Control of the Coffee Roasting Stage Using Artificial Vision Techniques

Abstract

<p>Artificial vision techniques were used to evaluate its application in the control of the coffee roasting stage. Coffee samples of Colombia and Castillo varieties were obtained and analyzed by comparing images during the roasting stage. A one-way ANOVA analysis exhibited 94.28% of similarity of the coffee varieties studied; a multivariate analysis showed significant differences (p<0.05) for the time factor and its interaction with the variety factor, no differences were observed (p>0.05) for the coffee varieties. Additionally, a Principal Component, with two components demonstrated 90.77% of the variance by differentiating the samples in the different roasting times. Therefore, the proposed technique could be used in the control of the coffee roasting stage.</p>

Computer vision techniques for modelling the roasting process of coffee (Coffea arabica L.) var. Castillo

“…In this respect, a number of studies have been conducted to optimise the coffee roasting step using image analysis, and many of these works are based on the infrared spectrum (Alessandrini et al 2008;De Luca et al 2016;Santos et al 2016a;Santos et al 2016b), which involves the use of expensive equipment. Other studies use inexpensive and easy to apply tools to monitor coffee roasting (Hernández et al 2008;Gabriel-Guzmán et al 2017;Sarria-González et al 2019) Most coffee roasting machines are designed to reach a temperature that remains constant in which coffee beans are heated at high temperatures (160-240 °C) for times ranging between 8 and 20 min depending on the desired characteristics of the final product (Fabbri et al 2011). Expert roasters use a set of auditory and sensory indicators and personal experience (Wieland et al 2012) to determine an appropriate time to obtain the perfect roasting degree, in which desirable characteristics are developed.…”