Chemical Content Evaluation of Peaberry Robusta Green Bean Using FT NIRS Method
Abstract
Mount Ijen is a prominent region for peaberry Robusta coffee beans, which has entered international markets. Accurate real-time estimation of its chemical components is crucial for export activities. This study evaluated moisture content, lipid, and caffeine in Robusta peaberry coffee beans from Ijen using FT-NIRS (Fourier Transform – Near Infrared Spectroscopy). A total of 50 samples were scanned in triplicate, generating 150 spectral data points. The data were optimized for wavelength selection and pre-treated using Standard Normal Variate Transformation (SNV), Second Derivative (dg2), Multiplicative Scatter Correction (MSC), and normalization. Results showed that FT-NIRS proved effective for rapid and accurate estimation of these components. The best calibration model used Kubelka-Munk transformation with dg2 pre-treatment in the 1000-2500 nm wavelength range. Optimal Partial Least Squares (PLS) factors were PLS 4 for lipid content (R2 = 0.98, SEP = 0.013%, SEC = 0.012%, CV = 0.81, RPD = 2.03, consistency = 95.21%), PLS 5 for moisture content (R2 = 0.94, SEP = 0.014%, SEC = 0.014%, CV = 0.80, RPD = 4.88, consistency = 101.02%), and PLS 5 for caffeine content (R2 = 0.94, SEP = 0.014%, SEC = 0.014%, CV = 0.80, RPD = 4.88, consistency = 101.02%).
Keywords: Absorbance, Caffeine, Lipid, Moisture Content, Pre-Treatment.
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