<b>Fuzzy control systems for decision-making in cultivars recommendation

Abstract

ABSTRACT. The objective of the present study was to propose fuzzy control systems to support the recommendation of cultivars of different agronomic crops. Grain yield data from 23 lines and 2 cultivars of red bean were used to evaluate the applicability of these controllers. Genotypes were evaluated in nine environments in the Zona da Mata region, Minas Gerais State, Brazil. Using the parameters of Eberhart and Russell analysis, fuzzy controllers were developed with the Mamdani and Sugeno inference systems. Analyses of adaptability and stability were carried out by the method of Eberhart and Russell. The parameters obtained for each genotype were submitted to the respective controllers. There were significant genotypes x environments interaction, which justified the necessity of performing an adaptability and stability analysis. For both controllers (Mamdani and Sugeno), seven lines presented general adaptability, while only one presented adaptability to unfavorable environments. It was also found that both inference systems were useful for developing controllers that had the aim of recommending cultivars. Thus, it was noted that fuzzy control systems have the potential to identify the behavior of bean genotypes.Keywords: common bean; adaptability and stability; computational intelligence.Sistemas de controle fuzzy para tomada de decisão na recomendação de cultivares RESUMO. O presente estudo tem como objetivo propor sistemas de controle fuzzy para auxiliar na recomendação de cultivares de diversas culturas agronômicas. Para avaliar a aplicabilidade desses controladores foram utilizados dados de produtividade de grãos de 23 linhagens e duas cultivares de feijão do grupo comercial vermelho, avaliados em nove ambientes da Zona da Mata do Estado de Minas Gerais, Brasil. A partir dos parâmetros da análise de Eberhart e Russell foram desenvolvidos controladores fuzzy com sistemas de inferência Mamdani e Sugeno. Foram realizadas análises de variância conjunta e de adaptabilidade e estabilidade pelo método de Eberhart e Russell e os parâmetros obtidos para cada linhagem foram submetidos aos respectivos controladores. Verificou-se a ocorrência de interação genótipos por ambientes significativa, existindo a necessidade da realização de análises de adaptabilidade e estabilidade. Em ambos os controladores (Mamdani e Sugeno), sete linhagens (2, 9, 14, 16, 17, 20 e 23) apresentaram adaptabilidade geral, enquanto que somente a linhagem 15 apresentou adaptabilidade a ambientes desfavoráveis. Verificou-se também que ambos os sistemas de inferência adotados, são úteis para desenvolver controladores que visam recomendação de cultivares. Assim, constatou-se potencialidade dos sistemas de controle fuzzy na identificação do comportamento das linhagens de feijoeiro.Palavras-chave: feijão comum; adaptabilidade e estabilidade; inteligência computacional.

Fuzzy logic in automation for interpretation of adaptability and stability in plant breeding studies

“…v.76, n.2, p.123-129, March/April 2019 For the fuzzy controller adapted for both the Annicchiarico (1992) and the Cruz Torres and Vencovsky approach (1989), it was found that the classification of genotype stability and adaptability had been made correctly, according to the traditional interpretation of estimated parameters. The same was verified by Carneiro et al (2018), when using fuzzy controllers in genotype classification for adaptability and stability following the methods of Eberhart and Russell (1966) and Lin and Binns (1988) using grain yield data from experiments with bean genotypes evaluated in nine environments. The correct classification by the fuzzy controllers is due to the composition of the input and output linguistic variables, allowing for the operator's experience to be codified in rules, enabling the computer to interpret and provide accurate and useful information for decision making (Simões and Shaw, 2011).…”

“…However, when a substantial number of genotypes are evaluated, the interpretation of the parameters of adaptability and stability becomes laborious, requiring considerable time on the part of the breeder and can lead to misunderstandings. In this case, automation of genotype classification by fuzzy logic is a viable option (Carneiro et al, 2018).…”

“…In order to bring automation to the decision making process, two fuzzy controllers were developed, one for the Annicchiarico (1992) and a second for the Cruz et al (1989) method. The controllers were developed based on routines established in the R software (R Development Core Team, 2010), and all the algorithms used in this study have been presented by Carneiro et al (2018).…”

“…In spite of the importance of these methodologies, their parameters are difficult to interpret, especially when a considerable number of genotypes are involved, which makes selection work slow and decisions by breeders difficult to make. Therefore, the use of tools and strategies that can help make assertive decisions are indispensable to the success of breeding programs (Carneiro et al, 2018). In this context fuzzy logic invites consideration.…”

“…In the genetic improvement of plants, the fuzzy logic was applied by Carneiro et. al (2018) to the classification of cultivars regarding the adaptability and stability following the methods of Eberhart and Russell (1966).…”