bioethanol production, andother industries, and it is also used as a eukaryotic modelorganism for genetic engineering and a promising cell factory
for biotechnological applications (Nevoigt E 2008). During
the fermentation steps using the budding yeast, the yeast cells
synthesize a large amount of acetaldehyde as a predominantintermediate of their anaerobic metabolism.
Acetaldehyde is high toxic compound against all living
things, because acetaldehyde readily forms adducts withintracellular compounds, such as proteins and nucleic acids,
thus acetaldehyde interferes with a wide range of cellular
metabolic activities, and then blocks cell growth (Israel Y et al1986). Therefore, it seems that the budding yeast needs topossess some acetaldehyde tolerance systems in order to takecare for intracellular toxicity of acetaldehyde during alcohol
fermentation step.
Aranda and del Olmo also identified acetaldehydeinducible/repressible genes using transcriptome analysis(Aranda A, del Olmo ML 2004). In acetaldehyde-inducible
genes, there are some functional groups, such as stressresponse, polyamine transport proteins, sulfur metabolism,
aryl alcohol metabolism and another metabolism.
Interestingly, genes in the vitamin B1 (thiamine) biosynthesis
pathway, such as THI4, THI12 and THI13, were notably upregulated under acetaldehyde stress (Aranda A, del Olmo ML
2004)
In this study, we aimed to demonstrate the importance ofthiamine in the budding yeast under the acetaldehyde stress. It
was suggested that the budding yeast requires thiamine for theacetaldehyde tolerance, and the thiamine transporter, thi7Δ,
has an essential function in maintenance of intracellularthiamine level under the acetaldehyde stress.

MATERIALS AND METHODS
Yeast strains and growth conditions
S. cerevisiae strain BY4741 (MATa, his3∆1, leu2∆0,
met15∆0, ura3∆0) was used as the wild-type strain. Genedisrupted strains originated from the strain BY4741 waspurchased from Invitrogen Co. (Carlsbad, CA., USA).
Complex YPD and synthetic SD media were used for
cultivation of S. cerevisiae strains. SD medium consisted of
2% glucose and 0.67% w/v yeast nitrogen base without aminoacids, supplemented with uracil, leucine, methionine, histidine
and thiamine hydrochloride as needed.
Cultivation was performed aerobically at 28°C with rotary
shaking, and growth was monitored by measuring the opticaldensity at 610 nm.

Thiamine is an essential factor for acetaldehyde
tolerance in the budding yeast
We observed effect of supplementation of thiamine to themedium on acetaldehyde sensitivity in the budding yeast inorder to show whether thiamine is an essential factor for
acetaldehyde tolerance or not. As a result, supplementation ofthiamine in the medium suppressed acetaldehyde sensitivity ofthe budding yeast, and the suppressive effect against
acetaldehyde stress (40 mM) by thiamine is increased
depending on increase in its concentration (Figure 1).
This result indicates that thiamine has important role in theacetaldehyde tolerance system in the budding yeast.

Figure 1. Yeast cell requires thiamine for their acetaldehyde tolerance.
Yeast cell suspensions (OD660=1, 0.2 and 0.04) were spotted on YNB
plates supplemented with or without acetaldehyde.

Thiamine-uptake system is importantacetaldehyde tolerance of the yeast.

for

The expression of THI4 and other thiamine biosynthesis
genes is inversely regulated by the amount of thiamine
available in the growth medium, with low thiamine inducing
THI gene expression and high thiamine repressing THI gene
expression (Hohmann S, Meacock PA 1998). Thiamine
pyrophosphate TPP is a coenzyme for pyruvate dehydrogenase,which converts pyruvate to acetyl-coenzyme A. If TPP is notavailable, the concentration of pyruvate is increased andoxidative energy metabolism is impaired. TPP also acts ascoenzyme for transketolase in the pentose phosphate shunt.

Figure 2. THI7 is essential gene for acetaldehyde tolerance system inProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P11
the budding yeast.

Next we observed phenotype of the mutant strains, which
are disrupted in thiamine related genes, i.e., thi4Δ, thi6Δ,
thi7Δ, and thi72Δ. As a result, strain thi7Δ showed severe
acetaldehyde sensitivity compared with the wild-type strain(Figure 2).
Moreover, we tried to check the effect of over-expression ofthiamine related genes on the acetaldehyde tolerance of theyeast (Figure 3). The strains overexpressed THI6, THI7,
THI72 and THI21 showed high acetaldehyde tolerance morethan the wild type strain. Micro-organisms, such as the yeast
Saccharomyces cerevisiae, either take up thiamine from thesurrounding medium and convert it to ThDP or they synthesise
ThDP de novo (Hohmann S, Meacock PA 1998 ). Two genes
involved in the acquisition of exogenously available thiamine
are THI7 (also known as THI10), which encodes a plasma
membrane thiamine transporter (Enjo F et al. 1997; Singleton
CK 1997)
These results indicate that thiamine has important functionin the acetaldehyde tolerance system in the budding yeast,
especially THI7, which is gene encoding the major thiaminetransporter, imports enough level of thiamine into the cell for
acetaldehyde tolerance system.

transketolase, which requires thiamine pyrophosphate (TPP)
as a co-factor. Transketolase is one of the members in the
pentose phosphate pathway (PPP) in the cell. The pentose
phosphate pathway is an important part of the primary carbon
metabolism in all living cells. In bacteria, the pathway canfunctionally replace the upper part of the glycolysis, thus
making it possible for cells to grow on glucose in the absenceof phosphoglucose isomerase (Vinopal RT et al 1975) It wasreported that PPP involved in acetaldehyde tolerance systemin the budding yeast, since (i) expression of all PPP genes are
upregulated by acetaldehyde (Aranda A, del Olmo ML 2004),(ii) all PPP gene disrupted mutants showed severe
acetaldehyde sensitivity (Matsufuji Y et al 2008) and (iii)
intracellular levels of intermediates in the PPP were increasedby acetaldehyde stress (data not shown). The yeast cellrequires a large amounts of thiamine under acetaldehyde stressin order to activate PPP, thus the cell need to overexpress thethiamine synthetic pathway and transporters together with PPP
under acetaldehyde stress.
In the yeast cell, there are many thiamine requiring enzymes.
Therefore, another enzymes, except for transketolase, may
participate to acetaldehyde tolerance system. In the next work,
we will identify the new thiamine requiring enzymes
participating to acetaldehyde tolerance system of the budding
yeast.

REFERENCES

Figure 3. Effect of overexpression of thiamine synthetic genes on
acetaldehyde tolerance. The yeast strains overexpressed gene yeast
cell suspensions (OD660=1, 0.2, 0.04) were spotted on YNB plates
supplemented with or without acetaldehyde.

DISCUSSION
In this study, we demonstrated that thiamine is one of theimportant factors for acetaldehyde tolerance system in thebudding yeast, because supplementation of thiamine into themedium suppressed acetaldehyde sensitivity of the budding
yeast. Moreover, uptake of thiamine by thi7Δ, which is amajor thiamine transporter, is the important steps for
acetaldehyde tolerance compared with thiamine synthesis,
although its synthetic pathway is activated by acetaldehydestress (Aranda A, del Olmo ML 2004).
Why does the yeast cell require thiamine for theiracetaldehyde tolerance system? Now we can not explain
function of thiamine in the acetaldehyde tolerance in detail.
However, our hypothesize now that yeast cell may requirethiamine as cofactors of some enzymes participating
acetaldehyde tolerance system in the budding yeast. For
example, there is a enzyme requiring thiamine as a cofactor in
the acetaldehyde tolerance genes. That is TKL1 encoding

Aranda A, del Olmo ML. 2004. Exposure of Saccharomyces
cerevisiae to acetaldehyde induces sulphur amino acidmetabolism and polyamine transporter genes, which depend
on Met4p and Haa1p transcription factors, respectively.
Appl. Environ. Microbiol. 70:1913–1922.
Enjo F, Nosaka K, Ogata M, Iwashima A, Nishimura H.
1997. Isolation and characterization of a thiamin transport
gene, THI10, from Saccharomyces cerevisiae. J. Biol. Chem.
272:19165–19170
Hohmann S, Meacock PA. 1998. Thiamin metabolism andthiamin diphosphate-dependent enzymes in the yeast
Saccharomyces cerevisiae: genetic regulation. Biochim.
Biophys. Acta 1385:201-219
Israel Y, Hurwitz E, Niemelä O, Arnon R. 1986.
Monoclonal and polyclonal antibodies against acetaldehydecontaining epitopes in acetaldehyde-protein adducts. Proc.
Natl. Acad. Sci. U S A 83:7923–17927
Matsufuji Y, Fujimura S, Ito T, Nishizawa M, Miyaji T,
Nakagawa J, Ohyama T, Tomizuka N, Nakagawa T.
2008. Acetaldehyde tolerance in Saccharomyces cerevisiae
involves the pentose phosphate pathway and oleic acidbiosynthesis. Yeast 25:825–833
Nevoigt E. 2008. Progress in metabolic engineeringof Saccharomyces cerevisiae. Microbiol. Mol. Biol. Rev.,
72:379–412
Singleton CK. 1997. Identification and characterization of thethiamine transporter gene of Saccharomyces cerevisiae.
Gene 199:111–121.
Vinopal RT. Hillman JD, Schulman H, Reznikoff W,
Fraenkel DG. 1975. New phosphoglucose isomerase
mutants of Escherichia coli. J. Bacteriol. 122:1172-1174.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P12

Comparison of typhoon HAIYAN (2013) and typhoon MELOR (0918)
using pseudo-global warming experiments
Masaya Toyoda, Jun Yoshino and Tomonao Kobayashi
Environmental and Renewable Energy Systems Division, Graduate School of Engineering, Gifu University

INTRODUCTION
The recent progress of the global warming often raise concern
about the future changes of a tropical cyclone (i.e. hurricane,
typhoon, and cyclone) and its associated coastal disaster. It isthought that the increases of both the sea surface temperatureand ocean heat contents by the global warming could induce anincrease of the typhoon intensity (Lin et al., 2014). However,even in the IPCC Fifth Assessment Report published in2013, the typhoon intensity in the future climate is notclarified. This is due to the large uncertainty of global
climate model (GCM) and global warming scenario(SRES) used for global warming impact assessment. In
the previous study, the authors conducted a pseudo-global
warming experiment for typhoon 1330, and evaluated thefuture change of typhoon intensity, maximum tide level ofstorm surge, and their uncertainty. However, this result is
limited to the area around the Philippines where Typhoon 1330
attacked, and it is expected that the typhoon that will hit Japan
will have different results, and further accumulation of cases isrequired. Therefore, in this study, we used a high-resolution
typhoon model and a storm surge model by targeting typhoon
0918 (Typhoon Melor) which moved not only typhoon 1330
which moved only in tropical zone but also subtropical zone
and midlatitude zone, ensemble pseudo-global warming
experiments are carried out. The purpose is to compare thefuture change of the typhoon intensities and uncertainties of
two furious typhoons that attacked different areas.

COMPUTATIONAL METHODS(1) High-resolution Typhoon Model (HTM)
In this study, to estimate the intensity changes of overall life
cycles of two super typhoons, using the high-resolution
typhoon model. (hereafter HTM), which is based on themesoscale meteorological model (hereafter MM5). MM5 is athree-dimensional, non-hydrostatic, fully-compressible, cloudresolving atmospheric model to predict mesoscale and localscale phenomena. The automatic movable nesting technique isintroduced into MM5 to efficiently reproduce the highresolution structure near the center of an intense typhoon fromthe genesis stage to the dissipating stage. Additionally, theseveral kinds of physical parameterizations (e.g. the ocean
mixed layer, dissipative heating, and sea-spray processes) are
newly implemented into MM5 to express realistic typhoon
intensity and structure accurately. The triply nested
computational domains used in this study have a horizontal
grid spacing of 27-km (D1), 9-km (D2), and 3-km (D3),respectively. The movable nesting technique is applied to bothD2 and D3. The four-dimensional data assimilation technique(nudging) is utilized to gradually assimilate typhoon
environment in the gridded analyses.

(2) Present climate and future climate experiments
First, present climate experiments for Haiyan and Melor(hereafter CNTRL) are carried out with using NCEP Final
Analyses (FNL) as initial and boundary conditions.
Additionally, future climate experiments are also conducted byusing the method of “pseudo-global warming downscaling”(Yoshino et al., 2015). Estimating the differences between
CNTRL and future climate experiments, we can quantify the
future changes of typhoon intensity and storm surge by the
global warming. The input dataset (initial and boundary
conditions) for the pseudo-global warming experiments are
created by adding to FNL the differences of ten-year averaged
monthly mean fields (e.g. temperature, sea surface temperature,geopotential height, east-west wind speed, north-south windspeed, and relative humidity), which are called as “global
warming differences (GWDs)” obtained from different GCMs
with different SRESs.
In this study, the uncertainties of the future changes oftyphoon intensity and storm surge are evaluated due to thedifferences of GWDs used among SRESs and among GCMs.
To conduct the ensemble pseudo-global warming experiments
among SRESs, a GCM “HadCM3” in CMIP3 is selected as areference model., which is divided into three emission
scenarios (B1, A1B, and A2) for three decadal periods (2030s,
2060s, and 2090s). To conduct the ensemble pseudo-global
warming experiments among GCMs, a SRES “A1B in the2090s” in CMIP3 is chosen as a reference scenario, which is
divided into a total of 15 GCMs. Both of two super typhoons
targeted in this study show a different pattern of typhoon
tracks. Haiyan moved east-westward in the tropical ocean,nearly parallel to the latitude lines. In contrast, Melor moved
south-northward from the subtropical to the mid-latitude ocean,roughly parallel to the meridians. Comparing the results among
the super typhoons simulated by HTM, it is expected that the
future change of typhoon intensity and its uncertainty may beevaluated at different latitudes at different seasons.

RESULTS AND DISCUSSION(1) Future change and its uncertainty of typhoon intensityof Haiyan
First, we discuss the results of the ensemble pseudo-global
warming experiments of Haiyan with changes of SRESs andGCMs (Figs. 1). The ensemble-averaged values of theminimum central pressures for SRESs and GCMs are 900.8
hPa and 905.0 hPa, respectively, at 5610 min. The futurechanges from CNTRL (897.1 hPa) are +3.7 hPa for SRESs and+7.9 hPa for GCMs, indicating that a well-mature typhoon
under the future climate tends to slightly weaken its intensity.
However, at the time of landfall (5760 min), the ensembleaveraged intensities for SRESs and GCMs are 906.3 hPa and907.5 hPa, respectively, showing a tendency to be slightly
strengthened compared with CNTRL (908.8 hPa). Therefore,
the future change of the peak intensity of a typhoon over thetropical ocean can be small. The standard deviations of theminimum central pressures among SRESs and GCMs are 5.89

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P12
hPa and 9.47 hPa, respectively, at 5610 min. The uncertainty of
future changes among GCMs is about 1.6 times larger than thatamong SRESs. The same tendency can be seen in the previous
study (Toyoda et al., 2016).
(2) Future change and its uncertainty of typhoon intensityof Melor
Next, we discuss the results of the ensemble pseudo-global
warming experiments of Melor with changes of SRESs andGCMs (Figs. 2). The ensemble-averaged values of theminimum central pressures for SRESs and GCMs are 902.3
hPa and 887.6 hPa, respectively, at 8640 min. The futurechanges from CNTRL (907.7 hPa) are -5.4 hPa for SRESs and-20.1 hPa for GCMs, implying that future typhoons for both
SRESs and GCMs are intensified in the subtropical ocean.
There is a tendency that the typhoon intensities among GCMs
are especially strengthened, rather than SRESs. Thus, futuretyphoons in the 2090s under the A1B scenario are likely to beintensified. Comparing the results of Haiyan with those of
Melor, there is a large difference of global warming impact on
typhoon intensity between the tropical ocean and subtropicalocean. The standard deviations of the minimum centralpressure are 20.1 hPa for GCMs and 18.8 hPa for SRESs at
8640 min. The uncertainty of the future changes of the peakintensity of Melor is much greater than that of Haiyan
described in section 3.1, while there is a smaller difference of
the uncertainty between SRESs and GCMs. Then, theensemble-averaged values of the central pressures at the time ofMelor’s landfall for SRESs and GCMs are 948.9 hPa and 952.2
hPa, respectively. The future changes of the intensity fromCNTRL (953.5 hPa) are -4.6 hPa for SRESs and -1.3 hPa for
GCMs. As with the peak time (8640 min), a future typhoon
making landfall at the Japan islands is likely to be intensified
although the future changes are relatively smaller. The standard
deviations of the central pressures at landfall are 7.8 hPa for
SRESs and 10.3 hPa for GCMs, meaning that the uncertainty
among GCMs is greater than that among SRESs, and theuncertainty of the future changes at landfall are significantly
suppressed more than that at the peak time when Melor moves
over the subtropical ocean.
(3) Key factors of uncertainty of typhoon intensity change. Key factors of the uncertainty of typhoon intensity change
is especially due to the uncertainties of wind speed in GWDs
derived from GCMs (Yoshino et al., 2017). Thus, the ten-year
averaged monthly mean differences of 300 – 850 hPa verticalwind shear between 2090s and 2000s are extracted from a totalof 15 GCMs in the A1B scenario along with the 6-hourly tracks
of Haiyan and Melor (Figs. 3).
As shown in Figs. 3(a) and 3(b), it is found that theuncertainty of vertical wind shear changes across the track ofMelor is larger than that across the track of Haiyan. In terms ofan uncertainty in Melor, the standard deviations of futurechanges of vertical wind shear is particularly larger during thepassage around the mid-latitude ocean (during 8640 – 12960
min) than during the passage around the subtropical ocean(during 0 - 8640 min). Therefore, it can be considered that thehigh uncertainty of typhoon intensity changes of Melor during
the time of peak and landfall, seen in Fig. 6, are due to theuncertainty of the future changes of vertical wind shear
obtained from GCMs.

