Elucidating Elemental Fingerprints Of Vicia Narbonensis And Vicia Sativa Through Fuzzy Logic Modeling

Abstract

Mineral element concentrations in forage impact both plant physiology and livestock nutrition, shaping forage quality and animal health. This study investigates the elemental profiles of Vicia sativa and Vicia narbonensis using a fuzzy logic method. Concentrations of 12 chemical elements (including Ca, Mg, K, Fe, etc.) were measured in both species, and a Mamdani-type fuzzy inference system mapped their unique elemental signatures. The fuzzy logic approach allowed modeling of complex non-linear relationships and accounted for biological uncertainty. Results revealed clear differences in several major and trace elements between the species, identifying distinct elemental fingerprints. These findings suggest species-specific mineral uptake and regulation mechanisms, with nutrient levels in Vicia sativa and Vicia narbonensis determined by genetic factors and physiological adaptations to their environments.