Classification of Cocoa Beans Based on their Level of Fermentation using Spectral Information
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| Natura: | Artículo científico |
| Lingua: | en |
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Instituto Tecnológico Metropolitano
2021
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| _version_ | 1876483794037374976 |
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| author | Karen Sánchez |
| author_facet | Karen Sánchez |
| contents | Classification of Cocoa Beans Based on their Level of Fermentation using Spectral Information Karen Sánchez Jorge Bacca Laura Arévalo-Sánchez Henry Arguello Sergio Castillo Ingeniería superpixel Cocoa beans hyperspectral images level of fermentation spectral classification Cocoa beans are the most important raw material for the chocolate industry and an essential product for the economy of tropical countries such as Colombia. Their price mainly depends on their quality, which is determined by various aspects, such as good agricultural practices, their harvest point, and level of fermentation. The entities that regulate the international marketing of cocoa beans have been encouraging the development of new classification methods that, compared to current techniques, could save time, reduce waste, and increase the number of evaluated beans. In particular, hyperspectral images are a novel tool for food quality control. However, studies that have examined some quality parameters of cocoa using spectroscopy also involve the chemical evaluation of cocoa powder and liquor and the interior of the beans, which implies an invasive analysis, longer times, and waste generation. Therefore, in this paper, we assess the quality of cocoa beans based on their level of fermentation using a noninvasive system to obtain hyperspectral information, as well as fast image processing and spectral classification techniques. We obtained hyperspectral images of 90 cocoa beans in the range between 350 and 950 nm in an optical laboratory. In addition, each cocoa bean was classified according to its fermentation level: slightly fermented (SF), correctly fermented (CF), and highly fermented (HF). We compared this classification with that carried out by experts from the Colombia National Federation of Cocoa Growers and reported in the Colombian technical standard No. 1252. The results show that the level of fermentation of dried cocoa beans can be estimated using noninvasive hyperspectral image acquisition and processing techniques. 2021 artículo científico 0123-7799 https://www.redalyc.org/articulo.oa?id=344264813021 https://www.redalyc.org/journal/3442/344264813021/ https://www.redalyc.org/journal/3442/344264813021/html/ https://www.redalyc.org/journal/3442/344264813021/344264813021.epub https://www.redalyc.org/journal/3442/344264813021/movil https://doi.org/10.22430/22565337.1654 en http://www.redalyc.org/revista.oa?id=3442 TecnoLógicas application/pdf Instituto Tecnológico Metropolitano TecnoLógicas (Colombia) Num.50 Vol.24 |
| format | Artículo científico |
| id | redalyc_344264813021 |
| institution | Redalyc |
| language | en |
| publishDate | 2021 |
| publisher | Instituto Tecnológico Metropolitano |
| spellingShingle | Classification of Cocoa Beans Based on their Level of Fermentation using Spectral Information Karen Sánchez Ingeniería superpixel Cocoa beans hyperspectral images level of fermentation spectral classification Classification of Cocoa Beans Based on their Level of Fermentation using Spectral Information Karen Sánchez Jorge Bacca Laura Arévalo-Sánchez Henry Arguello Sergio Castillo Ingeniería superpixel Cocoa beans hyperspectral images level of fermentation spectral classification Cocoa beans are the most important raw material for the chocolate industry and an essential product for the economy of tropical countries such as Colombia. Their price mainly depends on their quality, which is determined by various aspects, such as good agricultural practices, their harvest point, and level of fermentation. The entities that regulate the international marketing of cocoa beans have been encouraging the development of new classification methods that, compared to current techniques, could save time, reduce waste, and increase the number of evaluated beans. In particular, hyperspectral images are a novel tool for food quality control. However, studies that have examined some quality parameters of cocoa using spectroscopy also involve the chemical evaluation of cocoa powder and liquor and the interior of the beans, which implies an invasive analysis, longer times, and waste generation. Therefore, in this paper, we assess the quality of cocoa beans based on their level of fermentation using a noninvasive system to obtain hyperspectral information, as well as fast image processing and spectral classification techniques. We obtained hyperspectral images of 90 cocoa beans in the range between 350 and 950 nm in an optical laboratory. In addition, each cocoa bean was classified according to its fermentation level: slightly fermented (SF), correctly fermented (CF), and highly fermented (HF). We compared this classification with that carried out by experts from the Colombia National Federation of Cocoa Growers and reported in the Colombian technical standard No. 1252. The results show that the level of fermentation of dried cocoa beans can be estimated using noninvasive hyperspectral image acquisition and processing techniques. 2021 artículo científico 0123-7799 https://www.redalyc.org/articulo.oa?id=344264813021 https://www.redalyc.org/journal/3442/344264813021/ https://www.redalyc.org/journal/3442/344264813021/html/ https://www.redalyc.org/journal/3442/344264813021/344264813021.epub https://www.redalyc.org/journal/3442/344264813021/movil https://doi.org/10.22430/22565337.1654 en http://www.redalyc.org/revista.oa?id=3442 TecnoLógicas application/pdf Instituto Tecnológico Metropolitano TecnoLógicas (Colombia) Num.50 Vol.24 |
| title | Classification of Cocoa Beans Based on their Level of Fermentation using Spectral Information |
| topic | Ingeniería superpixel Cocoa beans hyperspectral images level of fermentation spectral classification |
| url | https://www.redalyc.org/articulo.oa?id=344264813021 https://www.redalyc.org/journal/3442/344264813021/ https://www.redalyc.org/journal/3442/344264813021/html/ https://www.redalyc.org/journal/3442/344264813021/344264813021.epub https://www.redalyc.org/journal/3442/344264813021/movil https://doi.org/10.22430/22565337.1654 |