Figure 1 Time series of the central pressure of Haiyan simulatedby pseudo-global warming experiments GCMs. Error
bars indicate the standard deviations of the central pressuressimulated among GCMs. (dotted line: CNTRL)

Figure 2 Time series of the central pressure of Melor simulatedby pseudo-global warming experiments GCMs. Error
bars indicate the standard deviations of the centralpressures simulated among GCMs. (dotted line: CNTRL)

Figure 3. (a)300 – 850 hPa vertical wind shear between 2090s and 2000s(SRES A1B), across the 6-hourly positions (track) of Haiyan.
(b) 300 – 850 hPa vertical wind shear between 2090s and 2000s(SRES A1B), across the 6-hourly positions (track) of Melor.

REFERENCES
Lin, I-I., I.-F. Pun., and C.-C. Lien. (2014) “Category-6”
supertyphoon Haiyan in global warming hiatus: Contribution
from subsurface ocean warming, Geophysical Research
Letters, Vol.41, pp.8547-8553.
Toyoda, M., Yoshino, J., and Kobayashi, T: Ensemble future
projections of storm surge in the Leyte gulf, Philippines, bypseudo-global warming experiments, JSCE B2(Coastal
Engineering), Vol.72, No.2, pp. I_1483-I_1488, 2016.
Yoshino, J., Shinohara, K., Toyoda, M., and Kobayashi, T:
Sensitivity experiments on future intensity changes anduncertainties of Typhoon HAIYAN (2013) using a HighResolution Typhoon Model, JSCE B2(Coastal Engineering),
Vol.73, No.2, 2017.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P13

Controlling the process of denitrification in flooded rice soils by using
microbial fuel cell applications
Tharangika Ranatunga1, Ken Hiramatsu2 and Takeo Onishi2
1.
The United Graduate School of Agricultural Science, Gifu University
2.
Faculty of Applied Biological Sciences, Gifu University

INTRODUCTION
Energy required in the fixation of fertilizer nitrogen fromthe unlimited atmospheric nitrogen is of very large quantities.
It is estimated that a field application of 150 kg/ha fertilizer
nitrogen as ammonia involves the consumption of 645 cubic
meters of natural gas (Olsan and Halstead, 1974). Process ofdenitrification is one of the main channels to cause nitrogen
deficiency in crop production. In submerged soils, thedenitrifying bacteria use NO3- in the absence of oxygen as theterminal electron acceptor in their process of respiration and isreduced to NO2-, NO, N2O and to N2, finally (Reddy &Patrick,1986). This leads to poor fertilizer nitrogen efficiency,
due to the loss of applied fertilizer. To improve nitrogen
fertilizer efficiency, more direct way to control the nitrogentransformation processes in the soil would be more promising.
Principle of microbial fuel cells (MFCs) can be applied to
the flooded soils. The electrons produced during oxidation oforganic matter are transferred directly to an electrode called
anode, and the electrons travel through an electrical circuit to
the cathode where oxygen is reduced to H2O. Potential
gradients could be generated between the anaerobic layer ofsoils beneath water and aerobic layer of upper soils, whenconnected externally through insulated wires. It is therefore,possible to generate electricity, if anode microbes have selfsustained extra-cellular electron transfer mechanisms (Lovley,2008). Since denitrification process of flooded rice fields are
redox reactions between organic carbon and oxidized forms ofnitrogen anions, the availability of organic carbon should be
one of the decisive factors of denitrification process. Electrons
resulted from oxidization of organic matter could be circulated
in an electric chain, through anaerobic and aerobic layer ofsoils, by conifguring an MFC. Thus, a competition forelectrons is expected to invoke for the generation ofelectricity, and to outcompete denitrification reactions.
This study is based on the hypothesis that denitrifying
conditions could be controlled by redox potential changes insoils that are invoked by MFCs. We investigated theapplicability of MFC to control soil redox potential andthereby to suppress denitrification – nitrogen losses in flooded
rice fields.

MATERIALS AND METHODS
Initial set up of experiment - planting pots with gas
chambers, MFC configuration, data loggers
Planting pots with gas chamber experiment was conductedwith three different conditions: MFC systems; MFC systems
with an externally applied voltage; and non-MFC systems forthe control. Each system was set in triplicates. In the rest of
this article, we call MFC systems as MFCs, MFC systems withan externally applied voltage as MFC-extV, and non-MFC
systems as non-MFCs. Externally applied voltage was aimed
at increasing the efficiency of MFC, since rapid movement ofelectrons towards the anodic area is expected to be enhancedby externally applied voltage. The external voltage kept at

between 25-50 mV was applied by the stabilizer (AD-8735A,
AND Co. Ltd) throughout the rice growth stages. Except for
non-MFCs, as for an anode, a carbon graphite-felt mat (S-221,
Osaka Gas Chemicals Co. Ltd.) of 20 cm × 20 cm × 0.5 cm,
was imbedded at 10 cm below the soil surface. As for cathode,a graphite rod (C-072591, Nilaco corporation) with a length of
8 cm, and diameter of 0.4 cm, was kept floating on the flooded
water in contact with air. Anode and cathode were connected
through insulated wires with a resister of 330 Ω. As a basal
application, ammonium based chemical fertilizer (NH4)2SO4
was applied at a rate of 30 kg Nha-1. Two rice seedlings (aged
3 weeks) were transplanted into each pot and then soil was
kept flooded for approximately 5 cm depth by using an
automatic water supply system. Soil redox potential, N2O gas
flux, total C/N ratios of soil, and NH4+, NO2-, NO3concentrations in soil pore water were periodically measured
over the rice growth stages; vegetative, reproductive, andmaturation stage. Nitrogen retention efficiencies anddenitrification loss rates were calculated and compared among
each system.
Gas flux, chemical measurements and data analysis
By applying closed chamber method, N2O concentration ingas samples (weekly) were measured by gas chromatography(GC-2014 equipped with an ECD detector, Shimadzu Co.
Ltd.). Gas was sampled at 11am, 1pm, and 3pm in each gas
sampling event. The monitoring of N2 emissions at the field
scale is impossible due to the high atmospheric background of
78 %, which precludes the measurement of fluxes. To quantify
accurate denitrification rate by microbial denitrification
processes, reduction of N2O gas into N2 should be prevented.
Acetylene inhibition technique was applied according to themethod proposed by Iida et al (2007). After converting
volumetric concentrations (ppm) to mass per volumeconcentrations by ideal gas law, flux was calculated by thefollowing equation(1).

F=∆m∆m / V
= h⋅
A⋅∆t
∆t

(1)

Where, F: N2O flux (µg m-2 min-1), Δt: measured time (min),∆m: mass change of the N2O gas during Δt, A: surface area ofthe chamber (m2), V: volume of headspace (m3), h: effective
height of headspace (m).
Redox potential at the depth near the anode was measuredby Eh meters (PRN-41, Fujiwara Factory Co. Ltd.)
continuously at 1-hour intervals. Generated voltage output by
MFCs and the soil temperature and temperature inside thechamber were recorded to data logger (CR-1000, Campbell
Scientific Inc.) with 10 minutes interval. Soil pore water was
sampled using pore water samplers (RHIZON MOM 10 cm,
Rhizosphere research products, Netherlands) at 3 depths; 10
cm, 20 cm, and 30 cm from the soil surface. Nitrogen ion
concentrations in pore water were analyzed by ion
chromatography (ICA-2000, TOA-DKK Co. Ltd.). Total
carbon and total nitrogen contents in soil particle wasProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P13
measured by CHNO elemental analyzer-Micro-corderJM10.
Using daily averaged redox potential data, and N2O flux, thedifferences between treatments were compared. Statisticalanalysis i.e., one-way ANOVA and multiple comparisons ofTurkey test was conducted with IBM SPSS Statistics version
24.The amount of inorganic nitrogen in the form of NH4+,
NO2-, and NO3- of each layer were summed up as follows inequation(2), to obtain the total inorganic nitrogen amount ofsoil pore water.
3
TN = ∑ C N ,i ⋅ Vi ⋅ θ ii =1( i = 1, 2, 3)

As a consequence of relatively high redox potential in MFCs
and MFC-extV, denitrification processes is suppressed, and as
a result, N2O flux is also suppressed in MFCs and MFC-extV.
It indicates that MFC systems have a potential to control thedenitrification process.

(2)

Where, i: index to represent layer, TN: total inorganic nitrogenamount (mg), CN,i: total inorganic nitrogen concentration at ith
layer (mg l-1), Vi: soil volume of ith layer, θi: soil porosity of
ith layer. Averaged rate of nitrogen flux of each rice growthstage was used to estimate the total denitrified nitrogen loss
with related to each growth stage as follows in equation(3):DN (growth stage ) = 1440 ⋅ N flux (growth stage ) ⋅ A ⋅ d (growth stage ) (3)Where, DN (growth stage): denitrified nitrogen amount ineach growth stage (mg), Nflux (growth stage): averaged
nitrogen flux in each growth stage (μg m-2 min-1), A: surface
area (m2), d (growth stage): number of days of each growthstage.

RESULTS AND DISCUSSION
Redox potential and N2O flux
Both MFCs and MFC-extV treatments showed higher redox
potentials compared with that of non-MFCs. During theperiod of reproductive stage, the redox differences between
MFCs and non-MFCs were clearly distinct. Reproductive
stage of rice could help more on root exudation to be able withhigher MFC performance, which in turn had its greater effecton controlling the soil redox status. Also non-MFCs has
distinctively the highest N2O flux rates of all. One-way
ANOVA results on daily-averaged redox data indicatessignificant difference between each treatment at 5% significant
level. Next, multiple comparisons test by Turkey HSD method
was applied to clarify differences among three groups.
There’s a significant difference in redox potentials between
MFCs and non-MFCs and between MFC-extV and nonMFCs. But, the difference between MFCs and MFC-extV was
not significant. It implies that applying an external voltage
does not significantly enhance the soil redox status as a whole.
One-way ANOVA results on N2O flux data indicates asignificant difference between each treatment at 5% significant
level. Next, Multiple comparisons by Turkey HSD test showedthat there’s a significant difference in N2O flux between MFCs
and non-MFCs, but the difference between MFCs and MFCextV was not significant.
Overlay of average N2O flux and average redox potential
with respect to each growth stage is shown in Fig.1. Common
trend of N2O flux in all treatments were decreasing from thestart towards the end of rice growth. However, N2O flux of
non-MFCs were significantly higher throughout all stages. All
treatments showed commonly a decreasing trend of redox
potential from start to the end of rice growth. However,decreasing trend is much stronger in non-MFCs. Soil redox
status in non-MFCs were far more reducing through all stages.

Fig.1 Behaviour of N2O flux and soil redox potential withrespect to each growth stage: Treatments with growthstages are on X axis. Averaged soil redox potential (mV) is
in line graphs and mean N2O flux (µg m-2 min-1) is in bar
graphs on Y axis.
MFCs frequently followed lower C/N ratios comparedwith that of non-MFCs; implying that availability of electrons
for denitrifying half reactions in the MFCs might be limited,
whereas availability of electrons for denitrifying redox
reactions in the non-MFCs were much higher. As calculated
by equation (2), both MFC and MFC-extV showed relatively
higher Nitrogen retaining efficiencies, especially at
reproductive stage of rice growth. As calculated by equation(3), both MFCs and MFC-extV showed lower denitrification
N losses comparatively.

CONCLUSION
We attempted to confirm the applicability of MFC theory to
suppressing denitrification in flooded rice soils. N2O flux of
MFCs and MFC-extV were significantly lower than that of
non-MFCs. Both redox potential trends and the C/N ratio in
MFCs and MFC-extV are also consistent with the result.
Whether the external application of voltage has a distinct
effect in redox potentials and N2O flux rates were not cleared.
This might be attributed to the design of anode. Anode design
should be better considered to cover the effect of external
voltage through the soil. We confirmed that the MFC theory
and its application help control denitrification N-losses inflooded rice soils. It would be a remedy for lowering thegreenhouse gas (N2O) emissions too.

REFERENCES
Iida, T., Deb, S. K., Kharbuja, R. M. (2007). Nitrous oxide
emission measurement with acetylene inhibition method in
paddy fields under flood conditions. Paddy Water
Environment 5: 83-91
Lovely, D. R., (2008). The microbe electric: conversion oforganic matter to electricity. Current Opinion in
Biotechnology 19: 564–571
Olson, R. A., Halstead, E. H. (1974). The fertilizer nitrogenproblem. Bulletin of International Atomic Energy Agency(16). In AGRIS (since 2012) v26-29(5)Reddy, K.R., Patrick, W. H. (1986). Denitrification losses
in flooded rice fields, Fertilizer research 9: 99-11

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P14

Effect of aeration time on total coliform and E. coli concentrations inexcess activated sludge
Shuailei Li1, Guangyu Cui2 and Fusheng Li3
1. Graduate School of Natural Science and Technology, Gifu University, Japan
2. Graduate School of Engineering, Gifu University, Japan
3. River Basin Research Center, Gifu University, Japan
separation was followed by centrifuging at 3500 rpm for 5
minutes. The obtained sludge was subjected to microbial
INTRODUCTION
analysis, and the supernatant was subjected to water quality
analysis after filtered through sterilized 0.45μm membranes.
With rapid urbanization, a rapidly increasing number ofsewage treatment plants are built over the world. This resultsin generation of large quantities of excess activated sludge
Water quality analysis—pH, redox potential (ORP), andmainly consisted of microorganisms that play the major roleelectrical conductivity (EC) were determined at the time ofin removing biodegradable organic substances in wastewater.
sampling for mixed liquid. Mixed liquor suspended solids
The large quantities of excess sludge should be handled(MLSS) and mixed liquor volatile suspended solids (MLVSS)
effectively in a sustainable and decentralized manner in orderwere determined according to standard drying andto alleviate adverse consequences on the environment (water,
incineration methods. Soluble chemical oxygen demand
air, soil, living space, etc.) and benefic resource recycling and(SCOD) was quantified by using the test kit for CODcr (Hach,reuse. (van der Werf et al.,2014; Pandey et al., 2016) At
USA). Ammonia nitrogen, nitrate and phosphate were
present, the following treatment and disposal methods for the
analyzed by ion chromatography. Fluorescence EEM ofsewage sludge are well used in the world: landfill, farmland
dissolved organic matter in the filter water phase was alsoutilization, dumping at sea and incineration before and after
analyzed.
biological stabilization and/or biological fermentation. In
biological treatment especially in composting andMicrobial analysis—Total coliform and E. coli werevermicomposting, pathogens (total coliform, fecal coliform, E.
analyzed by plate count method. In brief, 2g of centrifugalcoli, etc.) are an essential index that should be consideredsludge was added to an 18 mL tube containing physiologicalbecause pathogenic bacterial species can affect the safety ofsaline solution and oscillation was performed for 30 minutes
food and vegetation and also their yields when the final
at 200 rpm for distribution of bacteria uniformly in the tube.
product of composting is used as either soil modifier or
1mL of the solution was taken and injected into another tube
fertilizer for agricultural production.
containing 9 ml saline solution for dilution. This process was
In previous studies, researchers mainly focused on how torepeated in the same way till 102, 103,104 folds dilutions werereduce pathogens during the sludge treatment and disposal
achieved. 1mL of the sample was poured to a Petri dishes
processes. For example, many researchers have reported
containing Chromocult® Coliform Ager (Merk KGAA,
remarkable reductions in the number of coliform bacteria andDarmstad, Germany) and incubated for 24h at 37℃. All darkE. coli during composting or vermicomposting of municipal
blue to violet colonies were counted as E. coli, and all salmon
biosolids (Eastman et al., 2001; Sinha et al., 2010). But, there
to red colonies were counted as total coliform.
are few researchers who have paid attention to elimination andreduction of pathogens from the source. Supposing that this is
RESULTS AND DISCUSSION
possible through optimizing operations and techniques inwastewater treatment plants, the pressure incurred with
Effectofaerationonmajor
physicochemical
generation and treatment of excess activated sludge can get
characteristics—The physicochemical characteristics of the
reduced within the wastewater treatment plants. Accordingly,
sludge are shown in Table 1. As could be seen from this table,
as one of the major purposes of this study, the effects ofalong with the aeration, pH decreased and EC increased. The
aeration time on the concentrations of pathogenic biologicaldecreases of pH were probably caused by the promoted
indicators, total coliform and E. coli, in excess active sludge
occurrence of nitrification of ammonium formed during
were investigated through batch aeration experiments using
decomposition of cells. The increases of EC may also reflect
returned sludge from a representative municipal wastewater
the changes in cells. MLSS, MLVSS and UV260 decreased
treatment plant.

