Authors: Sunanda Biswas, Shrila Das, Ruma Das and Mandira Barman
Division of Soil Science and Agricultural Chemistry, ICAR-IARI, New Delhi-110012
*Corresponding author, email: sunandabiswas13@gmail.com, mob: +919732266623
Introduction
Soil is a wonderful gift of nature whose good health is essential for societal existence. Routine soil testing measures the status of soil nutrients and some physical properties of soil. Such analysis of soil is done to find out nutrient deficiency in soil and find out the strategy to manage deficient soils. But soil health encompasses various biological, chemical and physical parameters of soils which are important in the context of sustainable land use and management. Soil health can be defined as ‘the continued capacity of soil to function as a living system, within ecosystem and land use boundaries, to sustain biological productivity, maintain the quality of air and water environment and promote plant, animal, and human health’ (Doran et al., 1996).
However, assessing soil health is difficult, because soil health cannot be measured directly, but it may be inferred from management-induced changes in soil properties (Mandal et al., 2005). Soil health indicators are a composite set of measurable physical, chemical and biological attributes which relate to functional soil processes and can be used to evaluate soil health status.
Therefore it is necessary to develop such a diagnostic tool with simple, robust and process based indicators, both qualitative and quantitative, to discern mechanistically why a particular (management/cropping) system is favourable or unfavourable to soil health. This tool will help to evolve management practices that optimize the combined goals of high crop production, low environmental degradation, and a sustained soil resource. Andrews and Carrol (2001) described a statistical method for assessing the soil health index. A valid soil health index would help interpret data from different soil managements and show whether management and land use are having the desired result for productivity, environmental protection and soil health.
The soil health approach is better applied when specific goals are defined for a desired outcome from a set of decisions. Therefore soil health evaluation process which consists of a series of actions:-
• Selection of soil health indicators
• Determination of a minimum data set (MDS)
• Development of an interpretation scheme of indices
• On-farm assessment and validation
Selection of soil health indicators based on some criteria, they should (i) encompass ecosystem process, (ii) sensitive to variation in management practices and climate, (iii) easily measurable and reproducible, (iv) a component of existing soil database (v) be accessible to many users and applicable to field conditions, and (vi) integrate soil physical, chemical and biological properties and processes (Doran and Perkin, 1994).
Table 1. Soil health indicators (Karlen et al., 2003)
| Physical | Chemical | Biological | |
| Aggregate stability | pH | Soil organic matter | |
| Infiltration | Electrical conductivity | Respiration | |
| Bulk density | cation exchange capacity | Microbial biomass C & N | |
| Soil & rooting depths | Plant available N, P, K, S | Potentially mineralizable N | |
| Soil available water & distribution Soil surface cover | Enzyme activity | ||
Calculation of Soil Health Index:
Soil health index (SHI) is calculated through the following steps.
i) Data screening : The data is reduced to minimum dataset (MDS) of soil health indicators through a series of uni- and multivariate statistical methods.
ii) Choosing representative variables: Standardized principal component analysis (PCA) is performed based on correlation matrix of replicated data for each statistically significant variable. The principal components receiving high eigen values and variables with high factor loadings with such components best represent system attributes and is retained for MDS.
iii) Reducing redundancy: Simple correlation coefficients among the screened variables after PCA is performed to determine strength of linear relationship among such variables. The uncorrelated, highly weighted variables and variable with highest correlation sum is the best representative of the group and, therefore retain in the MDS.
iv) MDS validation: Multiple regressions is done by using the final MDS components as the independent variables and each management-goal attribute (e.g., yield and its quality product) as a dependent variable to check the MDS representation of management system goals.
v) Indicator transformation (scoring): After determining the variables for the MDS, every observation of each MDS indicator is transformed for inclusion in the soil health index by using linear scoring technique.
vi) Indicator integration into indices: soil health index is calculated by the summation of the indicator scores multiplies by Principal components weightage factor from MDS indicators.
Soil health index:
n
SHI = SWi X Si
i=1
Where S= indicator score, W = Principal components weightage factor
The soil health indexes (SHI) are worked out for soils under different treatments and cropping systems in of long-term fertility experiments in India by different researchers.
Table 2. Soil health index (SHI) under different soil types and cropping systems (Mandal et al., 2005)
| Treatment/ centre | AAU | ANGRAU | BHU | CRIDA | CRIJAF | CRRI | OUAT | BCKV |
| Control | 2.27 | 0.92 | 1.63 | 0.95 | 1.04 | 2.77 | 0.31 | 2.78 |
| N | 2.60 | - | 1.48 | - | 1.38 | 2.91 | 0.35 | - |
| NP | 2.59 | - | - | 1.02 | 1.66 | 3.21 | 0.78 | - |
| NPK | 2.79 | 0.97 | 1.52 | - | 1.87 | 3.10 | 0.81 | 2.69 |
| NPK+ FYM | 2.84 | 2.00 | 1.87 | 1.27 | 2.10 | 4.00 | 1.13 | 3.63 |
Conclusion
Higher soil health index value represents better soil health status for sustainable production. In most of the experiments higher SHI values were found in soils cultivated with balanced use of NPK than those cultivated with the imbalanced ones. Again, values of such SHI were always higher with than without organics/FYM.
References:
1. Andrews, S.S. and Carroll, C.R. 2001. Designing a soil quality assessment tool for sustainable agro-ecosystem management. Ecological Applications 11, 1573-1585.
2. Doran, J.W. and Parkin, T.B. 1994. Defining and assessing soil quality. In: J. W. Doran, D. C. Coleman, D. F. Bezdicek, and B. A. Stewart (eds). Defining Soil Quality for a Sustainable Enviroment. Soil Science Society of America Spec. Publ. No. 35, Madison,Wisconsin, USA, pp. 3-21.
3. Doran, J.W., Sarrantonio, M. and Liebig, M.A. 1996. Soil health and sustainability. Advance in Agronomy 56, 1-54.
4. Karlen, D. L., Doran, J. W., Weinhold, B. J. and Andrews, S. S. 2003. Soil quality: Humankind's foundation for survival. Journal of Soil and Water Conservation 58.
5. Mandal, B., Ghoshal, S.K., Ghosh, S., Saha, S., Majumdar, D., Talukdar, N.C., Ghosh, T.J., Balaguravaiah, D., Vijay, S.B.M., Singh, A.P., Raha, P., Das,D.P., Sharma, K.L., Mandal, U.K., Kusuma, G.J., Chaudhury, J., Ghosh, H., Samantaray, R.N., Mishra, A.K., Rout, K.K., Behera, B.B. and Rout, B. (2005)Assessing soil quality for a few long term experiments â€" an Indian initiative. In: Proc. Intl. Conf. Soil, Water and Environ. Qual.-Issues and Challenges, New Delhi, Jan. 28-Feb. 1, 2005, pp. 25.
About Author / Additional Info:
WORKING AS A SCIENTIST IN ICAR-IARI