Proceedings of UGSAS-GU & BWEL
Joint Poster Presentation on Agricultural andBasin Water Environmental Sciences 2023
Date: November 8, 2023
Venue: UGSAS-GU Building 6F Main Seminar Room

Organized by
The United Graduate School of Agricultural Science, Gifu University (UGSAS-GU).
Gifu University Rearing Program for Basin Water Environmental Leaders (BWEL).
Co-organized byInternational Consortium of Universities in South and Southeast Asia for the Doctoral
Education in Agricultural Science and Biotechnology (IC-GU12).

Table of Contents
P1: Behavior and Welfare of JapaneseBlack Cattle During Transportation
Activities

P6: FEM Analysis of Withdrawal
Performance of Self-Tapping Screw
and Cross-Laminated Timber Joint

Gianne Bianca P. Manalo and Shigeru
Ninomiya ....................................................... 1

Sarah Amira, Kenji Kobayashi and Keita
Ogawa ......................................................... 11

P2: Comparing the Prediction
Performance, Extrapolation Potential
of Different Algorithms While Using
Fourier Transform Infrared
Spectroscopy of Soil

P7: Effects of Ultraviolet Light on the
Post-harvest Quality of Cherry Fruits(Prunus avium L.)
Nabila Nurul Ahmeidiati, Teppei Imaizumi,
Manasikan Thammawong and Kohei Nakano.................................................................... 13

He Jingyun, Matsui Tsutomu and Tanaka S. T.
Takashi .......................................................... 3

P8: Quantitative Analysis of JapaneseCommercial Coating Penetration into
Fagus crenata Blume Wood Using Xray Microtomography

P3: Microbial Fuel Cell andMacropores Play Crucial Roles in
Suppressing Nitrous Oxide Emissions
from Rice Paddy Fields

Tyana Solichah Ekaputri, Ayuni Nur Apsari,
Takashi Tanaka and Kenji Kobayashi ........ 15

Adhia Azhar Fauzan, Ken Hiramatsu, Takeo
Onishi and Tomohiro Egusa .......................... 5

P9: Effects of Transglutaminase on
Retrogradation of Wheat Flour

P4: Predicting Rice Yields with Deep
Learning Using UAV-BasedMultispectral Imagery and Weather
Data

Dang Thi Kim Lien and Takahisa Nishizu . 17

P10: Carotenoid Metabolism is
Involved in the Granulation of Citrus‘Harumi’ Fruit During Postharvest
Storage

Md. Suruj Mia, Ryoya Tanabe, Luthfan Nur
Habibi, Naoyuki Hashimoto, Koki Homma,
Masayasu Maki, Tsutomu Matsui and Takashi
S. T. Tanaka ................................................... 7

Zhiwei Deng, Gang Ma, Lancui Zhang, Daiki
Kurata, Keisuke Nonaka, Fumitaka Takishita
and Masaya Kato ....................................... 19

P5: Biological Weed Control ThroughWeed Predation by Pill Bugs
(Armadillidium vulgare L.) in Nurseryof Tea Tree (Camellia sinensis)
Niken Nabilaputri Pranaasri and Yamashita
Masayuki ....................................................... 9iP11: Correlation Between Soil
Bacterial Communities and Nutrient
Status in Tea Plants

P16: Alleviative Effect of Gypsum to
Rhizotoxic Stressors on Acid Soil
Koffi Pacome Kouame, Raj Kishan Agrahari,
Yasufumi Kobayashi, Toshihiro Watanabe,
Akiko Maruyama, Koyama Hiroyuki and Yuriko
Kobayashi ................................................... 31

Shuning Zhang, Naoki Yanagisawa, Mio
Asahina, Hiroto Yamashita and Takashi Ikka..................................................................... 21

P12: Evaluation of the Impact of
Climate Change on River
Temperature

P17: Study on the Effect of CaBinding Chemical Agents to Induce
Intumescence Injury in Some Tomato
Cultivars

Khadiza Akter Mousumi, Takeo Onishi, Ken
Hiramatsu and Toshifumi Imaizumi ............ 23

Natassia Clara Sita, Sachiko Ohno, Yoshikazu
Kiriiwa and Katsumi Suzuk ........................ 33

P13: Evaluating the Effect of Soil
Clod Presence and Seeding Rate on
Soybean Yield and Seedling
Establishment Using BayesianMultilevel Mediation Analysis

P18: Effect of Plastic Mulch Residues
on Plant Growth and Soil Properties
Shiamita Kusuma Dewi, Zaw Min Han, Yongfen
Wei and Fusheng Li .................................... 35

Luthfan Nur Habibi, Tsutomu Matsui and
Takashi S.T. Tanaka ..................................... 25

P19: Comparison of Viral Infection
Status of Roses in Japan and Its Effectto Plant GrowthP14: Estimation of Metabolizable
Energy Value of Okara Meal in
Broiler Chicken Using Chick
Bioassay, Approximate Nutritive
Value, and in Vitro Digestibility
TechniqueThiara Celine Suarez, Kunio Yamada, Takashi
Nakatsuka and Masaki Ochiai ................... 37

P20: Reduction of Antibiotic
Resistance Genes in Large-Scale
Johkasou Treating Residential Area
Wastewater

Bagus Himawan Wicaksono, Norimatsu
Marina and Yamamoto Akemi ..................... 27

Su Haoning, Okumura Shinya and Li Fusheng.................................................................... 39

P15: Genome-Wide Association
Analysis of the Changes in Malate
Release Under Aluminum Stress in
Arabidopsis thaliana

P21: Fate and Behavior of Antibiotic
Resistance Genes in Activated Carbon
Adsorption

Congxiao Wang, Masafumi Shimizu, Hiroyuki
Koyama and Yuriko Kobayashi ................... 29

Sri Anggreini, Alma Rizky Aurellya andFusheng Li .................................................. 41

ii

P1

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Behavior and Welfare of Japanese Black Cattle During Transportation
Activities
Gianne Bianca P. Manalo1 and Shigeru Ninomiya2
1
2

The United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
Faculty of Applied Biological Sciences, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japanoccurrence of falling animals during pre-slaughter
handling (Grandin, 2017).
Animal behavior during the pre-slaughter phase issignificantly influenced by animal-human interactions at
an earlier stage in their lives. Consequently, cattle's fearof humans can impact their well-being and potentiallycompromise meat quality. Conversely, animals that haveexperienced good stockmanship may be less prone to thisissue, as they are accustomed to being handled prior to theslaughtering procedure (Njisane and Muchenje, 2017).
Therefore, farm personnel play a crucial role before theslaughtering process, responsible for reducing theanimal’s aggression and promoting calmness throughout
this phase.

INTRODUCTION
Pre-slaughter management of beef cattle is a criticalphase in beef production that involves preparing cattle forthe journey to the processing facility or slaughterhouse.
Proper pre-slaughter management entails strict adherence
to regulatory protocols and requirements established byauthorities to ensure meat quality and food safety while
upholding animal welfare. Despite optimal conditions,pre-slaughter activities such as transportation can inflict
injuries, pain, fear, and suffering on animals (Özdemir etal., 2022). Animals are compelled to cope with thesechallenges through their behavioral and physiologicalresponses (Day and Stull, 1997). Although transportation
is a relatively brief phase in beef cattle production, it canbe challenging to manage due to its detrimental impact on
animal welfare.
The primary objective of this study is to compare theeffects of two transportation methods on the behavior andwelfare of Japanese Black Cattle. Investigating thetransportation method is crucial because the process ofmoving animals to the slaughter facility influences thestress levels of cattle during exsanguination (Özdemir etal., 2022). By assessing their behavior and welfare,researchers can determine which mode of transportation
can minimize stress in cattle during this critical period.
Furthermore, studying cattle behavior in slaughterhouses
will guide researchers in identifying areas whereexperimental research is needed and will provide apreliminary assessment of animal welfare (Moss, 1984).

Transportation Stressors
Previous studies have examined both the duration andquality of transportation for animals intended for meatproduction (González et al., 2012; Nielsen et al., 2011).
They discovered that during transportation, shrinkage is asignificant economic factor. Moreover, Miranda-de laLama et al., (2012) emphasize that transportation was thelink of all the process prior to slaughtering of cattle.
Researchers also noted that factors such as speed, vehicle
design (size, space, and surface), and stocking density can
induce pre-slaughter stress. Inadequate management anda lack of control over the animal's external environment
may lead to abnormal behavior, as animals attempt to cope
through physiological changes (Broom, 2015). Slaughter
facilities present a new environment and experience forthe animals, requiring adjustments in their behavior andphysiology. Some studies have reported that age, gender,
species, and breed play crucial roles in how animals
respond to stress.
The duration of transportation is one of the mostextensively studied stressors, although some research has
focused on transport distance (Eldridge and Winfield,
1988; Wythes et al., 1981). Studies indicate that extended
hours of transport can increase the risk of water and tissue
loss, deplete energy reserves, and result in dehydrationand fatigue (Schwartzkopf-Genswein et al., 2012).
Moreover, unfavorable conditions are not solely
dependent on transport duration and distance; factors suchas loading and unloading, the number of stops duringtransport, driving style, and the interior design of thetransport vehicle also contribute to the stress experienced
by the animals (Dalla Villa et al., 2009).
In addition to ambient temperature, various
environmental factors, such as relative humidity (RH),

Influential factor during pre-slaughter stage
Several influential factors before the pre-slaughter
stage of beef cattle play a pivotal role in ensuring animal
welfare, meat quality, and food safety. A previous study
by Wibowo et al. (2022) revealed that the incidence offalling animals during pre-slaughter activities wasapproximately 6.3%, exceeding the animal welfare
standards set for Samari, Indonesia, which should be 1%
or less. Poor handling is one of the contributing factorsthat induces stress in beef cattle, making them moreaggressive, averse, and agitated, thereby making themdifficult to manage during the pre-slaughter phase.
Several management considerations, including but notlimited to feed withdrawal, water supply, healthassessment, rest and adaptation, facility maintenance,
vehicle design, temperature, ventilation, and otherenvironmental factors, are strongly linked to the1solar radiation, surrounding temperature, heat andmoisture produced by animals, heat loss from the vehicle,
microclimatic factors interact with each other and should
be considered when assessing animal welfare duringtransportation activities. Furthermore, animals withaggressive, active, and fearful behaviors require different
handling approaches.
The age and breed of the animals must also be taken
into account when determining their diet, appropriate
length of rest periods, and the selection of bedding
materials. Animal behavior is often significantly
influenced by their breed and temperament, which canalso impact the incidence of bruising during transportation
activities. The presence or absence of horns, skin texture,
thickness, and other behavioral traits vary among breeds.
As a result, transport-related injuries and bruisingexperienced by animals intended for meat production also
depend on these factors.

Eldridge GA and Winfield CG (1988) The behaviour andbruising of cattle during transport at different space
allowances. Aust. J. Exp. Agric., 28(6): 695–698.
González LA, Schwartzkopf-Genswein KS, Bryan M,
Silasi R and Brown F (2012) Space allowance duringcommercial long distance transport of cattle in North
America 1. J. Anim. Sci, 90: 3618–3629.
Grandin T (2017) On-farm conditions that compromise
animal welfare that can be monitored at the slaughter
plant. Meat Sci. 132: 52–58.
Hulbert LE, Carroll JA, Burdick NC, Randel RD, Brown
MS and Ballou MA (2011) Innate immune responsesof temperamental and calm cattle after transportation.
Vet. Immunol. Immunopathol., 143(1–2): 66–74.
Kent JE and R Ewbank (1986) The effect of roadtransportation on the blood constituents andbehaviour of calves. I. Three months old. Br. Vet. J.,
142: 326–335.
Miranda-de la Lama GC, Leyva IG, Barreras-Serrano A,
Pérez-Linares C, Sánchez-López E, María GA andFigueroa-Saavedra F (2012) Assessment of cattle
welfare at a commercial slaughter plant in thenorthwest of Mexico. Trop Anim Health Prod., 44(3),497–504.
Moss R (1984) Observation before experimentation
monitoring
animal/environment
interaction.
In Proceedings of the International Congress on
Applied Ethology in Farm Animals, pp. 378–381.
Nielsen BL, Dybkjr L and Herskin MS (2011) Road
transport of farm animals: Effects of journey duration
on animal welfare. Animal, 5(3): 415–427.
Njisane YZ and Muchenje V (2017) Farm to abattoir
conditions, animal factors and their subsequenteffects on cattle behavioural responses and beef
quality - A review. Asian-australas. J. Anim. Sci.,
30(6): 755–764.
Özdemir S, Ekiz EE and Ekiz B. (2022) Effect of lairage
duration on cattle behaviors and stockperson actionsin the slaughter corridor in Simmental and Swiss
Brown breeds. Trop Anim Health Prod ., 54(2): 139.
Schwartzkopf-Genswein KS, Faucitano L., Dadgar S,
Shand P, González LA and Crowe TG (2012) Road
transport of cattle, swine and poultry in North America
and its impact on animal welfare, carcass and meat
quality: A review. Meat Sci. 92(3): 227–243.
Swanson JC and Morrow-Tesch J (2001) Cattle
transport: Historical, research, and future
perspectives. J. Anim. Sci., 79: E102–E109.
Wibowo A, Ardhani F, Safitri A, Suhardi S, Inestika V,
Anindyasari D and Indana K. (2022). The Impact of
Pre-Slaughter and Slaughter Procedure on Animal
Welfare and Behavior Changes in Cattle at Local
Abattoir in Samarinda-Indonesia. In International
Conference on Tropical Agrifood, Feed and Fuel
(ICTAFF 2021). Adv. Biol. Res. Atlantis Press. 17:
236–239.
Wythes J R, Arthur RJ, Thompson PJM, Williams GE
and Bond JH (1981) Effects of transporting cows
various distances on liveweight, carcase traits andmuscle pH. Aust. J. Exp. Agric. 21(113): 557–561.

Effect of transportation stress on animal’s
physiology and welfare
Stress can have a negative impact on an animal's
physiology and welfare, potentially leading to the releaseof stress hormones, including cortisol. In fact, a previous
study reported that pre-slaughter stress during transport
can influence the immune system of cattle (Hulbert et al.,2011). Prolonged elevation of stress hormones,
particularly during transportation activities, can result in aweakened immune system, impaired metabolism, andvarious health issues.
A previous study reported that during the early phaseof transportation, cattle exhibit higher levels of socializing
and altered behavior (Swanson and Morrow-Tesch, 2001).
In a study by Kent and Ewbank (1986), older calves spentless time ruminating and lying and excreted morecompared to younger calves, indicating that transportation
activities are more stressful for them. On the other hand,
Deters and Hansen (2022) reported that road-transported
steers had a greater increase in the neutrophil-tolymphocyte ratio and serum nonesterified fatty acids,
indicating a stronger inflammatory and neuroendocrine
response compared to steers that were not transported.

REFERENCES
Broom, DM and Fraser AF (2015) Domestic Animal
Behaviour and Welfare. Vol. 5.
Dalla Villa PD, Marahrens M, Calvo AV, Di Nardo A,
Kleinschmidt N, Alvarez CF and Müller‐Graf C(2009) Project to develop animal welfare risk
assessment guidelines on transport. EFSA Supporting
Publications, 6(9), 21E.
Day F and Stull CL (1997) Stress and Dairy Calves.
Deters EL and Hansen SL (2022) Long-distance transit
alters liver and skeletal muscle physiology of beef
cattle. Animal, 16(6).

2P2Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Comparing the Prediction Performance, Extrapolation Potential ofDifferent Algorithms While Using Fourier Transform Infrared
Spectroscopy of Soil
He Jingyun, Matsui Tsutomu and Tanaka S. T. Takashi
The United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
since 2017. pH and Mineralizable Nitrogen (Min N) were
measured. Mid-infrared spectroscopy (wavenumber of
4000–500 cm–1) was obtained at the intervals of 4cm–1
using FTIR analytical instruments coupled with the
diffuse reflectance unit (FT/IR-4700, JASCO Company,
Japan).
Pre-treatment: When the wavelength is under 500,
the raw data were so noisy that we compared two
methods for each soil property, including the
wavelength under 500 (within noise) and removing the
wavelength under 500 (without noise). Three spectral
transformation
methods
includingnon-order
differential (NOD), first-order differential (FOD), andsecond-order differential (SOD) were compared to
select the appropriate number of differentiations
according to RMSE values. Thus, the best combinationof optimal regression method and differential times
were evaluated. Our results conclusively demonstrated
that the " NOD with the without noise " yieldedsuperior results for all sampled data.
Two distinct test dataset configurations were
implemented: Test 1 - Leave-one-prefecture-out CrossValidation (LOPO CV) for extrapolation; Test 2 Random
Cross-Validation(RandomCV)forinterpolation. All algorithms implemented in R. RMSE
(Root Mean Squared Error), RRMSE (Relative Root
Mean Squared Error), R2, and LCCC (Lin's Concordance
Correlation Coefficient) were evaluated.

INTRODUCTION
Precision agriculture (PA) is the application oftechnologies and principles to manage the spatial
variability associated with all aspects of agricultural
production to improve crop performance andenvironmental quality (Carrer et al., 2022; Zhang et al.,2002). Soil physical, hydrological, chemical, andbiological features are key knowledge forunderstanding the relationships between soil and crops,
especially in PA, environmental management, and crop
growth modeling (Bhakta et al., 2019). In recent years,
spectroscopy has attracted great attentions as it is a nondestructive and more time-saving analytical tool thatcan simultaneously analyze various soil properties
based on specific peaks. Combining Fourier Transform
Infrared Spectroscopy (FTIR) and multivariate
regression analysis is a viable alternative to traditional
chemical analysis methods. FTIR technology caneffectively estimate the target soil properties, such as
pH, soil organic carbon (SOC), nitrogen (N),phosphorus (P), potassium (K) and cation exchange
capacity (CEC), etc. (Peltre et al., 2014).
A majority of existing experiments predominantly
entail the analysis of data acquired from various areas.
In interpolation predictions are made using data comingfrom all geographic directions, while in extrapolation
predictions are based on data from one or a few
directions only, possibly from far away (Angelini et al.,2020). In the contexts of both interpolation andextrapolation, the utilization of ill-suited models may
result in diminished precision of the outcomes. A study
states that deterioration of performance when simple
interpolation is replaced by simple extrapolation. The
potential decrease in accuracy when employing RF for
extrapolation purposes remains unclear. (Takoutsing etal., 2020). Thus, we evaluated the aptitude of two
specific algorithms, namely Partial Least Squares
Regression (PLSR) and Random Forest (RF), withregard to their suitability for either of interpolation or
extrapolation task.

RESULTSIn this case, the pH model consistently
demonstrated strong performance, even whensubjected to LOPO CV(Table 1). This resiliencesuggests that pH predictions are relatively insensitive
to variations in sample origins. In contrast, the model
for Min N exhibited enhanced performance during
Random CV, underscoring the importance of localized
optimization for accurate Min N predictions.

DISCUSSION
Our analysis was limited to two soil properties,
and in-depth discussions concerning correlations wereconstrained. Further research is needed to encompass
an array of other soil properties and explore theircorrelations. Additionally, we will explore the viability

MATERIALS AND METHODS
A total of 2,890 soil samples were collected fromvarious regions (e.g., Gifu, Nara, Akita, Hyogo) in Japan,3

of substituting the soil testing process for the remaining
PLSR

RF

pH

Min N

pH

Min N

RMSE_T1

0.291

4.527

0.197

2.356

RMSE_T2

0.299

4.349

0.282

3.944

RRMSE_T1
RRMSE_T2

6.598
6.788

7.059
6.780

4.476
6.389

3.674
6.149

R2_T1

0.465

-0.013

0.678

0.401

R _T2
LCCC_T1

0.373
0.794

0.730
0.454

0.057
0.895

0.699
0.781

LCCC _T2

0.724

0.878

0.703

0.886

2

soil properties with FTIR.
Table. 1: Comparison model results. (T1: LOPO, T2:
Random CV, Min N: Mineralizable Nitrogen)

ACKNOWLEDGMENTS
The analysis of soil samples was conducted using the
FTIR and ICP-AES of the Division of Instrument
Analysis, Gifu University.

REFERENCES
Carrer, M J, de Souza Filho H M, Vinholis M D M B and
Mozambani C I (2022) Precision agriculture adoption
and technical efficiency: An analysis of sugarcane
farms in Brazil. Technol. Forecast. Soc. Change., 177:
121510.
Zhang N, Wang M and Wang N (2002) Precision
agriculture—a worldwide overview. Comput. Electron.
Agric. 36(2-3): 113-132.
Bhakta I, Phadikar S and Majumder K (2019) State‐of‐
the‐art technologies in precision agriculture: asystematic review. J. Sci. Food Agric., 99(11): 48784888.
Peltre C, Bruun S, Du C, Thomsen IK and Jensen LS(2014) Assessing soil constituents and labile soilorganic carbon by mid-infrared photoacoustic
spectroscopy. Soil Biol. Biochem., 77: 41-50.
Angelini ME, Kempen B, Heuvelink GBM, Temme AJ
and Ransom MD (2020) Extrapolation of a structural
equation
model
fordigitalsoil
mapping. Geoderma, 367: 114226.
Takoutsing B, Heuvelink GB, Stoorvogel JJ, Shepherd
KD and Aynekulu E (2022) Accounting for analyticaland proximal soil sensing errors in digital soil mapping.
European Journal of Soil Science, 73(2): e13226.

4

P3

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Microbial Fuel Cell and Macropores Play Crucial Roles in Suppressing
Nitrous Oxide Emissions from Rice Paddy Fields
Adhia Azhar Fauzan1, Ken Hiramatsu1, Takeo Onishi1 and Tomohiro Egusa3
1
2

The United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
Faculty of Agriculture, Shizuoka University, 836 Ohya, Suruga-ku, Shizuoka 422-8529, Japanavenue yet to be fully explored. Moreover, the role ofmacropores in the soil, another overlooked factor, shows
promise in reducing N2O emissions. Surprisingly, the ideaof combining PMFCs and macropores to address N2Oemissions remains uncharted territory, offering a newfrontier in the fight against climate change.
This study aimed to examine the emission of N2O,
redox, TOC (Total Organic Carbon) in water, TN (Total
Nitrogen) in soil, microbial, as well as plant growth. Theseobservations were made by implementing MFC,
macropore, or a combination of both methods. In this
exploration, we delve into the uncharted territory ofPMFCs, plants, and macropores, seeking to unlock theirpotential in reducing N2O emissions—a pursuit critical in
our quest to address climate change and preserve theplanet for future generations.

