Assessment of spatial variability in soil and leaf nutrients of mango orchards using geostatistical and multivariate...

Effective nutrient management in fruit orchards necessitates a comprehensive understanding of the spatial variability of both soil and leaf nutrients. This study aimed to assess the spatial distribution of soil fertility parameters and mango leaf nutrient concentrations across 57 orchards in the Bilaspur district of Himachal Pradesh, employing geostatistical techniques and principal component analysis (PCA). Composite soil samples were collected at two depths: surface (0-20 cm) and sub-surface (20-40 cm), along with corresponding leaf samples and analyzed for macro and micronutrient contents. Descriptive statistics revealed substantial variability, particularly in available P (CV: 39.27%), K (55.16%), Fe (47.59%), and Cu (44.16%). Semivariogram modeling indicated strong spatial dependence for soil pH, EC, and P, and for leaf P, K, Fe, and Mn, with nugget-to-sill ratios below 0.25. Spatial distribution maps generated through kriging revealed significant heterogeneity in both soil and leaf nutrient contents. Leaf Mg showed extremely high variability (CV: 124.84%), highlighting localized nutritional imbalances. PCA extracted four principal components at each depth, collectively explaining over 56.20% (surface) and 55.70% (sub-surface) of the total variance, with high loadings for K, Fe, S, Zn, and N. Pearson correlation analysis revealed significant associations between soil and leaf nutrients, notably available S with leaf K (r = 0.45) and soil organic carbon with leaf Mn (r = 0.31**). These findings highlight the pronounced spatial heterogeneity of nutrient distribution in mango orchards and underscore the critical need for depth and site-specific nutrient management strategies. Integrating spatial analysis with nutrient diagnostics can optimize input use, enhance mango yield and quality, and support the sustainable management of soil fertility in orchard ecosystems.