Harnessing fuzzy logic for adaptive and stable selection of upland rice lines

Abstract Fuzzy logic enables automated decision-making and classifies genotype suitability across environments. This study assessed the adaptability and stability of upland rice genotypes using fuzzy logic. To do so, eight lines from the Federal University of Goiás, 10 from the Federal University of Lavras, and two commercial cultivars were evaluated for grain yield, plant height, and flowering days in 13 environments in Goiás. The trials used a randomized complete block design with three replications. Adaptability and stability were analyzed using fuzzy controllers, which classified genotypes into four groups: general adaptability, poorly adapted, favorable, and unfavorable environments. The CSD 08004 line exhibited broad adaptability and stability for yield and plant height and was close to general adaptability for flowering days, making it suitable for cultivation in Goiás.