IJERD – International Journal of Environmental and Rural Development (2018) 9-1

Research article
erd

Soil Health Assessment of Soil under Miscanthus × giganteus
Cultivation
TORU NAKAJIMA*
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Email: tn206473@nodai.ac.jp

TAKAHIKO NAKAMURA
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan

MACHITO MIHARA
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, Japan
Received 7 March 2018

Accepted 10 May 2018(*Corresponding Author)

Abstract Soil health is the capacity of soil to function as a living ecosystem that sustains
plants, animals, and humans. Healthy soils support the optimal crop yields and also plays acrucial role in protecting water quality and other aspects of environmental stewardship.
Meanwhile, the agricultural damage by the earthquake causes serious crop productivity
degradation in Japan. Thus, there is a need for research on crop productivity, especially land
under the earthquake disaster. In addition, the global demand for renewable energy
resources such as Miscanthus spp., mainly the triploid interspecific hybrid Miscanthus ×
giganteus (M × g), has increased substantially. Because it has the potential to have a highyield, sequester the carbon into the soils, and improve the soil health. Therefore, theobjective of this study was to demonstrate soil health index assessment at Miscanthus spp.
fields. We investigated (1) to quantify the impact on land use changes including Miscanthus,pasture, and arable land on soil health index. T soil under M × g increases the over-all SHI
value to compare another land use. Therefore, it can be concluded that M × g is the better
land use management option in the cool climate regions such as Northern Japan.
Keywords soil health, soil management assessment framework, Miscanthus × giganteus

INTRODUCTION
What is a good soil or a bad soil? That is the ultimate question for soil scientists. The soil scientists
have been trying to answer that question as well as to find out the way to ensure the soil health.
Soil health is defined as the capacity of soil to function to sustain plant and animal productivities,
to maintain or improve water and air qualities and to support human health and habitation (Karlenet al., 1997). Soil health index (SHI) assessment involves an evaluation of soil physical, chemical,and biological attributes to know how well the resource is functioning. Therefore, SHI assessment
seeks to characterize the overall agro-ecological functions of soil by selecting soil physical,
chemical, and biological properties as indicators, measuring them, and calculating a score or index
for both the individual properties and overall soil health (Nakajima et al., 2015). Miscanthus spp.,
as source of biomass energy crop mainly the triploid interspecific hybrid Miscanthus × giganteus(M × g), has increased drastically. The M × g has the potential to mitigate greenhouse gas
emissions by replacing fossil fuels, sequestering carbon into the soils, and improve soil health(Clifton-brown et al., 2004, Guzman and Lal, 2014). In addition, the M × g requires low annual
energy net and financial inputs, including tillage, planting, and practical management such as
fertilizer, herbicide, and pesticide application. Yet, the effects of SHI on soil under M × g
cultivation vary by climate, soil type, management practices, and former land use history. Thus,
there is a need for site-specific research on M × g of SHI.

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OBJECTIVES
The objective of this study was to demonstrate SHI assessment at M × g fields. We specificallyinvestigated to quantify the impact on land use changes including M × g, M. sinensis, pasture, andarable land on SHI. The hypothesis tested in this study was that soil under M × g increases the overall SHI value to compare another land use.

METHODOLOGY
Study Site and Soil Sampling
The study site was established in 2009 at the Experiment Farm of the Field Science Center for
Northern Biosphere, Hokkaido University, Sapporo, Japan (43°04ʹ22ʹʹN, 141°20ʹ16ʹʹE). According
to the Japan Meteorological Agency, the annual average temperature and annual precipitation were
9.48 °C and 1209 mm, respectively from 2009 to 2015. The soil at the study site is classified as
Humic Andosols. The undisturbed soil core samples were collected with 100 cm3 steel soil coresampler (height = 5.0 cm, diameter = 4.8 cm) using a cylindrical hammer-driven core sampler forsoil depths of 0-5 cm, with three replicates. In addition, disturbed soil samples were obtained forsoil layers at depths of 0-5 cm, with three replicates per plot, using a hydraulic soil sampling device(FV-477, Fujiwara Scientific Company Co., Ltd., Okayama, Japan). The soil samples were
homogenized by replicate and sieved through 2 mm sieve and air-dried before the analysis.

Photo. 1 Miscanthus × giganteus and soil sampling at arable land
Soil Health Assessment
The SHI assessment was conducted by: (1) identifying a minimum data set of indicators, (2)selecting indicator interpretation criteria, and (3) integrating all indicator scores into an overall SHI
value (Andrews, et al., 2004, Nakajima, et al., 2015).
The SHI was basically computed by using the Soil Management Assessment Framework(SMAF) (Andrews et al., 2004, Karlen et al., 2001). The details for each step of the SHI assessment
is summarized as follows.
1. First, the minimum data set of soil physical, chemical, and biological indicators was selected
for evaluating for the management goal. The indicators were selected based on literature
review (Andrews et al., 2004, Nakajima et al., 2015).
2. For the second step, the minimum data set indicators were converted into unit less scores
ranging from 1 to 5 using the criteria presented in Table. 1. In general, there are three shapes ofscoring functions (Karlen and Stott, 1994, Wymore, 1993). If soil quality is improving as levelof an indicator increases, a “the more is better” curve is used. Conversely, a “less is better”
curve is suitable if soil quality is decreasing as the indicator value rises. Finally, a “optimum”
curve is used for those indicators that have an increasingly positive association with soilquality up to an optimal level, but beyond which, soil quality decreases.
3. Finally, after selecting the appropriate curve type and scoring individual indicators, the unit
less values can be incorporated in a single. Overall SHI value with appropriate weighting ofindividual indicators if needed.
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1. Indicator Selection
Minimum Data Set
Soil PhysicalIndicators