MATERIALS AND METHODS
Return activated sludge—Returned activated sludge was
sampled from the North Wastewater Treatment Plant of Gifucity, Japan. Static settling was allowed for 2 hours in order tofurther concentrate the sludge before subjected to direct
treatment by aeration for 8, 16, and 24 hours, respectively.
Experimental set up—Activated sludge after concentration
was added into a plastic reactor, to which wetted-air wasconsistently supplied through an air pump. The aeration
treatment was conducted in a room temperature controlled
room (25℃), and sampling was performed after running for at
8, 16, and 24 hours, respectively. After sampling, solid-liquid

Table 1. Physicochemical characteristics of samples
Parameter
pH
EC
ORP
MLSS
MLVSS
UV260
SCOD
NH4+
NO3-

Unit
mS/m
mV
mg/L
mg/L
m-1
mg/L
mg/L
mg/L

0h
6.85
39.4
-186
10293
7838
1.3884
52
10.08
0.2

8h
6.67
27.6
90
8673
6667
0.8885
37
4.42
0.12

16 h
5.85
40.1
105
8103
6250
0.5232
31
1.72
50.13

24 h
6.16
59.9
-91
9080
7003
0.5918
35
0.1
87.89

obviously after 8 hours of aeration, and then showedcomparatively small variations till the end of aeration forProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P14
totally 24 hours. Ammonium decreased and nitrate increased,suggesting the involvement of nitrifying bacteria wasenhanced within the whole aeration process.

the two peaks reflecting fulvic acids-like and humic acids-like
substances, respectively, was less apparent.

Effect of aeration on Total coliform and E. coli—The
variations of total coliform and E. coli during aeration aredisplayed in Fig. 1, and the removal rate of total coliform andE. coli are showed in Fig. 2. Total coliform and E. coli
concentrations decreased obviously in the first 8 hours; andthen fluctuated within narrower ranges, without revealing a
trend of further consistent decreases as aeration time wasincreased. The corresponding removal for E. coli was 80%
and that for total coliform was about 50%. To clarify thereason for the observed trend that further obvious removal did
not occur after aeration was extended to 16 hours and 24
hours is important and will be focused in coming studies.

7.E+05

7.E+04
6.E+04
Total coliform
E.coli5.E+055.E+04

4.E+05

4.E+04

3.E+05

3.E+04

2.E+05

2.E+04

1.E+05

1.E+040.E+00E. coli (cfu/g)

Total coliform (cfu/g)

6.E+050.E+000

5

1015Times (h)2025Fig. 1 Variations of total coliform and E. coli in activatedsludge during aeration

Fig. 3 Fluorescence EEM images of dissolved organic
matter in activated sludge during aeration
The results of this study showed that aeration can reduce
total coliform and E. coli concentrations. The concentration of
total coliform drop from 5.9×105 cfu/g to 2.7×105 cfu/g, andE. coli dropped from 6.1×104 cfu/g to 1.2×104 cfu/g.
Reduction of SCOD corresponded with the changes of in the
fluorescence EEM image. Further studies are needed to clarify
the reason why elimination of the pathogenic bacterialindicators did not continue after aeration time was further
extended, and to evaluate the changed of related enzyme
activity and microbial community structure during aeration.

REFERENCES
100

Removal (%)

80
60
40

E.coli
Total coliform

20
0
0

5

10

15

20

25

Times (h)Fig. 2 Variations in the removal of total coliform and E.
coli in activated sludge during aeration
Fluorescence EEM images—Fluorescence EEM images ofdissolved organic matter (DOM) in the water phase of theactivated sludge after aeration for different time lengths areshown in Fig. 3. DOM constituents in sewage are mainly
humus (Humic acid, Fulvic acid) and some hydrophilicorganic acids, nucleic acids and so on (Hao et al., 2007). The
strength of the peak reported to reflect protein-like substances
reduced significantly and nearly disappeared at the end of
aeration for 24 hours. The weakening extent in the strength of

Eastman , B.R., Kane, P.N., Edwards, C.A., Trytek, L.,
Gunadi, B., Stermer, A.L, Mobley, J.R., (2001) The
effectiveness of vermiculture in human pathogen reduction
for USEPA biosolids stabilization. Composting Science andUtilization 9: 38-49.
Hao R., Cao K., and Deng Y. (2007) Characterization ofdissolved organic pollutants in wastewater by threedimensional fluorescent spectroscopy. Chinese Journal of
Analysis Laboratory 26: 41-44.
Pandey, P.K., Cao, W., Biswas, S., Vaddella, V., (2016) A
new closed loop heating system for composting of green
and food wastes. Journal of Cleaner Production 133: 12521259
Sinha, R.K., Herat, S., Bharambe, G., Brahambhatt, A., (2010)
Vermistabilization of sewage sludge (biosolids) byearthworms: converting a potenital biohazard destined for
landfill disposal into a pathogen-free, nutritive and safe
biofertilizer for farms. Waste Management Research 28:
872-881.
Van der Werf, H.M.G., Garnett, T., Corson, M.S., Hayashi,
K., Huisingh, D., Cederberg, C., (2014). Towards ecoefficient agriculture and food systems: theory, proxis andfuture challenges. Journal of Cleaner Production 73: 1-9.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P15

The nitrogen cycling in a deciduous broad-leaved forest, central Japan
Ruoming Cao1, Siyu Chen2, Shinpei Yoshitake3, Chiyuki Asai1 and Toshiyuki Ohtsuka3
1. Graduate School of Natural Science and Technology
2. United Graduate School of Agricultural Science
3. River Basin Research Center
For the understory, biomass estimation need to be conductedin future.
INTRODUCTION
There is more and more nitrogen input to the forest
ecosystem by anthropogenic nitrogen deposition. This change
has disturbed the internal cycling and output of nitrogen inforest ecosystem. Excess nitrogen supply destroys the original
nutrition balance of plant and causes soil acidification anddeterioration of ground water and river. For example, the 55
kg N ha-1y-1 of nitrogen output from soil is more than 30 kg N
ha-1y-1 of annual atmosphere deposition input in a Japanesecedar forest ecosystem, indicating the disorder of nitrogen
cycling (i.e., Wakamatsu, T. et al.2001).
In this study, we measure the wet deposition of nitrogen inbulk precipitation (BP), throughfall above bamboo(TA),throughfall under bamboo(TU), stemflow(SF), litterleachate(LL) and soil solution to Takayama forest and identify
the dissolved nitrogen cycling of this forest for the first time.

MATERIALS AND METHODS
Site description—The Takayama Forest study site, adeciduous broad-leaved forest, located in the Takayama Forest
Research Station, River Basin Research Center, Gifu
University, on the central region of the main island of Japan(36°08′N, 137°25′E, 1420 m a.s.l.). The dominant trees
are Quercus crispula, Betula ermanii and Betula platyphyllavar. japonica. The forest floor is covered by a dense bamboo.
The study site has a seasonal cool-temperate climate. Annual
mean air temperature is 7.2℃, annual mean precipitation isabout 2130mm (2000-2016); snow depth is usually 1-2m in
winter (December-April).
Experimental setup—we set up the samplers of bulk
precipitation (3 replicates), stemflow (4 replicates for each of
three main species and 3 replicates of evergreen trees),
throughfall (9 replicates above bamboo and 9 replicates underbamboo), litter leachate (9 replicates) and soil solution (3replicates for each 20cm, 40cm, 60cm and 80cm below thesurface of soil) in 1 ha permanent plot and collected thesamples and measure the volumes at one time per month from
May to November 2016. At the same time, we collected thesamples from stream where water flows from forest.
Chemical analysis—After being filtering by 0.45 μ m
membrane filter, we measured the concentrations of total
dissolved nitrogen(TDN), NH4+ and NO3-+NO2- (dissolved
inorganic nitrogen DIN) by a QuAAtro 2-HR nutrient
analyzer. And dissolved organic nitrogen (DON) was
calculated by TDN-N -(NH4+-N + NO3-+NO2- -N).

RESULTS AND DISCUSSION
Ecosystem pools— Nitrogen storage in foliage and stem
was 86kg ha-1and 128×103kg ha-1, higher than other forests(Timothy J. Fahey et al., 1985, Lang et al., 1982) because of
relatively higher nitrogen concentration in foliage (2.21%).

Inputs—Wet deposition attributed 7.1 kg N ha-1 during
growing season to the forest, which is far less than otherforests (S.Izquieta-Rojano et al. 2016). Canopy leached 2.1 kg
ha-1of nitrogen. There is no obvious difference of nitrogen
deposition for throughfall between above and under bamboo.
Litter leachate contributed more nitrogen to the soil than thatin other water flux. In all, 22kg N ha-1 input to the forest by
the wet deposition during growing season. And DON was
dominant in the nitrogen species, especially for stemflow.
Internal cycling—After nitrogen input to the forest, thenitrogen was absorbed by the tree (foliage 40.4 kg ha -1, stem
2.4kg ha-1) and understory (bamboo 11.7kg ha-1). So
aboveground in forest needed 54.5kg ha-1 in 2016. The
concentration of inorganic nitrogen in soil solution was
extremely low, with most of the dissolved nitrogen beingorganic forms (0.41mg L-1).
Output—The concentrations of NH4+ and NO3-+NO2respectively are 0.04mg L-1 and 0.16 mg L-1 in stream, far lessthan most of other streams near Japanese forests (Shibata, H.
et al. 2001).
Conclusion—Wet deposition contributed 40.37% N toforest for plant uptake. And wet deposition input should not
be ignored. In other ways, more and more nitrogen supply
disturbed the nitrogen cycling of forest, however, in our study
site, nitrogen input with less air pollution is less than most offorests disturbed by more human activities. And there is lesspollution of streams.

ACKNOWLEDGMENTS
We are very grateful to the members of the Takayama
Forest Research Station for the support of field survey,
Institute for Basin Ecosystem Studies, Gifu University. And
we also really appreciate the field assistance of members of
Ohtsuka lab.

REFERENCES
Wakamatsu, T., K. Sato, A. Takahashi and H. Shibata (2001)
Proton budget for a Japanses cedar forest ecosystem. Water,Air, and Soil pollution, 130:721-726.
Timothy J. Fahey, Joseph B. Yavitt, John A. Pearson, andDennis H. Knight(1985) The nitrogen cycle in lodgepole
pine
forests,
southeastern
Wyoming.
Biogeochemistry1:257-275.
S.Izquieta-Rojano,
H.Garcia-Gomez,
L.Aguillaume,
J.M.Santamaria, Y.S.Tang, C.Santamaria, F. Valino, E.
Lasheras, R. Alonso, A. Avila, J.N. Cape ,D.
Elustondo(2016) Throughfall and bulk deposition ofdissolved organic nitrogen to holm oak forests in the Iberian
Peninsula: Flux estimation and identification of potential
sources. Environmental Pollution 210:104-112.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P15
Shibata, H., F. Satoh, K. Sasa, M. Ozawa, N. Usui,O. Nagata,
Y.Hayakawa and R. Hatano(2001) Importance of internal
proton production for the proton budget in Japanese
forested ecosystems. Water, Air, and Soil pollution,
130:685-690..

Per Gundersen(1991) Nitrogen deposition and the forest
nitrogen cycle: role of denitrification. Forest Ecology andManagement, 44:15-28.

Fig.1: Nitrogen cycling in Takayama forest. Squares indicate nitrogen pool (kg ha-1). Dotted squares indicate uptake ofnitrogen (kg ha-1 7months-1).The data in bracket show the net release of DON and DIN flux, and net contribution from eachcomponent to the total nitrogen flux.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P16

Small hydraulic generation using irrigation facilities: Case study of Meiji
Yousui district
Fenglan Wang¹, Keigo Noda², Kengo Ito² and Masateru Senge²
1.
The United Graduate School of Agricultural Science, Gifu University, Japan
2.
Faculty of Applied Biological Science, Gifu University, Japan
90% was set as the target flow rate of the maximum generation
power, and the facility utilization rate at that time was
INTRODUCTION
obtained.
Facility
utilization
rate=
actualgeneration/theoretical generation×100. Then, the criteria of
Looking at the recent various situations related in electricutilization rate in small scale hydropower was above 60%
power, oil prices have increased by about 20 times since theaccording to Inspection Committee's Report (December, 19th
first and second oil shocks, which have been causing major
in 2011) of Cost of the National Strategy. In this research, theproblems in Japan's economy and people's lives. As measure
actual annual and monthly generation were calculated whenagainst global warming by reducing CO₂, as well as because
utilization rate is 60% to evaluate the possibility of generation.
of the earthquake disaster in 2011, renewable energy such as
small hydro power generation, photovoltaic power generation,
RESULTSwind power and geothermal power generation have beendrawn attention as safe and clean energy to replace nuclear
Evaluation of potential generation in Meiji Yousui Headwork.
power. Among them, there is growing interest in smallhydropower generation, which has a small output scale but is
Fig. 1 shows the relations between the 20 years’ discharge
practical in terms of technology. Hydropower generation costs
quantity of the Headwork and excess probability(The flow rate
a considerable construction cost compared with otherat 9 a.m. every day is rearranged in descending order of thealternative energy, but maintenance and management expenses
flow rate, and the number of days exceeding a certain flow
are cheap, occupies a very important position as domestic
rate is divided by the number of days of 20 years (7, 305 days)
energy that makes the best use of Japan's weather conditions
and expressed as a percentage).
and topography conditions.
In this report, I will take a pioneering example of Meiji
Yousui as modern water facilities in Aichi prefecture andevaluate the possibilty of small hydropower generation. This
irrigation waterway intakes water from the Headwork of the
Meijiyousui placed in Yahagi River and then delivers
irrigation water to agricultural lands with using longwaterways. Because of the topographical restrictions, it does
not have an intermediate reservoir such as an adjustment
reservoir, in that case, various forms of administrative water
are generated when it intakes and divides water. In this report,
we focus on such management water and examine thepossibility and characteristics of small hydroelectric power
generation from the headworks managed by the Meiji Yousui
Land Improvement District to the end of the main water canal.
There were five research sites to be evaluated. They are Meiji
Yousui Headwork, Industrial water diversion work and three
Fig.1: Discharge quantity from Headwork.
check stands including Akamatsu, Nihongi and Higashiyamda.
MATERIALS AND METHODSIn this study, we will exmine the potential power generation
using discharge of the Meiji Yousui Headwork to thedownstream in Yahagi River, unused drop height existing in
the trunk line, distribution and administrative water occurredin each check stand and facility maintenance water occurred in
the space between Hirokute water gate and Chuto water
diversion work using the data from the Meiji Yousui Land
Improvement District. According to the flow rate (Q[m3/s])
and drop height (H[m]), power generation output (P[kw]) is
calculated as below; P＝9.8(g) × ŋ × Q ×H, g is gravity
acceleration and η is the total generation efficiency. Here, total
generation efficiency assumed as 0.72 (= generation efficiency(average value 0.9) ×waterwheel efficiency (average value 0.8)
（ Ministry of Economy, Trade and Industry, Agency for
Natural Resources and Energy · Japan Energy Foundation:
Hydro Valley Planning Guidebook, 2005:3-4）.
Flow rate of 20 years (7,305 days in total) was used. Firstly,
the flow rate corresponding to excess probability of 10% toFig.2: relations between the maximum output andutilization rate.
As we mentioned above, the annual actual generation andmonthly generation were calculated when the utilization rate is60%, and we got the maximum output as 941kW. Fig.3showsProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P16
the annual actual generation capacity and Fig.4 shows theactual monthly generation capacity.

