文章基本信息

标题：Computer vision techniques for modelling the roasting process of coffee ( Coffea arabica L.) var. Castillo
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作者：Eugenio Ivorra ; Juan Camilo Sarria-González ; Joel Girón-Hernández 等
期刊名称：Czech Journal of Food Sciences
印刷版ISSN：1212-1800
电子版ISSN：1805-9317
出版年度：2020
卷号：38
期号：6
页码：388-396
DOI：10.17221/346/2019-CJFS
出版社：Czech Academy of Agricultural Sciences
摘要：Artificial vision has wide-ranging applications in the food sector; it is easy to use, relatively low cost and allows to conduct rapid non-destructive analyses. The aim of this study was to use artificial vision techniques to control and model the coffee roasting process. Samples of Castillo variety coffee were used to construct the roasting curve, with captured images at different times. Physico-chemical determinations, such as colour, titratable acidity, pH, humidity and chlorogenic acids, and caffeine content, were investigated on the coffee beans. Data were processed by (i) Principal component analysis (PCA) to observe the aggrupation depending on the roasting time, and (ii) partial least squares (PLS) regression to correlate the values of the analytical determinations with the image information. The results allowed to construct robust regression models, where the colour coordinates (L*, a*), pH and titratable acidity presented excellent values in prediction (R2Pred 0.95, 0.91, 0.94 and 0.92). The proposed algorithms were capable to correlate the chemical composition of the beans at each roasting time with changes in the images, showing promising results in the modelling of the coffee roasting process.
关键词：Colombian coffee; visible spectrum; image processing; chemical composition