CONTROL OF THE COFFEE ROASTING STAGE USING ARTIFICIAL VISION TECHNIQUES

Juan Camilo Camilo Sarria-González, Eugenio Ivorra-Martínez, Joel Girón-Hernández

Abstract


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.


Keywords


variety Colombia, variety Castillo, visible spectrum

Full Text:

PDF

References


GARCÍA-LUNA, F.; MORALES-DÍAZ, A. Towards an artificial vision-robotic system for tomato identification. IFAC-PapersOnLine, v. 49, n. 16, p. 365-370, 2016.

doi.org/10.1016/j.ifacol.2016.10.067.

GELADI, P.; GRAHN, H. Multivariate Image Analysis. In Encyclopedia of Analytical Chemistry. Eds R. A. Meyers and R. A. Meyers. 2006. doi:10.1002/9780470027318.a8106

GIRÓN, J.; BARAT, J.; SÁNCHEZ, A.; GRAU, R. Aplicación de la espectrofotometría de infrarrojo (SW-NIR) para la clasificación de grasa de cerdos ibéricos. Agronomía Colombiana, Bogotá, v. 34 (1Supl.), p. S473-S476, 2016.

HERNÁNDEZ, J.; HEYD, B.; TRYSTRAM, G. Prediction of brightness and surface area kinetics during coffee roasting. Journal of Food Engineering, v. 89, n. 2, p. 156-163, 2008.

doi.org/10.1016/j.jfoodeng.2008.04.026.

IVORRA, E.; GIRÓN, J.; SÁNCHEZ, A.; VERDÚ, S.; BARAT, J.; GRAU, R. Detection of expired vacuum-packed smoked salmon based on PLS-DA method using hyperspectral images. Journal of Food Engineering, v. 117, 3, p. 342-349, 2013. doi.org/10.1016/j.jfoodeng.2013.02.022

IVORRA, E.; SÁNCHEZ, A.; VERDÚ, S.; BARAT, J.; GRAU, R. Shelf life prediction of expired vacuum-packed chilled smoked salmon based on a KNN tissue segmentation method using hyperspectral images. Journal of Food Engineering, v. 178, p. 110-116, 2016.

doi.org/10.1016/j.jfoodeng.2016.01.008.

LEE, L.; TAY, G.; CHEONG, M.; BIN, P.; LIU, S. Modulation of the volatile and non-volatile profiles of coffee fermented with Yarrowia lipolytica: II. Roasted coffee. LWT-Food Science and Technology, v. 80, p. 32-42, 2017. doi: 10.1016/j.lwt.2017.01.070

PICCARDI, M. "Background subtraction techniques: a review," IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), p. 3099-3104, 2004

PRATS-MONTALBÁN, J.; DE JUAN, A.; FERRER, A. Multivariate image analysis: A review with applications. Chemometrics and Intelligent Laboratory Systems, v. 107, (1), pp 1-23, 2011.

doi.org/10.1016/j.chemolab.2011.03.002.

Specialty coffee association SCAA. Grading Green Coffee, Specialty Coffee Association of America, USA, 2009. (September -2018).

SUN, X.; YOUNG, J.; LIU, J.; NEWMAN, D. Prediction of pork loin quality using online computer vision system and artificial intelligence model. Meat Science, v. 140, p 72-77, 2018.

doi.org/10.1016/j.meatsci.2018.03.005.

VALA. H.; ASTHA, B. A review on Otsu image segmentation algorithm. International Journal of Advanced Research in Computer Engineering and Technology, v. 2, n. 2, p. 387-389, 2013.

VERDÚ, S.; VÁSQUEZ, F.; IVORRA, E.; SÁNCHEZ, A.; BARAT, J.; GRAU, R. Hyperspectral image control of the heat-treatment process of oat flour to model composite bread properties. Journal of Food Engineering, v. 192, p. 45-52, 2017.

doi.org/10.1016/j.jfoodeng.2016.07.017.




DOI: http://dx.doi.org/10.25186/cs.v14i1.1517

Refbacks

  • There are currently no refbacks.