DISCUSSION
For Meijiyosui Headwork, we obtained the considerable big
generation potential, but it does not belong to agricultural
water use. The procedure related in water right will be needed
to make power generation in practical. For industrial water
diversion work, we obtained the relatively stable potential
generation although it has the big fluctuation between
irrigation period and non-irrigation period. For check stands,
Compared to agricultural water dependent type, it is possible
to generate electricity with high facility utilization rate even it
is small scale.
Fig.3 Annual generation when the maximum output is941kW in Headwork.

REFERENCES
Tanaka Satoru (1987) Improvement of Irrigation and Drainage
System. Japanese Society of Irrigation, Drainage and RuralEngineering, 55: 5-10.
Tokai Agricultural Administration Bureau Yahagawa
Agricultural Waterworks Office, Meiji Electricity National
Government Building Land Improvement Facility
Development Project Construction magazine (1984.3).
Chunichi News, Hydroelectric power resurrection - Aichi
prefecture natural energy symbol - ( 2012. 1.3).
Fig.4 Monthly actual generation when the maximum
output is 941kW in Headwork.

Ministry of Economy, Trade and Industry, Agency for Natural
Resources and Energy · Japan Energy Foundation: Hydro
Valley Planning Guidebook, 2005:3-4.

For other research sites, calculation method is same withmethod used in Headwork. However, characteristic of using
water to make generation is different. Summary of the
maximum output, annual generation and monthly generationof each research site were showed in table below.

Ministry of Agriculture, Forestry and Fisheries Rural
Promotion Bureau: Basic information survey on agricultural
infrastructure, 2016, p.8.

Table1 Summary of the maximum output, annual
generation and monthly generation (utilization rate=60%)
Generation site
Generation capacity
Maximum output

kW

Average: ① MWh/year
Annualgeneratio STDEV: ② MWh/yearn
Ratio: ②/①DimensionlessMonthly
generationIndustrial
Check stands
Headworwater
diversionk
Higashiwork Akamatsu Nihongi yamada
941

60.4

24.7

11.2

6.5

4,944

293

144.5

45.8

33.8

944

14.8

28.4

12.7

7.9

0.19

0.05

0.19

0.28

0.23

Max: ①

MWh/month 571 (Oct.) 44.8 (Jul.)14.8 (Feb.) 4.7 (Apr.) 3.6 (Oct.)

Min: ②

MWh/month 312 (Jun.) 6.4 (Nov.) 9.1 (Jun.) 3.1 (Jun.) 1.7 (Aug.)

Ratio: ①/②Dimensionless

1.83

7.0

1.62

1.51

2.12

Ministry of the Environment: 2010 Renewable Energy
Introduction Potential Investigation Report, 2011,p.174.
Energy · Environmental Conference Cost etc. Verification
Committee: Report on Cost etc. Verification Committee,
2011,p.57.
Ministry of Land, Infrastructure and Transport Water
Management Homeland Security Bureau, Tribal for
installation of small hydropower, 2016,p.32.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P17

Seasonal difference role on sediment rating curve at small broadleaves andconiferous forest catchments in Kuraiyama, Japan
Diana Hapsari1, Takeo Onishi2, Masateru Senge2, Fumitoshi Imaizumi3, Ali Rahmat1
1. The United Graduate School of Agricultural Sciences, Gifu University
2. Faculty of Applied Biological Science, Gifu University
3. Faculty of Agriculture, Shizuoka University

INTRODUCTION
Sediment rating curve (SRC) can be defined as an averagerelation between water discharge of the stream or river (Q)and sediment concentration (SS) or sediment load (L), in a
specific study area (Warrick, 2014). It can be applied forunderstanding the soil erosion from its capability to produce
predicted long term to short term sediment concentration by
only generating water discharge data (Guzman et al., 2013).
However, the accuracy of SRC tends to underestimates theobserved load.
There are a lot of factor’s affecting the accuracy of SRC,
such as natural factors and technical factors. Natural factors
are including rainfall, topography, soil type, vegetation,season change etc. and technical factors are including
sampling methods and equation used. Higgins et al. (2016)
spelled out that during one year with four season’s period,
sediment rating curve can be separated to understand thesediment movement and load characteristic. In this paper, weare trying to focus on the seasonal different role ondifferentiating the power of SRC on two small different
watersheds.

MATERIALS AND METHODSThis research was conducted at Kuraiyama experimental
forest of Gifu University, which is located near Gero city,
Gifu Prefecture, Japan. The study area was constructed oncatchment number 10 (10林) and catchment number 12 (12林)as shown in Fig.1. The major differences between 10林 and
12 林 is on the vegetation where 10 林 consists of 75%
coniferous and 12林consists of 77% broadleaves (Quercus).

at the outlet with V-shaped weir notch per 15 minutes in
winter and 3 minutes in summer period. Suspended sedimentconcentration (SS) were measured from a 1000 ml water
sample using ISCO automatic water sampler.
The water samplers were installed at the edge of outlet tocollect water during winter every 2 days and 2 hours during
low flow and high flow, respectively, and every 2 hours
during summer on high flow. The water samples were filteredusing glass fibre filter paper with 0.45 µm effective retention.
Then it was air dried 48 hours and weighed to determine themass of sediment captured per litter of discharge.
Load estimations are derived from continuously discharge
data and SS concentration from water sampling per period
taking, as written in equation below:
Lt=Qt x SSt x A(Eq. 1)

Where Lt refers to sediment load in time t (kg area-1 time-1).
Qt is water discharge in time t (m3s-1). SSt is suspended
sediment concentration in time t (mg l-1), and A is thecatchment area (km2).
SRC is used to predict suspended sediment load to get acomplete data each month. The most popular SRC equation
used for expressing relationship between suspended sedimentand water discharge is a sediment rating curve as a result of
power function as follow:
SSp or Lp= aQb(Eq. 2)

Where SSp refers to predicted suspended sediment [mg l-1]
and Lp refers to predicted suspended sediment load [kg ha-1
hour-1], Q refers to water discharge [m3s-1]. While a and b are
empirical expression from power regression coefficients. The
rating curve will be served as a scatter form data using
logarithm scale number performed in Equation below.
Log SSp or Lp = log a + b log Q(Eq. 3)Many researchers are agree that a represents an erosion
severity index and b represents an erosivity power of the river(Asselman, 2000).
Three kinds of evaluation will be used to judge which
equation performs better result on sediment concentration
prediction, which are Root Mean Squared Error (RMSE),
Pearson’s Correlation Coefficient (PCC) and Nash-Sutcliffe
Model Efficiency Coefficient (NSE). Evaluation of SRC isbased on all completed water sampling data which are takenfrom February 2015 – October 2015.
Figure 1. Research study area in Kuraiyama
Experimental Forest of Gifu University, Gero City, Gifu
prefecture, Japan. Upper side is the study area for 10林
and down side is 12林.
Water discharge (Q) were calculated from air and waterpressure data directed from HOBO-U20 logger measurement

RESULTSSS during summer are higher than winter – snowmelt
period, and 10林 has higher SS than 12林 at the same
sampling hour (Fig. 2) in average. General data sets (Fig.3),
which is taken from all sampling data shows that SRC whichleads from Load data produce higher coefficient ofProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P17
determination value (R2) than SS data based. To strengthen
the R2 value, the general load data of SRC will be divided
seasonally, winter and summer. The results are shown in Fig.
4-5.

event summer data based. Black line is SS data based,
stripped green line is Load data based.

Figure 2: The comparison of suspended sedimentconcentration (SS) at 10林 (X-axis) and 12林 (Y-axis),
taken from the same hour sampling period data.
Figure 5: Seasonal SRC from 12林 in logarithm scale.
X-axis is log Q [m3s-1], Y-axis is log SS [mg l-1]. (From left
to right) Up: all winter data based, all summer data based.
Middle: high flow winter data based, high flow summer
data based. Down: peak event winter data based, peak
event summer data based. Black line is SS data based,
stripped green line is Load data based.

DISCUSSION

Figure 3: SRC from all sampling data based inlogarithm scale. X-axis is log Q [m3s-1], Y-axis is log SS[mg l-1]. (From left to right) Up: SS data based, Load data
based from 10林. Down: SS data based, Load data based
from 12林.

It is obviously that SRC produces from Load data havehigher R2 value than from SS data. This can be said that the
SS data taken has a high variation so that weaken the power of
SRC. Seasonal separation affect SRC produces from SS
significantly. However, it does not affect much for SRC
produces from Load. On the other hands, due to the number ofsample, SRC produces on summer tends to have a stable SRC
than winter. We can conclude that season plays an importantrole on differentiating Q and SS relation. Other than that, area
apparently divine to be one of important factor to get moreaccurate of SRC.

REFERENCES

Figure 4: Seasonal SRC from 10林 in logarithm scale.
X-axis is log Q [m3s-1], Y-axis is log SS [mg l-1]. (From left
to right) Up: all winter data based, all summer data based.
Middle: high flow winter data based, high flow summer
data based. Down: peak event winter data based, peak

Asselman, N.E.M. (2000) Fitting and Interpretation of
Sediment Rating Curves. Journal of Hydrology 234: 228248
Guzman, C.D, Tillahun, S.A, Zegeye, A.D and Steenhuis, T.S.
(2013) Suspended Sediment Concentration – Discharge
Relationship in the (sub-) Humid Ethiopian highlands.
Hydrology and Earth System Sciences 17: 1067-1077
Higgins, A., Restrepo, J.C., Ortiz, J.C., Pierini, J. and Otero,
L. (2016) Suspended Sediment transport in the Magdalena
River (Colombia, South America): Hydrologic Regime,
Rating Parameters and Effective Discharge Variability.
International Journal of Sediment Research 31: 25-35
Warrick, J.A. (2014) Trend Analyses with River Sediment
Rating Curves. Hydrological Processess: Wiley Online
Library. DOI: 10.1002/hyp.101.98

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P18

Effects of thermal treatment on the release of organic matter fromwastewater sludge.
Ran Song1, Guangyu Cui1, Huijuan Shao2, Shuailei Li3, and Fusheng Li4
1.
Graduate School of Engineering, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan
2.
The United Graduate School Of Agriculture Science, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan
3.
Graduate School of Natural Science and Technology, Gifu University,1-1 Yanagido, Gifu 501-1193, Japan
4.
River Basin Research Center, Gifu University, 1-1 Yanagido, Gifu 501-1193, JapanINTRODUCTION
Activated sludge process is an effective biologicaltreatment method widely used in wastewater treatment. The
production of wastewater sludge is an inevitable drawback
inherent to the conventional wastewater treatment process(Sun et al., 2016). Excess activated sludge treatment anddisposal constitutes for 50 - 60% of total operation costs
needed for most wastewater treatment plants (L. Otero et al.,2008). Meanwhile the large quantity of excess activatedsludge may cause a series of environmental problems if notproperly handled. It is thus essential to find more efficient
treatment approaches.
Activated sludge is mainly composed of microorganisms
and extracellular polymeric substances (EPS). Extracellularpolymeric substances are a complex of lager molecularpolymers excreted by microorganisms during cell lysis anddecomposition (Sheng et al., 2010). In general, EPS accounts
for 50% to 90% of the total organic matters in waste activatedsludge (He et al., 2007), and is mainly composed of proteins,polysaccharides and nucleic acids (Lee et al., 2010). Dissolved
organic matter (DOM), including EPS, remaining in the waterphase after sludge treatment is also a great concern needs
addressed because it greatly affects the water quality ofreceiving water bodies.
Anaerobic digestion is an efficient method for sewage
sludge stabilization. It involves the following stages:hydrolysis, acidogrnesis and further degradation. Hydrolysis is
the rate-limiting step of the overall process owing to the timeneeded for solubilisation of particulate matter to occur. As
EPS obstructs sludge hydrolysis, various methods have beenstudied aiming to accelerate the rate of disruption andbreakdown for the floc structure and cells of sludge. Thermal,
chemical, mechanical and physical methods are likely
pretreatment processes (Sun et al., 2016). Thermal treatment
could break the polymeric network resulting in the release of
extracellular and possibly intracellular materials such asprotein, polysaccharide and some nucleic acid into the soluble
phase. It has been reported that thermal treatment at 150 ºC
could enhance the dewatering ability of activated sludge, andfurther increase the temperature to the 180 ºC could lead to amore pronounced effect. However, as an adversary effect, theformation of refractory COD compounds at higher thermal
treatment temperatures, which could reach about one third of
the total soluble COD in the water phase of the sludge, wasalso reported (Fisher et al., 1971). In a recent research, theeffects of heat pretreatment on dissolved organic matter andstructural and functional properties of organics in EPS wasinvestigated. It was found that the release of fluorescenceintensity and percent fluorescence response of easily
biodegradable soluble microbial byproducts were enhanced,
and meanwhile, non-biodegradable fulvic acid-like substance
was also accumulated after treated at 80 ºC for 25 minutes(Sun et al., 2016).
In this study, effects of thermal treatment on DOM
released and remaining in the water phase of activated sludge

were investigated, by focusing mainly on the quantity andcomposition in the pretreatment process under different
temperature conditions.

MATERIALS AND METHODS
Source and characteristics of activated sludge
Activated sludge was the returned sludge obtained from
Hokubu municipal wastewater treatment plant of Gifu-city,
Japan. The characteristics are shown in Table 1.
Table 1. Characteristics of sludge used in experiments
EC
SV
SCOD
Item
pH
(mS/m)(%)(mg/L)
Value
6.23
28
50
87.33
TS
VS
MLSS
MLVSS
Item
(mg/L)(mg/L)(mg/L)(mg/L)
Value
6420
4670
5626.674325.3Treatment conditions
Thermal treatment temperatures were 55, 70, 85, 100, 115
and 130 ºC, and time lengths were 10, 30, 60 and 120 minutes,
respectively. For treatment under 55, 70, 85 and 100 ºC, water
bath was used; for the treatment under 115 and 130 ºC,
autoclave was used.
Analysis
For each treatment, sludge was sampled and centrifuged at
5000rpm for 10 min. The obtained supernatant after filtration
through 0.45 um cellulose acetate membrane was subjected toanalysis for COD, TOC, UV260 and fluorescence EEM. TOC
was analyzed with a total organic carbon analyzer (TOC-V ws,
Shimadzu Co), UV260 with a UV-visible spectrophotometer(Model UV-1600, Shimadzu Co.), and the fluorescence EEM
with a fluorescence spectrophotometer (RF-5300, Shimadzu
Co.). For TS, VS, SS and VSS, they were measured
following standard gravimetric methods.

Results and Discussions
For treatment under 85 ºC for 60 min (Fig. 2), themaximum reduction of TS and VS was 15.1% and 24.2%
respectively. The reduction of SS, VSS was 25.0%, 29.1%
under130 ºC for 30 min (Fig. 3). The settling ability of sludge
showed a remarkable change after treatment: SV reached100% and the treated sludge did not settle when temperature
was elevated to 115 and 130 ºC.
The effects of heat treatment on the SCOD are shown in
Fig. 1 the trend of SCOD is basically the same as TOC. For
the raw sludge before thermal treatment, SCOD was 87.33
mg/L; however, after thermal treatment under 130 ºC for 120
min, the corresponding values increased to 2363 mg/L.
Thermal treatment could breakdown the cell wall and rupture
cell membrane of microorganisms in the waste sludge,
resulting in enhanced release of organic matter to the waterphase of the sludge.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P18
For the effect of treatment time lengths, as could be seenfrom Fig. 4 showing the results for the treatment under 85 ºC
as examples, the fluorescence intensity of Region І(Tryptophan-l like protein) and Region ІІ (soluble microbial
by-product) showed a trend of increase as the treatment timeincreased from 10 to 60 mins and then decreased after 60 min.

It thus suggested that the tryptophan-like proteins andsoluble microbe by-products were degraded at higher
temperatures. Moreover, higher temperatures may cause
conformational changes in protein structures and may enhance
the adhesion of proteins.

