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.
|Translated title of the contribution||Control of the coffee roasting stage usingsi-gnzáz1artificial j vision techniques|
|Number of pages||5|
|Publication status||Published - 2019|