Knowledge and up-scaling of status, availability, and distribution of soil micronutrients are hugely significant for enhancing crop productivity and profitability. However, regional database entailing spatial variability of key micronutrients for a major apple-producing region like the Kashmir Himalayan Region (KHR) is missing. We investigated 588 topsoil samples between 2016 and 2017 (to 30 cm depth) to estimate spatial variability of extractable Zn, Cu, Mn, and Fe; develop spatial maps; and delineate potential management zones (MZs) in apple orchards using geo-statistical methods. Soil sampling was performed post-harvest season. Principal component analysis and fuzzy c-mean clustering were performed to develop MZs. Results exhibited wide variation, with high coefficient of variation (%) for Mn and Cu (123.9 and 114.4, respectively) and low (71.6) and medium (104) variability for Fe and Zn. Mean concentrations followed the order: Fe > Mn > Cu > Zn, with deficiencies evident towards central and northern regions of the study area. The best-fitted model was exponential. The nugget/sill ratio values were 0.41, 0.08, 0.37, and 0.38 for Zn, Cu, Mn, and Fe, respectively, indicating strong spatial dependence for Cu and moderate dependence for Fe, Zn, and Mn. Correlations between elevation, slope, and soil pH with micronutrients were negative, whereas with soil organic carbon and electrical conductivity positive relationships were identified. Three principal components accounted for 67·18% data variance. Based on the fuzzy performance index and modified partition entropy, five MZs were delineated, which exhibited variations from each other. These MZs highlighted the need for specific supplemental provisions in increasing soil fertility and apple productivity.
Keywords: Apple orchards; Geo-statistics; Management zone; Micronutrients; Spatial variability.
© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.