INTRODUCTION
In the wake of alarming climate reports, including thesobering declaration by the United Nations SecretaryGeneral that 'The era of global warming has ended; the eraof global boiling has arrived,' our planet faces anunprecedented climate crisis. The signs are unmistakable–
sea ice has reached record lows, global sea surface
temperatures continue to break records, and the relentlessincrease in temperatures is unequivocally linked to heattrapping greenhouse gases.
Among these greenhouse gases, nitrogen oxide (N2O)
emerges as a significant contributor, despite its seemingly
modest percentage in the overall greenhouse gas
inventory. N2O, with a Global Warming Potential (GWP)
of 273 times that of carbon dioxide (CO2), holds the
dubious distinction of having the highest GWP.
Agriculture, an industry vital to our survival, is asurprising source of greenhouse gas emissions,
responsible for 10% of all emissions. Just like humans,
plants need to 'breathe' and, in doing so, release gases thatfurther exacerbate the issue. But here's a twist – only 30%of the fertilizers we use are effectively absorbed by theseplants, while the rest finds its way into groundwater or
evaporates into more N2O, aggravating the problem.
Despite our best intentions, the approaches we've taken
to combat these greenhouse gas emissions have been
flawed, primarily focusing on physical and chemical
methods, overlooking a hidden factor that has been rightunder our feet – microbes. These tiny organisms play apivotal role in the greenhouse gas equation, consuming
plant root exudates, generating electrons as they
metabolize them. To complete this process, they require
nitrates (NO3-) as electron acceptors, ultimately releasing
N2O gas into the atmosphere.
However, there is hope on the horizon. The journey toaddress global energy challenges and reduce ourdependence on fossil fuels, which began with the adventof Microbial Fuel Cells (MFC) (Davis and Yarbrough1962), has evolved into a clean and environmentallyfriendly energy source, aligning with the goals ofsustainable development. A combination of MFC andplants offers a novel solution to regulate redox potential(EH) and reduce greenhouse gas emissions. PlantMicrobial Fuel Cells (PMFCs) introduce artificial electron
acceptors, preventing the utilization of natural oxidants by
microbes, while the remaining oxidants in the soil serve
as vital nutrients for plants (Insam and Wett 2008).
The potential of PMFCs in mitigating greenhouse gas
emissions, particularly the notorious N2O, is a promising

MATERIALS AND METHODSThe Research Period spanned from June 19th toSeptember 13th, 2023, allowing for comprehensive datacollection and analysis across the designated parameters.
GHG Analysis involved the use of a static closed chamber
method. Gas samples were collected at 4 PM every week,
capturing measurements at five time points (0, 15, 30, 45,
and 60 minutes after chamber closure). Gas concentration
was determined using a GC 2014, allowing for the
calculation of gas flux. Redox Measurement wascontinuously monitored with a Hioki LR5041, recording
data at 5-minute intervals. Electrodes were strategicallyplaced at a depth of 10 cm near the plant roots. Soil
Sampling was performed on a weekly basis to collectsamples for total nitrogen (N) analysis. Additionally, atthe time of harvest, soil samples were gathered for
subsequent microbial analysis. Water Sampling involved
the collection of water samples from a depth of 20 cm
below the soil surface using a Daiki DIK-8392. The Total
Organic Carbon (TOC) content in the water samples wasdetermined through analysis with a TOC-V. Plant Data
Collection included the regular recording of plant heightmeasurements on a weekly basis throughout the research
period. During the harvest, plants were collected fornitrogen level analysis, and the weight of 1000 seeds wasdetermined.

RESULTS AND DISCUSSION
Increasing redox, leading to a positive value, can beinterpreted as a success in efforts to reduce N2O
emissions. This is because, in general, redox in flooded

5

rice fields is in the negative range. The research results
indicate that the MFC+MP treatment achieved
consistently high redox values over an extended period.
However, it's worth noting that this treatment also
exhibited higher inconsistency. On the other hand, while
the MFC treatment didn't reach the same high values as
the MFC+MP treatment, the results tended to be morestable, with consistently positive values. While both MFC
and macropore treatments can individually increase redox
values, the results of this research lead to the conclusionthat their combination does not yield improved results. In
fact, it leads to fluctuations.

150.0
100.0
50.0
0.0
ControlMP

MFC

MFC+MP

3-Jul

10-Jul18-Jul

25-Jul

1-Aug

8-Aug

22-Aug29-AugFig. 3: Plant height during researchControlMP

MFC

MFC+MPACKNOWLEDGMENTS

10
5
0
-5
-10
-15
-20

I would like to express my sincere gratitude to the
MEXT scholarship for providing me with the opportunity
to conduct this research.

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REFERENCES
Davis JB and Yarbrough HF (1962) Preliminary
Experiments on a Microbial Fuel Cell Two in Its
Metabolism , Might Produce Measurable Current. SuchWas the Case. When Escherichia Coli Was Added to
the Biological Half-Cell with Glucose as Substrate, The
Open Circuit Voltage in- Creased Fr. Virology: 1–2.
Insam H and B Wett (2008) Control of GHG emission at
the microbial community level. Waste Management28(4): 699–706. doi: 10.1016/j.wasman.2007.09.036.

Fig. 1: Redox during the research

The concentration data produced in this study indicatesthat the MFC treatment has the lowest concentration,
while the control group emits higher N2O concentrations.
This observation can be deduced from the redox results,
which lead to the following outcomes.

2-Sep

26-Aug

19-Aug12-Aug5-Aug

29-Jul

22-Jul15-Jul

8-Jul

1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Fig. 2: N2O concentration of all treatments during the study

Based on the results of data processing, the Macropore
treatment produced the tallest plants, followed by the
MFC treatment. However, field observations revealed thattreatments involving MFC (MFC or MFC+MP) resulted
in the tallest plant growth.

6

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Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Predicting Rice Yields with Deep Learning Using UAV-BasedMultispectral Imagery and Weather Data
Md. Suruj Mia1, Ryoya Tanabe2, Luthfan Nur Habibi1, Naoyuki Hashimoto3, Koki Homma4,
Masayasu Maki5, Tsutomu Matsui6 and Takashi S. T. Tanaka6,7
1

The United Graduate School of Agricultural Science, Gifu University, Gifu 501-1193, Japan
Graduate School of Natural Science and Technology, Gifu University, Gifu 501-1193, Japan
3
Faculty of Agriculture and Marine Science, Kochi University, Kochi 783-8502, Japan
4
Graduate School of Agricultural Science, Tohoku University, Miyagi 980-8572, Japan
5
Faculty of Food and Agricultural Sciences, Fukushima University, Fukushima 960-1296, Japan
6
Faculty of Biological Sciences, Gifu University, Gifu 501-1193, Japan
7
Artificial Intelligence Advanced Research Center, Gifu University, Gifu 501-1193, Japan2

weather and image data may also contribute to improving
yield prediction accuracy.
The objective of this study was to develop a multimodal
deep learning model to predict rice grain yield using UAV
images at the heading stage and weather data.

INTRODUCTION
Yield monitoring and satellite-based remote sensing
technologies have been developed to measure the spatial
distribution of crop yields in large-scale farming practices.
In agriculture, timely, nondestructive, inexpensive, andreliable large-scale yield forecasts are important andprerequisite for preventing climate risks and ensuring foodsecurity (Wang et al. 2014). Precision agriculture involves
collecting, processing, and analyzing temporal and spatial
data and integrating it with other relevant information to
support resource-efficient management decisions.
However, the precision of yield predictions has often been
constrained by the limited spatial and temporal resolutionof satellite data (Wang et al. 2010). In response to thesechallenges, unmanned aerial vehicles (UAVs) have been
widely used to collect data due to their superior spatial,
spectral, and temporal resolutions compared to airborneand satellite plat-forms (Maimaitijiang et al. 2020).
Yield estimation models are very dependent on
substantial and specific input information and requirehuge computational costs (Cai et al. 2019). Machinelearning algorithms possess the capability to devise novel
solutions for real-world challenges, enabling farmers tomake informed decisions while requiring minimal or evenno human intervention (Srivastava et al. 2022). Among all
machine learning techniques, Convolutional Neural
Network (CNN) algorithm is efficient in image
classification and analysis and able to predict crop yieldaccurately (Fu et al. 2022, Tanabe et al. 2023 and Yang etal. 2019). Weather is one of the major environmental
factors affecting crop growth and yield. Incorporating
weather data after image acquisitions into CNN models
may enhance the precision of the yield prediction model.
CNN models are recognized for their demanding
computational needs and substantial memory
requirements, which can limit their applicability inresource-constrained environments. It is widely
acknowledged that enhancing CNN architectures by
increasing depth and width can lead to improved model
performance (Alzubaidi et al. 2021). However, increasing
the depth of the architecture after the integration of

MATERIALS AND METHODS
Rice yield surveys were conducted in 22 farmers’ fields
in Japan over six years (2017–2022). Nine rice varieties
were planted, and crop management was conductedaccording to local conventional methods. Strip trials were
performed in 12 fields for basal fertilizer application to
obtain high yield variability and to determine whether theeffect of fertilizer application rate on rice yield could be
evaluated using a predicted yield map. A total of 894
samples were collected in all yield surveys, from an areaof approximately 1.0 m2 at the heading stage. UAV
multispectral
imagesandweather
data(https://amu.rd.naro.go.jp) for each region were collected
and processed. 18 architecture models consisting of two
types of CNN feature extractor layers (i.e., CNN_2conv
and AlexNet), three different depths of fully connected
layers, and three methods of integrating weather data (noweather data, weekly sum of weather data, and monthly
sum of weather data) into deep neural network models
were established. The model's performance was assessedby employing the R2, root mean squared error (RMSE),
and root mean squared percentage error (RMSPE)
metrics. The statistical analysis was conducted using
Python (version 3.8.10) and SciPy (version 1.9.1). An
analysis of variance (ANOVA) was executed to assess
how the architectures influenced the model's performance.
Tukey's honestly significant difference test (Tukey's
HSD) was employed to detect disparities in the mean
performance values of the models. In all the analyses, asignificance level of p < 0.05 was adopted.

RESULTS
The distribution of collected data was approximately
normal. The mean value was 6.65 t ha–1, and the standard
deviation was 1.46 t ha–1. There was no significant
difference between the AlexNet and CNN_2conv
7

architectures. The effects of the number of layers andweather data types on the model performance weresignificant but according to Tukey's HSD results, there
were no significant differences among various layers. The
top two accurate models with the lowest RMSE values
were found in models integrating weekly weather data as
input data with either AlexNet or CNN_2conv (Table 1).
Using the optimal models from both architectures, theyield maps predicted (one On-Farm Experimentation
field) are illustrated in Fig. 1. These yield maps, for bothscenarios, reveal variations in yield across the field, with
distinct areas where various rates of basal fertilizer wereapplied.

CNN architecture, farmers and researchers can make moreaccurate predictions, optimize resource allocation, andimprove overall agricultural sustainability.

REFERENCES
Alzubaidi L, Zhang J, Humaidi AJ, Al-Dujaili A, Duan Y,
Al-Shamma O et al. (2021) Review of deep learning:
Concepts,
CNN
architectures,challenges,
applications, future directions. J. Big Data, 8: 53.
Cai Y, Guan K, Lobell D, Potgieter AB, Wang S, Peng J etal. (2019) Integrating satellite and climate data to
predict wheat yield in Australia using machinelearning approaches. Agric. Meteorology, 274: 144–
159.
Fu Z, Yu S, Zhang J, Xi H, Gao Y, Lu R et al. (2022)
Combining UAV multispectral imagery andecological factors to estimate leaf nitrogen and grain
protein content of wheat. Eur. J. Agron., 132: 126405.
Maimaitijiang M, Sagan V, Sidike P, Hartling S, Esposito
F and Fritschi FB (2020) Soybean yield prediction
from UAV using multimodal data fusion and deeplearning. Remote Sens. Environ., 237: 111599.
Srivastava AK, Safaei N, Khaki S, Lopez G, Zeng W,
Ewert F et al. (2022) Winter wheat yield prediction
using convolutional neural networks fromenvironmental and phenological data. Sci. Rep., 12:3215.
Tanabe R, Matsui T and Tanaka TST (2023) Winter wheatyield prediction using convolutional neural networks
and UAV-based multispectral imagery. Field Crops
Res., 291: 108786.
Wang K, Franklin SE, Guo X and Cattet M (2010) Remotesensing of ecology, biodiversity and conservation: A
review from the perspective of remote sensing
specialists. Sensors, 10: 9647–9667.
Wang L, Tian Y, Yao X, Zhu Y and Cao W (2014)
Predicting grain yield and protein content in wheat
by fusing multi-sensor and multi-temporal remotesensing images. Field Crops Res., 164: 178–188.
Yang Q, Shi L, Han J, Zha Y and Zhu P (2019) Deep
convolutional neural networks for rice grain yield
estimation at the ripening stage using UAV-based
remotely sensed images. Field Crops Res., 235: 142–
153.

Table 1: Performance of best CNN models of botharchitecture for predicting rice yields

R2
RMSE (tha-1)
RMSPE (%)

Alexnet architecture CNN architecture
Train
Test
Train
Test
0.66
0.65
0.68
0.65
0.842
0.859
0.821
0.860
14
14
13
14

Fig. 1: Yield prediction map by using (a) Alexnetarchitecture-based CNN model and (b) CNN_2conv
architecture-based CNN model.

DISCUSSION
This research investigates the capability of multimodal
deep learning models, utilizing UAV multispectral andweather data, to achieve highly accurate predictions ofrice yield. Models trained with weekly weather dataconsistently outperform others. There has the spatial
variation of predicted yield maps across the different
models, despite similar prediction accuracy. By
incorporating weekly weather data and simplifying the8

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Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Biological Weed Control Through Weed Predation by Pill Bugs
(Armadillidium vulgare L.) in Nursery of Tea Tree (Camellia sinensis)
Niken Nabilaputri Pranaasri1, 2 and Yamashita Masayuki2
1
2

The United Graduate School of Agriculture Science, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
Graduate School of Integrated Science and Technology, Shizuoka University, 836 Ohya, Suruga, Shizuoka 422-8529,
Japan
Soil was filled up to 80% of containers sized 72 cm x
26 cm x 40 cm. Two 12-months-old tea trees were plantedin the middle of the containers (±15 cm apart) for eachcontainer. There were four treatments, each with 3
replicates: (A) tea tree only, (B) tea tree + weed seeds, (C)tea tree + pill bugs, and (D) tea tree + weed seeds + pillbugs. For the treatment using weed seeds, five weed
species were used, Crassocephalum crepidoides(Redflower ragleaf), Eleusine indica (Indian goosegrass),
Lolium multiflorum (Italian ryegrass), and Taraxacum sp(Dandelion), with seed sizes 2 mm, 4 mm, 6 mm, and 4mm, respectively. Fifty seeds of each weed species were
distributed at random to the containers of treatment B and
D. For the treatment using pill bugs, 30 male pill bugs witha length of approximately 2 cm were added to thecontainers of treatment C and D. Five individuals of pillbugs were added every week. To keep other insects andbirds out, the containers were netted. Water sprinklers
were installed for daily watering.
To investigate the effects of pill bugs on weeds, thegermination rates were calculated by counting the numberof germinated seeds in treatments B and D every week. To
examine the effects of pill bugs and weeds on the tea tree
growth, leaves number of the tea tree was recorded in the
all treatments.

INTRODUCTION
Tea is one of the world’s most valuable commodities.
To achieve high production, optimal cultivation is critical.
Weeds are one of the main challenges limiting
productivity in the fields. According to Peiris andNissanka (2016), uncontrolled broadleaf weeds can cover
15% of the ground area of a tea plantation. Weeds thatgrow rapidly harm the tea plants, causing poor bush frame.
Weeds that grow on the edges of the tea fields obstruct tea
plantation management and serve as hosts for pests(Ichihara et al, 2020).
For decades, herbicides have been widely used tocontrol weeds. However, excessive use of herbicides has
led to herbicide-resistant weeds. In Japan, glyphosateresistant grass weeds Lolium multiflorum (Italianryegrass) and Eleusine indica (Indian goosegrass) weredetected in rice paddy levees in 2011 (Heap, 2023). In
terms of ecology, the use of herbicide leaves chemical
residue in the ecosystem. Therefore, another effective
weed control method is necessary. Instead of usingchemicals, biological weed control takes advantage of thebenefits from ecosystem. Seed-predators are one of thebeneficial organisms. Ichihara et al (2012) reported thatseed predation by ground insects effectively decreases
seed emergence of Italian ryegrass.
Pill bugs (Armadillidium vulgare L.) are terrestrial
isopods that are common in grassland (Souty-Grosset andFaberi, 2018), and they feed on both dead and living
plants. Saska (2008) discovered that pill bugs are observed
feeding on plant seeds. According to our prior study, pillbugs were identified in abundance in tea fields. Therefore,
the potential roles of pill bugs as weed control in tea fields
are necessary to be investigated. Furthermore, since thepresence of weeds might interfere with the tea plants, therelationship between the presence of pill bugs, weeds, andtea plants is also essential to be explored. The main aim of
this study is to examine the potential role of weed
predation by pill bugs as a biological weed control in thenursery of tea plants.

RESULTSThe germination rates of weeds were recorded to besignificantly lower on C.crepidoides, Taraxacum sp., andL.multiflorum with pill bugs (in treatment B) compared tothose without pill bugs (in treatment D). In contrast, thegermination rates in E.indica did not differ between the
two treatments. However, there is a trend that its
germination rates tended to be lower in the treatment B(Fig.1). Pill bugs were observed feeding on the weed seeds
and seedlings. The seedling predation rates of each weed
species on C.crepiroides, Taraxacum sp., L.multiflorum,and E,indica were from 12.5% to 29.3%. These results
suggested that seedling predation by pill bugs was variedamong the weed species.
In the observation on tea tree, the results showed thatthe leaf numbers of the tea did not differ among
treatments, yet it can be seen that a trend showed the leaf
numbers in the treatment D was slightly higher comparedto the other treatments (Fig.2).

MATERIALS AND METHODSThe experiment was carried out in the experiment fieldof Shizuoka University from July 4th to August 22th, 2023.
Before the experiment, pill bugs were collected on thecampus of Shizuoka University and kept in incubators in
the laboratory at 25°C 12:12 LD.

9

Tea tree + Weed Seeds (B)Tea tree + Weed Seeds + Pill bugs (D)Ave. Germination rates (%) ± SE.

**
100
90
80
70
60
50
40
30
20
10
0

*
*

C.crepidoides Taraxacum sp. L.multiflorum

E.indica

Weed species

Fig.1. Germination rates of four weeds species in treatment
without pill bugs (B) and with pill bugs (D).

Ave. Leaves number ± SE.

70
60

a

a

a

a

50

then suggested that weed predation by pill bugs may be
used as biological weed control in the future.
When pill bugs are present, the weed population canbe suppressed. This will decrease the competition between
tea trees and weeds, allowing the tea to grow better.
Meanwhile, when pill bugs are not present, the weed
populations are not controlled. Massive growth of weeds
will interfere with the tea trees and may alter the growthof tea trees. Tea nursery (8-18 months old after planting)is said to be the critical period for weed intervention (Dekaand Barua, 2015). The development of the tea bushes in
tea nursery may be blocked by the growth of the weeds.
The presence of pill bugs was not adversely affecting
the growth of the tea tree, especially when weeds were
present together with the tea tree. Pill bugs are soil-surfaceorganisms. In this situation, dispersal seeds are easier toreach, hence, they tend to graze on the weeds rather than
the tea trees (Fig.2). In addition, since tea trees are woody
plants, they are considerably hard to be ingested by pillbugs. This may create the pill bug’s predilection for weeds
and tea trees.

REFERENCES

40

Deka J and Barua I C (2015) Weed of tea fields and theircontrol. National Seminar on Plant Protection in Tea.
Tea research Association Tocklai Tea ResearchInstitute Jorhat, Assam, India.
Heap I (2023) The International Herbicide-Resistant
Weed Database Online.
www.weedscience.org (Accessed on 12 October 2023)
Ichihara M, Inagaki H, Matsuno K, Saiki C, Yamashita M,
and Sawada H (2012). Postdispersal seed predation by
Teleogryllus emma (Orthoptera: Gryllidae) reduces theseedling emergence of a non-native grass weed, Italianryegrass (Lolium multiflorum). Journal of Weed
Biology and Management, 12: 131–135.
Ichihara M, Togawa M, and Haga H (2020) Vegetation in
tea field margins and climbing plants on tea bush
canopies in Shizuoka Prefecture, Japan. J. Weed. Sci.
Tech., 65: 114–117. (In Japanese)
Peiris H M P and Nissanka S P (2016) Affectivity ofchemical weed control in commercial tea plantations: A
case of study in Hapugastenne Estate, Maskeliya, Sri
Lanka. Procedia Food Science, 6: 318–322.
Saska P (2008) Granivory in terrestrial isopods.
Ecological Entolomogy, 33: 742–747.
Souty-Grosset C and Faberi A (2018) Effect ofagricultural practices on terrestrial isopods: A review.
Zookeys, 801: 63–96.

30
20
10
0
Tea tree only Tea tree + Tea tree + Pill Tea tree +(A)
Weed Seeds
bugs (C) Weed Seeds +(B)
Pill bugs (D)Fig.2. Average of leaves number of tea tree in eachtreatment.