Soil Biological
Indicators

Soil Chemical
Indicators

Those indicators were selected based on the management goal

2. Interpretation

Score

Score

Score

Three Type of Scoring Functions (Indicator to Score)

Indicator

Indicator

Indicator

More is better

Less is better

Optimum

3. Integration

Soil Health Index

Fig. 1 Conceptual framework for soil health index scoring function analysis adaptedfrom Andrews et al., 2004
Table 1 Scoring function chart for interpretations soil health index with source references
Indicator
BD
TextureUnit
Mg m-3-5<1.2Loam3
1.3-1.4
Clay loam,
Sandy loam2
1.4-1.5
Silty clay,
Loamy sand1>1.5
ClaySand

Reference
Lal (1994)
Lal (1994)

5.4-5.8,
7.4-7.8
500-700
10-30

5.0-5.4,
7.8-8.2
700-1000
5-10<5.2,>8.2>1000<5Andrews et al. (2004)

μS m-1g kg-16.07.0<300>504
1.2-1.3
Silt loam,
Silt,
Silty clay loam
5.8-6.0,
7.0-7.4
300-500
30-50

pH-EC
SOC
MWD

mm>2.5

2.0-2.5

1.0-2.0

0.5-1.0<0.5

Lal (1994)
Gregorich et al. (1994)
Lal (1994)
Lal (1994)

Statistical Analysis
Analysis of variance (ANOVA) was conducted, and comparisons between the M × g, M. sinensis,pasture, and arable land were performed R Studio (Studio, 2012). Statistical significance wasdetermined when P ≤ 0.05, unless otherwise stated.
RESULTS AND DISCUSSION
Implementation of SHI Analysis
Among all sites, the SHI ranged from 0.59 to 0.72, and the SHI under M × g (0.72) was slightly
higher than that under arable land (0.59), but with no statistical differences. The SHI weresignificantly affected among the sites. However, M × g cultivation could improve the SHI fromresults SHI assessment. It implies that under the M × g in Northern Japan influence soil health dueto their nutrient cycling between the rhizome and aboveground biomass, and recycling of nutrientsfrom leaf litter and the soil. In addition, this has several possible explanations after theestablishment of M × g, there was no major loss in SOC due to the minimal soil disturbance causedby the introduction of the perennial rhizomatous grass (Zimmermann et al., 2012).

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Table 2 Correlation coefficients for each soil physical and chemical properties
BDSOC
pHEC
Texture
MWDBD
1.000
0.202
0.089
0.289
0.013
0.144

SOCpHEC

Texture

MWD

1.000
0.466
0.177
0.286
0.808*

1.000
0.336
0.772*
0.650*

1.000
0.024
0.222

1.000
0.396

1.000

* Significant at the 0.05 level.
BD: bulk density (Mg m-3)
SOC: soil organic carbon (g kg-1)
EC: electric conductivity (mS m-1)
MWD: mean weight diameter from soil aggregation analysis (mm)The SOC, pH, MWD, Texture were the important key indicators for SHI assessment in thisstudy sites. For soil chemical function, the pH had the highest correlation coefficient. Other
important measured attributes were SOC and MWD. However, BD and EC were less responsive tothe management practices in comparison to other indicators.
1.0Soil Health Index

0.8

BDSOCpHEC
Texture
MWD

0.6

0.4

0.2

0.0

M ×g

M. sinensis

PastureArable landFig. 2 The soil health index (SHI) at M × g, M. sinensis, pasture, and arable land Error bars
indicate standard error
CONCLUSION
This study demonstrates SHI assessment using scoring function analysis for different sites. The
hypothesis tested in this study was that soil under M × g increases the over-all SHI value tocompare another land use was supported by the results. Therefore, it can be concluded that M × g is
the better land use management option in the cool climate regions such as Northern Japan.
Quantitative assessments of soil health may be useful for optimizing land use plans. However, valid,reliable, sensitive, repeatable, and accessible indicators must be identified and framework foroverall evaluation of soil quality must be developed (Nakajima et al., 2015).
ACKNOWLEDGEMENTS
This research was partly supported by the Japan Society for the Promotion of Science (JSPS)
KAKENHI “Grant-in-Aid for Research Activity Start-up” Grant No. 15H06661. The research onⒸ ISERD

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the biomass production of Miscanthus ssp. was supported by the New Energy and Industrial
Technology Development Organization and the Ministry of Agriculture, Forestry and Fisheries,
Japan. The authors gratefully acknowledge for Drs. Naoto Iwasaki, Masahiko Katoh, and Yoshihiro
Kakizaki at Meiji University for their laboratory work and invariable discussions and staff
members at the Experiment Farm of the Field Science Center for Northern Biosphere, Hokkaido
University for assisting with the research. We would like to thank to Dr. Jose G. Guzman at The
Ohio State University for his support with the writing.
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