Fig. 1 Changes of SCOD concentration after treated at
different temperature. 0 min is the control group.
For the temperature effect, the fluorescence intensity ofRegion І (Tryptophan-l like protein) and Region ІІ (soluble
microbial by-product) increased with the increasing of thetemperature from 55 ºC to 70 ºC, and then decreased from 85º
C to 130 ºC. The intensity of Region І and Region ІІ under 70ºC for 60 mins was much higher than treatment under othertemperatures.
30

TS
VS

Reduction (%)

25

Fig. 4 Fluorescence EEM images of DOM after thermal
treatment under 85 ºC for different time lengths. Region І
was reported reflecting Tryptophan-like protein andRegion ІІ soluble microbial by-product.

20

15

10
10

30

50

70

T(min)

90

110

130

Fig. 2 Reduction of TS and VS after thermal treatment
under 85 ºC for different time lengths.
35
SS
Reduction(%)

30

VSS

25
20
15
10
10

30

50

70
T(min)

90

110

130

Fig. 3 Reduction of SS and VSS after thermal treatment
under 130 ºC for different time lengths.

Thermal treatment of activated sludge enhanced therelease of organic matter to the water phase and reduced thecontent of SS.

References
J. Sun, L. Guo, Q. Li. (2016) Structural and functional
properties of organic matters in extracellular polymeric
substances (EPS) and dissolved organic matters (DOM)
after heat pretreatment with waste sludge. Bioresource
technology 219:614-623.
J. Zhang, X. CAI, L .Qi (2015a). Effects of aerationstrategy
on the evolution of dissolved organic matter and microbialcommunity structure during sludge bio-drying. Appl.
Microbiol. Biotechnol. 99 (17), 7321–7331.
R.A. Fisher, S.J. Swanwick. (1971)High temperature
treatment of sewage sludges, Water Pollut. Control 71:
255–370.
P. He, G. Yu, L. Shao (2008) Effects of proteins andpolysaccharides in sewage sludge on dewater ability,
Environmental science 29(12), 3457-3461.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P19

Seismic risk evaluation of irrigation tanks-Case study of two irrigation tanks in Ibigawa-cho, Gifu Prefecture, JapanChen Fang1, Hideyoshi Shimizu2, Shin-Ichi Nishimura2, Ken Hiramatsu2, Takeo Onishi2 and Tatsuro Nishiyama2
1. The United Graduate School of Agricultural Science, Gifu University
2. Faculty of Applied Biological Sciences, Gifu University

INTRODUCTION
Landslides are one of earth’s most serious types of natural
disasters and they are often induced by earthquakes. The
majority of infrastructural damage and loss of life is ascribed
to landslides brought about by great earthquakes. In Japan,
there are more than 200 thousand irrigation tanks, many ofwhich were built up to 200 years ago. In addition, due todestructive earthquakes that occur frequently, the sliding
phenomenon has been affecting many of these tanks. Once alandslide occurs, it will cause great damage to the economy
and people’s lives. Moreover, even for the irrigation tanks
which do not fail, relative movement takes place in theembankments and the tanks will fail more easily when thenext large earthquake strikes. Many scientists (Jibson, 2011;
Torii, 2008) have made comparisons between the Newmark
method and other methods for the slope stability analysis, andconcluded that the Newmark method is better for practicaluse. This paper provides a seismic risk evaluation of irrigation
tanks from the viewpoint of the maximum vertical settlement(MVS) by the Newmark method after obtaining the strengthparameters with the Bromhead ring shear apparatus.

MATERIALS AND METHODS
1. Study area
The samples were taken from Tanigumi Pond and Sugo
Pond. Both ponds are located in Ibigawa-cho, Gifu Prefecture,and both irrigation tanks are of the homogeneous type. The
dimensions of the tanks are listed in Table 1.
Table 1: Dimensions of irrigation tanks
Specimens
Tanigumi Pond
Sugo Pond
Height (m)
12.8
10.0
Crest width (m)3.2-3.7
4.1
Full water level (m)
10.23
8.01
Water storage capacity (m3)37,40020,000Specific density (g/cm3)
2.63
2.61
Saturated unit weight (kN/m3)
20.7
20.7
Soil typeSF*
F**SF: Fine-grained soil mixed sand; F: Fine soil (According to
the Japanese Unified Soil Classification System)

situation, peak frictional angle
and cohesion
under apeak strength situation), among the multiplicity of ring shear
apparatuses reported by scientists (Bishop et al., 1971;
Hvorslev, 1939), the Bromhead ring shear apparatus
developed by Bromhead is becoming widely used due to its
simplicity in operation, its reasonable cost and its availability
compared to previous models.
The main factor affecting the residual strength measured
with the Bromhead ring shear apparatus is the magnitude ofwall friction that develops along the inner and outercircumferences of the specimen. The farther the top porous
stone settles into the specimen container, the more wall
friction that develops on the shear plane and the higher themeasured residual strength. If the total settlement of the top
platen is less than 0.75 mm, the increase in shear stress with
continued displacement should not be significant. During theexperiment, if the total settlement is over 0.75 mm, the sample
has to be recompressed.

2.2 Slope stability analysis
It is possible to determine the amount of slope settlement ina short time because only a few parameters are required forthe calculation when using the Newmark method. Many
scientists prefer to use the Newmark method when designing
irrigation tanks or conducting risk evaluations for irrigation
tanks because of this advantage.
The Newmark method (Newmark, 1965) is a method for
determining the residual displacement on the arc slope
surface, for example, on the slope surface of irrigation tanks,
and for judging whether the amount of residual displacement
falls within the allowable range or not.
A seismic risk evaluation of an irrigation tank is analyzed
by the Newmark method with representative data from threeearthquakes, i.e., Great Hanshin Earthquake, Chuetsu
Earthquake and Iwate-Miyagi Nairiku Earthquake. To analyze
the seismic components, the NS and EW components aretaken into consideration.
In addition, the crest width in Tanigumi Pond varies from
3.2 m to 3.7 m. The safety of an irrigation tank increases as
the crest width increases. Therefore, the authors will analyze
the slope using a crest width of 3.7 m, and try to find out how
much the MVS will be from the viewpoint of safety.

2. Methodology
2.1 Bromhead ring shear test procedure
Compared with the direct shear apparatus, the main
advantage of the torsional ring shear apparatus is that it shears
the soil continuously in one direction for any magnitude ofdisplacement. This allows for the full orientation of the clay
particles parallel to the direction of shear and for thedevelopment of a true residual strength condition (Stark et al.,1992). To determine the shear strength parameters (residual
frictional angle, cohesion

under a residual strength

RESULTS
3.1 Residual strength parameters
The residual strength has been reached for every sample.
The value of parameters are shown in Table 2. It is easily seenthat the residual frictional angle and cohesion of theunsaturated samples from Tanigumi Pond and Sugo Pond are
all lower than those of the saturated samples.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P19

3.2 Slope stability analysis
In the slope stability analysis results, only the
representative figures for the vertical settlement amount are
input here for the earthquake data for each irrigation tankshown in Figure 1. It is found that the MVS of each irrigation
tank obtained with the Newmark method is very large when agreat earthquake strikes.

(a) Great Hanshin Earthquake (NS)

Table 2: Results of Bromhead ring shear tests
Specimens
Watercondition
(°)
(kPa)
(°)
Tanigumi
Saturated
34.4
0.7
36
Pond
Unsaturated
28.7
0
36
Sugo
Saturated
32.4
1.5
32.5
Pond
Unsaturated
27.5
0.8
31.7

(b) Chuetsu Earthquake (EW)

(kPa)
13
13
2.1
4.0

(c) Iwate-Miyagi Nairiku Earthquake (EW)

Fig.1: Vertical settlement amount by Newmark method

DISCUSSION
4.1 Residual strength
Many scientists agree that the residual frictional angle andcohesion will decrease with an increasing water content incommon soil. However, it is found that the residual strengthparameters (residual frictional angle and cohesion) of saturated
samples are higher than those of unsaturated samples in eachsoil from Tanigumi Pond or Sugo Pond. The difference in soil
texture may perhaps come from the irrigation tank and thedegree of compaction during the ring shear tests. Future work
should be done to illuminate this relationship.
4.2 Slope stability analysis
As for the permissible amount of displacement for a highembankment, no clear permissible range has yet been
established. Tokida et al. (2009) took the Chuetsu Earthquake
and the Iwate-Miyagi Nairiku Earthquake as references andpresented evaluation criteria for the seismic performance ofroad embankments. Their rank classification has four stages. In
rank 1, if the MVS is less than 2 cm, safety can be ensured and
it is feasible for cars and people to pass. In rank 2, if the MVS
is more than 2 cm and less than 25 cm, the slope surface does
not appear on the roadway portion as it will stop on theshoulder. It would not be good to travel along the road, but it isrelatively easy to ensure safety. In rank 3, if the MVS is morethan 25 cm and less than 50 cm, and the slope surface appearson the road, it is somewhat difficult to ensure safety. In rank 4,
if the MVS is more than 50 cm, it is difficult to perform
emergency restoration and the road must be closed.
Therefore, from the data on slope stability analyses in
Tanigumi Pond and Sugo Pond, the MVS for every tank has
been obtained as more than 20 cm when a great earthquake
occurs. In some cases, the MVS is even more than 50 cm,
which means the safety of the irrigation tank can’t be ensured.

In addition, for Tanigumi Pond, the height from the crest to
the full water level is 2.57 m, but when a great earthquake
strikes, the MVS is about 90 cm. And for Sugo Pond, theheight from the crest to the full water level is only 1.99 m, butwhen a great earthquake strikes, the MVS is more than 60 cm,
which is more dangerous.

REFERENCES
Jibson, R.W. (2011): Methods for assessing the stability ofslopes during earthquakes-A retrospective, Engineering
Geology, Vol. 122, Issues 1-2, pp. 40-44.
Torii, T (2008): Study on mechanism of collapse occurrence
caused by earthquake and risk assessment in highembankment and normal slope. Ph.D. Thesis, Kobe
University. (In Japanese).
Stark, T. D. and Vettel, J. J. (1992): Bromhead ring shear test
procedure, Geotechnical Testing Journal, Vol. 15, No. 1,
pp. 24-32.
Bishop, A. W., Green, G. E., Garga, V. K., Andresen, A. and
Brown, J. D. (1971): A new ring shear apparatus and its
application to measurement of residual strength,
Geotechnique, Vol. 21, No. 4, pp. 273-328.
Hvorslev, M. J. (1939): Torsion shear tests and their place inthe determination of the shearing resistance of soils,
Proceedings of American Society Material 39, pp. 9991022.
Newmark, N. M. (1965): Effects of earthquakes on dams andembankments, Geotechnique, Vol. 15, No. 2, pp. 137-160.
Japan Meteorological Agency webpage:
http://www.jma.go.jp/jma/index.html
Tokida, K. and Oda, K. (2009): Consideration on the directionof seismic performance evaluation of road embankment,
Proceedings of the Society of Civil Engineers, Vol. 65, No.
4, pp. 857-873. (In Japanese).

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P20

Malodor emission of activated sludge from municipal wastewater
treatment process after inoculation with sludge from a slaughtering housewastewater treatment facility
Guangyu Cui1, Manami Mori2, Yasushi Ishiguro2, Fusheng Li2
1. Graduate School of Engineering, Gifu University, Japan
2. River Basin Research Center, Gifu University, JapanINTRODUCTION
Malodor emission is a common phenomenon in many
wastewater treatment plant (WWTP), affecting the living
environment for people living around WWTP. How to lessen
or eliminate malodor emission has been a topic consistently
attracting the attention of both researchers and WWTP
managers. Main malodorous compounds generated during
wastewater and sludge treatment in WWTP include hydrogensulfide, mercaptan and ammonia. There are many factors, suchas the treatment process configuration, operating parameters(F/M ratio, hydraulic retention time, sludge retention time,etc.) and weather conditions, that affect the occurrence of
malodors. A recent investigation led to an interesting findingthat there is a slaughtering house WWTP whose sludge does
not release smell that people’s olfactory could detect evenplaced under normal environmental condition for months.
Although the reason has not been clarified, the difference ofthe sludge with sludge from municipal WWTPs in theproperty and composition of microorganisms, the main
constituting components of activated sludge, is highly
possible. The existence of specific bacterial species in thesludge that may possess the capability to decompose smellcausing compounds or precursors (Gerardi, 2006) is also
possible. In this study, laboratory scale semi-sequencing batch
experiments were conducted to investigate the occurrence of
malodors from municipal WWTP sludge after inoculation withthe sludge from the slaughtering WWTP at different ratios.
The microbial community structure was also evaluatedthrough PCR-DGGE analysis.

USA) after water samples were filtered through cellulose
membrane with pore size of 0.45 µm.
In order to fully reflect the malodorous gas release potentialof sludge, the malodorous gas test was carried out in anaerobic
conditions. In detail, centrifugation was performed and 10 g ofsludge after centrifugation was added into a 500 mL gas
collection bag. The gas collection bag was then filled withpure nitrogen gas and tightened with a lid to maintainanaerobic conditions inside the bag. The malodorous gas
release was allowed for 16 days at room temperature of 20°C.
The concentrations of three representative malodorous gases
in wastewater treatment (H2S, CH3SH, and NH3) were
determined using gas sampler (GASTEC, Japan) on the 4th,
8th and 16th day of the test, respectively. Bacterial community
was analyzed according to the PCR-DGGE method with somemodifications. To reduce error, the malodorous gas test foreach sludge sample was conducted in triplicate.

RESULTSSCOD in treated water—As shown in Fig. 1, SCOD in thetreated water of reactors inoculated with the slaughtering
house sludge was significant higher than that of others
reactors with different mixing ratios of this sludge with themunicipal WWTP sludge that displayed similar trends inchanges of SCOD. This result indicated that when slaughter
house sludge was inoculated, keeping the municipal activatedsludge above 30% did not affect the removal for dissolved
organic matter.
80

MATERIALS AND METHODS

Experimental setup—Reactors containing municipal
activated sludge respectively inoculated with different ratiosof slaughtering house sludge (SS) (100%, 70%, 50%, 30%
and 0%) were set up. One cycle of the experiment included
aerobic reaction for 8 hours and sedimentation for 2 hours.
Raw wastewater used for the experiment was taken from themunicipal WWTP. In order to maintain stable MLSS, 10% of
sludge was withdrawn for each reactor every day. The wholeexperimental process lasted for 1 month.
Analysis—Soluble chemical oxygen demand (SCOD) in thetreated water was determined using the COD test kit (Hach,

ＳCOD（mg/L）

60

Municipal sludge and slaughter house sludge—Municipal
sludge was sampled from a municipal WWTP of Gifu, Japan.
Slaughter house sludge was sampled from the slaughtering
house WWTP whose sludge does not release smell, also
located in Gifu, Japan. The initial MLSS concentration forthese types of sludge was 2389 mg/L and 6424 mg/L,
respectively; and the corresponding ratio of MLVSS/MLSS
was 0.73 and 0.93. The sampled sludge was settled naturally
for 2 hours in laboratory and the concentrated sludge was used
for the experiment.

40

20

0
11/1

11/5
SS-100%11/9
SS-70%

11/13

11/17

SS-50%

11/21
SS-30%

11/25

11/29

SS-0%

Fig. 1 Variations of COD in treated water for five reactors
Malodor emission— NH3 for all reactors were not detected.
The concentrations of H2S and CH3SH released within 3 time
periods of the sampling process were displayed in Fig. 2. The
concentration of H2S decreased when semi-sequencing batch
reactors were added with higher ratios of the slaughtering
house sludge. The lowest released concentration of H2S was
found in the reactor inoculated with only slaughtering housesludge. On the other hand, the reactor inoculated with only
municipal sludge represented the highest concentration of
CH3SH, while CH3SH was hardly detected in the reactor
inoculated with only slaughtering house sludge. Based onlevel of malodor released, it was found that the relative
concentration of H2S was higher than that of CH3SH during

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P20

H2S concentration mg/kg

SS- 0%

SS- 30%SS- 70%SS- 50%SS-30%
屠畜0%

SS- 0%

SS-30%
屠畜30%

SS- 100%

SS-50%
屠畜50%

Nov. 30

SS- 30%SS-70%
屠畜70%

BA

SS- 50%SS-100%屠畜100%

Oct. 28

SS- 70%4032during aerobic degradation process, which can be affected by
the operation conditions of the treatment plant (including
hydraulic retention time, sludge retention time, F/M ratio, etc.)
and needs clarification in coming studies.