DISCUSSION
This study revealed that pill bugs are effective indecreasing the weed population by reducing the numberof germinated seeds. Further, this study suggested that thedecrease in seed emergence was caused by seed predation.
Pill bugs feed on the seeds of the weeds regardless of theweed species. However, during the predation activity, pillbugs have different seed preferences depending on theweed species. Seeds of C.crepidoides are preferable to
Taraxacum sp. and L.multiflorum. Saska (2008) statedthat the size of weed seeds influences predator attack
encounters in post-dispersal seed predation. In this study,
C.crepidoides was the smallest-sized seed andL.multiflorum was the largest-sized seed among the used
weed species.
Pill bugs have been observed feeding on weed seeds
and seedlings, implying that they play roles in weed
control. Seed banks have been demonstrated to have asignificant impact on weed growth and population
dynamics. The presence of pill bugs may aid in reducing
the seed bank through weed seed predation. Furthermore,
seedling predation by pill bugs will cause damage andhamper the weed development. The results of this study

10

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Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

FEM Analysis of Withdrawal Performance of Self-Tapping Screw andCross-Laminated Timber Joint
Sarah Amira1,2, Kenji Kobayashi2 and Keita Ogawa2
1
2

The United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan
Faculty of Agriculture, Shizuoka University, 836 Ohya, Suruga-ku, Shizuoka 422-8529, Japan
Materials—The withdrawal strength of a single STS
inserted into a CLT was measured using a withdrawal
loaded test. The test materials used in this study werecomposed of small pieces of five-layered CLT made ofsugi (Cryptomeria japonica D. Don) lamina. Two types ofconnectors, fully threaded STS (PX8-260) and partiallythreaded STS (PS8-260), manufactured by Synegic Co.,
Ltd., with a thread diameter of 8 mm and total length L of
260 mm were considered and distinguished by theeffective length of the STS threaded part inserted into thespecimen lef (mm) (the shapes of the screw head and screw
tip were ignored). The lef of the fully threaded STS varies
depends on the thickness of the CLTs, whereas those of
the partially threaded STSs were set to 80 mm.
Withdrawal test—The STS was driven through theentire test specimen in order to avoid the tip influencing
the layer orientation, as shown in Fig 1. A turned washer
with a diameter of 8 mm was used to fix the screw head tothe screw grip. A screw grip shaped to fit the head of the
STS was attached to the load head of a universal testingmachine (UTM, Shimadzu Co., AG-I 250 kN) for
applying the monotonic static load at a constant rate of 1
mm/min. Four displacement gauges, one pair of CDP-10
with a capacity of 10 mm and one pair of CDP-25 with acapacity of 25 mm (manufactured by Tokyo Measuring
Instruments Laboratory Co., Ltd.), were attached in the
crossway each other to record the displacement during thewithdrawal test.
FEM simulation—The 3D models consisted of the STS
inserted into CLT were created using Autodesk Fusion
360 software and imported to the MSC Marc/Mentat
commercial finite element software as solid body andgenerated a mesh that consisted of linear tetrahedral
volumetric elements (with hybrid elements for partiallythreaded STS). Ten solid mesh seeds were applied to theedge of the thread-profiled hole on CLT as a parameter ofthe generated mesh elements number around the STSadjacent CLT. The mesh element of CLT was splined inorder to gives a more accurate representation of the actual
physical geometry and a more accurate calculation of thenormal vector (HEXAGON, 2022). Elements of the CLT
body were defined as elastic-plastic orthotropic material,
while elements of the STS body were defined as anelastic-plastic isotropic material. Therefore, thelongitudinal grain orientations were projected in x axis forthe odd layers (layers 1, 3, and 5) and y axis for the evenlayers (layers 2 and 4). The material properties of sugi
wood according to wood industry handbook (Forestry andForest Products Research Institute, 2004) and steel wasmodelled as an elastic and perfectly plastic material andthe Hill criterion was used for wood. The loads subjected

INTRODUCTION
Cross-laminated timber (CLT) is an engineered wood
product used in wooden houses to achieve environmental
sustainability in Europe, Australia, and North America.
Interest in CLT as a newly developed technology has
increased in Japan. Izzi, et al. (2018) stated that CLT
structures exhibit satisfactory performance under seismic
conditions because of the high strength-to-weight ratio
and in-plane stiffness of the CLT panels and the capacityof connections to resist loads with ductile deformations
and limited strength impairment.
Self-tapping screw (STS) optimized primarily for axial
loading, represent the state-of-the-art fastening andreinforcement technology in CLT construction(Mohammad et al., 2013; Kobayashi, 2015; Dietsch and
Brandner, 2015). Recently, the Japanese Industrial
Standard for STSs for timber joints (JIS A 1503) has been
published. However, this standard does not include
withdrawal strength and head pull-through properties
because their inclusion requires the consideration of theproperties of the adjacent wood; the JIS is primarily
focused on the fastener property (Goto et al., 2018).
The appropriate modelling and formulations in finite
element method (FEM) simulation can be a nondestructive analysis for the precaution of the possible
withdrawal deformations occurrence of the CLT-STS
joint resisting the withdrawal load on STS, which isdifficult to be visually observed in the laboratory
experiment. Previous studies have numerically andtheoretically investigated the mechanism of axially loaded
STS withdrawal strength through the wooden member
with the simplified models (Avez, et al., 2016; Honda etal., 2021). Through the linear elastic analysis from FEM,
the simulation results generally follow the stiffness trendof the experimental values. However, the failure modes
and deformation were less representative due to thesimplified models. This study evaluated the initialstiffness of an STS inserted into small pieces of CLT
where the 3D models were made more precise and as
similar as possible to the actual shape, concerned with theorientation of each lamina in CLT layers in the same stateof the specimen as the experimental withdrawal test, andthe deformations that occurred within both components
were observed through FEM simulation.

MATERIALS AND METHODS

11

to the specimen were approximated to the mesh elements
in boundary condition. The withdrawal displacement was
defined as fixed displacement applied to the six nodes on
the screw head surface in positive z-axis direction, while
the CLT elements were fixed to zero in the axial androtational to the z-axis with the slight fixed x and y-axes
to keep the main position.

failure in withdrawal test, characterized by the shear
failure at the wooden members surrounding the STS to thesticking out of the upmost layer of CLT around the STS(Pang et al., 2020). Within two seconds of simulation, themajor displacement of the CLT member with fully
threaded STS occurred along the STS threads-contacted
parts with the highest withdrawal displacement at 1.599
mm and the surface of the upmost layer was sticking out
which is also found on the experimental withdrawal
failure. In the model of those with partially threaded STS,
withdrawal deformation occurred inside the CLT memberthat only in contact with the threads section of partiallythreaded STS with the maximum displacement of 4.008
mm.

RESULTS AND DISCUSSION

Load (kN)

Load (kN)Comparison
betweenFEM
simulation
andexperimental results—In the current progress, the FEM
simulation prescription were only attaining the elastic toplastic state after 111 trials. The softening behaviour after
a maximum load has been reached could not be
represented from the simulation due to damaged softening
behaviour can lead to numerical solution nonconvergence (Zhang, Chun, Lin, Wang, & Li, 2022).
Therefore, the initial stage of the scheme of axial static
loading subjected to a STS inserted into CLT was
evaluated in linear elastic analysis by comparing the initialstiffness K0.1~0.4 (the stiffness within the range of 10-40%
of maximum load). The initial stiffness obtained from
FEM simulation overestimated those of experimental
result 22% for CLT with fully threaded STS and 38% forpartially threaded STS, as projected in Fig. 1. As theprescriptions of the FEM simulation described the CLT as
an orthotropic material, the other natural characteristics ofwood have not well represented yet and it was leading to
the uncompleted static load and displacement curve as
intended.
18
16
14
12
10
8
6
4
2
0
18
16
14
12
10
8
6
4
2
0

REFERENCES
Avez C, Descamps T, Serrano E and Le´oskool L (2016)
Finite element modelling of inclined screwed timber totimber connections with a large gap between theelements. Eur. J. Wood Prod., 74: 467–471.
Dietsch P and Brandner R (2015) Self-tapping screws andthreaded rods as reinforcement for structural timberelements - a state-of-the-art report. Construction and
Building Materials, 97: 78–89.
Forestry and Forest Products Research Institute. (2004).
Wood Industry Handbook 4th Revised Edition], pp.
135–136. Maruzen Publishing. Tokyo. (In Japanese)
Goto Y, Jockwer R, Kobayashi K, Karube Y andFukuyama H (2018) Legislative background andbuilding culture for the design of timber structures in
Europe and Japan. World Conference on TimberEngineering. Seoul, Republic of Korea.
HEXAGON. (2022). Marc Volume A: Theory and User
Information. Hexagon. California, United States.
Honda W, Ochiai Y, Aoki, K and Inayama M (2021)
Mechanism of Withdrawal Resistance of Screws
Embedded Perpendicular to Grain and Evaluation
Method of Withdrawal Strength. Mokuzai Gakkaishi,
67(4): 178–187. (In Japanese with English abstract)
Izzi M, Casagrande D, Bezzi S, Pasca D, Follesa M andTomasi R (2018) Seismic behaviour of CrossLaminated Timber structures: A state-of-the-art review.
Engineering Structures, 170: 42–52.
Kobayashi K (2015) Present and future tasks for screw
joints in timber structures. Mokuzai Gakkaishi, 61(3):162–168. (In Japanese with English abstract)
Mohammad M, Douglas B, Rammer D and Pryor SE(2013) Chapter 5 - Connections in cross-laminatedtimber buildings. In: E. Karacabeyli, and B. Douglas(Eds.), CLT handbook: cross-laminated timber, pp. 3–
44. FPInnovations. Canada.
Pang SJ, Ahn KS, Kang SG and Oh JK (2020) Predictionof withdrawal resistance for a screw in hybrid crosslaminated timber. J. Wood Sci., 66(79): 1–11.
Zhang C, Chun Q, Lin Y, Wang H and Li P (2022)
Experimental and nonlinear finite element. J. Wood
Sci., 68(41): 1–18.

(A) Fully threaded STS
FEM simulation
Experimental results(B) Partially threaded STS
FEM simulation
Experimental results

0

1

2

3

4

5

6

7

8

9

10

Displacement (mm)Fig. 1: Load-displacement comparison of FEM simulationand experimental result. (A) CLT with fully threaded selftapping screw; (B) CLT with partially threaded self-tapping
screw.

Visualisations of withdrawal deformations—The
deformation observed visually through the contour bands
scalar simulation results. Withdrawal failure is an initial

12

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Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Effects of Ultraviolet Light on the Post-harvest Quality of Cherry Fruits(Prunus avium L.)
Nabila Nurul Ahmeidiati, Teppei Imaizumi, Manasikan Thammawong and Kohei Nakano
The United Graduate School of Agriculture Science, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japantransporation was around 2 days. Cherries then stored for
14 days under the temperature of 0.5 °C in incubator.

INTRODUCTION

Vitamin C
A pitted fresh cherry around 4 grams (+/- 1 gram) was
finely chopped and extracted with 15 mL of
metaphosphoric acid. The homogenized solution of cherry
is measured using High Performance Liquid
Chromatography (HPLC). The amount of vitamin C per
100 grams of cherries was calculated. Vitamin C wasmeasured in day 0, day 2, day 4, day 6, day 8, day 10, day,12, and day 14.

Cherries are considered a remarkable nutritious fruitthat contains substantial quantities of vital nutrients andbioactive elements. These include glucose, fructose,
vitamin C, anthocyanins, quercetin, flavan-3-ols,
flavonols, and hydroxycinnamates (Zhang et al., 2021).
The decline in quality observed in cherry fruits from thetime of harvest to consumption can be attributed to various
factors, including physical alterations, chemicaltransformations, enzymatic reactions, and microbiologicalchanges. The potential repercussions of this quality
degradation resulting from microbial activity pose asignificant threat to consumers, as it may lead to thepresence of harmful toxins or pathogens. Additionally, it
is accompanied by economic losses stemming from these
deteriorations (Saparov et al., 2023). Therefore, thepreservation of cherry fruits over an extended period issignificantly important, serving the dual purpose of
facilitating fruit marketing and preserving its quality
attributes. The degradation of vitamin C during processing
and storage is a significant concern for nutrition experts,
food processors, and consumers alike. Vitamin C isemployed as a gauge of the health-related quality of fruits
because it is more susceptible to deterioration whencompared to other beneficial compounds.
Ultraviolet (UV) radiation is considered to begermicidal against microorganisms such as bacteria,
viruses, protozoa, yeasts, moulds and algae (Keyser et al.,2008). It disrupts the cellular DNA of a wide range of
microorganisms by changing the formation of pyrimidine
dimers, and it has been frequently employed fordisinfection purposes (Bintsis et al., 2000). However, it
must be noted that overexposure of UV light may resultin lipid peroxidation, membrane damage as wellas programmed cell death and thus shorten the shelf lifeof fresh produce if not in the correct dosage. Therefore,
the most efficient dosage of UV light radiation to preserve
the quality of cherry fruits is investigated. Especially invitamin C as one of the main nutrients in cherry fruits.

RESULTSOn Day 0 of the storage, as seen on Fig.1, vitamin C
levels exhibited higher concentrations for cherries
subjected to UV exposures of 0 mJ/cm2, 50 mJ/cm2, and1000 mJ/cm2, while lower concentrations were observed
for those exposed to UV 100 mJ/cm2 and 150 mJ/cm2.

Fig. 1 : Vitamin C of cherry fruits during Day 0 storage.

This concentration of vitamin c collerates with color of the
fruits (Fig 2), where it is shown in the visual observationthat cherries exposed with UV 100 mJ/cm2 and 150
mJ/cm2 has lighter color compared to the one with higher
vitamin C concentration.

MATERIALS AND METHODS
A fresh cherries from Yamagata Prefecture subjected
to various dosage of UV-C radiation of 0 mJ/cm2 , 50
mJ/cm2 , 100 mJ/cm2,, 150 mJ/cm2, and 1000 mJ/cm2 wastransported to lab in Gifu Universty, Gifu Prefecture bycommercial delivery company. Duration of theFig. 2: Cherry fruits color observed in Day 0 storage.

13

Observed until the day 14 of storage (Fig.3), a gradualdecline in vitamin C levels was noted over time forcherries exposed to UV 0 mJ/cm2, 50 mJ/cm2, and 1000mJ/cm2, with minimal fluctuations in the vitamin C levels
for those exposed to UV 100 mJ/cm2 and 150 mJ/cm2. Itis hypothesized that cherries exposed to UV levels of 0,
50 mJ/cm2, and 1000 mJ/cm2 experienced a gradualreduction in vitamin C content from Day 0 to Day 14. In
contrast, cherries subjected to UV 100 mJ/cm2 and 150
mJ/cm2 exhibited a swift decline in vitamin C content
within a single day, likely attributable to the stress induced
by UV radiation.

main pigment in red colored fruits. Gao and Maza (1999)
mentioned that the color of cherries is predominantly
determined by the arrangement and amount of various
anthocyanins present in their skin.
In contrast, cherries exposed to UV 100 mJ/cm² and 150
mJ/cm² exhibited a swift decline in vitamin C content
within a single day. This rapid reduction can be attributed
to the higher levels of UV radiation, which overwhelmed
the cherries' antioxidative capacity. Such exposure might
have led to the increased production of reactive oxygen
species, leading to a faster degradation of vitamin C. It isessential to consider that high levels of UV radiation may
not only trigger oxidative stress but could also directly
affect the stability of vitamin C.
Overall, the findings suggest that cherries have a
differential response to UV exposure, with low levels of
UV potentially stimulating protective mechanisms, whilehigh UV levels lead to rapid vitamin C degradation until
it reaches certain saturation where vitamin C level
increases again. Further research is needed to explore
the specific biochemical and molecular mechanisms
underlying these responses. Understanding thesemechanisms can have significant implications for
optimizing cherry preservation and enhancing theirnutritional value under various environmental conditions.

REFERENCES

Fig. 3: Vitamin C of cherry fruits during Day 14 storage

Bintsis T, Litopoulou‐Tzanetaki E and Robinson RK(2000). Existing and potential applications ofultraviolet light in the food industry–a criticalreview. Journal of the Science of Food andAgriculture, 80(6): 637–645.
Gao L and Mazza G (1995) Characterization, quantitation,and distribution of anthocyanins and colorlessphenolics in sweet cherries. Journal of Agriculturaland Food Chemistry, 43(2): 343–346.
Keyser M, Műller IA, Cilliers FP, Nel W and Gouws PA(2008) Ultraviolet radiation as a non-thermal
treatment for the inactivation of microorganisms infruit juice. Innovative food science and emerging
technologies, 9(3): 348–354.
Saparov DE, Sultonova SA, Pulatov MM and Boltaboyev
KK (2023) Experimental study of processing sweet
cherries with ultraviolet radiation. In IOP Conference
Series: Earth and Environmental Science, 1231(1):p.012033.
Zhang Q, Yang W, Liu J, Liu H et al. (2021). Postharvest
UV-C irradiation increased the flavonoids andanthocyanins
accumulation,phenylpropanoid
pathway gene expression, and antioxidant activity insweet cherries (Prunus avium L.). Postharvest Biology
and Technology, 175: 111490.

DISCUSSION
The initial divergence in vitamin C concentrations on
Day 0, with higher levels in cherries exposed to 0 mJ/cm²,
50 mJ/cm², and 1000 mJ/cm² of UV, compared to lower
levels in those exposed to 100 mJ/cm² and 150 mJ/cm²,
suggests a differential response to UV radiation. Thisinitial contrast may be attributed to the induction ofprotective mechanisms in cherries exposed to lower UVlevels, potentially triggering the synthesis defense
compounds that disturb the production of vitamin C as canbe seen to effect the vitamin C level of 100 mJ/cm² and150 mJ/cm² exposure. However, once it reaches
saturation, the defense mechanism get deactivated andvitamin C is produced without disruption, as observed in1000 mJ/cm² of UV exposure which is way higher than its
counterpart.
The gradual reduction in vitamin C levels observed
over the course of the study for cherries exposed to UV 0
mJ/cm², 50 mJ/cm², and 1000 mJ/cm² indicates asustained oxidative stress response. It is plausible thatthese cherries were able to maintain a certain degree of
defense against UV-induced oxidative damage, slowing
the degradation of vitamin C over time. This could be dueto the activation of antioxidant systems or the presence ofprotective compounds that counteracted the effects of UV
exposure. As seen on Fig. 2, UV 0 mJ/cm², and 50 mJ/cm²
treated cherry that are more pale compared to othertreatment, it may indicates that UV 0 mJ/cm², and 50
mJ/cm² delay the production of anthocyanin which is the

14

P8

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Quantitative Analysis of Japanese Commercial Coating Penetration into
Fagus crenata Blume Wood Using X-ray Microtomography
Tyana Solichah Ekaputri1, Ayuni Nur Apsari1, Takashi Tanaka2 and Kenji Kobayashi2
1

2

The United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
Graduate School of Integrated Science and Technology, Shizuoka University, Oya 836, Suruga-ku, Shizuoka City 4228529 Japanray microtomography for coatings applied to the surfaceof Japanese beech (Fagus crenata Blume).

INTRODUCTION

MATERIALS AND METHODSThe use of film thin layer has become ubiquitous
practice across much of the scientific and industrial sector,
recently. Coatings can enhance physical, chemical andaesthetic properties with lower the costs of the final
product. Coating applications such as varnish, stain andpaint, are commonly used in the furniture industry.
The interactions between coatings and natural material
like wood and the very complex formulations of coatings
make predictions of their service life and performancechallenging (Hazir and Koc, 2021). Coatings are used toobtain a synergistic action between the characteristics ofsubstrate and the covering materials (Hazir and Koc,2019). The fact well-known that the coating performance
namely adhesion is depending on a hygroscopic
characteristic of wood composite panels (Dilik, et al.,2014). Therefore, coating type plays an important role on
coating performance such as film thickness which affects
the abrasion resistance and the adhesion of the coating
itself. According to Cassens and Feist (1986), finishing
characteristics of coatings on wood surfaces depend on alarge number of variables, of which the coating-film
thickness is an important one. In addition, the penetrationof the coating into the wood become important for several
reasons. Firstly, coating penetration can improve water
repellence and dimensional stability and reduce thesurface cracks. Second, the adhesion of the coating to thewood material will benefit from a certain degree ofpenetration as well such as mechanical entanglement orinterlocking, adsorption interaction by polar anddispersive forces, and intermolecular diffusion. Third,
coating contained fungicides might have improved
penetration of the fungicide because it penetrates together(Meijer, 1998).
Coating penetration is mainly determined by the abilityof the coating to flow into the lumina of either tracheid or
ray-cells. Therefore, the anatomical microscopic
penetration is fundamental to be investigated. In previous
study by Ekaputri et al. (2021), Japanese commercial
coatings penetration into Fagus crenata veneer was
successfully visualized using X-ray microtomographythat resulted in 2D and 3D images. To deeply understandthe penetration scheme of coating materials into wood
affected by the chemical content of it, the quantitative
analysis is important to be investigated.
Accordingly, the aim of this study was to determine theeffects of chemicals on the coating penetration using X-

Fagus crenata Blume veneer was prepared withdimension 300 mm x 300 mm x 1.3 mm. Four veneers
were prepared and proceed with cold-pressing and hotpressing with the pressure 1 MPa for 20 min and hotpressed with pressure 1 MPa at 125 °C for 4 min. Aftercooling down, the veneers were cut into 100 mm x 100
mm (length and width) for the coated veneer and one
control sample.
Japanese commercially available coating waspurchased from Shizuoka, Japan. The specification of
coating used to finish the veneer sample explained on
Table 1.
Table 1. Coating specifications
Material
Name

Color

IngredientsThat Might
Affect X-ray
Interaction
Titanium
DioxidePercentage(%)

Chemical
FormulaAspen
LacquerSpray(Asahipen)

Brown
(BR)

0.1–1

TiO2

Matte
White
(MW)

Amorphous
Silica

1.0–5.0

SiO2

Titanium
Dioxide1.0–10

TiO2

Pink
(PK)

Titanium
Dioxide1.0–10

TiO2

White
(WH)

Titanium
Dioxide1.0–10TiO2

The experiment continued into X-ray scanning processusing µXCT (Rigaku nano3DX) with tube voltage at 50
kV, and tube current 24 mA, using L1080 lens (F.O.V
φ3.6 (diameter) × 2.8 (height) mm), and X-ray target was
Mo. The dimension of the X-ray specimens was cut into
10 x 50 x 1.3 mm to fit the F.O.V of the L1080 lens. Afterthe completion of the image acquisition, the CT
reconstruction processes were implemented using thecomputer connected with the apparatus and thus 1234 16bit gray-scale tomograms with the resolution of 1648 ×
1648 (2.2 μm/pixel) were obtained.
The quantitative analysis was performed using ImageJ
and VGStudio software with processing the image
obtained. The determination of tangential axis (5 lines)
and longitudinal axis (6 lines) was carried out using
VGStudio software with 3D image explained in Figure 1.
After the image cutting, the grey value was analyze using
ImageJ to determine the penetration distance.

15

74.55

3.4

White
Pink
Matte White
Brown

283.15250.25229.6
229.25

Tangential cut (mm)

(a)

(b)

(c)

3.1

132.65201.9
207.552.5

298.48

149.8

0

100

385.7

310.1
453.95103.42

2.2

Fig. 1 The mechanisms of partition of the woodcoated samples (a) The determination of vertical andhorizontal axis; red arrow indicates the longitudinal
cut and orange line indicates the tangential cut ofwood-coated surface; (b) tangential cut; (c)longitudinal cut

321.6573.15

2.8

371.72241.15

218.4
233.1

200

300

400

500

Penetration Distance (µm)

Fig 3. Average penetration amount of Japanese commercial
coatings (Tangential cut)

In conclusion, the use of µXCT visualization caninvestigate the penetration of Japanese commercial
coatings in the veneer and quantify its penetration amount.
This finding is important for industrial aspects that might
combine many wood species and coating products.

RESULTS AND DISCUSSION
The µXCT was applicable to visualize the coating
penetration into the wood and distinguish between the
woody material of Japanese beech veneer and the coating.
The high-resolution image in 2D and 3D made it possible
to quantify the coating penetration in three dimensionally.
The existed of the coating were marked by the white lineon the veneer and white dots in the veneer (Fig 2).

ACKNOWLEDGMENTS
The authors express their appreciation to JSPS
KAKENHI for funding (Fund No.: 20K06163).

REFERENCES

a.

b.

c.

