Fuzzy-Soft Modeling to Determine the Best Fertilizer for Lactuca sativa
L. Crop Considering Three Agronomic Variables
Himera Hamburguer1, Vicente Vergara-Fl´orez1, Kandy Ferrer Sotelo2, Osmin Ferrer Villar3,
Jos´e Sanabria3, ∗
1Universidad de Sucre, Facultad de Ingenier´ıa, Sincelejo, Colombia
2Universidad Pontificia Bolivariana, Facultad de Ingenier´ıas y Arquitectura, Monter´ıa, Colombia
3Universidad de Sucre, Facultad de Educaci´on y Ciencias, Sincelejo, Colombia Emails:
himerahamsa@gmail.com; viceunisucre@yahoo.com; kandy.ferrer@upb.edu.co;
osmin.ferrer@unisucre.edu.co; jose.sanabria@unisucre.edu.co
Abstract
Set-based theories have become key tools to address uncertainty and imprecision in complex systems. Fuzzy
sets model gradual membership, soft sets add flexibility through parameterization, and neutrosophic sets gen-
eralize both by incorporating truth, indeterminacy, and falsity degrees. In this manuscript, a fuzzy-soft expert
system is described to determine the efficiency of different fertilizations in lettuce (Lactuca sativa L.) crops
considering agronomic variables such as fresh weight (FW), number of leaves (NL), and crown diameter
(CD). The model, based on fuzzy membership functions and soft set operations, effectively manages the un-
certainty inherent in agricultural data and provides a novel decision-support tool. Although this work focuses
on fuzzy and soft sets, its extension to the neutrosophic framework could further enrich the analysis by ex-
plicitly modeling indeterminacy and inconsistency, offering a more comprehensive approach to agricultural
decision-making.
Keywords: Fuzzy set; Soft set; Biomass; Agriculture; Lattuce