TY - JOUR
T1 - Nondestructive classification analysis of green coffee beans by using near-infrared spectroscopy
AU - Okubo, Naoya
AU - Kurata, Yohei
N1 - Publisher Copyright:
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
PY - 2019/2
Y1 - 2019/2
N2 - 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.
AB - 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.
KW - Green coffee beans
KW - Near-infrared spectroscopy
KW - SIMCA
UR - https://www.scopus.com/pages/publications/85063229919
U2 - 10.3390/foods8020082
DO - 10.3390/foods8020082
M3 - Article
AN - SCOPUS:85063229919
SN - 2304-8158
VL - 8
JO - Foods
JF - Foods
IS - 2
M1 - 82
ER -