Abstract
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.
Highlights
Agribusiness is one of the most important sectors of the Brazilian economy, representing about 20% of the Gross Domestic Product (GDP) in the last twenty years (CEPEA, 2015)
The present study aimed to develop a classifier using neural networks to distinguish green coffee fruits from cherry coffee fruits based on the detachment force, in order to determine the ideal moment to begin the mechanical harvest aiming at grain selectivity
Grains at the cherry stage substantially increased in the 1st and 2nd half of June (HJ), but dehydrated and dried fruits appeared in the 2nd HJ, which may reduce the quality of the coffee drink
Summary
Agribusiness is one of the most important sectors of the Brazilian economy, representing about 20% of the Gross Domestic Product (GDP) in the last twenty years (CEPEA, 2015). According to CONAB (2016), the Brazilian coffee production in 2016 was the highest one in its history, reaching a volume of 51.37 million 60 kg sacks of the processed product For this sector to continue being competitive and in economic growth, it is necessary to always use new strategies. Silva et al (2010) observed that coffee detachment force differs according to grain maturity stage, obtaining lower values for the cherry stage compared with the green stage. Such variation can be an important factor to perform a selective mechanical harvest. Such variation can be an important factor to perform a selective mechanical harvest. Silva et al (2013) concluded that fruit detachment force proved to be an objective parameter to indicate the starting moment of coffee selective harvest and a possible parameter for mechanical harvest management
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