RT journal article
T1 Enhanced Differentiation of Wild and Feeding Civet Coffee Using Near-Infrared Spectroscopy with Various Sample Pretreatments and Chemometric Approaches
A1 Prajna, Deyla
A1 Alvarez, Maria
A1 Barea Sepúlveda, Marta
A1 Pérez Calle, José Luis
A1 Suhandy, Diding
A1 Setyaningsih, Widiastuti
A1 Palma Lovillo, Miguel
A2 Química Analítica
K1 Boruta algorithm
K1 civet coffee
K1 ground coffee
K1 hierarchical cluster analysis
K1 principal component analysis
K1 random forest
K1 support vector machine
AB Civet coffee is the world’s most expensive and rarest coffee bean. Indonesia was the first country to be identified as the origin of civet coffee. First, it is produced spontaneously by collecting civet feces from coffee plantations near the forest. Due to limited stock, farmers began cultivating civets to obtain safe supplies of civet coffee. Based on this, civet coffee can be divided into two types: wild and fed. A combination of spectroscopy and chemometrics can be used to evaluate authenticity with high speed and precision. In this study, seven samples from different regions were analyzed using NIR Spectroscopy with various preparations: unroasted, roasted, unground, and ground. The spectroscopic data were combined with unsupervised exploratory methods (hierarchical cluster analysis (HCA) and principal component analysis (PCA)) and supervised classification methods (support vector machine (SVM) and random forest (RF)). The HCA results showed a trend between roasted and unroasted beans; meanwhile, the PCA showed a trend based on coffee bean regions. Combining the SVM with leave-one-out-cross-validation (LOOCV) successfully differentiated 57.14% in all sample groups (unground, ground, unroasted, unroasted–unground, and roasted–unground), 78.57% in roasted, 92.86% in roasted–ground, and 100% in unroasted–ground. However, using the Boruta filter, the accuracy increased to 89.29% for all samples, to 85.71% for unground and unroasted–unground, and 100% for roasted, unroasted–ground, and roasted–ground. Ultimately, RF successfully differentiated 100% of all grouped samples. In general, roasting and grinding the samples before analysis improved the accuracy of differentiating between wild and feeding civet coffee using NIR Spectroscopy.
PB MDPI
SN 2311-7524
YR 2023
FD 2023
LK http://hdl.handle.net/10498/32488
UL http://hdl.handle.net/10498/32488
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 11-nov-2026