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Artificial neural network for prediction of the area under the disease progress curve of tomato late blight Scientia Agricola
Alves,Daniel Pedrosa; Tomaz,Rafael Simões; Laurindo,Bruno Soares; Laurindo,Renata Dias Freitas; Silva,Fabyano Fonseca e; Cruz,Cosme Damião; Nick,Carlos; Silva,Derly José Henriques da.
ABSTRACT: Artificial neural networks (ANN) are computational models inspired by the neural systems of living beings capable of learning from examples and using them to solve problems such as non-linear prediction, and pattern recognition, in addition to several other applications. In this study, ANN were used to predict the value of the area under the disease progress curve (AUDPC) for the tomato late blight pathosystem. The AUDPC is widely used by epidemiologic studies of polycyclic diseases, especially those regarding quantitative resistance of genotypes. However, a series of six evaluations over time is necessary to obtain the final area value for this pathosystem. This study aimed to investigate the utilization of ANN to construct an AUDPC in the...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Phytophthora infestans; ANN; AUDPC; Artificial intelligence; Plant breeding.
Ano: 2017 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162017000100051
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