TAILIEUCHUNG - A comparative study of fuzzy linear regression and multiple linear regression in agricultural studies: a case study of lentil yield management

This study investigates the advantages of two fuzzy linear regression (FLR) models, namely the Tanaka and the Savic and Pedrycz models, over multiple linear regression (MLR) for lentil yield management. We used a fuzzy approach to model the yield of lentil genotypes in which the input is crisp and the output fuzzy. | Turkish Journal of Agriculture and Forestry Research Article Turk J Agric For (2018) 42: 402-411 © TÜBİTAK doi: A comparative study of fuzzy linear regression and multiple linear regression in agricultural studies: a case study of lentil yield management 1, 2 3 Karim SORKHEH * , Ahmad KAZEMIFARD , Shakiba RAJABPOOR Department of Agronomy and Plant Breeding, Faculty of Agriculture, Shahid Chamran University of Ahvaz, Ahvaz, Iran 2 Department of Mathematics, Faculty of Mathematics and Computer Science, Shahid Chamran University of Ahvaz, Ahvaz, Iran 3 Department of Biology, Payme-Noor University, Tehran, Iran 1 Received: Accepted/Published Online: Final Version: Abstract: This study investigates the advantages of two fuzzy linear regression (FLR) models, namely the Tanaka and the Savic and Pedrycz models, over multiple linear regression (MLR) for lentil yield management. We used a fuzzy approach to model the yield of lentil genotypes in which the input is crisp and the output fuzzy. Moreover, after finding FLR equations, we estimated the output corresponding to the collection of fuzzy inputs by using fuzzy algebraic operations and an appropriate defuzzification method known as the center of area method. Results showed the superiority of the Tanaka model over MLR because of reducing the included variables, especially variables available after harvest. The study also emphasizes the advantage of the Savic and Pedrycz model in comparison to the other two models with a smaller error rate. Key words: Fuzzy linear regression, multiple linear regression, Lens culinaris 1. Introduction For millennia, human beings have been aware of the importance of agricultural products in their life and have benefited from plants and their different parts like fruits, leaves, and seeds, for food, clothing, medicine, and animal feed (Ercisli, 2009; Erturk et al., 2010; Canan et al.,

• Nông nghiệp
• Lntil yield management
• Fuzzy linear regression
• Multiple linear regression
• Lens culinaris
• Pedrycz models
• Lentil genotypes
• Agricultural science
• Molecular some lentil
• Biochemical markers in some lentil
• SDS–PAGE and ISSR
• Yield and its attributes
• Drought tolerance
• Geometric mean productivity
• Some lentil genotypes
• Context of drought tolerance indices
• Genetic variability
• Genetic advance
• Genetic variability of lentil
• Genotypes in acidic soil
• Acidic soi
• Seed traits
• Variability in seed parameters
• Germination allied enzymes
• Association analysis
• Physical properties
• Water absorption capacity
• Seedling vigour index
• Bulk density