SOIL HEALTH STUDY OF DIFFERENT SOIL TYPES UNDER PROMINENT CROPPING SYSTEMS OF BIHAR
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Date
2022
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Dr.RPCAU, Pusa
Abstract
There are many factors that contribute to soil health, including physical, chemical,
and biological factors. Some of them are dynamic in nature and behave differently
based on the agro-ecological zone in which they occur and therefore are quantified
using a soil health index (SHI), which measures the soil health in various agroecological
zones (ACZs). A study entitled “SOIL HEALTH STUDY OF
DIFFERENT SOIL TYPES UNDER PROMINENT CROPPING SYSTEMS OF
BIHAR” was conducted at the Department of Soil Science, Dr. Rajendra Prasad
Central Agricultural University Pusa (Bihar) with the objective to evaluate the
variability in soil health parameters, minimum data sets (MDSs) to construct a soil
health index (SHI) and correlation and regression to find out the direct determinants
yield which will be useful in evaluating the sustainability of crops in different agroecological
zones of Bihar, under rice-wheat and rice-maize cropping systems
including four different ACZs, namely Sitamarhi (ACZ-I), Saharsa (ACZ-II), Banka
(ACZ-IIIA) and Rohtas (ACZ-IIIB). Based on the properties of the surface soil layer
(0-15 cm) that were measured by Comprehensive Assessment of Soil Health (CASH),
20 parameters were utilized to develop the soil heath index (SHI). Under R-W and RM
cropping system a wide range of variations were observed in soil properties in
surface soil samples that was found by descriptive analysis. Pearson’s correlation
studies revealed that strong significant correlation among SOC, available N, available
P2O5, WAS, AWC, sand content, soil respiration and system yield (R-W and R-M).
Stepwise regression analyses showed that under the R-M cropping systems, the key
soil properties like SOC and available N were the main determinants for R-M system
yield in all the four ACZs, available K2O in ACZ-I and II, WAS in ACZ-I and IIIA
and AWC in ACZ-IIIB. However, stepwise regression analyses showed that under the
R-W cropping system also SOC and available N were the main soil determinants for
R-W system yield in all the four ACZs, along with available P2O5 in ACZ-I and II,
Clay in ACZ-I, IIIA and IIIB and soil respiration in ACZ-IIIB. A scoring function
(non-linear) was used to convert each indicator of the MDS into a dimensionless score
which in turn was integrated into four separate SHIs based on scoring functions (nonlinear).
Soil health index (SHI) of R-M system showed that the overall SHI varied
from 0.41-0.49. The highest SHI was found in Rohtas (0.49) followed by Saharsa
(0.48). Among all the soil health parameters SOC, available N, available P2O5,
available K2O, available S, soil respiration and AWC were the main contributor for
the SHI. Maximum contribution was found for SOC is 13.50% in Sitamarhi (ACZ-I)
followed by 12.50% in Saharsa (ACZ-II). Soil health index (SHI) of R-W system
revealed that the overall SHI varied from 0.43-0.51. The highest SHI was found in
Rohtas (0.51) followed by Sitamarhi (0.50). Maximum contribution was found for
SOC is 15 % in Rohtas (ACZ-IIIB) followed by 14 % in Sitamarhi (ACZ-I).
Quantitative predictive relationship between R-W and R-M system yield and SHI
showed a positive correlation. The results demonstrated that R2 values are 0.79, 0.54,
0.65 and 0.76 in R-W system and 0.70, 0.62, 0.65 and 0.64 in R-M system for Rohtas,
Banka, Saharsa and Sitamarhi respectively. On the basis of this index, it was
determined that prominent cropping systems were able to be used to quantify soil
health under four different ACZs. Based on this result, it was determined what would
be the most suitable cropping system. Thus, it can be concluded that SHI can be used
as a tool for quantifying soil health to a satisfactory level. Based on the variability
observed across 20 soil health indicators across two prominent cropping systems
under four different agro-climatic zones (ACZs) of Bihar, this study provides a
framework for the quantitative assessment of soil health throughout four ACZs. It also
helps to identify which cropping system for a given ACZ is the most suitable among
existing cropping systems carried out in a particular ACZ.