Nutrient imbalance and antagonistic interactions in calcareous soils severely constrain Phaseolus vulgaris (Pinto bean) productivity in semi-arid agroecosystems, where high soil pH, calcium carbonate dominance, and phosphorus fixation restrict nutrient availability and uptake efficiency. Conventional univariate diagnostic approaches often fail to capture these multielement interactions, resulting in inefficient fertilization strategies and yield instability. This study aimed to (i) establish the first integrated CND-DOP-PCA diagnostic framework for Pinto bean in semi-arid calcareous systems, (ii) identify novel critical thresholds (NBI = 200; CND-r2 = 14.33) beyond which yield declines accelerate by 34%, and (iii) elucidate mechanistic Fe-Cu-Mn antagonisms that constrain symbiotic nitrogen fixation under calcareous stress. A three-year field investigation (2022-2024) was conducted across 101 commercial farms in Fars Province, Iran. Leaf and soil samples were collected at flowering, and grain yield was measured at harvest. Multivariate nutrient models were integrated with principal component analysis to elucidate nutrient interaction patterns, while cubic regression analyses were applied to determine yield-critical nutrient thresholds. Severe deficiencies of phosphorus (91%), zinc (60%), iron (51%), and boron (38%) were identified, primarily driven by Ca-P precipitation and micronutrient antagonisms. Fields exhibiting a nutrient balance index greater than 200 produced 34% lower yields than nutritionally balanced systems. The CND approach explained 23% more yield variability than DOP and more effectively captured hidden antagonistic interactions among micronutrients. Overall, integrating region-specific CND diagnostics into precision fertilization programs improves nutrient-use efficiency, stabilizes yield under semi-arid stress, and supports sustainable intensification of legume-based food production in calcareous environments and climate-resilient agricultural systems.