Cassens DL and Feist WC (1986) Finishing Wood
Exteriors. Forest Service Press., United States.
Dilik T, Koc KH, Hazir E and Erdinler ES (2014) Surface
treatment, layer thickness and surface performance
relations of wood materials. Proceedings of the 57th
International Convention of Society of Wood Scienceand Technology. DOI: 10.13140/RG.2.1.3082.4488.
Ekaputri TS, Apsari NA and Tanaka T (2021)
Visualization of commercial coating penetration into
Fagus crenata blume wood using a non-destructive Xray microtomography. Coatings, 11: 927.
Hazir E and Koc KH (2019) Evaluation of wood surface
coating performance using water based, solvent based,
and powder coating. Maderas., 21: 467–480.
Hazir E and Koc KH (2021) Evaluation of wood-based
coating performance for ultraviolet roller andconventional air-atomization process. Maderas, 23: 1–
10.
Meijer M, Thurich K and Militz H (1998) Comparative
study on penetration characteristics of moderm woodcoatings. Wood Science and Technology, 32: 347–365.
Žigon J, Pavlič M, Petrič M and Dahle S (2021) Surface
properties of coated MDF pre-treated with atmosphericplasma and the in-fluence of artificial weathering.
Mater. Chem. Phys., 263: 0254–0584.

d.

Fig 2. X-ray image of Japanese beech applied by (a) whitecoating; (b) matte white coating; (c) brown coating; (d)pink coating. (red arrow): white dots; (orange line): coatingline.

The coating that used has the same active content (TiO2)
showed different penetration phenomenon andpenetration amounts (Fig 3). The deepest coating
penetration amount was found in white coating sample inaccordance with its X-ray image results in Fig 2, whereas
the other coating samples had shallower penetration. This
could be caused by the concentration used by the chemical
constituents of the coating which will affect the anchoringand penetration power of the coating. The different
concentration of the chemical content could be caused thedifferent viscosity level among the coatings. In addition,
the anatomy of the wood used has different porosity andabsorption even though was cut from the same veneer. In
accordance with Žigon et al. (2021) stated that theadhesion of coatings to wood depends mainly on the
diffusion and penetration of the liquid coating into theporous structure of the wood substrate.

16

P9

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Effects of Transglutaminase on Retrogradation of Wheat Flour
Dang Thi Kim Lien1 and Takahisa Nishizu2
1
2

The United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
Faculty of Applied Biological Sciences, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
resulting in a 25% (w/w) solid WF suspension. TG wasadded at concentrations of 0%, 0.04%, 0.05%, and 0.06%(w/w) relative to the protein content (coded as Control,
TG0.04, TG0.05, and TG0.06, respectively). The mixture
was stirred for 30 minutes at 160 rpm in a water bathmaintained at 50°C. After treatment, samples were cooledin ice for 5 mins and kept at 4°C to inhibit enzyme activity
for microstructure observations by Confocal Scanning
Laser Microscopy (CSLM). For DSC and swelling power,
samples were freeze-dried for 3 days and powdered. For
XRD, samples were steamed at 104°C for 30 minutes,
stored at 4°C for up to 7 days, then lyophilized and sieved
to 100-µm for testing.
Swelling power (SP): —SP was conducted using amodified method from Konik-Rose et al. (2001). 40 mg
WF and 1 ml water were mixed in a 1.5 ml centrifuge tube.
After mixing, it was heated at 92.5 °C for 30 min withregular inversion. After colling and centrifugation, thesupernatant was discarded, and residue weight determined
the SP: SP = Weight of residue / Dry weight of sample
Differential scanning calorimeter (DSC): — 8.00 mg
sample with triple its weight in distilled water were addedin an aluminum pan. Measurement was conducted by a
DSC (7000X, Hitachi, Japan) from 25-100°C at 2 °C/min.
An empty pan (40 mg) was used as the reference.
RD by X-ray diffractometer (XRD):— XRD was used
to measure RD as detailed by Taguchi et al. (2023). Wheat
gel powder was added with 0.8% Zinc Oxide and 70%
water before testing. The SmartLab XRD (Rigaku Co.,
Japan) was used at 45 kV and 200 mA, scanning at 2°/min
between 10–37°. RD was determined by a given equation.
RD = A17°/As
Where A17° and As are the areas of the peaks near 2θ ≈17° and the zinc-oxide peak (2θ ≈ 37°), respectively.

INTRODUCTION
Recently, the application of Transglutaminase (TG) in
the food industry has notably increased, especially inwheat-based products. TG modifies proteins in wheat
flour (WF), thereby improving both the product properties
and the flour processability. In wheat-based products,
retrogradation is a primary quality assessment criterion.
The enzymatic activity of TG might influence thisprocess. Consequently, it is essential to understand how
TG impacts WF during heating and storage.
Retrogradation involves the crystallization of amylose
and amylopectin in gelatinized starch as it cools, affecting
the texture and shelf life of starch-based foods. Besides
starch, protein in WF strongly affects the retrogradation
process. Studies indicate that protein and its nature could
promote or inhibit the retrogradation process (Chang etal., 2021).
TG is protein-glutamine γ-glutamyl-transferase (EC2.3.2.13) that catalyzes the cross-linking reaction throughan acyl transfer of glutamine and lysine. By modifying
protein structure and changing its interaction with othercomponents, TG can alter the physical and functional
properties of protein in WF (Bauer et al., 2003a, 2003b).
Specifically, TG reaction could modify protein molecularweight and its hydrophobicity, thus could possibly affect
the WF properties during gelatinization and storage.
However, scientific literature lacks substantial evidence
regarding the impact of TG on starch properties duringcooking and storage of WF.
This study aims to evaluate the effect of TG on WF by
examining flour microstructure changes, thermal
behaviors during gelatinization, and starch retrogradation
after storage. The goal is to understand the TG and WF
interaction to optimize its use in starchy foods.

RESULTS

MATERIALS AND METHODS

Microstructure by CLSM: —The results frommicrostructure observation indicated binding tendency ofstarch granule to protein network in TG treatment. The
protein network in TG sample was covered by starch
granules while control sample did not show thisphenomenon (Picture was presented in poster section).
Swelling power: — SP of TG sample was showed in Fig
1. Samples with TG treatment had lower SP value
compared to control sample. SP value also presented forwater adsorption of starch granule during heating. In thisexperiment, TG inhibited the water adsorption of wheat
starch, especially at the enzyme concentration of 0.05%.
Thermal properties (DSC): —The data revealed
alterations in gelatinization enthalpy (ΔH) without
affecting gelatinization temperatures. The adding of TG

Materials: —WF contained 13.7% protein (dry weight)(Nippn Co., Japan) was purchased from a local
supermarket. Activa@ TG-K containing 1% microbial
Transglutaminase was provided by Ajinomoto Co.
(Tokyo, Japan).
Purification of TG: Two grams of Activa@ TG-K was
dissolved in 10 ml of 0.1 M Tris/HCl buffer (pH 7.5). The
mixture was centrifuged at 15,000 rpm at 4°C for 30 mins.
The supernatant was collected and dialyzed at 4°C for 6
hrs in Tris/HCl buffer (pH 7.5), changing the buffer every
2 hours. The final solution was a 0.2% TG solution.
Sample preparation: — Each sample was prepared bymixing 15 g of WF with 45 g of water in a 200 ml beaker,

17did not lead to the change in the starch gelatinization
temperature, suggesting the starch structure remained
unaltered (data not shown). However, a significant
increase in ΔH was observed upon the addition of TG atconcentrations of 0.05% and 0.06% (showed in Fig 1)

facilitate this transition and break the hydrogen bonds inthe crystalline regions is termed the gelatinization
enthalpy. If the penetration of water is hindered, starch
granules cannot swell effectively. The limited swelling in
the TG sample is caused by the protein network formation
around the starch granules, which prevents full crystalline
disruption. Therefore, more energy is required to disrupt
this additional region. As a result, the ΔH in TG0.05 andTG0.06 increased accordingly.
The retrogradation reduction by TG treatment ispossibly due to the reinforcement of protein network,
which subsequently decreases SP and minimizes amylose
leaching during gelatinization. This delay in amylose
recrystallization consequently reduces the RD of wheat
starch (Fig 2). Furthermore, the data also suggests a
concentration-dependent effect of TG, with the optimal
concentration being approximately 0.05%.
In conclusion, the result obtained from this study
confirmed the application of TG has a significant impact
on reducing starch retrogradation in WF. These findings
underscore the significant potential and benefits ofincorporating TG into the production of wheat-based
products to improve overall quality.

Fig. 1: Swelling power and gelatinization enthalpy ofsamples. TG0.04, TG0.05, and TG0.01 are samples with 0.04,
0.05, and 0.06%bTG (w/w of protein) respectively. Different
letters indicate significant differences (p ≤ 0.05).

Retrogradation of stored wheat gel (XRD): — The RD
observed in samples treated with TG was lower comparedto the control after storage, as showed in Fig 2. The RD
increased along with the long period of storage in all
samples. The addition of TG at 0.05% had a significant
inhibitory effect on the retrogradation of WF.

REFERENCES
Basman A, Köksel H and Ng PK (2002) Effects ofincreasing levels of transglutaminase on the rheologicalproperties and bread quality characteristics of two
wheat flours. European Food Research andTechnology, 215, 419–424.
Bauer N, Koehler P, Wieser H and Schieberle P (2003a)
Studies on effects of microbial transglutaminase on
gluten proteins of wheat. I. Biochemical Analysis.
Cereal Chemistry, 80(6), 781–786.
Bauer N, Koehler P, Wieser H and Schieberle P (2003b)
Studies on effects of microbial transglutaminase on
gluten proteins of wheat. II. Rheological Properties.
Cereal Chemistry, 80(6), 787–790.
Chang Q, Zheng B, Zhang Y and Zeng H (2021) A
comprehensive review of the factors influencing theformation of retrograded starch. International Journalof Biological Macromolecules, 186, 163–173.
Konik-Rose CM, Moss R, Rahman S, Appels R, Stoddard
F and McMaster G (2001) Evaluation of the 40 mg
Swelling Test for Measuring Starch Functionality.
Starch - Stärke, 53(1), 14–20.
Ogilvie O, Roberts S, Sutton K, Larsen N, Gerrard J andDomigan L (2021) The use of microbial transglutaminase in a bread system: A study of gluten
protein structure, deamidation state and protein
digestion. Food Chemistry, 340, 127903.
Taguchi T, Onishi M, Katsuno N, Miwa N, Oomoto C,
Sato M, Sekita M, Yamaguchi H, Imaizumi T and
Nishizu T (2023) Evaluation of starch retrogradation by
X-ray diffraction using a water-addition method. LWT,
173, 114341.

Fig. 2: Retrogradation degree of samples after 7 days ofstorage at 4oC. Different letters indicate significant
differences (p ≤ 0.05). TG0.04, TG0.05, and TG0.01 aresamples with 0.04, 0.05, and 0.06% TG (w/w of protein)respectively.

DISCUSSION
Integrating all the findings, it can be inferred that TG
impact on the protein network restricts water absorption,
modifies thermal properties of wheat starch, andsubsequently influences starch retrogradation behavior
during storage.
In Fig 1, we observe a decrease in swelling and anincrease in ΔH with the addition of TG. As starch granules
absorb water and start to swell, they experience a phasetransition. The energy required to facilitate this transition
and break the hydrogen bonds in the crystalline areas is
termed the gelatinization enthalpy. The energy required to

18

P10

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Carotenoid Metabolism is Involved in the Granulation of Citrus ‘Harumi’
Fruit During Postharvest Storage
Zhiwei Deng1,2, Gang Ma2, Lancui Zhang2, Daiki Kurata2, Keisuke Nonaka3, Fumitaka Takishita3
and Masaya Kato2,*
1

The United Graduate School of Agricultural Science, Gifu University, Gifu, Japan
Department of Bioresource Sciences, Faculty of Agriculture, Shizuoka University, Shizuoka, Japan
3
Institute of Fruit Tree and Tea Science, National Agriculture and Food Research Organization (NARO), Okitsu,
Shizuoka, Japan
2

INTRODUCTION

in the juice sacs of S fruit after harvest, in which no
obvious granulation occurred during the storage period.
Previous studies indicate that the lignin content isinevitably increased in the granulated juice sacs, and theoveraccumulation of lignin is an essential step in the
granulation process. The lignin content in the juice sacs
was increased by 1.5 to 5-fold in the granulated fruit of‘Ponkan’ mandarin, ‘Sanhongmiyou’ pomelo, and navel
orange (Huang et al., 2023).

Juice sacs granulation is a serious physiologicaldisorder of citrus fruit that often occurs during postharvest
storage. This granulation causes the colorless of the juicesacs, resulting in the loss of marketable values. The lignin
content in the juice sacs is an important indicator forevaluating granulation. Moreover, carotenoids are themajor pigments accumulated in citrus fruit, and theircontents and compositions are crucial indicators forassessing citrus commercial and nutritional values of
citrus fruit (Ma et al., 2021). However, the molecularmechanisms underlying the carotenoid accumulation in
granulated fruit have not been clarified so far. In thepresent study, to elucidate the mechanism of granulation,
we investigated the granulation rating, lignin content, andcarotenoid metabolism during the granulation process indifferent sizes of ‘Harumi’ fruit.

MATERIALS AND METHODS‘Harumi’ fruit originated from a hybrid between‘Kiyomi’ tangor (Citrus unshiu × C. sinensis) and Ponkan(C. reticulata mandarin) were harvested from NARO
(Shizuoka). According to the fruit size, the fruit weredivided into two groups: S fruit (transverse diameter of 5.0- 6.5 cm) and L fruit (transverse diameter of 8.5 - 10.0cm). The fruit were stored at 10 ◦C for five months under
80 - 90 % RH. The degree of granulation was assessed
according to the method of Hofman (2010). Lignin was
extracted using the spectrometer method described by Li
et al. (2022). The carotenoids were extracted following
Kato’s methods and measured by HPLC (Kato et al.,2004). Total RNA was extracted by using the phenolchloroform method (Kato et al., 2004). The reaction
mixture of Real-Time PCR was made according to theprevious method (Ma et al., 2021).

Fig. 1: Changes in the granulation rating (A) and lignin
content (B) in the juice sacs of the S and L ‘Harumi’ fruit
during the storage period.

Carotenoid contents — Carotenoids are an importantquality index of citrus fruit. As the loss of orange color isa typical characteristic of granulated juice sacs, thechanges in carotenoid contents are an important indicatorof granulation, which could be used to predict the degreeof granulation in citrus fruit. El-Zeftawi (1978) found that
granulated juice sacs accumulated fewer carotenoids thanhealthy juice sacs in Valencia orange. The results in thisstudy showed that S fruit accumulated more carotenoids
than L fruit in the juice sacs. Moreover, the contents of βcryptoxanthin, β-carotene, all-trans-violaxanthin, and 9cis-violaxanthin in S fruit continued increasing after
harvest, and the orange color of the juice sacs deepened
gradually during the storage period. In L fruit, in contrast,
the contents of β-cryptoxanthin, all-trans-violaxanthin,
and 9-cis-violaxanthin decreased when the granulation
aggravated in the third week after harvest, which led thejuice sacs color to turn yellowish. These results indicatedthat the occurrence of granulation inhibited carotenoid
accumulation and coloration in the juice sacs of L fruit in‘Harumi’

RESULTS AND DISCUSSION
Granulation rating and lignin content — In this study,
we found that the granulation rating of L fruit increased
rapidly from the first month. Moreover, the lignin content
in L fruit increased rapidly from the first month after
harvest. In contrast, the lignin content slightly increased19

Fig. 2: Changes in the carotenoid content in the juice sacs of
S and L fruit during the storage period.

Expression of carotenoid metabolism genes — To
explore the molecular mechanism that causes the loss oforange color in the granulated juice sacs, the changes inthe expression of carotenoid metabolic genes were
investigated in this study. Genes expression showed thatthe modification of carotenoid accumulation was highly
regulated at the transcriptional level in the granulated
fruit. The expression of carotenoid biosynthetic genes
CitPSY, CitPDS, and CitZEP increased with a peak at thefirst month in S fruit after harvest, while it decreased
rapidly in L fruit during the storage period. Moreover, theexpression of CitLCYb2 and CitHYb, which are the key
genes responsible for the β-cryptoxanthin biosynthesis,
was higher in S fruit than in L fruit during the storage
period. The changes in the gene expression suggested thatcarotenoid biosynthesis was inhibited in the granulated
fruit of ‘Harumi’. In addition, ABA is a downstream of
metabolite of carotenoid, which is synthesized from thecleavage of 9-cis-violaxanthin and 9 ′ -cis-neoxanthin
catalyzed by NCEDs. In this study, the results showed thatthe gene expression levels of CitNCED2 and CitNCED3
were higher in L fruit than in S fruit. The high expressionof ABA biosynthetic genes and low content of ABA
precursor in L fruit indicated that ABA biosynthesis was
activated during the granulation process. The positive
relationship between ABA and granulation was also
reported in blood orange, in which ABA content increasedin the granulated fruit (Hou et al., 2022). In this study, we
found that the activation of ABA biosynthesis was
accompanied by the enhancement of lignin content in the
granulated fruit, which indicated that endogenous ABA
triggered the lignin biosynthesis during the granulation
process in L fruit of ‘Harumi’.

Fig. 3: Changes in the expression of carotenoid metabolism
genes in the juice sacs of S and L fruit during the storage
period.

REFERENCES
El-Zeftawi BM (1978) Factors affecting granulation andquality of late-picked Valencia oranges. J. Hortic. Sci.,
53 (4): 331–337.
Hou J, Yan D, Huang M, Zeng K and Yao S (2022)
Alteration of pectin metabolism in blood orange fruit(Citrus sinensis cv. Tarocco) in response to vesiclecollapse. Food Qual. Saf., 6: fyac050.
Huang C, Hou J, Huang M, Hu M, Deng L, Zeng K and
Yao S (2023) A comprehensive review of segment
drying (vesicle granulation and collapse) in citrus fruit:
Current state and future directions. Sci. Hortic., 309:
111683.
Kang C, Cao J, Wang Y and Sun C (2022) Advances ofsection drying in citrus fruit: The metabolic changes,
mechanisms and prevention methods. Food Chem.,
395: 133499.
Kato M, Ikoma Y, Matsumoto H, Sugiura M, Hyodo H
and Yano M (2004) Accumulation of carotenoids andexpression of carotenoid biosynthetic genes during
maturation in citrus fruit. Plant Physiol., 134 (2), 824–
837.
Li Q, Yao S, Deng L and Zeng K (2022) Changes inbiochemical properties and pectin nanostructures ofjuice sacs during the granulation process of pomelo
fruit (Citrus grandis). Food Chem., 376: 131876.
Ma G, Zhang L, Kudaka R et al. (2021) Exogenous
application of ABA and NAA alleviates the delayedcoloring caused by puffing inhibitor in citrus fruit.
Cells, 10 (2): 308.

20

P11

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Correlation Between Soil Bacterial Communities and Nutrient Status in
Tea Plants
Shuning Zhang1, Naoki Yanagisawa2, Mio Asahina2, Hiroto Yamashita2 and Takashi Ikka1,2,3
1

The United Graduate School of Agricultural, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan
Faculty of Agriculture, Shizuoka University, 836 Ohya, Shizuoka 422-8529, Japan
3
Research Institute of Green Science and Technology, Shizuoka University, 836 Ohya, Shizuoka 422-8529, Japan
2rRNA sequencing, and some physicochemical properties.
The nutrient contents of leaves and roots were followedby our laboratory-described methods including free aminoacids (FAAs), catechins and caffeine, and mineralelements (Yamashita et al. 2020; Yamashita et al. 2021).

INTRODUCTION
Soil bacteria were attributed to be key biologicalindicators for assessing soil conditions, which directly
participated in the soil nutrient cycle and rapidly
responded in response to changes in the soil environment(Fierer and Jackson. 2006; Hermans et al. 2017). They
also expanded the metabolic capacity of plants andparticipated in diverse processes including plantdevelopment, nutrient absorption, and stress responses(Bai et al. 2022). Soil pH has been shown to be thestrongest factor affecting the diversity and composition ofsoil bacterial communities (Rousk et al. 2010). In
addition, the rhizosphere was the important zone that
direct interaction between roots and active microbes. It
was also crucial to compare the differences between
rhizosphere soil and bulk microbes.
Tea is known to thrive in an acid-tolerant
environment, growing well in soil pH levels of 4-5. This
unique soil environment encompasses various properties,
nutrients, and microbes. However, it was insufficient tofocus solely on the isolated effect of soil conditions on tea
quality, as it overlooked the relationships between the
belowground and aboveground components of tea plants.
In this study, we emphasized the bacterial communities intea soils from various tea plantations. Subsequently, we
analyzed the nutrient status of tea plants, including their
growth, tea quality, and essential mineral elements.
Finally, we elucidated the interactions between soil
microorganisms and tea plants. This allowed us to assess
deeply the relationships between soil bacteria and tea
nutrient status.

RESULTS AND DISCUSSION
To explore the difference in five soils from different
pH ranges between core and noncore regions, we analyzed
physicochemical indexes after a period of pot cultivation(Table 1). The results revealed that soil pH ranged
between 3.31 and 6.37, with Carbon (C) to nitrogen (N)ratio (C/N) value ranging between 7.9 and 11.7, while
there were no significant differences between soils withplants and soils w/o plants. In soils with inappropriate pHlevels, tea leaves, both new and mature commonly
exhibited mineral deficiencies. The concentrations of Ca,
Mg, Fe and Al showed significant deficiency in newleaves. The tea growth was also inhibited in soil withhigher pH levels.
The sequencing of soil bacterial communities
showed that the species and diversity of bacterial
communities in tea soils were higher than in soil without
tea plants, indicating that tea plants could recruit a moreabundant bacterial population (Fig. 1a). The principal
coordinates analysis (PCoA) showed the points from thesame soil types clustered closely and the cluster fromdifferent soil types separated clearly (Fig. 1b). The
community analysis showed the most dominant bacterial
phyla in tea soils were Proteobacteria, Actinobacteria,
Chloroflexi, and Actinobacteria, while the most dominantfamilies were Acidobacteriaceae, Solirubrobacteraceae,
Acetobacteraceae, and Mycobacteraceae (Fig. 2). Basedon the p-value and FDR value, key bacteria were screened
and analyzed the relationships with tea quality andnutrient elements. The results showed that key families
including Micropepsaceae, Acidobacteriaceae andMicroscillaceae were found to actively participate inplant-microbe interactions (Fig.3).

