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	Provedor de dados Agronomy (2) Bragantia (2) Scientia Agricola (1) AGRIAMBI (1) Autor Azevedo,Alcinei Mistico (3) Carneiro, Vinícius Quintão (2) Cruz, Cosme Damião (2) Santos, Iara Gonçalves dos (2) Silva Junior, Antônio Carlos da (2) Soares, Plínio César (2) Andrade Júnior,Valter Carvalho de (1) Aquino,César Fernandes (1) Carneiro,Anna Regina Tiago (1) Cruz,Cosme Damião (1) Damasceno,Flavio A. (1) Dornas,Marcus Flavius Silva (1) Ferraz,Gabriel A. e S. (1) Ferraz,Patrícia F. P. (1) Hernandez-Julio,Yamid F. (1) Melo,Leonardo Cunha (1) Oliveira,Celso Mattes de (1) Pedrosa,Carlos Enrrik (1) Pereira,Helton Santos (1) Salomão,Luiz Carlos Chamhum (1) Mais... Palavra-chave Computational intelligence (6) Clustering technique (2) Oriza sativa L. (2) Broiler (1) Colorimetric parameters (1) Common bean (1) Crop breeding (1) Gain selection (1) Genotype by environment interaction (1) Genética melhoramento de plantas (1) Lactuca sativa (1) Multi-layer-perceptron (1) Multilayer perceptro (1) Musa spp. (1) Phenomic (1) Physiological responses (1) Plant breeding (1) SOM. (1) SOM. Genética melhoramento de plantas (1) Mais... Tipo do documento Info:eu-repo/semantics/article (6) Ano 2019 (1) 2018 (3) 2016 (1) 2015 (1) País Brazil (6) Idioma Inglês (6)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 6 Primeira ... 1 ... Última Application of artificial neural networks in indirect selection: a case study on the breeding of lettuce Bragantia Azevedo,Alcinei Mistico; Andrade Júnior,Valter Carvalho de; Pedrosa,Carlos Enrrik; Oliveira,Celso Mattes de; Dornas,Marcus Flavius Silva; Cruz,Cosme Damião; Valadares,Nermy Ribeiro. The efficiency of artificial neural networks (ANN) to model complex problems may enable the prediction of characteristics that are hard to measure, providing better results than the traditional indirect selection. Thus, this study aimed to investigate the potential of using artificial neural networks (ANN) for indirect selection against early flowering in lettuce, identify the influence of genotype by environment interaction in this strategy and compare your results with the traditional indirect selection. The number of days to anthesis were used as the desired output and the information of six characteristics (fresh weight of shoots, mass of marketable fresh matter of shoots, commercial dry matter of shoots, average diameter of the head, head... Tipo: Info:eu-repo/semantics/article Palavras-chave: Lactuca sativa; Multi-layer-perceptron; Gain selection; Plant breeding; Computational intelligence. Ano: 2015 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052015000400387 Fuzzy logic in automation for interpretation of adaptability and stability in plant breeding studies Scientia Agricola Carneiro,Anna Regina Tiago; Sanglard,Demerson Arruda; Azevedo,Alcinei Mistico; Souza,Thiago Lívio Pessoa Oliveira de; Pereira,Helton Santos; Melo,Leonardo Cunha. ABSTRACT: The methods of Annicchiarico (1992) and Cruz et al. (1989) are widely used in phenotypic adaptability and stability analyses in plant breeding. In spite of the importance of these methodologies, their parameters are difficult to interpret. The aim of this research was to develop fuzzy controllers to automate the decision-making process employed by adaptability and stability studies following the methods adopted by Annicchiarico (1992) and Cruz et al. (1989) and check their efficiency using experimental data from common bean cultivars. Fuzzy controllers have been developed based on the Mamdani inference system proposed by these two methods of adaptability and stability studies. For the first fuzzy controller parameters were considered favorable... Tipo: Info:eu-repo/semantics/article Palavras-chave: Common bean; Genotype by environment interaction; Crop breeding; Computational intelligence. Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162019001200123 Genetic fuzzy system for prediction of respiratory rate of chicks subject to thermal challenges AGRIAMBI Ferraz,Patrícia F. P.; Yanagi Junior,Tadayuki; Hernandez-Julio,Yamid F.; Ferraz,Gabriel A. e S.; Silva,Maria A. J. G.; Damasceno,Flavio A.. ABSTRACT The aim of this study was to estimate and compare the respiratory rate (breath min-1) of broiler chicks subjected to different heat intensities and exposure durations for the first week of life using a Fuzzy Inference System and a Genetic Fuzzy Rule Based System. The experiment was conducted in four environmentally controlled wind tunnels and using 210 chicks. The Fuzzy Inference System was structured based on two input variables: duration of thermal exposure (in days) and dry bulb temperature (°C), and the output variable was respiratory rate. The Genetic Fuzzy Rule Based System set the parameters of input and output variables of the Fuzzy Inference System model in order to increase the prediction accuracy of the respiratory rate values. The two... Tipo: Info:eu-repo/semantics/article Palavras-chave: Broiler; Computational intelligence; Physiological responses. Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662018000600412 High-efficiency phenotyping for vitamin A in banana using artificial neural networks and colorimetric data Bragantia Aquino,César Fernandes; Salomão,Luiz Carlos Chamhum; Azevedo,Alcinei Mistico. ABSTRACT Banana is one of the most consumed fruits in Brazil and an important source of minerals, vitamins and carbohydrates for human diet. The characterization of banana superior genotypes allows identifying those with nutritional quality for cultivation and to integrate genetic improvement programs. However, identification and quantification of the provitamin carotenoids are hampered by the instruments and reagents cost for chemical analyzes, and it may become unworkable if the number of samples to be analyzed is high. Thus, the objective was to verify the potential of indirect phenotyping of the vitamin A content in banana through artificial neural networks (ANNs) using colorimetric data. Fifteen banana cultivars with four replications were evaluated,... Tipo: Info:eu-repo/semantics/article Palavras-chave: Musa spp.; Colorimetric parameters; Computational intelligence; Multilayer perceptro; Phenomic. Ano: 2016 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052016000300268 Self-organizing maps in the study of genetic diversity among irrigated rice genotypes Agronomy Santos, Iara Gonçalves dos; Carneiro, Vinícius Quintão; Silva Junior, Antônio Carlos da; Cruz, Cosme Damião; Soares, Plínio César. This study presents self-organizing maps (SOM) as an alternative method to evaluate genetic diversity in plant breeding programs. Twenty-five genotypes were evaluated in two environments for 11 phenotypic traits. The genotypes were clustered according to the SOM technique, with variable topology and numbers of neurons. In addition to the SOM analysis, unweighted pair group method with arithmetic mean clustering (UPGMA) was performed to observe the behavior of the clustering when submitted to these techniques and to evaluate their complementarities. Genotype ordering according to SOM was consistent with UPGMA results, evidenced by the basic structure of UPGMA groups being preserved in each group of the maps. Regarding genotype arrangement and the group... Tipo: Info:eu-repo/semantics/article Palavras-chave: Oriza sativa L.; Computational intelligence; Clustering technique; SOM.; Genética melhoramento de plantas. Ano: 2018 URL: http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/39803 Self-organizing maps in the study of genetic diversity among irrigated rice genotypes Agronomy Santos, Iara Gonçalves dos; Carneiro, Vinícius Quintão; Silva Junior, Antônio Carlos da; Cruz, Cosme Damião; Soares, Plínio César. This study presents self-organizing maps (SOM) as an alternative method to evaluate genetic diversity in plant breeding programs. Twenty-five genotypes were evaluated in two environments for 11 phenotypic traits. The genotypes were clustered according to the SOM technique, with variable topology and numbers of neurons. In addition to the SOM analysis, unweighted pair group method with arithmetic mean clustering (UPGMA) was performed to observe the behavior of the clustering when submitted to these techniques and to evaluate their complementarities. Genotype ordering according to SOM was consistent with UPGMA results, evidenced by the basic structure of UPGMA groups being preserved in each group of the maps. Regarding genotype arrangement and the group... Tipo: Info:eu-repo/semantics/article Palavras-chave: Oriza sativa L.; Computational intelligence; Clustering technique; SOM. Genética melhoramento de plantas. Ano: 2018 URL: http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/39803 Registros recuperados: 6 Primeira ... 1 ... Última

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