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Foods 2019, 8(2), 82; https://doi.org/10.3390/foods8020082

Nondestructive Classification Analysis of Green Coffee Beans by Using Near-Infrared Spectroscopy

1
Graduate School of Bioresource Sciences, Nihon University, 1866 Kameino, Fujisawa, Kanagawa 252-0880, Japan
2
College of Bioresource Sciences, Nihon University, 1866 Kameino, Fujisawa, Kanagawa 252-0880, Japan
*
Author to whom correspondence should be addressed.
Received: 11 January 2019 / Revised: 12 February 2019 / Accepted: 18 February 2019 / Published: 22 February 2019
(This article belongs to the Special Issue Foods Quality Assessed by Chemometrics)
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Abstract

Near-infrared spectroscopy (NIRS) is a powerful tool for the nondestructive evaluation of organic materials, and it has found widespread use in a variety of industries. In the food industry, it is important to know the district in which a particular food was produced. Therefore, in this study, we focused on determining the production area (five areas and three districts) of green coffee beans using classification analysis and NIRS. Soft independent modeling of class analogy (SIMCA) was applied as the classification method. Samples of green coffee beans produced in seven locations—Cuba, Ethiopia, Indonesia (Bari, Java, and Sumatra), Tanzania, and Yemen—were analyzed. These regions were selected since green coffee beans from these locations are commonly sold in Japan supermarkets. A good classification result was obtained with SIMCA for the seven green bean samples, although some samples were partly classified into several categories. Then, the model distance values of SIMCA were calculated and compared. A few model distance values were ~10; such small values may be the reason for misclassification. However, over a 73% correct classification rate could be achieved for the different kinds of green coffee beans using NIRS. View Full-Text
Keywords: near-infrared spectroscopy; green coffee beans; SIMCA near-infrared spectroscopy; green coffee beans; SIMCA
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Okubo, N.; Kurata, Y. Nondestructive Classification Analysis of Green Coffee Beans by Using Near-Infrared Spectroscopy. Foods 2019, 8, 82.

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