SS- 100%

the whole experiment. It is reported previously that people are
more sensitive to CH3SH (threshold: 0.00007 ppm) that H2S(threshold: 0.00014 ppm) (Nagata, 2003). It is thus referablefrom our results that the inoculation of slaughtering house into
municipal WWTP sludge may attenuate emission of CH3SH
that people’s olfactory sense reacts strongly.

24

16

1
8

0
4th

8th
16th
Oct. 31

4th

8th
16th
Nov. 19

4th

8th
Nov. 30

16th

CH3SH concentration mg/kg

14
12

2

10
8
6
SS- 0% (Oct. 28)

4
2
0
4th

8th
Oct. 31

16th

4th

8th
16th
Nov. 19

4th

8th
Nov. 30

16th

Fig. 2 Variations of H2S (A) and CH3SH (B) released fromthe sludge generated at the different stages of municipal
wastewater treatment in the experimentBacterial community structure—Malodor emission has aclose relationship with the property and composition of
microbial community in the sludge. The DGGE finger printingof 16S rDNA bacterial fragment and its cluster analysis are
given in Fig. 3. The raw slaughtering house sludge exhibited
difference in bacterial community structure with the raw
municipal sludge, especially for band 1 and band 2 because
they not only have higher signal intensities but also only exist
in the raw slaughtering house sludge. At the end of theexperiment, the two specific bands still appeared in the sludgeof all reactors except the municipal sludge reactor.
Furthermore, sequencing result showed that band 1 and band2 are affiliated to uncultured Rhodocyclaceae bacterium anduncultured Chloroflexi bacterium, separately. Rhodocyclaceae
bacterium exhibits very versatile metabolic capability andplays an important role in biological degradation in
wastewater treatment plant; while Chloroflexi bacterium canscavenge organic substances derived from anammox bacterial
cells (Kindaichi, et al., 2012). This suggests that, bothbacterial species are not directly involved in the abatement of
malodorous gases. Additionally, the cluster analysis of the
DGGE images reveals that the sludge in three municipal
sludge reactors added with the slaughtering house sludge haveclose bacterial community diversity with the sludge inmunicipal sludge reactor. This further implies that theobserved attenuation effect in the emission of malodors was
not a direct result of microbial community; rather, it wasprobably related to the physicochemical features of sludge,i.e., the activity and decaying situation of the microorganisms

BenchmarkShannon
index

3.08

SS- 70% (Nov. 30)

3.19

SS- 0% (Nov. 30)

2.92

SS- 30% (Nov. 30)
SS- 50% (Nov. 30)

3.10
3.26

SS- 100% (Oct. 28)

3.34

SS- 100% (Nov. 30)

3.15

SS- 70% (Oct. 28)

3.31

SS- 30% (Oct. 28)

3.41

SS- 50% (Oct. 28)

3.41

Fig. 3 DGGE image of 16S rDNA fragment and its cluster
at the start and end of the experiment
In conclusion, higher ratios of the slaughtering housesludge inoculated in the municipal activated sludge reactor
lead to lower concentration of H2S. Similar bacterial
community structures were found in all activated sludge ofreactor except reactor containing the slaughtering housesludge alone, suggesting that bacterial structures evaluatedbased on 16S rDNA was not the key factor that could
explain the diminishing effect on malodor emission fromthe slaughtering house sludge and the municipal sludge
after inoculated with the slaughtering house sludge tested inthis study.

REFERENCES
Gerardi, Michael H. Wastewater bacteria. Vol. 5. John Wiley& Sons, 2006.
Nagata Yoshio. Measurement of odor threshold by triangle
odor bag method. Odor measurement review 118 (2003):
118-127.
Kindaichi Tomonori, et al. Ecophysiological role and functionof uncultured Chloroflexi in an anammox reactor. Water
Science and Technology 66.12 (2012): 2556-2561.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P21

Hydrological characteristics under different vegetation types in small
watershed, Central Japan
Ali Rahmat1, Keigo Noda2, Kengo Ito2 and Masateru Senge2
1. The United Graduate School of Agricultural Science, Gifu University1
2. Faculty of Applied Biological Science, Gifu University, Japan2
Fig. 2 rising limb and falling limb of water discharge in theevergreen coniferous forest is faster than deciduous broadleaf.
INTRODUCTION
high precipitation, discharge peak in the evergreen coniferous
forest is higher than deciduous broadleaf forest. In this case,Land use changes have big impact on hydrologic cycle atthe lag time between the peak of rainfall to a peak of
the watershed level (Chen, et al., 2009). Soil, topography, anddischarge in the deciduous broadleaf forest and an evergreen
land cover are three primary watershed characteristics thatconiferous forest is same (one hour).
govern rainfall-runoff-erosion response in watersheds.
Therefore, the response of watershed hydrology will be varied
over time depends on changes in the distribution and types ofland cover (Miller et al., 2002). The change of land cover may
influence evapotranspiration, canopy interception, percolationand eventually promote flood or drought disaster (Chang,2007, Chen et al., 2009, Lin et al., 2015). The hydrologicalcycle inside of forest was strongly influenced by change ofvegetation (the type or canopy coverage) (Swank andDouglass, 1974; Bosch and Hewlett, 1982). The availability of
information the effects of changes in land cover management
or vegetation management on water quantity and water quality
Fig. 1: Flow duration curve (log interval) from 2008-2016
is a valuable component in developing catchment
in No.12 and No.10 basin.
management policies. In this paper will explain about
relationship of vegetation types on hydrological characters.

MATERIALS AND METHODSThe Kuraiyama experimental forest is located in Gero City,
Gifu Prefecture, Japan. The investigation carried out in No.10(evergreen coniferous forest) and No.12 (deciduous broadleaf
forest). There is a right triangle weir has been built at eachstream of basin and data logger has been placed at the bottomof stream. Data logger is HOBO-U20. The data recorded wasfrom 2008 to 2016. Record interval is 5 or 3 minutes insummer and 15 or 20 minutes in winter. The precipitation datacollected using tipping bucket rain gauge, has been placed in
No.12 basin. Yearly base flow index (BFI) has been
calculated as a predictor. It is as the ratio of average annual
minimum daily flow over the average annual daily flow.
BFI is a measure of the amount of flow in a river during dry or
low flow periods.
No.10 basin forest is an evergreen coniferous forest of
Chamaecyparis obtuse (dominant). The area is 0.6 km2. 74%of the basin is covered by 40-50 years old artificial coniferous
forest, 18% are broadleaf forest and 8% are a naturalconiferous forest. The No.12 basin forest is a deciduous
broad-leaved forest of Quercus sp (dominant), the area is
0.73km2. 77% of the No.12 basin is covered by deciduous
broadleaf forest, 14% is covered by 50-70 years old artificial
coniferous forest, and 9% is covered by natural coniferous
forest. The ground is also covered with a high density of bush,sasa bamboo grass, and litter layer.

Fig. 2: Peak discharge in No.12 and No.10 basin at 22-23
July 2015.

RESULTSThe flow duration curve is a plot that shows the percentageof time that flow in a stream is likely to equal or exceed somespecified value of interest. The flow duration curve is one way
to look water discharge condition. Based on Fig.1 and T-test,
water discharge in the deciduous broadleaf forest issignificantly higher than evergreen coniferous forest. From

Fig. 3: Relationships peak discharge in No.12 and No.10
basin at 2014.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P21

Fig. 4: Relationships runoff coefficient in No.12 andNo.10 basin at 2014.

Leaf shape and configuration affects water storage (Horton,
1919). Some leaves only store water as a thin coating whilst
others also store capillary spaces between leaves. For thisreason, flat leaves (deciduous species) store less than trees thathave clumped leaf patterns like trees with needles (coniferous)(Keim, et al., 2006).
About peak discharge was mention before if the rising limb
and the falling limb in the evergreen coniferous forest were
faster than deciduous broadleaf forest and also runoff
coefficient in the evergreen coniferous forest were higher thandeciduous broadleaf forest. Could be the reason is thecharacteristic of forest floor in both basins is different.
In method was mention, one of the characteristic No.12
deciduous broadleaf forest basin, in the ground/forest floor
growth many sasa bamboo grass and other grass, existence ofsasa bamboo grass make roughness of forest floor and candelay or decrease speed of surface flow, and bamboo species
have well developed root systems (Kawai et al, 2008) and theroot systems would enhance preferential flow in the soil
(Johnson and Lehman, 2006; Liang et al., 2011). Chang(2013), mention the root systems, organic matter, and litter
floor increase the infiltration rate and soil moisture (water
holding capacity). Therefore, many waters from precipitation
will saved in aquifer area and will released as groundwater(base flow) when rainfall not occurs or in winter season, andmake base flow index in deciduous broadleaf forest higher
than evergreen coniferous forest.

REFERENCE
Fig. 5: Yearly base flow index in No.12 and No.10 basin.
From Fig. 3 and Fig. 4 Show if peak discharge and runoff
coefficient in an evergreen coniferous forest is higher than in
the deciduous broadleaf forest. Yearly base flow index in a
deciduous broadleaf forest higher than coniferous forest andconsistencies from 2008-2016 (Fig.5).

DISCUSSION
The Canopy character of the evergreen coniferous forest is
the leaf always green a year, but different with deciduous
broad leaved forest they lose the leaf in autumn season andgrow in the spring season. From this condition loss of leaf inautumn season give positive impact in winter season for
deciduous broad leaved forest. Because lost the leaf in thedeciduous forest, many snows can reach to the ground and alittle amount of snow in the trees, and opposite in coniferous
forest, lots of snow in trees (trapped/blocked by the canopy),
and a little amount of snow on the ground. This phenomenon
is the first factor why water discharge in deciduous broadleaf
was greater than coniferous forest, because snowpack will
melt and be water discharge.
Furthermore, the different structure and tree species will
make different on rainfall interception/ canopy interception/
forest interception. Forest canopies stand up in the air, serving
as a barrier against precipitation reaching the ground. A
portion of precipitation is inevitably intercepted by the canopy(canopy interception), flow along the stem to the groundsurface (stem flow), drips from the foliage and branches orpasses through canopy openings to the ground (through fall),or is further intercepted by forest floor (litter interception).
These processes cause a reduction in precipitation quantityand a redistribution of precipitation toward the soil.

Chen, Y., Xu,Y., and Yin, Y., (2009) Impacts of land usechange scenarios on storm-runoff generation in
Xitiaoxi basin, China. Quaternary International.
208:121-128.
Miller, SN., Kepner, W.G., Mehaffey, M.H., Hernandez, M.,
Miller, R.C., Goodrich, D.C., Devonhold, K.K.,
Heggem, D.T., Miller, W.P. (2002) Integratinglandscape assessment and hydrologic modeling forland cover change analysis. Journal of theAmerican Water Resources Association. 38 (4):915-929.
Chang, H. (2007) Comparative streamflow characteristics inurbanizing basins in the Portland Metropolitan
Area, Oregon, USA. Hydrol. Process., 21 (2): 211222.
Lin, B., Chen, X., Yao, H., Chen, Y., Liu, M., Gao, L., James,
A. (2015). Analyses of landuse change impacts oncatchment runoff using different time indicators
based on SWAT model. Ecological Indicators,
Volume 58, 2015, Pages 55-63.
Swank, W.T., Douglass, J.E. (1974) Streamflow greatly
reduced by converting deciduous hardwood stands
to pine. Science. 185: 857–859.
Bosch J.M. and Hewlett J.D. (1982) A review of catchment
experiments to determine the effect of vegetation
change on water yield and evapotranspiration.
Journal of Hydrology. 55:3–23.
Keim, R.F., Skaugset, A.E., Weiler, M. (2006) Storage ofwater on vegetation under simulated rainfall ofvarying intensity. Advances in Water Resources. 29(7): 974–986.
Johnson, M.S., and Lehmann, J. (2006) Double-funneling oftrees: stemflow and root-induced preferential flow.
Ecoscience. 13: 324–333.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P22

Analysis of solar irradiance fluctuations for photovoltaic (PV) module
outdoor performance testingJunfang Zhang, Kota Watanabe, Tomonao Kobayashi and Jun Yoshino
Graduate School of Engineering, Gifu University

INTRODUCTIONRESULTS AND DISCUSSIONS

Recently, outdoor photovoltaic (PV) module performance
characterization (testing) is developing and is tried to install
for measurement of module performance (Hishikawa et al.
2016). While the testing, steady solar irradiance is required forhigh-accuracy measurement. But unfortunately, weather inJapan changes frequently and therefore solar irradiance also
fluctuates. The fluctuation of the irradiance includes time
fluctuation of solar irradiance and space variation of solar
irradiance, which caused by shading of clouds. In this study,
the solar irradiance and cloud condition are observed with PV
module sensors and a sky camera, respectively, and thecharacteristics of the solar irradiance fluctuation and thecorresponding cloud condition are analyzed. Furthermore,
short time and space variations of the irradiance for sometypical events caused by clouds' moving are discussed in thisstudy.

Figure 3 shows the solar irradiance time series when theirradiance fluctuation is strong. The corresponding clouds'
image taken by the sky camera is also indicated in Fig. 4. In
the event in the figure the change rate of the irradiance is 63.4%/sec. This event is one of the largest solar irradiancefluctuations. In the cloud image photo, the sun is behind the
shadow-blade. The large fluctuations tend to occur whenedges of thick cloud pass in front of the sun.

OBSERVATION APPARTUS AND METHODS
Twelve PV module sensors (PVMSs) introduced in our
University for this study are shown in Fig.1. PVMS consistsof a crystalline silicon cell for measuring global-irradiance.
The sensors are arranged in a line, and they can detect thevariation of solar irradiance with high speed. Six PVMSs arelocated from West (No.1) to East (No.6), and the others arefrom South (No.1) to North (No.6). Distance between
neighboring sensors is 1.145 m. The sampling speed of solar
irradiance is 10ms. The sky camera has the shadow-blade foravoiding the direct solar irradiance into the lens as shown in
Fig.2. Clouds just near the sun can be taken with help of theblade. The observation started from March 2016, andcontinues more than one year.

Fig. 1: Overview of observation system

Fig. 2: Sky camera

Fig. 3: An example of time series solar irradiance intensity(April 17, 2016, Gifu University)

Fig. 4: Cloud image when solar irradiance changes
suddenly. It's taken by sky camera. Black band in it is the
shadow blade. (April 17, 2016. 13:07)
A cumulative frequency of the solar irradiance change rate
in 1 second is shown in Fig. 5. In 95 % of the observation
period, the change rate in 1 second is less than 1.0 %. In theoutdoor testing of PV modules, the measurement period is 1
second or less. It means that the stable irradiance condition forthe outdoor testing can be found easily under Japanese
weather. Large fluctuation events which change rate is morethan 0.6, like the event in Fig. 3, occur once at every couple
months. As shown in Fig. 5, the distributions of irradianceProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P22change rate in every month are different each other’s due toweather conditions.

Fig. 7: Clouds' image corresponding to irradiance in Fig.
6.
Fig. 5: Cumulative frequency distribution of solar
irradiance change rate in 1 second.
We pick up the event around 12:28:10 in April 12, 2016
and others. Solar irradiance time series observed by West-East
PVMSs in daily and short period around the event is shown in
Fig. 6. The corresponding clouds' images are shown in Fig. 7.
In this figure, the sun locates behind the shadow-blade.
Difference of the instantaneous irradiance observed by each
PVMS in Fig. 6 indicates the space distributions of theirradiance. Moreover, in Fig. 6, each sensor follows to thefluctuation of the irradiance of No.6 with the same pattern. Itmeans that clouds traveled from upstream (East, No.6) todownstream (West, No.1), and the PVMSs measure thetravelling shadows of the clouds running are them from East
to West. Figure 8 shows the solar irradiance distributions inspace in each time around the target time, 12:28:10 in April
12, 2016. The reference of the irradiance is PVMS No. 1 in
the figure. From this figure, the maximum difference in theirradiance between the sensors No. 1 and 6 is about 130 W/m2
and it corresponds to 1.8 %/m in non-uniformity of theirradiance.

