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https://locus.ufv.br//handle/123456789/25481
Tipo: | Artigo |
Título: | Classification of macaw palm fruits from colorimetric properties for determining the harvest moment |
Autor(es): | Pinto, Francisco de A. de C. Motoike, Sérgio Y. Braga Júnior, Roberto A. Costa, Anderson G. Gracia, Luis M. Navas |
Abstract: | Macaw palm (Acrocomia aculeata) is a promising crop for biofuel production due to the high concentration of its fruit oil, but the harvest date is an issue to be better understood so it could be cultivated on an industrial scale. The aim of this study was to use the colorimetric properties of the macaw palm fruits to develop a neural network classifier to determine the ideal moment for harvesting, based on the oil content of the fruit mesocarp. During nine weeks of maturation were sampled 900 fruits of macaw palm fruits and the colorimetric properties of the RGB, HSI and CIELab color models were used to classify the fruits into immature and mature fruits. Kappa index and the overall accuracy values were used to access the classifier performance. The classifiers based on RGB parameters and on hue were considered equivalents having a Kappa index of 0.901 and 0.942, respectively, indicating the 59th week of maturation as the ideal time to harvest with the highest oil content. |
Palavras-chave: | Digital images Maturation Neural networks Oil content |
Editor: | Engenharia Agrícola |
Tipo de Acesso: | Open Access |
URI: | http://dx.doi.org/10.1590/1809-4430-eng.agric.v38n4p634-641/2018 http://www.locus.ufv.br/handle/123456789/25481 |
Data do documento: | Jul-2018 |
Aparece nas coleções: | Engenharia Agrícola - Artigos |
Arquivos associados a este item:
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artigo.pdf | Texto completo | 388,47 kB | Adobe PDF | Visualizar/Abrir |
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