MATERIALS AND METHODS
The pot culture was conducted in the greenhouse at
Shizuoka University (Shizuoka, Japan). One-year-old
rooted tea cuttings of “Yabukita” were transplanted into
Wagner pots. The five cultured soils were collected fromone conventional soil and four fields with typical tea
gardens in Shizuoka, and these soils were named soil A,
B, C, D, and E respectively, which was according to theorder of soil pH value (from the lowest to highest). In
addition, each soil was set into two groups which named
soil w/o plants (soil without tea plants in the pot) and soil
with plants. All samples included rhizosphere soils, bulk
soils, roots, stems, mature leaves, and new leaves. Soils
were used to analyze bacterial communities using 16S

CONCLUSIONSInappropriate soil pH results in growth inhibition anddeficiency of various nutrients from tea leaves and roots.
Exploring the intricate soil-microbe-plant interactions canhelp optimize nutrient management for high-quality tea.
Further research will continue to track these key microbial

21

communities to understand their specific contributions to
tea plants.

Fig. 3: Relationships between key bacteria and nutrient
status in tea plants.

REFERENCES
Fierer N and Jackson RB (2006) The diversity andbiogeography of soil bacterial communities.
PNAs,103(3): 626–631.
Hermans SM, Buckley HL, Case BS, Curran-Cournane F,
Taylor M and Lear G (2017) Bacteria as emerging
indicators of soil condition. Applied and environmental
microbiology, 83(1): e02826–16.
Bai B, Liu W, Qiu X, Zhang J, Zhang J and Bai Y (2022)
The root microbiome: Community assembly and its
contributions to plant fitness. Journal of Integrative
Plant Biology., 64(2): 230–243.
Rousk J, Bååth E, Brookes P.C, Lauber C.L, Lozupone C,
Caporaso J.G and Fierer N (2010) Soil bacterial andfungal communities across a pH gradient in an arable
soil. The ISME journal, 4(10): 1340–1351.
Yamashita H, Fukuda Y, Yonezawa S, Morita A and Ikka
T (2020) Tissue ionome response to rhizosphere pH andaluminum in tea plants (Camellia sinensis L.), a species
adapted to acidic soils. Plant-Environment Interactions,
1(2): 152–164.
Yamashita H, Kambe Y, Ohshio M, Kunihiro A, Tanaka
Y, Suzuki T and Ikka T (2021) Integrated metabolome
and transcriptome analyses reveal etiolation-induced
metabolic changes leading to high amino acid contents
in a light-sensitive Japanese albino tea cultivar.
Frontiers in Plant Science, 11, 611140

Fig. 1: The diversity of bacterial communities in soils fromdifferent pH conditions. (a) The α-Diversity (Chao1 index) ofsoil bacterial communities. (b) The β-Diversity (PCoA
analysis) of soil bacterial communities.

Fig. 2: The composition of bacterial communities in different
soil types

Table 1 Physicochemical properties in different soil types

A
B
C
D
E

Soil typewith plants

pH

EC (ms·cm-1)

Total P (mg/100g)

Total N (%)

Total C (%)

C/N

3.31±0.14f

0.23±0.04cd

1026.42±66.87d

3.70±0.11a

43.19±0.95a

11.70±0.58a
11.63±0.26a

w/o plants

3.48±0.06f

0.34±0.04a

1109.44±76.09cd

2.60±0.10a

41.97±0.76a

with plants

3.73±0.10e

0.15±0.02e

1260.46±35.21b

2.58±0.20b

28.97±0.79bc

11.26±0.71a

w/o plants

3.77±0.11de

0.16±0.02e

1274.92±43.37b

2.70±0.22b

29.73±0.34b

11.08±0.83abwith plants

3.97±0.03cd

0.06±0.00f

643.26±27.39e

0.61±0.07d

6.87±0.82f

11.40±1.18a

w/o plants

4.10±0.06c

0.07±0.00f

613.00±40.59e

0.52±0.06d

5.62±0.27f

10.78±0.94abwith plants

4.72±0.12b

0.18±0.03de1757.95±72.48a

3.45±0.23a

26.51±1.68d

7.87±0.23c

w/o plants

4.59±0.12b

0.33±0.06ab

1870.30±79.14a

3.42±0.27a

26.85±1.97cd

7.86±0.21c

with plants

6.37±0.05a

0.27±0.03bc

1118.18±70.25cd

1.45±0.10c

14.66±0.65e

10.19±1.04ab

w/o plants

6.49±0.14a

0.33±0.02ab

1173.16±63.02bc

1.44±0.12c

13.86±0.28e

9.69±0.62b

22

P12

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Evaluation of the Impact of Climate Change on River Temperature
Khadiza Akter Mousumi1, Takeo Onishi2, Ken Hiramatsu2 and Toshifumi Imaizumi3
1

The United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
Faculty of Applied Biological Sciences, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
3
Faculty of Agriculture, Shizuoka University, 286, Ohya, Suruga-ku, Shizuoka-shi, Shizuoka 422-8529, Japan2

Ø To determine the influence of changing stream
temperature on water quality, habitats of riverand on the lifestyle of people.
Ø To find the best way to mitigate climate change
and to adapt with the changing situation
Ø To develop long-term strategies andmanagement policies to match with climatechange phenomenon.

INTRODUCTION
In aquatic ecosystems, river temperature is a crucial
indicator of biodiversity and sustainability. River
discharge and water temperature directly affect water
quality (Ducharne 2008; Haag and Westrich 2002; Ozaki
et al. 2003), the growth rate and distribution of freshwaterorganisms (Eaton and Scheller 1996; Ebersole et al. 2001;
Mohseni et al. 2003). The dynamics and kinetics ofbiochemical reactions are influenced by river temperature,
which also affects the availability, behavior, and kind of
aquatic species in the ecosystem to which it belongs. The
availability and temperature of water are also
economically important, for example for thermoelectric
power production (Forster and Lilliestam 2011; Koch andVo¨gele 2009; Manoha et al. 2008), drinking waterproduction (Ramaker et al. 2005; Senhorst and Zwolsman2005), fisheries (Bartholow 1991; FAO 2008; Ficke et al.
2007) and recreation (EEA 2008b; Webb et al. 2008).
Climatic conditions have a strong influence on watertemperature. The increase in stream temperatures has
already been observed in many countries., including
Austria (Webb and Nobilis 1994), China (Chen et al.
2016), Germany (Arora et al. 2016), Poland (Kedra andWiejaczka 2018; Graf and Wrzesinski 2020), UK (Orr etal. 2015), Switzerland (Michel et al. 2020) or USA(Kaushal et al. 2010; Seekell and Pace 2011; Isaak et al.
2018). Changes to natural water temperature regimes canresult in myriad effects on aquatic organisms, water
quality, circulation patterns, recreation, industry, andutility operations. Consequently, livelihood of the
inhabitants depending on the river will also change. So,
tracking changes in water temperature is key to better
understanding the potential effects of global climatechange on freshwater ecosystems.
Predicting the impact of climate change on river systems
is imperative for effective management of aquatic
ecosystems. This study will demonstrate the potential
impact of climate on rivers temperature and how thismight affect the future ecological systems. The objectivesof the study are:
Ø To evaluate the processes involving climatic,hydrologic, and their interactions that determine
the stream temperature.
Ø To investigate the impact of air temperature andstreamflow changes on river temperature.
Ø To investigate the effect of changing temperatureon aquatic ecosystem.

MATERIALS AND METHODS
The study site for this research is Nagara river. The
Nagara River has its source in the city of Gujō, Gifu
Prefecture, and its mouth in the city of Kuwana, Mie
Prefecture, Japan. With a length of 166 km (103 mi), it
drains an area of 1,985 square kilometres (766 sq mi) in
the Chūbu region and empties into Ise Bay. To evaluation
climate change impacts on the study site the dataset of thefollowing website will be used.
http://www.miroc-gcm.jp/~pub/d4PDF/index_en.html
Present and future climate data will be generated by usinga regional climate mode through dynamic downscaling
approach. In this study, a watershed hydrology model,
Soil and Water Assessment Tool (SWAT) will be utilized
to simulate flow which is developed by the United States
Department of Agriculture (USDA) and one of the mostwidely used simulators for hydrologic modelling (Arnold
et al. 2012). It is a semi-distributed hydrological simulator
used to simulate several processes over an extended
period, primarily in rural catchments (Arnold et al. 1998).
The SWAT model has been extensively applied to various
problems such as land cover changes, agricultural
management, and climate changes. The several input data
and their sources are given in the following table:
Table 1: Input data for SWAT and their sources

Data
DEM
Land use
Soil type
Discharge

Sourcehttps://asterweb.jpl.nasa.gov/
https://www.eorc.jaxa.jp/ALOS/en/dataset/lulc_e.htm
https://www.mlit.go.jp/en/
http://www1.river.go.jp/

River temperature data will be observed in the research
project '水防災・農地・河川生態系・産業への複合的な気候変動影 響と適応策の研究', which is fundedby The Environment Research and Technology
Development Fund of the Ministry of Environment.

EXPECTED RESULTS

23

•
•
•

Haag I and Westrich B (2002) Processes governing riverwater quality identified by principal component
analysis. Hydrological processes, 16(16): 3113–3130.
Isaak DJ, Luce CH, Chandler GL, Horan DL and Wollrab
SP (2018) Principal components of thermal regimes inmountain river networks. Hydrology and Earth System
Sciences, 22(12): 6225–6240.
Kaushal SS, Likens GE, Jaworski NA, Pace ML, Sides
AM, Seekell D, Belt KT, Secor DH and Wingate RL(2010) Rising stream and river temperatures in the
United States. Frontiers in Ecology and theEnvironment, 8(9): 461–466.
Koch H and Vo¨gele S (2009) Dynamic modelling ofwater demand, water availability and adaptation
strategies for power plants to global change.
Ecological Economics, 68: 2031–2039.
Kędra M and Wiejaczka Ł (2018) Climatic and daminduced impacts on river water temperature:
Assessment and management implications. Science of
the Total Environment, 626: 1474–1483.
Manoha B, Hendrickx F, Dupeyrat A, Bertier C, and Parey
S (2008) Climate change impact on the activities ofElectricite de France. Houille Blanche-Revue Internationale De L Eau, 55–60.
Michel A, Brauchli T, Lehning M, Schaefli B and Huwald
H (2020) Stream temperature and discharge evolution
in Switzerland over the last 50 years: annual andseasonal behaviour. Hydrology and Earth System
Sciences, 24(1): 115–142.
Mohseni O, Stefan HG and Eaton JG (2003) Global
warming and potential changes in fish habitat in US
streams. Climatic change, 59(3): 389–409.
Orr HG, Simpson GL, des Clers S, Watts G, Hughes M,
Hannaford J, Dunbar MJ, Laizé CL, Wilby RL,
Battarbee RW and Evans R (2015) Detecting changing
river temperatures in England and Wales.
Hydrological Processes, 29(5): 752–766.
Ozaki N, Fukushima T, Harasawa H, Kojiri T,
Kawashima K and Ono M (2003) Statistical analyses
on the effects of air temperature fluctuations on riverwater qualities. Hydrological Processes, 17(14):2837–2853.
Ramaker TAB, Meuleman AFM, Bernhardi L and Cirkel
G (2005) Climate change and drinking waterproduction in The Netherlands: a flexible approach.
Water Science and Technology, 51: 37–44.
Seekell DA and Pace ML (2011) Climate change drives
warming in the Hudson River estuary, New York
(USA). Journal of Environmental Monitoring, 13(8):2321–2327.
Senhorst HAJ and Zwolsman JJG (2005) Climate change
and effects on water quality: a first impression. Water
Science and Technology, 51: 53–59.
Webb BW and Nobilis F (1994) Water temperature
behaviour in the river Danube during the twentiethcentury. Hydrobiologia, 291(2): 105–113.
Webb BW, Hannah DM, Moore RD, Brown LE andNobilis F (2008) Recent advances in stream and rivertemperature research. Hydrological Processes, 22:902–918.

The results of the study will provide tool(s) thatwill determine the climate change effects on rivertemperature.
The findings of the study will show the effects ofchanging river temperature on aquatic
ecosystems.
The results of this study can be very useful inwater resource planning, effective managementof aquatic ecosystems.

REFERENCES
Arnold JG, Srinivasan R, Muttiah RS and Williams JR(1998) Large area hydrologic modeling andassessment part I: model development. Journal of theAmerican Water Resources Association, 34 (1): 73–
89.
Arnold JG et al. (2012) SWAT: model use, calibration,and validation. American Society of Agricultural andBiological Engineers, 55 (4): 18.
Arora R, Tockner K and Venohr M (2016) Changing
River temperatures in northern Germany: trends anddrivers of change. Hydrological Processes, 30(17):3084–3096.
Bartholow JM (1991) A modeling assessment of thethermal regime for an urban sport fishery.
Environmental Management, 15: 833–845.
Chen D, Hu M, Guo Y and Dahlgren RA (2016) Changes
in river water temperature between 1980 and 2012 in
Yongan watershed, eastern China: Magnitude, drivers,and models. Journal of Hydrology, 533: 191–199.
Ducharne A (2008) Importance of stream temperature toclimate change impact on water quality. Hydrology
and Earth System Sciences, 12(3): 797–810.
EEA (2008b). Impacts of Europe’s Changing Climate –Indicator-based Assessment. EEA, Copenhagen.
Eaton JG and Scheller RM (1996) Effects of climate
warming on fish thermal habitat in streams of theUnited States. Limnology and oceanography, 41(5):1109–1115.
Ebersole JL, Liss WJ and Frissell CA (2001) Relationshipbetween stream temperature, thermal refugia andrainbow trout Oncorhynchus mykiss abundance inarid‐land streams in the northwestern United States.
Ecology of freshwater fish, 10(1): 1–10.
FAO (2008) Climate Change Implications for Fisheries
and Aquaculture. FAO, Rome, Italy, p. 41.
Ficke AD, Myrick CA and Hansen LJ (2007) Potential
impacts of global climate change on freshwater
fisheries. Reviews in Fish Biology and Fisheries, 17:
581–613.
Forster H and Lilliestam J (2011) Modelingthermoelectric power generation in view of climatechange. Regional Environmental Change, 4: 327–338
Graf R and Wrzesiński D (2020) Detecting patterns ofchanges in river water temperature in Poland. Water,
12(5).

24

P13

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Evaluating the Effect of Soil Clod Presence and Seeding Rate on Soybean
Yield and Seedling Establishment Using Bayesian Multilevel Mediation
Analysis
Luthfan Nur Habibi1, Tsutomu Matsui2 and Takashi S.T. Tanaka2, 3
1

The United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
Faculty of Applied Biological Sciences, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
3
Artificial Intelligence Advanced Research Center, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan2

yield prediction model with UAV-based imagery andweather data established using LASSO regression modelwith accuracy measurement of root mean square error of
51.96 kg ha–1 (Habibi et al. in prep). Yield within 3×3 m2
grids were quantified for further data analysis.

INTRODUCTION
The yield of soybean (Glycine max (L.) Merr.) isaffected by the interaction of multiple factors including
genotype, environmental effect, and also management
practices. This interaction created variation in the optimal
yield-to-seeding rates, where the environment that havehigh yield tend to need lower seeding rates compared to in
low-yielding environments (Carciochi et al. 2019;
Corassa et al. 2018). Environmental factors could hinder
the establishment of soybean seedling that can affect the
final plant population.
In Japan, soil clods easily appeared in the field surface
after heavy rain. Soil clods result from the interaction
between soil organic matter, soil moisture, and particle
size distribution. The existence of soil clods during the
emergence stage can hinder seedling establishment,
making it a limiting factor for plant population and final
yield. Ideally, soil properties should be incorporated ascovariates in crop yield response modeling, but
destructive measurement of soil properties are costly for
on-farm experimentation. Therefore, soil clods can beused as the proxy for soil properties data in crop yield
response model. Remote sensing can be utilized tosimultaneously assess soil clods and established seedlingnumbers using advanced segmentation algorithm based on
deep learning technique.
The direct impact of soil properties on the final yield,
apart from the indirect influence mediated by seedlingestablishment, can be evaluated by measuring soil clods.
Bayesian multilevel mediation analysis can be used toestimate the direct and indirect effect between variables
through mediator variable (Tofighi et al. 2013). This study
aimed to investigate the interaction between soil clod
presence, established seedling numbers, and final soybean
yield using multilevel mediation analysis. Moreover, an
on-farm experiment was conducted to assess the effects ofdifferent seeding rates on the seedling number and final
yield.

Measurement of seedling establishment and soil clod—
The number of established seedlings and soil clod
percentage in field were evaluated using RGB imagery
with YOLACT, a semantic segmentation algorithm.
Images of the fields were taken using a Sony A-6400
camera mounted on a DJI Matrice 300. The images were
captured specifically during the seedling emergence stage.
Model for measuring the number of establishedsoybean seedlings was trained using 200 images with anaverage of 15 seedling annotations per image. The numberof seedlings within 3×3 m² grids, corresponding to theyield observations, was counted. Meanwhile, the soil
clods was measured using model trained with 70 images
with an average of 350 soil clod annotations per image.
Predicted soil clod with diameter larger than 2 cm weretransformed into binary images. These binary images
were overlaid with a grid of 3×3 m² polygons to extract
the percentages of soil clod presence.
Multilevel mediation analysis—The 1-1-1 multilevel
mediation model was presented in the following
equations:Level-1 models!""#$%&' &)*+",!" = .#" + .$ !0%$ 1$0#! + "!"2%"$#!" = +#" + +$ !""#$%&' &)*+",! + +% !0%$ 1$0#! + 3!"

Level-2 models.#" = .# + )#"+#" = +# + 4#"

Error terms"!" ~ 6(0, σ%& )3!" ~ 6(0, σ'% )
σ%(!"
)#"
<4 = ~ 6(0, Σ); Σ = @#"σ(!",*!"

MATERIALS AND METHODS

σ(!",*!"σ%*!"A

where yieldij is the observed soybean yield (kg ha-1) in thecorresponding j seeding rate (the outcome), seedlingnumberij is the number of established seedlings in plot
area (the mediator), soil clodi is the percentage of soil clod
in plot area (the independent variable), a0j and b0j denotethe intercepts of the mediator and outcome models foreach seeding rate j, a1j represent the effect of soil clod

Experimental design and data collection—On-farmexperiments were carried out in two soybean fields
located in Kaizu City, Gifu. The experimental design was
randomized strip trial with total of eight different seeding
rates. The experiment then evaluated using data-driven

25

presence on established seedling, b1j signifies the effect ofsoil clod presence on soybean yield, and b2j indicates theeffect of established seedling number on yield while
holding soil clod constant. The 1-1-1 multilevel mediation
model scheme was presented in Fig. 1.

Notable differences were observed in the establishedseedling numbers between the two fields. The use oflarger seeds in Field 2 potentially contributed to better
average seedling emergence. Planting high-vigor seeds
and adjusting seed spacing and at optimum seeding rates
during sowing can be implemented to ensure sufficient
seedling numbers (Hyatt et al. 2007). Nonetheless, theyield performance of Field 1 exceeded that of Field 2
significantly at lower seeding rates. Consequently, it is
crucial to optimize the seeding rate for each fieldaccording to agronomic knowledge of the yield response
to environmental factors, rather than solely concentratingon the number of established seedlings.
In this study, soil clods measured using UAV imagery
proved to be suitable proxies for soil property covariates
when evaluating yield in on-farm experimentation studies.
The higher presence of soil clod in field surface could
reflect a lower water holding capacity or drainage
capability, which directly affected the yield.
Implementing water table management, including
drainage and sub-irrigation systems, could offer a solution
to mitigate soybean yield performance instability due toflooding or drought (Matsuo et al. 2018). Other factors
during the latter growing stages that were not accounted
in current study could also impact the yield. Additional
research is required to consider the environmental effects
on the soybean yield component and final yield,
particularly during the pod initiation and seed-fillingstages.

Fig. 1: The 1-1-1 multilevel mediation model scheme andresults.

The average direct effect (ADE) of soil clod presenceon yield was denoted by the b2 value, whereas the averagecausal mediated effect (ACME) or the indirect effect wascalculated by multiplying the a1 and b1 values. The
mediator effect was represented by the b1 value. The total
effect was computed by summing up the direct andindirect effects. The proportion mediated was determinedby dividing the ACME value by the total effect. The
mediation analysis was carried out using the mediation
feature provided by ‘bayestestR’ package in R. Bayesianestimation was performed using Markov chain Monte
Carlo (MCMC) chains with 4000 saved iterations for theposterior inference. The Bayesian analysis was performed
through the stan_mvmer feature available in ‘rstanarm’
package in R.

REFERENCES
Carciochi WD et al. (2019) Soybean seed yield responseto plant density by yield environment in North America.
Agron. J., 111: 1923–1932.
https://doi.org/10.2134/agronj2018.10.0635
Corassa GM, Amado TJC, Strieder ML, Schwalbert R,
Pires JLF, Carter PR and Ciampitti IA (2018) Optimum
soybean seeding rates by yield environment in southern
Brazil. Agron. J., 110, 2430–2438.
https://doi.org/10.2134/agronj2018.04.0239
Gong H, Zeng Z and Qi L (2019) A discrete element
model of seed-soil dynamics in soybean emergence.
Plant Soil, 437, 439–454.
https://doi.org/10.1007/s11104-019-04007-y
Hyatt J, Wendroth O, Egli DB and TeKrony DM (2007)
Soil compaction and soybean seedling emergence.
Crop Sci., 47, 2495–2503.
https://doi.org/10.2135/cropsci2007.03.0171
Matsuo N, Yamada T, Takada Y, Fukami K and Hajika M(2018) Effect of plant density on growth and yield of
new soybean genotypes grown under early planting
condition in southwestern Japan. Plant Prod. Sci., 21,
16–25.
https://doi.org/10.1080/1343943X.2018.1432981
Tofighi D, West SG and Mackinnon DP (2013) Multilevel
mediation analysis: The effects of omitted variables in
the 1-1-1 model. Br. J. Math. Stat. Psychol., 66, 290–
307.
https://doi.org/10.1111/j.2044-8317.2012.02051.x

RESULTS AND DISCUSSION
Causal mediation analysis results—Soil clod presence
had indirect effect to soybean yield through the seedlingestablishment by an average of -8.61 kg ha–1 per one
percent increase under typical conditions (Fig. 1). The
direct effect of soil clod appearance in the field had less
impact than the mediated effect through seedling number.
The total effect was estimated at -14.93 kg ha–1.
Soil clods had a negative impact on yield performancethrough both direct and indirect relationships.
Specifically, soil clods significantly influenced yield byaffecting seedling numbers during the emergence stage.
Soil clods presence could hinder seedling emergence as
growing seedlings must overcome the soil impedance
caused by the clods and soil compaction, which could
result in seedling mortality (Gong et al. 2019).
Effect of seeding rates on seedling number and yield—
The average established seedling number in the fields
varied from around 6 to 9 plants m-2 depending on theseeding rate (data not shown). The field conditions had asignificant impact on the average number of seedlings.
The typical yield performance in both fields plateaued inapproximately 110 kg ha–1 in the most optimized seeding
rate setup in both fields.

