Use of classifier to determine coffee harvest time by detachment force

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.

The best moment to carry out the selective harvest of coffee fruits

“…The strength of detachment of the fruits varies according to: the variety of coffee (da Silva et al., 2010, 2013; Santos et al., 2010), crop nutrition and soil water content (Silva et al., 2016), the altitude and location of the coffee plantation (Figueiredo et al., 2017), harvest year period (de Barros et al., 2018), and according to the solar incidence on the plant. Although there are already studies that base the selective harvest of coffee on maturation and detachment force per third of the plant (Kazama et al., 2021), the period of the day (TT) in which the harvest is carried out and the face of sun exposure of the plant were not explored as variables that can bring benefits to a selective harvest.…”