Fig. 8: Instantaneous space distributions of solar
irradiance. (12:28:00-12:28:20 in April 12, 2016. Gifu
University)

CONCLUSIONS
Short-period fluctuation of solar irradiance and thecorresponding cloud condition are observed with PVMSs andthe sky camera. In the observation, large fluctuation of theirradiance induced when edges of thick clouds pass in front of
the sun. Irradiance change rate less than 1% in 1 second,which is measuring period in the outdoor PV module testing,is dominant, 95 % in the observation period. On the other
hand, large fluctuations also observed under the characteristics
cloud conditions, but the occurrence is low. Two dimensional
solar irradiances are observed continuously in the field andshort time and space variations. The clouds' image taken by asky camera shows that the short time and space variations arecaused mainly by travelling clouds. The maximum spacevariation is 1.8 %/m. The travelling speed of clouds’ shadow
is also evaluated from the observation.

ACKNOWLEDGMENTS

Fig. 6: Time series of solar irradiances around 12:28:10 inApril 12, 2016.
Similar characteristics can be found in the time series solar
irradiance observed by PVMSs in the South-North line. Fromthese analysis the clouds was moving over the target point andtheir shadow running on the PVMSs with 12.1 m/s in speed
toward to north-northwest.

This research was supported by New Energy and Industrial
Technology Development Organization (NEDO) and National
Institute of Advanced Industrial Science and Technology(AIST)REFERENCES
Yoshihiro, H., T. Doi, M. Higa, K. Yamagoe, H. Ohshima,(2016) Precise Outdoor PV Module Performance
Characterization Under Unstable Irradiance, IEEE Jour.
Photovoltaics, Vol. 6, No. 5, pp.1221-1227.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P23

Structural change and biomass increment of a subtropical/warm-temperate
Lucidophyllous (evergreen broad-leaved) forest over a 28-year period,
central Japan
Siyu Chen1, 2, Ruoming Cao1, 3, Shogo Kato3, Shinpei Yoshitake1, Akira Komiyama3 and Toshiyuki Ohtsuka1
1. River Basin Research Center, Gifu University
2. United Graduate School of Agricultural Science, Gifu University
3. Faculty of Applied Biological Sciences, Gifu University
dynamics since 1989, in lower slope of Mt. Kinka. The present
research investigates the development of stand structure, and
INTRODUCTION
biomass recovery of secondary lucidophyllous forest during
28 years (1989 to 2017) using the permanent plot. The
Biomass increment in forests is one of the most important
objectives were as follows: (1) to assess the community
components of carbon sequestration of terrestrial ecosystem.
structural change of secondary stands during 28 years, (2) toEspecially, forests in the middle and high latitudes of the
document temporal trends in biomass accumulation withnorthern hemisphere, where human dominated area, had highspecial reference to stand development.
potential of carbon sequestration during the end of 20 century
due to the enhancement of plantations or forest recovery
MATERIALS AND METHODS
during secondary succession (Fang et al. 2014, Pan et al.
2011). Even in tropical forests, aboveground biomass recovery
A 0.7 ha study plot (70 m × 100 m) was established on
during secondary succession is resilient, and has high potential
the lower slopes of Mt. Kinka (ca. 60 m a.s.l., 35°26′N,of carbon sequestration that compensates carbon release from136°47′E) in 1989. The forest canopy is dominated byland-use change (Poorter et al. 2016). On the other hands, it isCastanopsis cuspidata, and the understory is dominated bywell known facts that biomass production declines as
Cleyera japonica and Eurya japonica. The plot was divided
ecosystem development (Odum 1969). For example, forest
into 70 subplots of 100 m2 using a compass survey. In May
age-sequence studies revealed that aboveground NPP reaches
1989, all stems of tree species with a diameter at breast heighta peak early in stand development and then gradually decline(DBH) greater than or equal to 10 cm were mapped as x-y
by as much as 76%, with a mead reduction of 34% (Gower etcoordinates, identified to species and measured for DBH. A
al. 1990). Magnani et al. (2007) also reported that the age
number tag was attached on each trunk at 1.3 m height using aeffects account for 92% of the total variability in NEP from
stapler, and the measuring position was marked using paint.
boreal coniferous to temperate broadleaf forests. Therefore,
The DBH of these stems were remeasured in May 1995 (6the age-related change of biomass increment is crucial for thegrowing season after 1989) and October 2004 (10 growing
global carbon cycling in near future.
season after 1995) at the same painted position of trunks
Lucidophyllous (evergreen broad-leaved) forests are widely
together with new recruited stems over 10 cm and dead stems
distributed in the subtropical and warm temperate regions ofduring the intervals. In January 2017 (12 growing season after
east Asia (Ohsawa 1990, Tagawa 1995). Lucidophyllous
2004), this 0.7 ha plot was reconstructed using the tree map
forests mainly dominated by evergreen species of Fagaceae,
and the remaining numbered tags on trunks, and we can
Lauraceae, Theaceae, Magnoliaceae, and Hamamelidaceae,
identify all tree stems over 10 cm in 2004. Then all tree stems
especially Castanopsis is one of the typical dominant species
greater than 1.3 m height were re-tagged and measured DBH
from coast area of central Japan to southwestern Japan.
together with dead stems greater than 10 cm in 2004.
Ohsawa (1993) suggested that the tropical lower montane
To estimate aboveground biomass (AGB) of forest standforests that mainly dominate evergreen Fagaceas (especiallyat each measurement time (1989, 1995, 2004 and 2017), we
Castanopsis) can be correlated to the horizontal
used the allometric equations of evergreen broad leaved forest
subtropical/warm-temperate zone of East Asia.
as follows (Kawanabe, 1977):
Mt. Kinka (35°26′N, 136°47′E, the peak is 329 m) is
log Wf = 0.885 log (DBH)2 −1.591 (1),located in Gifu Prefecture of central Japan. A famous castle
log Ws= 1.022 log (DBH)2 − 0.710 (2),(Gifu castle) stands on the top of Mt Kinka from 11 century,
log Wb= 1.266 log (DBH)2 −1.852 (3),and around the area of Mt. Kinka is human dominated area.
AGB= Wf + Ws + Wb (4),Therefore, Pinus densiflora predominated in 17 to 18 century
where DBH is the diameter at breast height (cm), Wf, Ws,
due to utilization as fertilizer or fuel by residents around Mt.
Wb is the dry weight (kg) of foliage, stems and branches,
Kinka. However, these forests were over-used in 19 century
Stand increment (SI) of aboveground biomass during theand then managed the area as productive forest from 1889. In
measurement interval can be estimated as follows (Clark et al,
Japan, secondary forests such as coppice woods and pine2001):
forests are dominated in the region due to the strong
SI = ∑ BIs + ∑ BIi (5),anthropogenic disturbance for a long time. From 1947, thewhere BIs represents aboveground biomass increments ofarea prohibit to cut and protected as natural secondary forest,
surviving trees in the plot and BIi represents abovegroundthus most individuals of Castanopsis recruit as secondary
biomass increments of ingrowth trees that reach the minimum
forest after 1947. Nowadays, almost all area (597 ha) of Mt.
DBH during the study period.
Kinka, consist of secondary natural forests (93%) and artificial
coniferous forests (2%). Especially, the lower slopes of
RESULTS AND DISCUSSION
Mt.Kinka are covered by secondary evergreen broad-leaved
The total forest aboveground (including foliage)
forests that predominate Castanopsis cuspidata, where thebiomass for all trees with DBH≥10cm was estimated tolatitudinal northern limit of lucidophyllous forests that reachbe 138.8 t ha-1, 145.4 t ha-1, 162.0 t ha-1 and 186.5 t ha-1
sea level at ca 35N central Japan (Ohsawa 1990). We set a2permanent plot (7,000 m ) and long-term study on forest
in the survey of 1989, 1995, 2004 and 2017,

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P23

Aboveground biomass increment (t d.w. ha −1)

respectively (Fig. 1b). The major proportion ofaboveground biomass was from Castanopsis cuspidata.
In addition, the aboveground biomass continued toincreasing from 1989 to 2017, but showed a different
patterns across DBH size classes during the 28 years(Fig. 1b). Initially, the aboveground biomass of all trees
at 10–30cm classes

(a)

30
20

Castanopsis
cuspidata

10

Other
trees

Other
trees

Other
trees

0
-10
-20
200

Aboveground biomass (t d.w. ha −1)

Castanopsis
cuspidata

Castanopsis
cuspidata

40

References
Clark D. A., Brown S., Kicklighter D. W., Chambers J.
Q., Thomlinson J. R., Ni J., Holland E. A. (2001) Net
primary production in tropical forests: an evaluation andsynthesis of existing field data. Ecological Applications,11(2), 2001, pp. 371–384
Fang J. et al. (2014) Evidence for environmentallyenhanced forest growth. Proc. Natl. Acad. Sci. USA
111, 9527–9532(b)
10 - 20 cm
30 - 40 cm

180
160

20 - 30 cm
40 - 50 cm

140
120
100
80
60
40
20
0

1989

1995

2004

Due to mortality was much higher than recruitment inboth evergreen and deciduous trees, the abovegroundbiomass increment by recruitment approached 0, and theaboveground biomass increment mainly came fromgrowth, moreover, more than 90% of growth increment
was from Castanopsis cuspidata (Fig. 1a). The annual
growth increment of aboveground biomass during thethree survey period 1989-1995, 1995-2004 and2004-2017 was 240 g m-2 yr-1, 390 g m-2 yr-1 and 340 g
m-2 yr-1, respectively, which was highest during the
1995-2004 period, accordingly, the decrease
aboveground by death was also highest during thisperiod. Thus, the highest net annual increment ofaboveground biomass was during the 2004-2017 period(Fig.1a).
Though the stem density of Castanopsis cuspidata
continued reducing from 1989 to 2017, the individual
biomass increased in reverse, which implied that the
intraspecificcompetition
betweenCastanopsis
cuspidata such as self-thinning (Yoda et al., 1963).

2017

Fig. 1: (a) Change of aboveground biomass of each DBH
class in the permanent quadrat. (b) Aboveground biomass
increments by surviving (open bars) and recruit trees(hatched bars), and losses (Shaded bars) by dead trees
during measuring interval of Castanopsis cuspidate andother tree species.

accounted for most of the total aboveground biomass inthe survey of 1989 (71.2%) and 1995 (59.8%).
However, in the survey of 2004 and 2017, theaboveground biomass of trees with DBH ≥ 30cm
accounted for most of the total aboveground biomass(63.4% and 78.4%, respectively, Fig. 1b). Comparing
the survey of 1989 and 2017, the forest biomass
composition changed markedly, the abovegroundbiomass at 10-20cm DBH class consisted of 20.3% of
the total aboveground biomass in 1989, and there wasno aboveground biomass from ≥50 cm DBH class.
Nevertheless, the aboveground biomass at 10-20cm
DBH class only constituted 3.6% of the total
aboveground biomass, and the aboveground biomass
from ≥50 cm DBH class was up to 14.2% of the total
aboveground biomass in 2017 (Fig. 1b).

Tagawa H (1995) Distribution of lucidophll
Oak-Laurel forest formation in Asia and other areas.
Tropics 5, 1-40
Ohsawa M (1990) An interpretation of latitudinalpatterns of forest limits in south and east Asian
mountains. J Ecol 78, 326–339
Ohsawa M (1993) Latitudinal pattern of mountainvegetation zonation in southern and eastern Asia. J
Veg Sci 4, 13–18
Odum E. P. (1969) The strategy of ecosystemdevelopment. Science 164 (3877), 262–270. doi:
10.1126/science.16413877.262
Pan et al. (2011) A large and persistent carbon sink in
the world's forests. Science, 333 (2011), pp. 988–993
Yoda K, Kira T, Ogawa F, Hozumi K (1963)
Self-thinning in overcrowded pure stands undercultivated and natural conditions (Intraspecificcompetition among higher plants. XI). J Biol Osaka
City Univ 14:107–129
Magnani, F. et al. (2007) The human footprint in the
carbon cycle of temperate and boreal forests. Nature
447, 848–850

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P24

Leaching behaviors of arsenic during temporary storage of tunnel spoil:
evaluation based on column test
Wenjiao Li1, Tsutomu Sakakibara2, Atsushi Umeda2, Taro Tsuge 2 and Fusheng Li 3
1. Graduate School of Engineering, Gifu University, Japan
2. Meihoextech Co. Ltd., Japan
3. River Basin Research Center, Gifu University, JapanINTRODUCTION
Tunnel construction is always accompanied with large
scales of excavation, resulting in the generation of larger
quantities of dumped soil, called also as spoil. Based on thegeological condition of soil and/or rock environment to be
excavated, tunnel spoil contains hazardous substances, in mostcases heavy metals and metalloid elements. Arsenic, as ametalloid element, exists in many forms and can change theirforms in water and soils environments based on chemical andbiological conditions therein. Elemental arsenic and arsenic
compounds are classified as toxic and dangerous for theenvironment, ecosystems and humans. Arsenic is known tocause arsenicosis when present in drinking water, and the mostcommon species being arsenate As (V) and arsenite As (III),with the latter being more poisonous than the former. Due tothese reasons, careful management and disposal of tunnel spoil
containing arsenic are required based on existing regulations.
To deal with larger quantities of tunnel spoil containing
arsenic, onsite temporary storage is generally considered as afeasible and unavoidable practice. The precondition for such apractice is that the diffusion and transfer of arsenic tosurrounding environments (water, soil and air) throughparticularly the leachate generated during rainfall andsnow-thawing seasons can be effectively prevented. Chemical
immobilization by addition of effective binding agents is
considered as one of the likely approaches to prevent the
diffusion and transfer of arsenic, however, its effect needs
further validation.
Accordingly, as the main aim of this study, the leaching
behaviors of arsenic from tunnel spoil containing arsenic witha concentration requiring suitable treatment were evaluatedthrough a column leaching experiment and corresponding
water quality analysis for arsenic, pH, EC and ORP in theleachate from the columns.

2. Column experimentThree plastic columns with the diameter of 10.4 cm andheight of 40 cm were used. A plate with holes ofapproximately 1 mm in width distributed uniformly wasplaced at the bottom to support the spoil. The weight of spoil
packed to each column was 1.35 kg and the packed bed depth
was 10 cm.

Fig. 1: Diagram of the column experiment system
The diagram of the column system is presented in Fig. 1.
Tap water adjusted to pH 4.97 (rainwater observed in Nagoya,Japan) was used to simulate rainwater and was pumped to thecolumn at a rate the same as the rate of water penetrated
through the packed spoil bed to the outlet. The water inside
the tank was prepared every day through pH adjustment with
HNO3. The columns were run for 180 hours and the flow rate
was controlled at 424.5 ml/hr to simulate the yearly rainfall of
about 1800 mm observed in Nagoya, Japan. Water height overthe bed was controlled at about 5 cm in order to simulate
penetration of rainwater through the tunnel spoil undersaturated condition.

MATERIALS AND METHODS
1. Materials
Tunnel spoil was collected from a temporary storage site forthe dumped material of rocks and soils from a geologic
stratum located in the eastern of Gifu Prefecture, Japan. The
contained content of arsenic excelled the standard value
regulated according to the leached concentration by the Soil
Contamination Countermeasures Act of Japan, with theleached concentration from the collected spoil being measured
as 0.026 mg/L. After crushed and sieved through a sieve withthe opening of 4.75 mm, the tunnel spoil was used for theexperiment. For immobilization treatment, a pre-adjusted
liquid agent with ferric and calcium as the main constituents insuspended forms was used as the immobilizer and was addedby changing its volumes to make three different
concentrations comparison: 0%, 3% and 10% (wt/wt). The
tunnel spoil after addition of the immobilizer was mixed
sufficiently and was then subjected to curing for one day.
Then, after natural drying, the immobilization-treated spoil
was packed into columns for leaching experiment.

3. Leachate collection and measurement
The leachate was sampled for 500 ml every time from eachcolumn. The sampling times were designed for running after
1, 2, 3, 6, 12, 24, 48, 72, 108, 144, 180 hours, equivalent to a
total water volume of rainfall for 0.03, 0.06, 0.08, 0.17, 0.33,
0.67, 1.33, 2, 3, 4, 5 years, respectively. The sampled leachate
was filtered through 0.45μm membrane filter before subjected
to analysis for pH, electrical conductivity (EC),oxidation-reduction potential (ORP) and arsenic.