26

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Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Estimation of Metabolizable Energy Value of Okara Meal in Broiler
Chicken Using Chick Bioassay, Approximate Nutritive Value, and in Vitro
Digestibility TechniqueBagus Himawan Wicaksono1, Norimatsu Marina2 and Yamamoto Akemi2
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, JapanINTRODUCTION

samples used in this experiment, four samples from tofu
productions and two samples from soymilk processing.
Proximate Analysis—The levels of moisture content(MC), CP, crude ash (CA), and fat (Ether Extract or EE)
were measured using AOAC (2006) methods. While thenitrogen-free extract (NFE) value acquired fromsubtraction of all proximate analysis parameter.
In Vivo (Chick Bioassay)—A total of 105 Chunky strain
male broiler chicken 25-days-old were used. Okara’s ME
was evaluated by using the method of Kong & Adeola(2014). The amount of given feed was 89 g/chick/day. The
last three-day of experiment, fecal or excreta werecollected, dried in oven, and measured the gross energy(GE) using bomb calorimeter (Shimadzu, CA-4PJ).
In Vitro (Laboratory Assay)—The energy digestibility
was determined using modified Furuya et al. (1979)
methods. About 0.5 gram of samples were mixed with 10
ml of 20 mg pepsin/ml 0.0075M HCl solution (pH 2.0) in
100 ml flask. Each flask then gently shaked for 4h at 39ºC.
Afterwards, about 10 ml of 50 mg/ml pancreatin (pH 6.8)
was used, shaked in the same conditions. Aftercentrifugation, sample was filtered and dried in oven
before energy analysis. The digestibility values were
examined using equation: [1 – (Residue/Sample) x 100].
Statistical analysis—Okara’s nutritive value were
examined using Pearson correlation. ME estimation were
outlined using step-wise regression, while in vivo and invitro digestibility correlation using linear regression.

The investigation of cost-effective resources that offer
similar nutritional value to commercial diet is greatinterest (Sugiharto 2022). Okara, also known as soybean
by-product residue, is derived from the ruptured cotyledon
cells of soybeans. Globally produced 14 million tonnes,
yet half of the byproduct is discarded (Privatti &Rodrigues 2021). Dried okara has gained attention as apotential feed ingredient for broiler chickens. The crude
protein (CP) of dried okara ranges from 22% to 40%,
depending on the soybean variety and processing methods
such as milling and heating (Sugiura et al. 2009).
Although the CP is lower than soybean meal (SBM),
okara has variable and relatively high levels of crude fiber(CF) between 12-20%, potentially interfere the feed
digestion process in poultry (Diaz-Vargaz et al. 2016)
One of the key factors that determine the suitability ofa feed ingredient for broiler chickens is metabolizableenergy (ME) content (Edwards & Hemsworth, 2021).
Studies have shown that dried okara has ME values
ranging from 1572 to 2700 kcal per kilogram of dry matter(Diaz-Vargaz et al. 2016). Okara from soymilk residue
contains higher nutritive value compared to the tofu
residue (Toda et al. 2007), since the filtration process
occurred once to obtain soymilk residue. Subsequently,
higher filtration frequency affects lowering non-starchpolysaccharides in CF (Olukosi et al. 2015), increasing
nutrient digestibility. As results, ME values of dried okara
are vary by these consequences. Due to this situation,
inaccurate feed formulation might occur and lower the
production efficiency of poultry.
The current ingredient databases provide insufficientnutritive value of okara, particularly in terms of its energy
value as a poultry feed. It is indispensable to determine theprecise nutritive and ME value, ensuring broilers obtainedbalanced rations both nutrient requirement as well as
energy necessity. To promote the acceptance of okara as apoultry feedstuff, understanding of chemical components
and okara’s utilization in broiler meal are crucial to beundertaken. Thus, this research aims to determine ME anddigestibility of six okara samples using chick bioassay,
approximate nutritive value, and in vitro digestibility
technique.

RESULTS AND DISCUSSION
The results of this research shown that samples A, B, C,
E, and F have high CP (>22%) which generally requiredin chicken diets in the first 4-weeks. However, only
samples B and E that recommended for poultry feedstuff,
specifically in terms of CF to be 8% or lower (Table 1).
Sample E has features in moderate CA, highest amount ofCP, low CF, lowest EE, and high NFE compared to all
samples. Whereas, from tofu sources, sample B can beconsidered as secondary alternative feedstuff, referring
the adequate CP level & low CF value.
Table 1: Nutrient compositions of okara as fed-basis
Samples
Tofu
A
B
C
D
Soymilk
E
F

MATERIALS & METHODS
Okara Sampling—Dried okara samples were takenfrom various tofu and soymilk factory. There are six

27

MC

CA

CP

CF

EE

NFE

4.6
4.4
8.8
7.6

5.3
5.5
4.6
6.2

22.6
25.2
24.9
16.1

11.3
8.2
17.4
20.3

14.7
17.7
20.0
13.9

46.3
43.4
33.1
43.5

6.0
6.7

6.4
8.1

37.9
25.1

8.8
19.1

10.7
12.7

36.2
34.9

nutritive value combined with step-wise regression. In
case of other laying-hen feedstuff, study from Furuya etal. (1979) showed good relationship between in vivo andin vitro digestibility. While okara, this feedstuff could be
unique, presuming the water absorption ability. Hence,
estimation using in vitro technique require improvement
for predicting okara’s digestibility.

In Vivo Digestibility (%)

In vivo assay showed digestibility of various okara thatwere utilized as feedstuff, averagely accounted 59.5%
digestibility. Four evaluated tofu okara samples showedsimilarity with Diaz-Vargaz et al. (2016), accounted for
2.7 Mcal/kg DM tofu okara. While the okara fromsoybean processing resulted higher ME. This is
supporting Toda et al. (2007) study, stating that soymilk
okara have higher nutritive value which resulting higher
ME respectively. As a result, both GE and ME from two
soymilk okara samples are higher compared to tofu okara.
It can also be seen that higher digestibility value followedwith higher CP combined against lower CF, specificallyin soymilk okara (Table 1 and Table 2).
Table 2: In vivo energy digestibility of okara
Samples
Tofu
A
B
C
D
Soymilk
E
F
AverageSD

ME(Mcal/kg DM)

GE(Mcal/kg DM)

Digestibility
(%)

2.79
2.78
2.78
2.95

4.99
4.96
5.22
4.72

56.0
56.1
53.3
62.6

3.30
3.30
2.98
0.25

5.10
5.12
5.02
0.17

64.8
64.5
59.5
5.0

2

Equation (Kcal/kg)-69.60 X + 3960.45-66.54 X1 – 27.32 X2+ 5104.57

R2
0.72

p-value
0.032*

0.96

0.008*

60
50
40
50

60
70
80
In Vitro Digestibility (%)

90

REFERENCES
Diaz-Vargaz M, Murakami AE, Ospina-Rojas IC, Zanetti
LH, Puzotti MM & Guerra AFQG (2016) Use of okara(aqueous extract reside) in the diet of starter broiler.
Canadian Journal of Animal Science, 96: 416–424.
Edwards LE & Hemsworth PH (2021) The impact ofmanagement, husbandry and stockperson decisions on
the welfare of laying hens in Australia. Animal
Production Science, 61: 944–967.
Furuya S, Sakamoto K & Takahashi S (1979) A new invitro method for the estimation of digestibility using theintestinal fluid of the pig. Br. J. Nutr., 41: 511–520.
Olukosi OA, Beeson LA, Engliyst K & Romero LF (2015)
Effects of exogenous protease without or withcarbohydrases on nutrient digestibility anddisappearance of non-starch polysaccharides in Broiler
Chickens. Poultry Science, 00: 1–8.
Privatti RT & Rodrigues CEDC (2021) An overview of
the composition, applications and recovery techniquesof the components of okara aimed at the biovalorizationof this soybean processing residue. Food Reviews
International, 29: 1–24.
Kong C & Adeola O (2014) Evaluation of amino acid andenergy utilization in feedstuff for swine and poultry
diets. Asian Australas. J. Anim. Sci., 27: 917–925.
Sugiharto S (2022) Feeding fermented agricultural
byproducts as a potential approach to reduce carbon
footprint from broiler production – a brief overview.
Reviews in Agricultural Science, 10: 90–100.
Sugiura K, Yamatani S, Watahara M & Onodera T (2009)
Ecofeed: animal feed produced from recycled foodwaste. Veterinaria Italiana, 45: 397–404.
Toda K, Chiba K & Ono T (2007) Effects of components
extracted from okara on the physicochemical properties
of soymilk and tofu texture. Journal of Food Science,
72: 108–113.

Table 3: Estimated equation of apparent ME
Predictors
EE (X)EE (X1)
NFE (X2)

70

Fig. 1: Relationship between in vivo and in vitro digestibilities
energy (□) of broiler chicken

Through the examined okara’s nutritive value data,
Pearson correlation showed that CA and EE were strongly
related to apparent ME value. estimation of apparent ME
equation using stepwise regression. Stepwise regression isa statistical method used in the context of multiple linear
regression analysis, which aims to select the most relevant
independent variables (predictors) for building a
predictive model. Its primary goal is to choose a subset ofpredictors that best explain the variation in the dependent
variable while minimizing overfitting.
Model
1

80

In table 3, the equation are outlined into two models.
Model one has moderate R2 value, by only using EE data.
Prediction of apparent ME by only using EE data resulting
lower accuracy. Hence, the second model from stepwise
regression are using EE and NFE data. Though the R2
value is comprisingly high, acquiring NFE data was timeconsuming.
Fig. 1 shows the relationship between in vivo and invitro digestibility energy. Based on the linear regression,accuracy of in vivo and in vitro relationship equation isconsidered very low. Nutritional compositition offeedstuff supposed to be similar in order to obtain goodequation (Furuya et al. 1979). As a result, the relationshipbetween in vivo and in vitro digestiblities was different
from one to another okara samples.
Based on this experiment, the preferred technique inestimating ME of okara feedstuff is using approximate

28

P15

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Genome-Wide Association Analysis of the Changes in Malate Release
Under Aluminum Stress in Arabidopsis thaliana
Congxiao Wang1, Masafumi Shimizu1, Hiroyuki Koyama1 and Yuriko Kobayashi1
1Faculty of Applied Biological Sciences, Gifu University, 1-1 Yanagido Gifu 501–1193, Japan
complex interplay between genes and traits, providing
essential information for disease prevention, diagnosis,
and treatment. Furthermore, it offers valuable tools forresearch in fields such as agriculture, ecology, andbeyond.

INTRODUCTION
Soil aluminum toxicity, characterized by an excessive
presence of soluble aluminum ions in the soil, typicallyoccurs in acidic soils (Shetty,2021). This issue is prevalent
on a global scale and poses significant challenges toagriculture and ecosystems. Acidic soils generally exhibit
low pH values, primarily due to factors such asatmospheric acid rain, soil erosion, and prolonged use ofacidic fertilizers. In acidic soils, aluminum exists in theform of soluble aluminum ions. These aluminum ionsseverely impact the growth of plant roots. Aluminum
toxicity is primarily characterized by damage to root cell
walls, inhibition of root growth, and a resulting decreasein a plant's ability to absorb and utilize water and nutrients(Panda, 2009). Soil aluminum toxicity also hasrepercussions on natural ecosystems (Alengebawy, 2021).
It can lead to soil acidification, disrupt the activities of soil
microorganisms, and disturb the balance of the soil
ecosystem. Addressing the issue of soil aluminum toxicity
is crucial for enhancing agricultural sustainability.

MATERIALS AND METHODS
Arabidopsis Accessions
Plant Materials Seeds of natural A. thaliana accessions
were obtained from the Arabidopsis Biological Resource
Center (Columbus, OH, USA), The Nottingham
Arabidopsis Stock Center (Nottingham, UK), and the
RIKEN BioResource Center (Tsukuba, Japan). Progeny
lines were obtained by controlled self-pollination using
the single-seed descent method.

Malate Release and Measurement
Seedlings were grown for 4 d aseptically in the mannerof Hoekenga et al. (2003), substituting 100% MGRL
solution with 1% (w/v) suc. at pH 5.0. Other conditions
were as described above. Seeds were sown on 10-mm
squares of plastic mesh (25 plants), after 4 d, the seedlings
were transferred to wells in a 6-well microtiter platecontaining 2 mL of root exudate collection medium alongwith the aluminum stress environment (10μM Al, 2%
MGRL nutrients, and 1% [w/v] suc.), and gently shaken
on a rotary shaker (60 rpm) at 25°C in darkness for 24hours. Malate concentrations in exudation media were
determined by a NAD/NADH cycling-coupled enzymatic
method as Takita et al., (1999) or capillary electrophoresis
as described (Hoekenga et al., 2003). All experiments
were carried out at least three times and means and SE
values are reported.

Plants employ a variety of physiological, biochemical,
and molecular strategies to resist aluminum toxicity(Inostroza-Blancheteau ,2012). Among these strategies,
the secretion of organic acids plays a pivotal role, withmalate being a key player in this process. The mechanismsof organic acid secretion primarily involve the active
efflux mechanism, transporter-mediated organic acidefflux, etc. Through these pathways, malate, secreted byplants, can chelate with aluminum ions in the soil, forming
insoluble aluminum-organic acid salts (Rout, 2001). This,in turn, lowers the concentration of free aluminum ions inthe soil solution, thereby alleviating the impact ofaluminum toxicity on plants.
Genome-Wide Association Analysis (GWAS) is a
crucial genetic research method used to investigate therelationships between genes and specific traits or diseases(Visscher,2012). This method aims to discover genetic
variations that influence particular traits and how thesegenetic variations impact an individual's characteristics,
susceptibility to diseases, and more. GWAS explores therelationships between hundreds of thousands to millions
of genetic markers, such as Single Nucleotide
Polymorphisms (SNPs), and an individual's phenotypic
expressions. This approach helps us comprehend the
intricate connections between genes and traits, as well as
how different genotypes affect an individual's response to
specific characteristics. Genome-Wide Association
Analysis serves as a pivotal tool in modern genetic
research, which aids in gaining profound insights into the

Genome-wide Association study
The GWAS calculations were completed using the
GWAPP(http://gwas.gmi.oeaw.ac.at), a web application
for GWAS. The genome-wide SNPs used in this study
wereobtainedfromapublicdatabase(https://cynin.gmi.oeaw.ac.at/,
http://1001genomes.org/index.html). In total, 171,474
SNPs were used for the GWAS after SNPs with missing
data or a minor allele frequency below 10% were
removed. The average r 2 values were plotted against the
number of top-ranked SNPs in the GWAS. A local
association study was similarly conducted for 80 A.
thaliana accessions using the TASSEL program withmore polymorphisms in the peak region of chromosome 429(Figure 1A and Supplemental Table 3) identified throughsequencing or mined from a public database (http://
1001genomes.org/index.html).

65-log10(p)

4
3
2
1
0

12648000RESULTS AND DISCUSSIONAl+

Due to the number of accessions, the precision of this
GWAS is limited. If we continue to measure malate
release in different accessions, the results will become
more reliable. Based on the results of GWAS, further
analysis can be conducted to understand the underlying
mechanisms, and validation can be performed by using
knockout seeds for the specific gene.

REFERENCES
Shetty R, Vidya CSN, Prakash NB et al. (2021)
Aluminum toxicity in plants and its possible mitigationin acid soils by biochar: A review[J]. Science of the
Total Environment, 765: 142744.
Panda S K, Baluška F and Matsumoto H. (2009)
Aluminum stress signaling in plants. Plant signaling &behavior, 4(7): 592–597.
Alengebawy A, Abdelkhalek ST, Qureshi SR et al. (2021)
Heavy metals and pesticides toxicity in agricultural soil
and plants: Ecological risks and human health
implications. Toxics, 9(3): 42.
Inostroza-Blancheteau C, Rengel Z, Alberdi M et al.
(2021) Molecular and physiological strategies toincrease aluminum resistance in plants. Molecular
Biology Reports, 39: 2069-2079.
Rout G, Samantaray S and Das P. Aluminium toxicity inplants: a review. Agronomie, 2001, 21(1): 3-21.
Visscher PM, Brown MA, McCarthy MI et al. (2012) Fiveyears of GWAS discovery. The American Journal of
Human Genetics, 90(1): 7–24.
Hoekenga OA, Vision TJ, Shaff JE et al. (2003)
Identification and characterization of aluminum
tolerance loci in Arabidopsis (Landsberg erecta x
Columbia) by quan- titative trait locus mapping: aphysiologically simple but genetically complex trait.
Plant Physiol., 132: 936–948.
Takita E, Koyama H and Hara T (1999) Organic acidmetabolism in aluminum- phosphate utilizing cells ofcarrot (Daucus carota L.). Plant Cell Physiol., 40: 489–
495.

Al-

7.0
6.0

malate releasement(nmol/plant)

12656000

Fig. 3: Manhattan plots from the genome-wide association
study (GWAS) of Aluminum tolerance in A.thaliana. Figureright side shows the position of a candidate gene.

The malate releasement over a 24-hour period wasmeasured in 42 accessions under 10 µM aluminum stress.
It was observed that there is a significant variation in
malic acid secretion among the different accessions,which is favorable for conducting Genome-Wide
Association Studies (GWAS). This is further supported by
the distinct root lengths of different accessions underaluminum stress, as illustrated in Fig. 2. In general,variations in root length under aluminum stress areindicative of different levels of aluminum tolerance.
Longer root lengths suggest less impact from aluminumstress and higher malic acid secretion. Based on theseresults, it is demonstrated that the selected accessions inthis experiment are suitable for further GWAS analysis.
8.0

12652000
Position(bp)

5.0
4.0
3.0
2.0
1.0

K

ro
-0
Ct
-1
Rd
-0
K
oz
S
S h ij -1
ig
uK 1
Co il- 0
nd
ra
Fr
-4
M Co
or - 3an
Vi 1
e0
Tu EieV 2
13
Le S tch 0
Ed o-1
en
An 1
Dr -2
a2
C2
Bl 4
h2

0.0

Fig. 1: Malate releasement under 24-hour aluminum stressin 42 Accessions

Fig. 2: Different root length under 24-hour aluminum stress

Several candidate genes can be identified through
Manhattan plots, with a prominent peak on the third
chromosome. As more accessions are included in themeasurements, this result becomes increasingly
pronounced. After identifying the position of this gene, it
can be subjected to further validation and analysis.

30

P16

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Alleviative Effect of Gypsum to Rhizotoxic Stressors on Acid Soil
Koffi Pacome Kouame1, Raj Kishan Agrahari1, Yasufumi Kobayashi2, Toshihiro Watanabe3, Akiko
Maruyama4, Koyama Hiroyuki1 and Yuriko Kobayashi1
1

The United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
Japan International Research Center for Agricultural Science, 1-1 Owashi, Tsukuba-shi, Ibaraki 305-8686, Japan
3
Faculty of Agriculture, Hokkaido University, Kita 8, Nishi 5, Kita-ku, Sapporo, Hokkaido 060-0808, Japan
4
Faculty of Agriculture, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan2(CS22622),Ts-5(CS1558), SULTR2:1-KO, SULTR3:1KO, SULTR3:5-KO from (Kyushu university).
Soil culture: Soybean and Wheat were used for the soil
experiment. First, the soil was supplemented with basal
nutrients. Then, we proceeded to the pH measurement andAl exchangeable extraction (Kissel et al., 1971).
Hydroponic culture and root measurement: The
seedlings of Arabidopsis were grown hydroponically in
2% strength modified MGRL medium into 10% without
Pi as described by Kobayashi et al. (2007). pH wasadjusted to 5.0 with AlCl3.6H2O (4μM) under a 12-hlight/ 12-h-dark photoperiod (120μmol quanta m-2s-1).
Malate measurement: The same accessions used forthe hydroponic culture were grown in a liquid medium
according to Hoekenga et al. (2003). The basal nutrient
solution is composed of 100% MGRL (high strength) with
1% sucrose at pH=5.6. 25 Seeds were sown on each 10mm
square plastic mesh in Magenta GA-7 vessels containing
150ml of high-strength media.
RNA extraction and quantitative RT-qPCR: About 120
seeds were sown in basal MGRL solution (2%) plus Pi(Phosphate). After 10d growth, the seedlings were
stressed in basal medium (2%) as those used in malate
release without sucrose. Total RNA was isolated from theroots according to Suzuki et al. (2003) using SepasolRNA I Super G (Nacalai Tesque) following the methods
indicated by the manufacturer.

INTRODUCTION
This study aimed to elucidate the mechanisms of thealleviative effect of gypsum on Al toxicity using
Arabidopsis accessions, with a focus on sulfur (S). In acidsoils (pH<5.5), Al3+ toxicity and phosphates (Pi)
deficiency drastically reduce crop yield worldwide(Kochian et al.,2015). Gypsum improves subsoil acidity
by chelating with Al3+ to form an aluminum sulfate(AlSO4+) which is less toxic and increases S and Pi uptake.
In fact, when Arabidopsis and crops grow in acid soil, thetoxicity could be alleviated by CaSO4 (pH 4.7) as well as
CaCO3 (pH 5.5). In the case of Al toxicity, Plants have
evolved bi-directional mechanisms of Al tolerance like
Al-detoxification (Internal tolerance) and exclusion(external tolerance) to cope with the constraints of Al
toxicity in acid soils (Kochian et al.,2015).
Organic acids have been identified in several crops
like soybean (Glycine max) (Siguira et al.,2021) for citrateand Arabidopsis (Kobayashi et al.,2007) and Wheat(Sasaki et al.,2004) for malate. A new study revealed thatorganic acid secretion enhances P acquisition by S
application (Siguira et al.,2021). Sulfur(S) has been
proven to play an important role in regulating plant
responses to various biotic and abiotic stress (Sheng etal.,2016). Sulfate deficiency causes growth retardation,
decreases Glutathione (GSH), and Glucosinolate (GSL),
and reduces crop yields and quality (Sheng et al.,2016). In
Arabidopsis, SULTR3:5 was colocalized with SULTR2:1
low-affinity sulfate transporter in the xylem parenchyma
and pericycle cell root (Kataoka et al., 2004b). Sulfur
application mitigated Mn toxicity by sequestering Mn into
the vacuole (Sheng et al.,2016).

Root fresh weight (g)RESULTS and DISCUSSION

0.04
0.02

**

**

*

0
017 0
00- 0
2 4 17 0024
0

MATERIALS AND METHODS

0.06

Hydroponic culture materials
Arabidopsis (Arabidopsis thaliana) accession wild
type Columbia Col-0 was obtained from the RIKEN
BioResource Center and Al sensitive accessions from
Arabidopsis Biological Resource Center Wei-0

Fig. 1: Fresh weight plotted against different treatments 0-0
indicated soil not treated, 170-0 soil treated with CaCO3, 0170 soil treated with CaSO4, and 240-240 soil with both
treatments.

31Col-0TS-5(5)100

treatment. AtALMT1 and SULTR35 could be involved in Al
regulation.

