Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6402748 | LWT - Food Science and Technology | 2014 | 7 Pages |
Abstract
The aim of this research was to design, implement and calibrate a Computer Vision System (CVS), for use in real-time, in order to measure the color on minimally processed yacon slices. For this purpose, a device (software and hardware) was designed and implemented which consisted of two steps: a) image acquisition and b) image processing and analysis. For both, an algorithm and a graphical user interface (GUI) were developed in MatLab. CVS calibration was performed with a conventional colorimeter (Model CIE L*a*b*). Minimally processed yacon slices were obtained and stored at 5 °C. Color changes were estimated every 2 h, for 26 h, obtaining its color parameters. L* decreased from 65.9 to 60.8, with a tendency to a black color; a* increased from 7.3 to 17.7, approaching a red color; b* increased from 35.1 to 41.5, presenting a tendency to a yellow color. Moreover, C* increased from 35.9 to 40.1, H* decreased from 78.2 to 66.9 and ÎE* increased from 2.6 to 13.2. Low errors calculated (eL* = 5.001%, and ea* = 2.287%, and eb* = 4.314%) ensure suitable and efficient application in industrial process automation and quality control in the food industry.
Keywords
Related Topics
Life Sciences
Agricultural and Biological Sciences
Food Science
Authors
Erick Saldaña, Raúl Siche, Wilson Castro, Rosmer Huamán, Roberto Quevedo,