SOIL QUALITY ASSESSMENT AND ITS VARIATION IN RELATION TO RICE CROP PRODUCTIVITY IN MAHABUBNAGAR DISTRICT OF TELANGANA STATE
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Date
2024-03-11
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PROFFESSOR JAYASHANKAR TELANGANA STATE AGRICULTURAL UNIVERSITY
Abstract
Soil quality is the integrated effect of management on most soil properties that
determine agricultural crop productivity and sustainability. The present investigation was
undertaken for assessing the soil quality of high (HPRS), medium (MPRS) and low
(LPRS) productive rice soils of Mahabubnagar district to establish the Minimum Data Set
(MDS) of soil quality indicators and discriminate the variation in productivity areas. A
total of 225 samples, comprising 75 from each category (HPRS, MPRS, LPRS), were
meticulously collected before transplanting for rabi season, 2022-2023 using stratified
random sampling method. Twenty-four soil parameters encompassing physical [soil
texture (sand, silt, clay %), BD, MWHC], chemical [(pH, EC, SOC, TC, available N,
P2O5, K2O, S, Cu, Mn, Fe, Zn, exchangeable cations (Caex, Mgex, Naex and Kex)], and
biological (DHA, ACP, ALP) parameters were determined. For biological analysis, fresh
soil samples were collected. The Karl-Pearson correlation analysis unveiled significant
correlations among the soil properties at both the 0.05 and 0.01 significance levels.
Further scrutiny through one-way ANOVA highlighted the significance of soil properties
(P ≤ 0.05) namely clay content, BD, MWHC, EC, SOC, avail. N, S, Zn, Caex, Mgex, Naex,
Kex, DHA, ALP as the distinguishing soil characteristics among the three rice productivity
soils. The Tukey’s Honestly Significant Different test indicated that under LPRS; BD,
EC and Naex were significantly higher than HPRS; whereas MWHC, SOC, avail. N, Zn,
Kex, DHA, ALP were significantly lower than HPRS and clay content, Avail. S, Caex,
Mgex were significantly lower than HPRS and MPRS. Remarkably, HPRS showed
markedly superior soil characteristics like lower BD, EC, and Naex coupled with higher
clay content, MWHC, SOC, available N, S, Zn, exchangeable cations and improved DHA
and ALP activity than those of LPRS. The fourteen attributes having significant
differences underwent principal component analysis (PCA), revealing that the first five
PCs (eigen value ≥1) accounted for 72.40 % of the total variance. The resulting MDS
included SOC in PC1, Caex in PC2, EC in PC3, Naex in PC4 and Avail. Zn in PC5. The
respective weighing factors for PCs are 0.445, 0.224, 0.124, 0.107 and 0.100 for PC5.
The contribution of retained MDS variables followed the order: SOC (44.5 %) > Caex
(22.4 %) > EC (12.4 %) > Naex (10.7 %) > Avail. Zn (10.0 %). Discriminant analysis
identified clay content, BD, avail. S, avail. Zn, Caex, Mgex, Naex and ALP as the
discriminating soil quality indicators between HPRS, MPRS, and LPRS, particularly
highlighting distinctive features of LPRS. After scoring and weighting for the retained
MDS indicators, soil quality index (SQI) was calculated that showed varying mean ± SD
for HPRS (0.61 ± 0.10), MPRS (0.56 ± 0.10), and LPRS (0.48 ± 0.08). A significant
correlation was observed between SQI and farmer’s rice yields of the three rice
productivity soils. The relation between MDS (independent variable) and rice yields
(dependent variable) tested using step-wise regression analysis inferred that all the five
MDS significantly correlated the yield (R2 = 0.76) and of them; SOC, Caex, Avail. Zn
exhibited positive correlations, while EC and Naex displayed negative correlations with
the rice yields and explained 76 % variation. The remaining 24 % variation is explained
by the soil properties which were dropped and not considered in the study.
The findings underscore the critical role of soil quality assessment in shaping
sustainable land use management and enhancing grain yield, particularly addressing the
constraints associated with low SOC, Caex, Avail. Zn, and elevated EC and Naex in LPRS.