Geostatistically resolved PCA and fuzzy C-means clustering based delineation of multi-nutrient soil-fertility management zones for site-specific nutrient management in maize

Abstract Sustainable maize production in spatially heterogeneous smallholder fields requires nutrient recommendations that reflect within-field variation in soil fertility and its spatial structure, particularly where micronutrient constraints can coexist with adequate macronutrient supply. This study aimed to convert dense field-scale soil information into operational management zones (MZs) linked to soil-test target-yield fertilizer prescriptions, maize yield, and profitability in a farmer-managed field in the northern Deccan Plateau (Telangana, India). Two hundred georeferenced composite topsoil samples (0–15 cm) were analyzed for 11 indicators (pH, EC, OC, available N, P 2 O 5 , K 2 O, S, and DTPA-extractable Fe, Mn, Zn, Cu). After integrity checks and property-specific transformations, each attributes spatial dependence was modeled via semivariograms and mapped by ordinary kriging, standardized variables were reduced by PCA and clustered using fuzzy C-means with multi-index validation. All attributes showed strong spatial dependence (nugget to sill < 25%), with effective ranges of 24.99–41.22 m and cross-validation R 2 of 0.67–0.87. Variability was low for pH (CV 3.55%) but high for S and micronutrients (CV 34.17–48.78%). Correlations revealed a dominant positive fertility network (e.g., N–S r = 0.96; P 2 O 5 –K 2 O r = 0.93), while Zn opposed this gradient (e.g., Zn–pH r = − 0.81). PCA retained two components explaining 90.2% variance (PC1 86.9%), preserving the antagonistic Zn signal. Validity indices supported three contiguous MZs with significant interzone differences for all indicators ( p < 0.05) and within-zone CV reductions up to 35.30% (pH) and 28.87% (Zn), Zn decreased from 4.7 to 2.9 mg kg −1 from MZ-1 to MZ-3 despite higher macronutrients in MZ-3. Zone prescriptions rebalanced fertilization versus farmer practice (N 249–251 vs 175 kg ha −1 ; P 2 O 5 44–45 vs 60; K 2 O 78–82 vs 40), increasing yields to 70.42–74.14 vs 68.29 q ha⁻ 1 and improving profitability most in MZ-2 (net return ₹85,921 ha −1 ; B:C 2.58). The results show that an integrated geostatistical—PCA—fuzzy zoning framework can translate multivariate soil gradients into actionable nutrient decisions, while highlighting that enriched zones may still require micronutrient-specific diagnosis (Zn) and response validation through replicated trials.