Data/hora: 02/06/2024 19:01:33

Provedor de dados: | 91
País: | Brazil
Título: | Use of classifier to determine coffee harvest time by detachment force
Autores: | Barros,Murilo M. de; Silva,Fábio M. da; Costa,Anderson G.; Ferraz,Gabriel A. e S.; Silva,Flávio C. da.
Data: | 2018-05-01
Ano: | 2018
Palavras-chave: | Coffee cultivation; Management; Maturation; Supervised classifiers.
Resumo: | ABSTRACT Coffee quality is an essential aspect to increase its commercial value and for the Brazilian coffee business to remain prominent in the world market. Fruit maturity stage at harvest is an important factor that affects the quality and commercial value of the product. Therefore, the objective of this study was to develop a classifier using neural networks to distinguish green coffee fruits from mature coffee fruits, based on the detachment force. Fruit detachment force and the percentage value of the maturity stage were measured during a 75-day harvest window. Collections were carried out biweekly, resulting in five different moments within the harvest period. A classifier was developed using neural networks to distinguish green fruits from mature fruits in the harvest period analyzed. The results show that, in the first half of June, the supervised classified had the highest success percentage in differentiating green fruits from mature fruits, and this period was considered as ideal for a selective harvest under these experimental conditions.
Tipo: | Info:eu-repo/semantics/article
Idioma: | Inglês
Identificador: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662018000500366
Editor: | Departamento de Engenharia Agrícola  - UFCG
Relação: | 10.1590/1807-1929/agriambi.v22n5p366-370
Formato: | text/html
Fonte: | Revista Brasileira de Engenharia Agrícola e Ambiental  v.22 n.5 2018
Fonte: | info:eu-repo/semantics/openAccess