Wei-0

RRL Al+/Al- (%)**

80

Gypsum triggered AtALMT1 which encodes
AtALMT1 proteins to bind with Al. On the other hand,
SULTR35 could be involved in internal and external
detoxification during the sulfate transfer from root toshoot.

*

60
40

REFERENCES

20
0
S(0)

Hoekenga OA, Vision TJ, Shaff JE, Monforte AJ, Lee G
P, Howell SH and Kochian LV (2003) Identificationand characterization of aluminum tolerance loci in
Arabidopsis (Landsberg erecta×Columbia) byquantitative trait locus mapping. A physiologicallysimple but genetically complex trait. Plant
Physiology, 132(2): 936–948.
Kataoka T, Hayashi N, Yamaya T and Takahashi H(2004b) Root-to-shoot transport of sulfate inArabidopsis. Evidence for the role of SULTR3; 5 as acomponent of low-affinity sulfate transport system in
the root vasculature. Plant Physiology, 136(4): 4198–
4204.
Kissel DE, Gentzsch EP and Tomas GW (1971)
Hydrolysis of nonexchangeable acidity in soils duringsalt extractions of exchangeable acidity. Soil Sci.,
111:293–297.
Kobayashi Y, Hoekenga OA, Itoh H, Nakashima M, Saito
S, Shaff JE et al. (2007). Characterization of
AtALMT1 expression in aluminum-inducible malate
release and its role for rhizotoxic stress tolerance inArabidopsis. Plant Physiology, 145(3): 843–852.
Kochian LV, Piñeros MA, Liu J and Magalhaes JV (2015)
Plant adaptation to acid soils: the molecular basis forcrop aluminum resistance. Annual Review of Plant
Biology, 66: 571–598.
Sasaki T, Yamamoto Y, Ezaki B, Katsuhara M et al.
(2004) A wheat gene encoding an aluminum‐activatedmalate transporter. The Plant Journal, 37(5): 645–653.
Sheng H, Zeng J, Liu Y, Wang X et al. (2016) Sulfur
mediated alleviation of Mn toxicity in polish wheat
relates to regulating Mn allocation and improving
antioxidant system. Frontiers in Plant Science, 1382.
Sugiura H, Miyaji S, Yamamoto S et al. (2020) Inductionof citrate transporter gene expression in soybean roots
by sulfur application. Soil Science and Plant
Nutrition, 68(5-6): 547–552.
Suzuki Y, Hibino T, Kawazu T, Wada T, Kihara T andKoyama H (2003) Extraction of total RNA fromleaves of Eucalyptus and other woody and herbaceous
plants using sodium isoascorbate. Biotechniques
34: 988–990.

S(600) S(800) S(1000)

Fig. 2: Relative Root Length plotted against different
concentrations of CaSO4. S represents CaSO4 treatment
TS-5

Wei-0

stop1-ko

1.5

**

1.2
*

0.9
0.6
0.3
0

S(
0)
(A
l -)
S(
0)
(A
l+
S(
)
60
0)
(A
l -)
S(
60
0)
(A
l+
)

Malate release (nmol/plant)

Col-0

40

(/UBG1)

30

**

20

*

10

*
*

Wei-0

Ts-5

Col-0

Wei-0

Ts-5

*
*

S(0)/Al+

Wei-0

Ts-5

S(600)/Al+

35
30
25
20
15
10
5
0

Col-0

(/UBQ1)SULTR35 expression

S(0)/Al+

Col-0

Wei-0

Ts-5

0
Col-0

ALMT1 expression

Fig. 3: Malate release. Ts-5 and Wei-0 secreted more malate
with CaSO4(600 μM) than when no treatment (control)
both in the presence of Al(10μM) 12h later. S means
CaSO 4 treatment.

S(600)/Al+

Fig. 4: AtALMT1 and SULTR35 expression levels weresignificantly induced in Ts-5 and Wei-0 with CaSO4(600μM) then when no treatment (control). In thepresence of Al(10μM) 24h later. S means CaSO 4

32

P17

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Study on the Effect of Ca-Binding Chemical Agents to Induce
Intumescence Injury in Some Tomato Cultivars
Natassia Clara Sita1,2, Sachiko Ohno2, Yoshikazu Kiriiwa2,3 and Katsumi Suzuki2,3
1

The United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
Faculty of Agriculture, Shizuoka University, 836 Ohya, Suruga-ku, Shizuoka 422-8529, Japan
3
Graduate School of Integrated Science and Technology, Shizuoka University, 836 Ohya, Suruga-ku, Shizuoka 4228529, Japan
2

INTRODUCTION

MATERIALS AND METHODS

Intumescence injury is a physiological disorder usuallyfound in Japan's greenhouse cultivation. It is characterized
by the elongation of epidermal and/or palisadeparenchyma cells on the adaxial/abaxial surfaces of leaves
or stems (Suzuki et al. 2020). Intumescence injury, also
known as oedema or edema, commonly occurs in
Solanaceae, such as tomatoes (Atkinson 1893) andpotatoes (Douglas 1907).
Environmental conditions, such as low UV irradiance(Lang and Tibbitts 1983) and high humidity (Atkinson
1893; Lang and Tibbitts 1983), are the main factors
causing intumescence injury in greenhouse or plantfactories. Other studies found that differences in theintumescence severity among several cultivars of tomato
were genetically dependent (Prinzenberg et al. 2022).
Previous reports suggested that chemical agents could
contribute to intumescence injury, such as copper spray incauliflower (Schrenk 1905) and potato leaves (Douglas1907).
Recent findings reported that calcium (Ca) deprivation
can cause intumescence injury as opposed to otherphysiological disorders, such as tip burn, blossom end rot(White and Broadley, 2003), and internal browning(Suzuki et al. 2019). Ca is a macronutrient essential for
maintaining the structural integrity of cell walls andmembranes (Marschner, 1995; White and Broadley,
2003). A lack of Ca can result in intumescence injury in
the leaves of Russet Burbank potato (Schabow and Palta
2019) and several tomato cultivars (Sita et al. 2023).
Recent research conducted in our laboratory discoveredthat the application of ethylene glycol tetraacetic acid
(EGTA), a Ca-chelator known to produce tipburn inlettuce (Carassay et al. 2012), caused intumescence injury
to occur in cabbage leaves. Ca-chelators (EGTA andEDTA) and Ca-inhibitors (such as LaCl3 and nifedipine)
are known to inhibit growth and cause Ca-deficiencyrelated injuries in vegetables. However, no study has
clarified the chemically induced intumescence injury
recently.
Thus, this study aimed to identify the correlation andsignificance of the Ca deficit in tomato leaves caused by
Ca-binding chemical treatment. This study also
investigated the correlation between Ca nutrient solution
and Ca-binding chemical agents to intumescence injury intomato leaves.

Experimental conditions—Three cultivars of tomato(Solanum lycopersicum): ‘Rinka 409’, ‘Misora 64’, and‘CF Momotaro York’ were used as plant materials in thisstudy. All plants were sown in rockwool cube (1 ´ 1 ´ 1inch), and after seven days of sowing, seedlings weretransferred into an artificial climate chamber and thenutrient solution (Enshi formula nutrient solution ½
strength (EC 1.2 dS·m−1, diluted in well-water (EC0.15 dS·m−1), which contained a total of 4.5 me·L−1 Ca)
were supplied from the bottom with aeration. The averagetemperature during all experiments was 23.5-25 °C with arelative humidity of 50-78 %.
Experiment 1 and 2—The topical treatments used inExperiment 1 were EGTA and LaCl3, each 1 mM and 10
mM, and distilled water (control). All treatments wereapplied on the leaves' edges on the adaxial and abaxial
surfaces. Treatments were applied once three weeks aftersowing on the third leaves, and intumescence injury
severity was observed one week after treatment.
The topical treatments used in Experiment 2 were
EDTA, EGTA, LaCl3, nifedipine, each 10 mM, andcontrol. All treatments were applied on the second leaves'whole adaxial and abaxial surfaces. Treatments wereapplied thrice weekly, and the intumescence injury
severity was observed afterward.
Experiment 3—Three levels of Ca nutrient solution
were used, each containing 0.5 me·L−1 Ca, 4.5 me·L−1 Ca,
and 9.5 me·L−1 Ca. In this experiment, four topicaltreatments, including control, EGTA 10 mM, LaCl3 10
mM, and nifedipine 10 mM, were applied four times as inExperiment 2. The intumescence injury severity wasscored after ten days of treatment.
Intumescence injury severity scoring—The following
scale determined intumescence injury severity: 0 = nointumescence, 1 = intumescence slightly appeared, 2 =moderate intumescence, 3 = severe intumescence, 4 =severe intumescence with slightly to moderate wilting, 5= severe intumescence with sever wilting.
Statistical analysis—Student’s t-test was used to
identify the differences between control and Ca-binding
chemical treatments in each experiment.

33

with Ca-binding chemical treatments applied. (DW=
distilled water, each Ca-binding agent concentrated 10 mM).

RESULTS AND DISCUSSION

Previous studies showed that ‘CF Momotaro York’showed tolerance against intumescence injury, even whenconditioned in low UV and high relative humidity
environments and when the Ca was insufficient in nutrient
solution (Sita et al. 2023). We treated this cultivar with
Ca-binding agents to chemically induce intumescence inthis study. The result, however, showed no intumescenceoccurrence in all experiments, indicating other factors
might contribute to the tolerance trait of this cultivar, suchas genetic factors (Prinzenberg et al. 2022) or thedifferences related to its morphological characteristics.
Further studies are needed to clarify this phenomenon.
This study concluded that EGTA, LaCl3, and nifedipine
induced intumescence injury in ‘Misora 64’ and ‘Rinka
409’. Ca-binding chemical agents could induce
intumescence injury in ‘Misora 64’ and ‘Rinka 409’, evenunder insufficient Ca conditions.

Experiments 1 and 2 showed that multiple applicationsof Ca-binding agents are more effective than one-time
applications to chemically induced intumescence injury.
In Experiment 1, Ca-binding agents did not significantly
induce intumescence in ‘Rinka 409’, while in Experiment2, only nifedipine 10 mM significantly induced
intumescence (data not shown). Significant differences
between control and Ca-binding chemical agents wereobserved in ‘Misora 64’ leaves in Experiment 2 (Fig 1).
Among all treatments, only EDTA did not significantly
induce intumescence injury.

REFERENCES
Atkinson GF (1893) Oedema of the tomato. Cornell Univ.
Agr. Stn. Bull., 53: 77–108.
Carassay LR, Bustos DA, Golberg AD, Taleisnik E (2012)
Tipburn in salt-affected lettuce (Lactuca sativa L.)
plants results from local oxidative stress. J. Plant
Physiol., 169: 286–293.
Douglas GE (1907) The formation of intumescences on
potato plants. Botanical Gazette, 43: 233–250.
Lang SP and Tibbitts TW (1983) Factors controlling
intumescence development on tomato plants. J. Amr.
Soc. Hort. Sci., 108: 93–98.
Marschner H (1995) Mineral nutrition of higher plants,
2nd ed. Academic Press, London.
Prinzenberg AE, van der Schoot H, Visser RGF, Marcelis
LFM, Heuvelink E and Schouten HJ (2022) Both major
QTL and plastid-based inheritance of intumescence indiverse tomato (Solanum lycopersicum) RIL
populations under different light conditions. Plant
Breed., 141: 574–584.
Schabow JE and Palta JP (2019) Intumescence injury in
the leaves of russet burbank potato plants is mitigatedby calcium nutrition. Am. J. Potato Res., 96: 6–12.
Schrenk Hv (1905) Intumescences formed as a result ofchemical stimulation. Missouri Botanical Garden
Annual Report, 1905: 125–148.
Sita NC, Kousaka A, Tamoi R, Ozawa C, Iriawati, Kiriiwa
Y and Suzuki K (2023) Incidence of intumescenceinjury in several tomato cultivars under different
calcium conditions. Hort. J. Preview.,
doi: 10.2503/hortj.QH-072.
Suzuki K, Ozawa C and Kiriiwa Y (2020) Morphologicalstudy on the incidence of intumescence injury in tomato
plant leaves. Hort. J., 89: 567–574.
Suzuki K, Suzuki D, Numajiri M, Matsushiro J, Yamane
M and Y. Kiriiwa (2019) Anatomical analysis ofinternally brown tomato fruit. Hort. J., 88: 263–269.
White PJ and Broadley MR (2003) Calcium in plants.
Ann. Bot., 92: 487–511.

Fig. 1: Effect of several Ca-binding chemical agents (each 10mM) to intumescence injury on ‘Misora 64’ leaves. (*indicate significant difference at p < 0.05 by Student t-Test,
NS, not significant).

Intumescence injury level

Experiment 3 showed a negative correlation between
Ca concentrations in nutrient solution and intumescenceinjury severity in ‘Misora 64’ (Fig 3). This was alignedwith the previous report, which suggested that increasing
Ca concentration in nutrient solution could lower the
degree of intumescence injury (Sita et al. 2023). However,
Nifedipine 10 mM, although not significant, induced
intumescence injury even in 9.5 me·L−1 Ca concentration,
indicating that Ca-binding chemical agents could induce
intumescence injury in tomato leaves.
2.5

DW

2

EGTA
LaCl3

1.5

Nifedipine

1
0.5
0
0

2
4
6
8
10
Ca concentration in nutrient solution (me·L−1)
Fig. 2: Correlation between Ca concentration in nutrient
solution and intumescence injury level on ‘Misora 64’ leaves

34

P18

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Effect of Plastic Mulch Residues on Plant Growth and Soil Properties
Shiamita Kusuma Dewi1, Zaw Min Han2, Yongfen Wei3 and Fusheng Li3
1

The United Graduate School of Agricultural Science, 1-1 Yanagido, Gifu-shi, Gifu 501-1193 Japan
Faculty of Engineering, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193 Japan
3
River Basin Research Center, Gifu University, J1-1 Yanagido, Gifu-shi, Gifu 501-1193 Japan2

Mulch plastic and amendments addition to soil – The
soil sample was mixed with each type of mulch plastic
film at a concentration of 0.1% (w/w dry weight of soil)
and soil amendment with a dose of 0.75% (w/w dry weightof soil). Therefore, 0.5 g of each mulch plastic film and3.75 g of each soil amendment were mixed into 500 g ofsoil by stirring with a spoon in a big container before
transferring the mixture into the pot. The potted
experiment design and treatments are shown in Fig. 1.
Each treatment has 3 replicates; therefore, a total of 27
pots were prepared.

INTRODUCTION
Mulching is a common practice used by farmers tomodify soil temperature, minimize weed competition,
reduce soil erosion and evaporation, and improve soil
physical condition. However, due to its low recycling
rates, conventional plastic mulch (polyethylene (PE)plastic mulch) tends to accumulate in the soil after use,
potentially harming soil quality and reducing crop yield.
Biodegradable mulch is becoming increasingly favoredas an eco-friendly substitute for PE plastic mulch, given
its capacity to completely break down in the soil, making
it more environmentally friendly. While biodegradable
mulch film is designed to decompose within two years, its
degradation process is influenced by environmental
factors such as temperature, moisture content, and themicrobial community present in the soil. Furthermore,biodegradable film degrades more rapidly than PE films.
Thereby causing a greater impact on agricultural land andcrops (Zhou et al., 2023).
On the other hand, during agricultural practice, adding
soil amendments of organic materials such as crop
residues, compost, and animal manure can increase soil
fertility, improve soil properties, and enhance microbialactivities. However, the effect of soil amendments onplastic mulch residues contaminated soil remains
unknown. To study the effect of plastic mulch residues onplant growth and soil properties, as well as the changes inthis impact under the addition of soil amendments, a pot
experiment is designed and carried out.

Plastic mulch film 10
mm : 0.1 %Cultivate for 77 days

500 g soil

Plant in greenhouse

Soil amendment 0.75%

Water twice a week

Fig.1: Design of the potting experiment
Table 1. Properties of soil and soil amendment
ParameterpH-1

EC (dS m )OM content (%)-1

TN (mg g )-1

TP (mg g )-1

Soil
6.33 ± 0.00
1.48 ± 0.08
10.62 ± 0.52
5.81 ± 3.20

Compost8.08 ± 0.05
6.25 ± 0.17
67.83 ± 2.61
33.39 ± 0.52

Biochar10.09 ± 0.04
1.01 ± 0.01
17.03 ± 4.31
5.10 ± 0.97

1.31 ± 0.05

1.30 ± 0.09

0.74 ± 0.04

8.34 ± 0.16

4.95 ± 1.60

ND

-

-1

0.01 ± 0.00

0.04 ± 0.00

0.01 ± 0.00

-

-1

ND

0.05 ± 0.03

0.01 ± 0.00

7.61 ± 0.48

4.02 ± 0.16

ND

TK (mg g )N-NO2 (mg g )N-NO3 (mg g )-1

EK (mg g )Note: Values represent mean ± standard deviation (n = 3). EC:
electrical conductivity; OM: organic matter; TN: total nitrogen;
TP: total phosphorous; TK: total potassium; N-NO2-: watersoluble nitrite; N-NO3-: water-soluble nitrate; EK: Exchangeable
potassium.

MATERIALS AND METHODS
Soil sample and amendments – Soil sample wascollected from vegetable fields located in Gifu University.
Two soil amendments were used in the study: compost
and biochar. Compost was made from a mixture of foodwaste and cow manure. The biochar was derived from ricehusk and was obtained from the TAKII SEED
corporation. The soil was sieved through a 2-mm meshsieve and homogenized.
Mulch Plastic – Low-density polyethylene (PE) andPolybutylene
succinateadipatemulch
films(Biodegradation, here referred to as Bio) were manually
cut into a square shape with a cutter and ruler. The size
was 10 mm.

The pH and electrical conductivity (EC) of thesupernatant suspension were determined using a 1:5 (w/v)
ratio of sample to water. The organic matter (OM) content
was determined as the incineration loss at 600º. Total
nitrogen (N) in soil and plant tissues was analyzed by CN
analyzer. The alkaline potassium persulfate digestion-UV
spectrophotometer method measured soil and planttissues' total phosphorus (P). 1 mol L−1 hot HNO3
extraction method was used to determine total potassium(K) in soil and plant. Exchangeable-K of soil was
extracted with 1 M ammonium acetate, water-soluble
nutrient extracted with 1:5 = soil: ultrapure water and35

In Fig 2, it is demonstrated that the addition of compost
and biochar led to a significant increase in both shoot andtotal dry weight, indicating a positive effect on plant
growth.
TN uptake in shoot (mg/g)

30

50

a

25

b

b

20
15
10
5
0
CK

RESULTS AND DISCUSSION

p value
Soil amendment
0.018
0.068
0.025
0.097
0.322
0.126
0.144
0.014
0.695
0.289

Shoot

Dry weight (g)

A

15

b

b

20
10
0
CK

PE

Bio

Table 3: Two-way ANOVA results: significance (p-value) of
the independent variables plastic-type, soil amendments, andinteraction effects on soil properties
p value

Total

B

20

ab

30

Soil properties — The results of the two-way ANOVA(Table 3) indicated a significant influence of plastic typeon dissolved phosphate (P-PO4-) levels and soil
dehydrogenase activity (DHA). The interaction effect(plastic type x soil amendment) was significant only forsoil DHA.

Plastic type x soil
amendment
0.799
0.292
0.558
0.394
0.571
0.513
0.279
0.065
0.709
0.432

Note: TNU: Total nitrogen uptake (mg g -1); TPU: Total
phosphorus uptake (mg g -1); TMg uptake: Total magnesium
uptake (mg g -1); SL: stem length (cm); LA: leaf area (cm2);
LN: leaves number (leaves); SDW: Shoot dry weight (g); RDW:
Root dry weight (g); TDW: Total dry weight (g). The effect wassignificant for p-value < 0.05.
25

40

As shown in Fig 3, the effects of plastic mulch residues
and soil amendments on plant nutrient uptake were
examined. The total nitrogen (TN) content in shoots ofJapanese mustard spinach shoots grown in pots was
significantly decreased by 14.85% and 25.75% in PE andBio-contaminated soil compared to control, respectively(p < 0.05). For magnesium uptake, the presence of PBSA
mulch film residues significantly reduced by 28.14%
compared to the control treatment.

Table 2: Two-way ANOVA results: significance (p-value) of
the independent variables plastic-type, soil amendments, andinteraction effects on plant growth characteristics
Plastic type
0.078
0.204
0.096
0.683
0.869
0.402
0.487
0.006
0.681
0.026

Bio

a

Fig 3: Effect of plastic mulch residues on the total nitrogenand total magnesium uptake of plants in all treatments.
Different lowercase letters indicate significant differences
between treatments (P < 0.05).

Plant growth characteristics — Two-way ANOVA
result (Table 2) revealed that plastic type significantly
affected the total nitrogen and magnesium uptake. On thecontrary, all plant morphological traits were notsignificantly affected by plastic type. The soil
amendments effect was significant for total dry weight
and total nitrogen uptake. The interaction effect (plastic
type x soil amendment) was not significant for all plant
growth characteristics.

Plant growth
characteristics
SDW
RDW
TDW
SL
LA
LN
R/S
TNU
TPU
TMg

PE

Mg uptake in shoot (mg/g)

measured with ion chromatograph method. Soildehydrogenase activity was measured using triphenyl
tetrazolium chloride (TTC). The soil and soil amendments
used in this study are summarized in Table 1.
Statistical analysis – Statistical analyses wereconducted using SPSS 19.0 (p ≤ 0.05). Analysis ofvariance (ANOVA) – two ways were used to determine
the differences between different treatments. Tukey’s
multiple comparison tests method at the probability level
0.05 was used to separate mean differences of the plant
growth performance and soil properties.

Bb

Soil properties
EC
OM
TN
TP
TK
Tca
N-NO 2 -Plastic type
0.256
0.834
0.82
0.758
0.961
0.555

Soil amendment
0.455
0.211
0.175
0.195
0.62
0.596

Plastic type x soil
amendment
0.238
0.977
0.319
0.717
0.874
0.694

0.27

0.094

0.615

P-PO4-

0.035

0.095

0.284

Na+
DHA

0.14
<0.001

0.258
0.001

0.138
0.026

Note: Na+: natrium ion. The effect was significant for p-value <
0.05.

a
10

In this study, the following results were obtained.
1. The presence of plastic mulch film residues
significantly decreased TN and TMg uptake.
2. The addition of compost and biochar resulted in asignificant increase in both shoot and dry weight.
3. The interaction between plastic-type and soil
amendment was found to be significant only in
relation to soil DHA.

5

0

CK

CompostBiocharFig 2: Effect of soil amendments on the dry weight of plants
in all treatments. Different lowercase letters indicate
significant differences between treatments (P < 0.05).

