Rapid and non-destructive prediction of moisture content on intact gayo coffee beans using near infrared spectroscopy

Abstract

Abstract Presented work explores the potential of Near-Infrared Spectroscopy (NIRS) as a rapid, non-destructive analytical method for predicting moisture content in intact Gayo coffee beans. The moisture content is an essential parameter affecting the quality, processing, and shelf life of coffee beans. While conventional moisture determination techniques involve invasive procedures and considerable time, NIRS emanates as an innovative technique offering non-invasive, swift analysis. Using a robust representative selection of Gayo coffee bean samples, we acquired numerous spectra and employed multivariate analysis to construct a calibration model correlating the spectral data with reference moisture values. The initial results exhibit a high correlation coefficient (r) of 0.93 and ratio prediction to deviation (RPD) index of 3, suggesting that the NIRS technique can effectively predict the moisture content within the beans. This research underpins the potential usage of NIRS which, if validated through further testing, could transform quality control operations in the coffee industry by offering a real-time, non-destructive approach for moisture content determination.