Computational Multivariate Framework for Assessing Agricultural Carbon Emissions across Crop, Soil and Fertilizer Management Factors
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Abstract
Agricultural carbon emissions reflect the combined influence of crop characteristics, soil conditions and input-management decisions. This study integrates two complementary descriptive analyses: (i) the association between chemical versus organic fertilizer treatment and carbon emissions, and (ii) the three-way structure of crop type × soil type × fertilizer-loss level. The supplied dataset contains 45 crop–soil–loss combinations covering citrus, corn, rice, vegetable and wheat; clay, loamy and sandy soils; and low, medium and high fertilizer-loss levels. Total CO₂e is the principal outcome. The results show a highly consistent monotonic increase in Total CO₂e from low to medium to high fertilizer loss across every crop–soil combination. Mean Total CO₂e is approximately 232.63 at low loss, 282.25 at medium loss and 331.97 at high loss, giving an average low-to-high difference of about 99.34 CO₂e units. Rice has the highest crop-wise average, while vegetables have the lowest. Mean differences among clay, loamy and sandy soils are comparatively small, and soil rankings vary across combinations. The fertilizer-treatment analysis additionally reports lower emission values under organic fertilizer than chemical fertilizer across the crops examined; the difference is largest in absolute terms for the higher-emission crops, particularly rice and corn. These findings identify fertilizer-loss management, nutrient-use efficiency and context-sensitive fertilizer selection as important dimensions of low-carbon agricultural management. The study is descriptive and associative; it does not establish causality or statistical significance. Future research should apply factorial models, uncertainty analysis and field-validated life-cycle emission measurements.
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