RESULTS AND DISCUSSION
The initial concentration of arsenic that could leach fromthe spoil was 0.026 mg/L, 2.6 times as high as the value
regulated in the standard. The initial concentration that could
leach from the spoil after immobilization treatment was
decreased to 0.0002 and 0.0001 mg/L with the addition of
immobilizer for 3% and 10%, respectively, as shown in Table
1, indicating a strong effect of the used immobilizer inProceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P24
inhibiting the initial release of arsenic from the contaminatedspoil to water.

differences appeared among the three spoil samples packed.
Contrary to the trends of pH and ORP, EC reached 2500
mS/m in a very short time period and then decreased rapidly tolevels around 65 mS/m. The results of pH, ORP and EC
suggested that no apparent differences may occur during
temporary storage of the spoil no matter if it is treated by theimmobilizer or not.
For arsenic, the leached concentration reached its peak of
0.057 mg/L with the No.1 column packed with the spoil
without immobilization treatment after running for 1 hour(liquid-solid ratio: 0.9), then turned to a trend of decreases
until the final value of 0.013 mg/L at the end of run for 180
hours (liquid-solid ratio: 56.6). For No. 2 and No. 3 columns
packed with spoil after treatment with 3% and 10% of
immobilizer, the initial rapid release of arsenic observed in
No. 1 column was completely inhibited. For these twocolumns, with penetration continued, the released arsenic
concentration increased; however, the increasing gradient wasvery slow, and the final concentration at the end of theexperiment was also observably lower than the No. 1 column.
Based on the results of this study, it is estimated that theaccumulative amount of arsenic released from the spoil due torainfall for five years could be reduced by about 3/4 if the
spoil is treated by immobilization with the immobilizer used inthis study at a mixing ratio of 10%.

Table 1: Initial released concentration of arsenic fromspoil with and without immobilization treatment.
Column No.

Immobilizer
additional rate (%)

No.1
No.2

0
3

Released arsenic
concentration(mg/L)
0.026
0.0002No.3

100.0001

The changing trends of pH, ORP, EC and arsenic
concentration during penetration of water through the packed
bed of tunnel spoil are shown in Fig. 2. As the accumulative
volume of penetrated water increased, pH increased rapidly
and then maintained at around 7.7 for about 70 hours(equivalent to liquid-solid ratio of 22) before turning todecreases to about 7.0. Marked differences in pH were notobserved between the spoil with and without undergoing
immobilization treatment. For ORP, except for a short initialstage where its values were higher for the two columns with
spoil after immobilization treatment, marked differences did
not appear throughout the experiment and no significant

350
350

8.1
No.1
7.9

No.1
330
330
ORP
ORP (mV)
(mV)

No.2

7.7

No.3

pH

7.5
7.3
7.1
6.9

No.2
No.3

310
310
290
270

6.7
250

6.5
0

10
20
30
40
50
Accumulative liquid-solid ratio (L/Kg)

0

60

60
60

0.06

10000

No.1
Arsenic conc. (mg/L)

No.1
No.2
EC (mS/m)

10
20
30
40
50
Accumulative liquid-solid ratio (L/Kg)

No.3

1000

100

0.05

No.2
No.3

0.04
0.03
0.02
0.01
0.00

10
0

10

20

30

40

50

Accumulative liquid-solid ratio (L/Kg)

60

0

10

20

30

40

50

60

Accumulative liquid-solid ratio (L/Kg)

Fig. 2: The trends of pH, ORP, EC and arsenic concentration in leachate from columns as a function of liquid-solid ratio.

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P25

Sorption and distribution of cesium on different additives applied tocontaminated soils
Huijuan Shao1 and Yongfen Wei1, 2
1 The United Graduate School of Agricultural Science, Gifu University, Japan
2 River Basin Research Center, Gifu University, JapanINTRODUCTION
Large amounts of radionuclides were released into thenatural environment from the Fukushima Daiichi Nuclear
Power Plant following the great East Japan earthquake andtsunami in March 2011. The radionuclides were widelydispersed and deposited in the northeastern part of Japan,
mainly in the Fukushima Prefecture, where forests cover
approximately 70% of the area. Since Cesium-137 (137Cs)
contamination is a great concern for human health andecosystems because of its relatively long half-life (30 years),decontamination is consistently an issue of great concern. So
far, decontamination operation has been carried out in urban
areas; however, for the large scale of polluted forest areas, theproblem remains to be solved.
Cs immobilization by additives is one of the feasible
environmental management strategies for Cs-contaminatedsoils in forested areas. Numerous soil additives have beentested in pots or fields for remediation purposes (Namgay et
al. 2010). However, for the purpose of immobilization of Cs inforest soils, effective additives have not yet been found.
In the study, five different low-cost materials were selected
and used as additives, in order to screen out an additive withhigher amendment effects and efficiency for remediating soils
contaminated with Cs. For this, we investigated sorption
capacity of Cs onto different additives added with different
weight ratios to soil, and the distribution of Cs on the
additives was also examined. The sorption capacity wasevaluated based on sorption equilibrium experiments and data
analysis by Freundlich isotherm model. And the distributionof Cs was evaluated through analyses with SEM/ EDX.

(3) Sorption experiment
Each additive was added into the soil with the following
five different weight ratios to soil: 1:0, 7:3, 5:5, 3:7 and 0:1.
The obtained mixtures were used for sorption experiment
performed using the bottle point batch sorption method. For
Cs concentration, the dosage was set to the following fivelevels: 10, 50, 100, 500 and 1000 µg/L. To each bottle, 0.1 gof dried sorbent was added, followed by addition of 30 mL of
the Cs solution prepared immediately before the experimentthrough dilution of the stock solution of Cs to thecorresponding designated concentration. All bottles wereshaken for 48 hours at 20°C for sorption to reachequilibration. After shaking, samples were filtered through 0.2µm filters, and the obtained filtered solutions were thensubjected to Cs quantification by ICP-MS.

MATERIALS AND METHODS(4) Sorption isotherm model
The relationship between the amount of adsorbed Cs (q)and its concentration in the solution (C) at equilibrium isusually described by isotherm models that incorporate
sorption parameters reflecting the interactions among theadsorbate, adsorbents and the solution chemistry of thesorption system (Nilchi et al. 2011). Among available
isotherm models, Freundlich and Langmuir isotherm models
are widely used for modeling adsorption data. To evaluate theadsorption characteristics, in the study, Freundlich isotherm
model is used.
q = K C1/n
The linear format of model is shown below:
Log q= log K + 1/n log C
K is the Freundlich constant reflecting the sorption capacity
and strength, and 1/n is the exponent reflecting the affinity
between Cs and the sorbent.

(1) Cesium solution
The stable non-radioactive 133Cs was used in the study
since it exhibits similar behavior with 137Cs in water and soil
environments and had been widely used as a surrogate forstudies.

(5) Distributions of adsorbed Cs on all additives
The distribution of adsorbed Cs on the additives wasanalyzed using a scanning electron microscopy (SEM) andenergy dispersive X-ray spectroscopy (EDX) (Hitachi SU3500).

(2) Soil samples and additives
Soil was sampled from a forested area located in the upperstream of Ijira River in Gifu Prefecture of Japan. Soil was
taken from the surface layer (0-15 cm depth) after removing
vegetation and litter layers. For soil additives, the following
five different types with very low cost were used: (1) Biochar
1 (charcoal produced from coconut shells); (2) Biochar 2(charcoal produced from rice husks); (3) Blast furnace slag (abyproduct of iron and steel manufacturing processes, mainlycontains CaO, SiO2 and MgO); (4) Incinerated sewage sludgeash (ISSA, a by-product after P recovery from incineration ashof excess sewage sludge); and (5) Carbonized night soil
sludge used as fertilizer (CNSF). After dried at 35°C, alladditives were then sieved through a 2.0 mm sieve.

RESULTS AND DISCUSSION(1) Sorption capacity of Cs onto all additives
Table 1 showed the values of Freundlich constant K and
1/n for the additives and their mixtures with soil (totally 21
cases) based on the sets of adsorption isotherm data obtained
from sorption experiment. As shown in the table, allcorrelation coefficients are more than 0.9, indicating that theadsorbed Cs on the sorbents could be fairly-well described by
the Freundlich isotherm model.
Among all five additives, Biochar 1 showed the largest K
value (0.656) while Blast furnace slag the smallest (0.233). In
addition, compared to soil, the sorption capacity of Biochar 1,
CNSF and ISSA was shown to be larger. On the other hand,the effects of different mixing ratios of additive to soil on K
for 5 additives were not uniform. For Biochar 1 and CNSF, K

Proceedings of International Symposium on Soil Management for Sustainable Agriculture 2017
UGSAS-GU & BWEL Joint Poster Session on Agricultural and Basin Water Environmental Sciences: P25
showed the largest value when the ratio of additive to soil was
7:3. For the other additives, K showed the largest when the
Table 1 Estimated Freundlich parameters of Cs on all sorbents
K
Sample1/n
R2[(µg/g)/(µg/L)]1/n
Additive: soil=0:1
0.321
1.298
0.95
0.656
1.221
0.94
Biochar 1: soil=1:0
0.393
1.229
0.92
Biochar 1: soil=7:3
0.354
1.283
0.95
Biochar 1: soil=5:5
0.301
1.324
0.97
Biochar 1: soil=3:7
0.267
1.002
0.93
Biochar 2: soil=1:0
0.172
1.391
0.94
Biochar 2: soil=7:3
0.252
1.417
0.96
Biochar 2: soil=5:5
0.237
1.362
0.97
Biochar 2: soil=3:7
CNSF: soil=1:0
0.571
1.013
1.00
CNSF: soil=7:3
0.494
1.086
1.00
CNSF: soil=5:5
0.361
1.106
0.95
CNSF: soil=3:7
0.308
1.179
0.97
ISSA: soil=1:0
0.400
1.174
0.98
ISSA: soil=7:3
0.319
1.230
0.97
ISSA: soil=5:5
0.355
1.228
0.99
ISSA: soil=3:7
0.254
1.331
0.97
Slag: soil=1:0
0.233
1.265
0.96
Slag: soil=7:3
0.166
1.335
0.90
Slag: soil=5:5
0.252
1.274
0.94
Slag: soil=3:7
0.167
1.364
0.93

Table 2 shows the average mass ratios of Cs adsorbed
both on soil and additives of five different mixtures. The
results displayed that soil adsorbed less amount of Cs but
additive adsorbed more in the cases of Soil-Biochar 1 andSoil-CNSF mixtures, implying that the amendment effect ofBiochar 1 and CNSF is higher than that of other three
additives.
Table 2 Mass ratios of Cs for different Soil-additive mixtures
Mass ratios of Cs (%)
Mixtures
Soil
Additive
Soil-Biochar 1
0.04 ± 0.01
0.08 ± 0.02
Soil-Biochar 2
0.07 ± 0.02
0.03 ± 0.01
Soil-CNSF
0.05 ± 0.01
0.08 ± 0.01
Soil-ISSA
0.06 ± 0.01
0.04 ± 0.01
Soil-slag
0.08 ± 0.02
0.01 ± 0.00

CONCLUSIONSThe sorption and distribution of Cs onto forest soil anddifferent additives were investigated through batch sorption
experiments and SEM/EDX analysis. Biochar 1, Carbonizednight soil sludge fertilizer and Incinerated sewage sludge ash
were selected since they showed larger sorption capacity forCs than the forest soil. Elemental composition analysis results
indicated that Cs was adsorbed more onto additive than soil
for the mixtures of Soil-Biochar 1 and Soil-CNSF.

ratio of additive to soil was 5:5.

REFERENCES(2) Distribution of Cs on different sorbents
For each additive, elemental analysis by SEM/EDX wasconducted by focusing on five different spots selected
randomly from the overall SEM image. Fig. 1 shows thesurface image and elemental composition after Cs sorption for
the forest soil and 5 additives. As shown, the mass ratio of Cs
adsorbed on Biochar 1 was the largest (0.09 %), followed byforested soil (0.06%), Biochar 2 (0.06 %), CNSF (0.05 %),ISSA (0.03%) and Slag (0.03%). For the soil-additive
mixtures, there were no significant differences on Cs mass
ratio under different mixing ratios (detailed data not shown).

Forest soil

Biochar 2

Elements
C
N
O
Na
Mg
Al
Si
P
S
K
Ca
Ti
Fe
Zn
Cs

Mass ratio (%)
17.19 ± 2.15
1.43 ± 0.26
52.38 ± 5.22
0.06 ± 0.01
0.15 ± 0.02
2.61 ± 0.38
23.48 ± 3.35
0.06 ± 0.01
0.03 ± 0.01
0.56 ± 0.20
0.16 ± 0.04
0.21 ± 0.07
1.61 ± 0.46
0.02 ± 0.01
0.06 ± 0.01

Elements
C
N
O
Na
Mg
Al
Si
P
S
K
Ca
Ti
Mn
Fe
Cu
Zn
Cs

Mass ratio (%)
44.92 ± 2.48
3.03 ± 0.05
36.32 ± 3.32
0.07± 0.02
0.20 ± 0.06
2.44 ± 0.07
10.64 ± 0.77
0.02 ± 0.01
0.07 ± 0.01
0.43 ± 0.07
0.30 ± 0.09
0.11 ± 0.01
0.10 ± 0.02
1.27 ± 0.06
0.01 ± 0.00
0.01 ± 0.00
0.06 ± 0.02

Biochar 1

Slag

Namgay, T., Singh, B., & Singh, B. P. (2010). Influence ofbiochar application to soil on the availability of As, Cd, Cu,
Pb, and Zn to maize (Zea mays L.). Soil Research, 48(7):638–647.
Nilchi, A., Saberi, R., Moradi, M., Azizpour, H., Zarghami, R.
(2011). Adsorption of cesium on copper hex cyanoferratePAN composite ion exchanger from aqueous solution.
Chemical Engineering Journal, 172 (1): 572–580.

Elements
C
N
O
Na
Mg
Al
Si
P
S
K
Ca
Ti
Fe
Cu
Zn
Cs

Mass ratio (%)
77.05 ± 1.36
0.87 ± 0.17
19.78 ± 1.68
0.10 ± 0.01
0.07 ± 0.02
0.39 ± 0.12
0.59 ± 0.13
0.02 ± 0.01
0.03 ± 0.01
0.66 ± 0.04
0.14 ± 0.05
0.02 ± 0.01
0.19 ± 0.03
0.01 ± 0.00
0.01 ± 0.00
0.09 ± 0.03

Elements
C
N
O
Na
Mg
Al
Si
S
K
Ca
Ti
Mn
Fe
Cu
Zn
Cs

Mass ratio (%)
16.99 ± 2.77
1.21 ± 0.06
40.97 ± 2.58
0.12± 0.01
2.56 ± 0.09
5.30 ± 0.08
9.69 ± 0.52
0.48 ± 0.07
0.18 ± 0.03
21.50 ± 1.14
0.43 ± 0.10
0.09 ± 0.01
0.45 ± 0.03
0.03 ± 0.01
0.03 ± 0.00
0.03 ± 0.01

Incinerated sewage sludge ash

Carbonized night
night soilsoil
sludgeCarbonizedfertilizer
sludge fertilizer

Fig. 1 SEM image and elemental composition of all sorbents after Cs sorption

Elements
C
N
O
Na
Mg
Al
Si
P
S
K
Ca
Ti
Fe
Cu
Zn
Zr
Ba
Cs

Mass ratio (%)
15.76 ± 1.87
1.96 ± 0.11
45.55 ± 4.28
0.28± 0.05
2.10 ± 0.08
4.57 ± 0.08
6.88 ± 0.47
6.53 ± 1.02
0.10 ± 0.02
0.69 ± 0.10
4.77 ± 0.89
0.74 ± 0.06
7.44 ± 1.04
0.37 ± 0.03
0.61 ± 0.09
1.03 ± 0.06
0.60 ± 0.05
0.03 ± 0.01

Elements
C
N
O
Na
Mg
Al
Si
P
S
K
Fe
Ca
Ti
Cs

Mass ratio (%)
34.96 ± 3.21
5.69 ± 0.87
35.88 ± 2.25
0.09 ± 0.02
0.41 ± 0.11
2.41 ± 0.36
8.40 ± 1.18
3.06 ± 0.46
0.14 ± 0.02
0.69 ± 0.15
7.42 ± 1.22
0.57 ± 0.08
0.23 ±0.03
0.05 ± 0.01

The United Graduate School of Agricultural Science, Gifu University
1-1 Yanagido, Gifu 501-1193, Japan
Tel: +81-58-293-2984 (or, 2985)
E-mail: renno@gifu-u.ac.jp
Home Page: http://www1.gifu-u.ac.jp/~rendai/eng/

Promotion Office of Gifu University Rearing Programfor Basin Water Environmental Leaders, Gifu University
1-1 Yanagido, Gifu 501-1193, Japan
Tel: +81-58-293-2085
E-mail: bwel@green.gifu-u.ac.jp
Home Page: http://www.green.gifu-u.ac.jp/BWEL/eng/index.html

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