Jimenez Juan C, Amores Freddy M, Solórzano Eddyn G, Rodríguez Gladys A, La Mantia Alessandro, Blasi Paolo, Loor Rey G
Programa Nacional de Cacao, Instituto Nacional de Investigaciones Agropecuarias (INIAP), Estación Experimental Tropical Pichilingue, Los Ríos, Ecuador.
Universidad Técnica Estatal de Quevedo, Los Ríos, Ecuador.
J Sci Food Agric. 2018 May;98(7):2824-2829. doi: 10.1002/jsfa.8790. Epub 2018 Jan 8.
BACKGROUND: Ecuador exports two major types of cocoa beans, the highly regarded and lucrative National, known for its fine aroma, and the CCN-51 clone type, used in bulk for mass chocolate products. In order to discourage exportation of National cocoa adulterated with CCN-51, a fast and objective methodology for distinguishing between the two types of cocoa beans is needed. RESULTS: This study reports a methodology based on computer vision, which makes it possible to recognize these beans and determine the percentage of their mixture. The methodology was challenged with 336 samples of National cocoa and 127 of CCN-51. By excluding the samples with a low fermentation level and white beans, the model discriminated with a precision higher than 98%. The model was also able to identify and quantify adulterations in 75 export batches of National cocoa and separate out poorly fermented beans. CONCLUSION: A scientifically reliable methodology able to discriminate between Ecuadorian National and CCN-51 cocoa beans and their mixtures was successfully developed. © 2017 Society of Chemical Industry.
背景：厄瓜多尔出口两种主要类型的可可豆，一种是备受推崇且利润丰厚的“国民”型，以其美妙的香气闻名；另一种是CCN - 51克隆型，大量用于大众巧克力产品。为了抑制用CCN - 51掺杂的“国民”型可可豆出口，需要一种快速且客观的方法来区分这两种可可豆。 结果：本研究报告了一种基于计算机视觉的方法，该方法能够识别这些可可豆并确定其混合比例。该方法用336个“国民”型可可豆样本和127个CCN - 51样本进行了验证。通过排除发酵程度低的样本和白色可可豆，该模型的判别精度高于98%。该模型还能够识别和量化75个“国民”型可可豆出口批次中的掺假情况，并分离出发酵不良的可可豆。 结论：成功开发出一种科学可靠的方法，能够区分厄瓜多尔“国民”型和CCN - 51型可可豆及其混合物。© 2017化学工业协会。
J Agric Food Chem. 2022-7-20
J Agric Food Chem. 2010-12-8
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