Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-11210
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Main Title: Developing an Automatic Color Determination Procedure for the Quality Assessment of Mangos (Mangifera indica) Using a CCD Camera and Color Standards
Author(s): Ratprakhon, Khanitta
Neubauer, Werner
Riehn, Katharina
Fritsche, Jan
Rohn, Sascha
Type: Article
Language Code: en
Abstract: Color is one of the key sensory characteristics in the evaluation of the quality of mangos (Mangifera indica) especially with regard to determining the optimal level of ripeness. However, an objective color determination of entire fruits can be a challenging task. Conventional evaluation methods such as colorimetric or spectrophotometric procedures are primarily limited to a homogenous distribution of the color. Accordingly, a direct assessment of the mango quality with regard to color requires more pronounced color determination procedures. In this study, the color of the peel and the pulp of the mango cultivars “Nam Dokmai”, “Mahachanok”, and “Kent” was evaluated and categorized into various levels of ripeness using a charge-coupled device (CCD) camera in combination with a computer vision system and color standards. The color evaluation process is based on a transformation of the RGB (red, green, and blue) color space values into the HSI (hue, saturation, and intensity) color system and the Natural Color Standard (NCS). The results showed that for pulp color codes, 0560-Y20R and 0560-Y40R can be used as appropriate indicators for the ripeness of the cultivars “Nam Dokmai” and “Mahachanok”. The peels of these two mango cultivars present two distinct colors (1050-Y40R and 1060-Y40R), which can be used to determine the fruit maturity during the post-ripening process. However, in the case of the cultivar “Kent”, peel color detection was not an applicable approach for determining ripeness; thus, the determination of the pulp color with the color code 0550-Y20R gave promising results.
URI: https://depositonce.tu-berlin.de/handle/11303/12370
http://dx.doi.org/10.14279/depositonce-11210
Issue Date: 21-Nov-2020
Date Available: 7-Jan-2021
DDC Class: 540 Chemie und zugeordnete Wissenschaften
Subject(s): mango color
CCD camera
computer vision system
NCS color standard
License: https://creativecommons.org/licenses/by/4.0/
Journal Title: Foods
Publisher: MDPI
Publisher Place: Basel
Volume: 9
Issue: 11
Article Number: 1709
Publisher DOI: 10.3390/foods9111709
EISSN: 2304-8158
Appears in Collections:FG Lebensmittelchemie und Analytik » Publications

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