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

Foods
Naoya Okubo, Yohei Kurata

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.

References

Sep 30, 2016·Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy·Katrul Nadia BasriAhmad Sabirin Zoolfakar
Nov 1, 2017·Comprehensive Reviews in Food Science and Food Safety·Y DixitCarl Sullivan

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Methods Mentioned

BETA
PCA

Software Mentioned

SIMCA
Unscrambler

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