36

P19

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Comparison of Viral Infection Status of Roses in Japan and Its Effect to
Plant Growth
Thiara Celine Suarez1, Kunio Yamada2, Takashi Nakatsuka3 and Masaki Ochiai2
1

The United Graduate School of Agricultural Science, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan
Faculty of Applied Biological Science, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan
3
Faculty of Agriculture, Shizuoka University, 836 Ohya, Suruga-ku, Shizuoka 422-8529, Japan2of viruses associated with RMD. This study identified a
total of ten different viruses contributing to the disease.
In Jordan, Mansour (2010) utilized serological testing
via DAS-ELISA to determine the causal agents of RMD.
It was determined that this condition could be linked to thepresence of PNRSV and ApMV, either as singular
infections or in the form of mixed infections.
A study of virus infection was conducted in Japan by
Takenaga (2021) wherein it was found that roses were
infected with RCV-1 and RSDaV. However, the study
was limited to Gifu World Rose Garden and Gifu
University Research Field. The inherent constraints ofthis localized study have emphasized the necessity for abroader, more comprehensive examination of the virallandscape impacting roses across Japan. The pressing
knowledge gaps include a scarcity of data concerning the
precise viral strains responsible for infecting roses, an indepth understanding of the physiological damage inducedby these viral agents, and the geographic distribution ofthese infections within the country.
Therefore, the objective of this study is to detect virus
from roses planted in rose gardens around Japan andcompare the growth and rooting characteristics between
virus-infected and non-infected roses. Through thiscomprehensive approach, it aims to gain a thoroughunderstanding of the complex interplay between viral
infections and rose development.
It is with high hopes that results of this study will
improve rose cultivation by addressing viral infections,employ a unique approach by comprehensively studying
infections and growth effect and envision a future whereroses thrive without viral threats.

INTRODUCTION
Roses are considered as one of the popular flowers
worldwide for their ecological and cultural significance.
In Japan, they are used for medicinal, perfumery andornamental purposes. As mentioned by the Ministry ofAgriculture, Forestry and Fisheries of Japan (2023), theproduction of roses in the country is among the thirdlargest in terms of cut flower production. However, roses,
like all living organisms, are susceptible to various
pathogens, pests and diseases like aphids, spider mites androse mosaic disease (RMD). When this happens, roses
suffer from reduction of flower quality, productivity, andplant vigor.
RMD is caused by more than one pathogen includingApple mosaic virus (ApMV) and Prunus necrotic ringspot
virus (PNRSV). According to Karlik et al. (2020), thevirus is transmitted when virus-infected roses are
subjected to grafting onto uninfected plant materials. It
was mentioned that empirical evidence suggests that the
spread of rose mosaic can occur through root grafts.
Infected roses may show no symptoms until after
transplanting, and the virus usually persists for the plant's
lifetime. Virus infection results in a range of leaf
symptoms, including yellow, white, or brownish lines,
bands, rings, vein clearing, yellowing, oak-leaf patterns,or blotches. In some cases, only a portion of the plant is
impacted.
Research conducted across various parts of the world
has shed light on the prevalence of these viral pathogens,contributing to our understanding of the global landscapeof RMD.
In Turkey, a comprehensive investigation was
conducted, involving the collection of rose samples fromdiverse regions. These samples underwent testing to
identify the presence of distinct viruses that afflict rose
plants. The study revealed the presence of PNRSV, rose
cryptic virus-1 (RCV-1), rose spring dwarf-associatedvirus (RSDaV), rose yellow vein virus (RYVV), and
ApMV infections (Karanfil, 2021).
Meanwhile, in New Zealand, Milleza et al. (2013)
uncovered a similar viral panorama affecting roses. RCV1, PNRSV, RSDaV, RYVV, and Arabis mosaic virus(ArMV) were identified as the viral agents responsible for
infecting roses in this region.
Further investigations by Chen et al. (2022) in Taiwan
revealed that a substantial proportion of rose samples specifically, fifty out of 294 - were affected by a variety

METHODSThis study consists of two primary experiments
designed to investigate the status of viral infections inroses. These experiments aim to provide a comprehensive
understanding of the viral infections affecting these plants
and their associated effects.
The first experiment involved the systematic collectionof rose samples from diverse geographical locations inJapan. These samples will be subjected to identification
process using advanced molecular techniques to detectand categorize the specific viral strains affecting the rosesamples.
The second experiment will be conducted to evaluate
the impact of viral infections on rose plants. In thisexperiment, both infected and non-infected rose samples

37

will be examined. The evaluation will include several
components. The morphological characteristics of therose samples will be examined for any visible signs ofdisease under the microscope. Biochemical analysis of theinfected and non-infected samples will be performed togain insights into the biochemical changes associated withviral infections. This analysis will reveal alterations in thecomposition of plant tissues and the presence of specificbiomarkers linked to viral infections. The effects of viral
infections on root and overall growth development will be
understood through an investigation of root systems forsigns of damage or restricted growth and an assessment of
the overall growth patterns of infected versus non-infectedroses.

stressors. On the other hand, single symptoms might belinked to specific issues, while mixed symptoms might
indicate a more complex manifestation of leaf problems.
The existence of mixed symptoms in both areas implies
that the plant health issues might be complex, involving a
combination of factors that contribute to the observed
symptoms. The asymptomatic samples suggest that a
portion of the plants may be healthy or resilient to theissues observed in other samples.
In summary, these results offer an initial indication into
the state of roses in Nishiyama Park and Rose Hill Park
Shimada. However, they do not provide a definitive
explanation for the observed symptoms. Further research
will be conducted.

RESULTS AND DISCUSSION

REFERENCES

The preliminary collection of samples took place in two
key areas: Nishiyama Park in Toyota City, Aichi
Prefecture, and Rose Hill Park in Shimada City, Shizuoka
Prefecture. Subsequently, an initial examination was
conducted to identify any potential symptoms indicating
the presence of a virus.
In Nishiyama Park, out of the fifty samples assessed,
twenty samples displayed a single symptom. This
category was characterized by a variety of specificsymptoms, with the most prevalent being moderate tosevere chlorotic line patterns observed in six samples.
Additionally, there were six samples that exhibitedmottling, five with vein banding and netting, one withyellowing on the leaf edge, one with distortion, and one
displaying ringspot symptoms. Furthermore, the study
identified seventeen samples with mixed symptoms,
reflecting a more complex manifestation of leaf issues.
These mixed symptoms were combinations of different
specific symptoms, such as mosaic, mottling, leaf cutter
bee damage, vein banding, yellowing on the leaf edge,
distortion, holes in the leaf, and black veins. On the other
hand, thirteen samples out of the total did not display any
visible symptoms and were categorized as asymptomatic.
In Rose Hill Park Shimada, a total of fifty samples were
examined. Among the seventeen samples displaying
single symptoms, specific leaf issues were observed.
These single symptoms included moderate to severe
chlorotic line patterns in three samples, mottling in sevensamples, vein banding and netting in five samples,ringspot in one sample, and distortion in one sample. Mostof the samples, a total of twenty-seven, exhibited mixed
symptoms, which indicated more complex manifestationsof leaf issues. The mixed symptoms included
combinations like mottling with ringspot, vein banding
with ringspot, chlorotic line patterns with ringspot, veinbanding with mottling, and others. Six samples wereasymptomatic or showed no visible symptoms.
There is a noticeable diversity of symptoms in both
locations, encompassing issues like chlorotic line patterns,
mottling, vein banding, and ringspot. This diversity
suggests that the plant populations in these areas may be
experiencing a range of problems, potentially caused byseveral factors, such as viruses, pests, or environmental

Chen TC, Lin YC, Lin CC, Lin YX and Chen YK (2022)
Rose Virome Analysis and Identification of a Novel
Ilarvirus in Taiwan. Viruses, 14(11): 2537.
Karanfil A (2021) Prevalence and Molecular
Characterization of Turkish Isolates of the Rose
Viruses. Crop Protection, 143: 2.
Karlik JF, Golino DA, Al Rwahnih M (2020) UC IPM
Pest Notes: Roses: Diseases and Disorders. Universityof California Agriculture and Natural Resources
Publication 7463.
Mansour A (2010) Identification of Rose Viruses
Associated with Rose Mosaic Disease in Jordan. Jordan
Journal of Agricultural Sciences (The University of
Jordan). 2: 4.
Milleza, EJM, Ward LI, Delmiglio C, Tang JZ, Veerakone
S, Perez-Egusquiza Z (2013) A survey of viruses
infecting Rosa spp. in New Zealand. Australasian Plant
Pathol., 42: 313–320.
Ministry of Agriculture, Forestry and Fisheries (2023)
Statistics of Agriculture, Forestry and Fisheries.
Planted area and shipment number of flowers produced
in 2022. (In Japanese translated to English) 農林水産
統計 令和４年産花きの作付（収穫）面積及び出荷量．
https://www.maff.go.jp/j/tokei/kouhyou/sakumotu/sakkyou_kaki/attach/pdf/index-1.pdf
Takenaga Y (2021) Survey on virus infection in roses.
Master Thesis, Gifu University. (In Japanese translated
to English) 武永有利 (2021) バラにおけるウイル
ス感染の実態調査. 修士論文, 岐阜大学大学院自然科学技術研究科.

38

P20

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Reduction of Antibiotic Resistance Genes in Large-Scale Johkasou
Treating Residential Area Wastewater
Su Haoning1, Okumura Shinya１and Li Fusheng2
1
2

Graduate School of Engineering, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
River Basin Research Center, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
PCR (qPCR). Two tetracycline resistance gene (tetG,
tetM), two sulfonamide resistance genes (sul1, sul2), a
mobile genetic element (MGE) (integrase class 1 gene,
intl 1), and total bacteria reflected by 16S rDNA were
quantified by qPCR with the utilization of SYBR®
Premix Ex Taq™ (TaKaRa, Japan) based on the
manufacturers' manual.
(3) Statistical analysis
Non-metric multidimensional scaling (NMDS) andprincipal coordinates analyses (PCoA) were created basedon the data set comprising the relative amounts of ARGs.
These analyses were conducted using the Bray–Curtis
distance and implemented through R software.

INTRODUCTION
Antibiotic resistance genes (ARGs) are emerging
environmental contaminants and pose serious threat to
public health. Wastewater from livestock, agriculture,industry, hospitals, antibiotic manufacturers, andhouseholds is the main source of ARGs. For Johkasou, afacility treating household wastewater, the fate andbehavior of ARGs remains unclear. In this study,
quantitative and qualitative changes of ARGs in thetreatment processes of Johkasou was evaluated and theexisting state of ARGs in relation to the size of suspended
solids in wastewater and sludge was clarified.

RESULTS AND DISCUSSION

MATERIALS AND METHODS(1) Fates of ARGs undergoing treatment processes(1) Sample collection and pre-treatment
Water and sludge samples were collected from eightsampling points (Fig. 1) in a large-scale Johkasou locatedin Aichi, Japan. Sampling was performed weekly in 2
months, corresponding to the operation time after cleaning
accumulated sludge.
To classify ARGs on suspended solids remaining inwater and in sludge, Sample filtration was conductedusing sieves with the opening of 250, 125, 75 and 25µm
respectively, and a membrane filter with the pore size of 3
µm. The filtrates were used for ARGs quantitation

Raw water storage
Pre-aeration
1st & 2nd aeration
Sedimentation

SludgestorageFig. 2: NMDS biplots of relative ARGs and MGE
abundances by target genes (tetG, tetM, sul1, sul2
and intl1) across the treatment process. The process
trajectory is represented by dashed lines (in black);
original explanatory variables are displayed as vectors(in red).

Post-aeration
Re-sedimentation&Disinfection

Fig. 1: Flow diagram of the Johkasou and sampling
points ( Water sample
Sludge sample)

As shown in Fig. 2, The relative amount of ARGs
increased during the biological treatment processes (Preaeration, 1st aeration and 2nd aeration) and decreased via
sedimentation. The Bray-Curtis distance was longest
between the biological and sedimentation processes.
These results indicate the largest shifts in ARGs
occurrence patterns during those processes. Changes in(2) DNA extraction and determination of genes
DNA extraction for all samples was conducted using
Power Soil DNA Extraction Kit (MOBIO, USA) based on
manufacturer's manual. The extracted DNA was stored at−25 °C for determination of target genes by quantitative39

directions showing the trajectory of sampled sites indicate
significant shifts in the ARGs community as a result of
having undergone various treatment processes inJohkasou. In the operation of 7 to 63 days after sludge
cleaning, the fate and behavior of ARGs were similar, but
the extent of ARGs reduction was higher for the time of
28 days from the influent to the effluent (Fig. 3)

Fig. 3 Log reduction of 16S rDNA, intl1, tetG, tetM,
sul1 and sul2 during operation of 7 to 63 days after
cleaning.
(2) Fates of ARGssludge
undergoingtreatment processes

The budget of genes ‘mass and distributions in water
Fig. 5: Average mass fluxes of targeted genes of input,
sludge, changes and output (upper). Daily mass inpercentage of targeted genes (lower).

0.5

A>250 µm

PCoA2 (21.4%)

125-250 µm

and sludge are estimated to further evaluate the operative
removal process in the Johkasou, and the results weresummarized in Fig. 5. All the genes demonstrated a
relatively high mass flow in biological treatment andsludge. tetG, sul1 and intl1 behaved similarly in terms of
distribution in wastewater and sludge, as well as thenegative loss due to biological treatment that means theproliferation of genes. In addition, a significant portion ofgenes are enriched in the sludge. Although the sludge isperiodically removed, during its maximum retention
period of two months, a considerable portion will re-enter
the aeration unit through backflow. Consistent with results
mentioned before, there is a risk that suspended matter, inwhich small particles have poor settleability, will carry
more resistant genes back into circulation or remain in the
supernatant and be discharged with the treated water.
Overall, the results improve the understandings on fate
and transport of ARGs in household wastewater treatment
facility. ARGs carried by suspended solids with small size
may be the bottleneck of controlling the spread of ARGs
from the hotspots into the receiving environment.

75-125 µm

025-75 µm
3-25 µm< 3 µm
-0.5

-0.7

PCoA1
-0.1 (39.3%)

0.5

Fig. 4: Bray-Curtis distance-based PCoA of sizefractionated ARGs and MGEs (relative abundances),‘Size fraction’ and ‘treatment unit’ were set as the two
factors.
In general, the PCoA results are used to show the
distribution of different size related ARGs during thewhole treatment process. The PCoA based on the relative
abundances of ARGs showed the varied distribution on
the suspended solids with different size in wastewater andsludge samples (Fig. 4). The samples with size lower than
3µm clustered together, while there was a shift in genes
abundance for the treatment processes from influent andaeration to post-aeration, effluent and sludge. The samples
with relative bigger size (25 - 250µm) forming two
clusters were not similar while the relative longer
distances created by sampling sites. The distances
between pre-aeration, sedimentation, post-aeration,
settled and re-settled sludge samples with size range of 3
– 25µm were closer, creating another cluster. The results
indicated that the fates of ARGs and MGEs werepotentially different for different size fractions andtreatment process.

REFERENCES
Yu K, Li P, He Y, Zhang B, Chen Y and Yang J (2020)
Unveiling dynamics of size-dependent antibiotic
resistome associated with microbial communities infull-scale wastewater treatment plants. Water Res., 187:
116450.

40

P21

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation on Agricultural and Basin Water Environmental Sciences 2023

Fate and Behavior of Antibiotic Resistance Genes in Activated Carbon
Adsorption
Sri Anggreini1, Alma Rizky Aurellya2 and Fusheng Li1,3
1

Graduate School of Engineering, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
Graduate School of Natural Science and Technology, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan
3
River Basin Research Center, Gifu University, 1-1 Yanagido, Gifu-shi, Gifu 501-1193, Japan2

containing 100 μg/mL ampicillin overnight. The
confirmed colonies containing the desired plasmid were
cultured overnight with LB medium and ampicillin.
Plasmid pUC19 was extracted from E. coli DH5α using aplasmid extraction kit (MACHEREY-NAGEL, Germany),
and the concentration of the purified plasmid wasdetermined by Quantus Fluorometer analysis. Further, thepurified plasmid was diluted with sterile deionized water
to obtain the ARGs solution and used for adsorption
experiments.
Adsorption and desorption experiments—The initialconcentration of ARGs was set at 0.01 ng/µL. After 180
minutes of shaking, centrifugation was conducted for 10
minutes at 12,000 g to separate AC particles. The obtained
supernatant was subjected to ARGs quantification by
quantitative polymerase chain reaction (qPCR). The
settled AC was subjected to desorption experiments byadding 1 ml of sterilized deionized water to the settled AC
and kept shaking under the same conditions as theadsorption experiments. The concentration of ARGs
before and after desorption was also quantified using
qPCR analysis. The pseudo-first and pseudo-second-orderkinetic models described below were used to analyze thedata from the experiments.

INTRODUCTION
The dissemination of antibiotic resistance genes(ARGs) in aquatic environments has become a global
health issue. Nowadays, antibiotic resistance causes
700,000 deaths globally each year (Mao et al., 2014).
Extracellular ARGs (eARGs) in water, such as plasmid or
chromosomal DNA, have gained interest due to their
durability and contribution to the spread of antibiotic
resistance. It has been found that eARGs can persist forseveral months in water and spread more easily in theaquatic environment compared to intracellular ARGs(iARGs) (Mao et al., 2014).
Powdered activated carbon (AC) is commonly added at
the receiving well of water treatment before thecoagulation process to enhance organic matter removal.
This process produces sludge, which is commonly
dewatered. The water is recycled as raw water, while thesolid materials containing AC are discharged into theenvironment. Depending on the physicochemical featuresof AC, eARGs may penetrate into AC pores before thecoagulation process. Further, eARG can probably be
carried with solid materials into the environment or carried
with recycled water as raw water. eARGs may persist overmany generations and enable the dissemination of
antibiotic resistance traits via transfer. In this study, thefate and behavior of eARGs during contact with AC were
investigated. For this purpose, plasmid pUC19 that carries
an ampicillin resistance gene (ampR) was selected, and ten
types of commercially available ACs with different poresize distributions were used.

!"!
= %" ("# − "! )
!#

(1)

!"!
= %$ ("# − "! ) $!#(2)

where qt (copies/mg) is ARG adsorbed onto AC at time t,qe (copies/mg) is adsorption capacity at equilibrium, k1 andk2 (copies.min/mg) are the pseudo-first and pseudosecond-order rate constant, respectively.

MATERIALS AND METHODS
Activated carbon—Ten commercially available ACs
with different pore size distributions were used, namely
carbon A, B, C, D, E, F, G, H, I, and J. Carbon A, B, C,
D, and E are coal-based ACs, while carbon F, G, H, I, andJ are wood-based ones. All ACs are steam-activated.
Preparation of plasmid-encoded ARGs— Plasmids were
propagated by transformation into E. coli DH5α. One
hundred μL of E. coli DH5α were mixed with 10 μL of
plasmid. The mixture was incubated on ice for 30 min,then immediately transferred into an incubator at 42 °C for
45 s and placed back on ice for 2 min. After heat shock, themixture was added into 890 μL of SOC medium andcultured in a shaking incubator (200 rpm) at 37 °C for 1 h.
The incubated samples were plated onto LB agar plates

RESULTS AND DISCUSSION
Residual concentration of ARGs after adsorption—The
residual concentrations of ARGs during contact withdifferent types of AC are displayed in Fig. 1. The rate ofadsorption was rapid at the beginning and gradually
decreased with increasing contact time until equilibrium
was attained within 120 min. To ensure complete
equilibrium, the experimental data was quantified up to
180 min. The lowest residual concentration in coal-based
and wood-based ACs was obtained from carbon A and H.
However, the highest residual concentration was found in
carbon B for coal-based ACs and carbon F and G for woodbased ACs. The pore size, pore volume, and surface
41

Proceedings of UGSAS-GU & BWEL Joint Poster Presentation 2023

chemistry of the AC may contribute to the adsorbability of
ARGs.
A

1.2

B

C

D

E

by the low adsorption capacity of those ACs (data notshown).
3.5E-08

Control

(a)

(a)

A

3.0E-08

1.0

B

C

D

100
Time (min)150E

2.5E-08

C/C0

t/qt

0.8

0.6

2.0E-08
1.5E-080.4

1.0E-080.2

5.0E-09

0.0

0.0E+00

0

F

1.2

50

100
Time (min)

G

H

I

J

150

0

200
2.5E-08

Control

(b)

50

(b)

F

G

H

200

I

J

2.0E-081.0

1.5E-08

C/C0

t/qt

0.8
0.6

1.0E-080.4

5.0E-090.2

0.0E+00

0.0
0

0

50

100
150
200
Time (min)Fig. 1: Residual concentrations of ARGs during contact with(a) coal-based and (b) wood-based ACs (C0 = 3.4 × 1012
copies/L, AC dose = 1 g/L)

50

100
Time (min)

150

200

Fig. 2: Pseudo-second-order kinetic models for adsorption of
ARGs on (a) coal-based and (b) wood-based ACs (C0 = 3.4 ×
1012 copies/L, AC dose = 1 g/L)

2
Desorbed ARGs (%)

Adsorption kinetics of ARGs on different types of AC—
Model analysis indicated that the pseudo-second-orderkinetic model fitted all experimental data much better thanthe pseudo-first-order ones as shown in Fig. 2. The R2
value of the pseudo-second-order was very high (R2>0.9699), and the calculated qe value was in good
agreement with the experimental one, suggesting theapplicability of the pseudo-second-order kinetic model todescribe the adsorption kinetic of ARGs onto AC. Thismodel implies that chemisorption occurs during theadsorption process and the adsorption rate depends on theadsorption capacity, not on the adsorbate concentration.

1.6
1.2
0.8

0.4
0
A

ARGs concentration after desorption that remains inwater—ARG-carrying plasmids were desorbed from ten
different types of AC, as illustrated in Fig. 3. The desorbed
ARGs from carbon B, F, and G were generally higher thanother types of AC. Carbon B, F, and G were highly
microporous, with pore volume percentages of 98.1, 96.4,
and 90.9 % at pore sizes below 15 Å, respectively. This
result indicates that the size exclusion effect prevents
ARGs from entering the AC pores below 15 Å, and most
ARGs only stick on the external surface of AC, leading toeasier desorption into water. This result is also supported

B

C

D

E F G
AC types

H

I

J

Fig. 3: Desorbed ARGs from different types of AC remaining
in water

REFERENCES
Mao D, Luo Y, Mathieu J, Wang Q, Feng L, Mu Q, Feng
C and Alvarez PJJ (2014) Persistence of Extracellular
DNA in River Sediment Facilitates Antibiotic
Resistance Gene Propagation. Environ. Sci. Technol. 48(1), 71–78.

42

Proceedings of UGSAS-GU & BWEL
Joint Poster Presentation on Agricultural andBasin Water Environmental Sciences 2023
Publisher:
The United Graduate School of Agricultural Science,
Gifu University
1-1 Yanagido, Gifu-shi, Gifu 501-1193 Japan
ISBN 978-4-909365-09-5