Rapid prediction of single green coffee bean moisture and lipid content by hyperspectral imaging - Caporaso, Nicola; Whitworth, Martin B.; Grebby, Stephen; Fisk, Ian D. (Elsevier, 2018)
Hyperspectral imaging (1000–2500 nm) was used for rapid prediction of moisture and total lipid content in intact green coffee beans on a single bean basis. Arabica and Robusta samples from several growing locations were scanned using a “push-broom” system. Hypercubes were segmented to select single beans, and average spectra were measured for each bean. Partial Least Squares regression was used to build quantitative prediction models on single beans (n = 320–350). The models exhibited good performance and acceptable prediction errors of ∼0.28% for moisture and ∼0.89% for lipids.