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Prediction of ‘Gigante’ cactus pear yield by morphological characters and artificial neural networks AGRIAMBI
Guimarães,Bruno V. C.; Donato,Sérgio L. R.; Azevedo,Alcinei M.; Aspiazú,Ignacio; Silva Junior,Ancilon A. e.
ABSTRACT Estimating cactus pear yield is important for the planning of small and medium rural producers, especially in environments with adverse climatic conditions, such as the Brazilian semi-arid region. The objective of this study was to evaluate the potential of artificial neural networks (ANN) for predicting yield of ‘Gigante’ cactus pear, and determine the most important morphological characters for this prediction. The experiment was conducted in the Instituto Federal Baiano, Guanambi campus, Bahia, Brazil, in 2009 to 2011. The area used is located at 14° 13’ 30” S and 42° 46’ 53” W, and its altitude is 525 m. Six vegetative agronomic characters were evaluated in 500 plants in the third production cycle. The data were subjected to ANN analysis using...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Yield estimation; Artificial logic; Production; Opuntia fícus indica.
Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662018000500315
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