Diding Suhandy, Meinilwita Yulia, Slamet Widodo, Hirotaka Naito, Dimas Firmanda Al Riza
The authentic Arabica coffee renders it vulnerable to fraud and adulteration. Arabica, Robusta, and Liberica green beans appear different. After roasting and grinding, authentic coffee seems identical to inferior varieties. A proper analytical technique for ground-roasted coffee authentication is needed. This study uses portable LED-based fluorescence spectroscopy and chemometrics to identify and quantify roasted soybeans in ground-roasted Arabica. Supervised classification algorithms PLS-DA, LDA, PCA-LDA, and SVMC are compared. Three easy-to-use regression approaches were employed to predict soybean adulteration in adulterated Arabica coffee: PLSR, PCR, and MLR. Classification accuracy was 100 % for the linear kernel-SVMC model, outperforming PLS-DA, LDA, and PCA-LDA. PLSR had the lowest LOD of 4.96 % (w/w) and the best regression model for soybean adulteration (RMSEC of 2.01 % (w/w), RMSECV of 2.10 % (w/w), R2c of 0.99, and R2cv of 0.99). The RPD and RER were 11.39 and 31.07, beyond practical applicability. The proposed method is simpler, non-destructive, and cost-effective authentication method. © 2025 Elsevier Ltd
Department of Agricultural Engineering, Faculty of Agriculture, The University of Lampung, Jl. Soemantri Brojonegoro No.1, Bandar Lampung, 35145, Indonesia; Spectroscopy Research Group (SRG), Laboratory of Bioprocess and Postharvest Engineering, Department of Agricultural Engineering, Faculty of Agriculture, The University of Lampung, Jl. Soemantri Brojonegoro No.1, Bandar Lampung, 35145, Indonesia; Department of Agricultural Technology, Lampung State Polytechnic, Jl. Soekarno Hatta No. 10, Rajabasa, Bandar Lampung, 35141, Indonesia; Department of Mechanical and Biosystem Engineering, IPB University, Dramaga, Bogor, 16002, Indonesia; of Bioresources, Department of Environmental Science and Technology, Mie University, 1577 Kurima-machiya-cho, Mie, Tsu, 514-8507, Japan; Department of Biosystems Engineering, Faculty of Agricultural Technology, University of Brawijaya, Jl. Veteran, Malang, 65145, Indonesia
