Abstract

A method to discriminate between green peaberry beans and normal beans was developed using an excitation and emission spectrometer that can be used to construct a simple optical system to save farm workers' labor. The excitation and emission matrix were obtained in the wavelength range of 300 - 800 nm using a hand-held spectrophotometer combined with a diffraction grating and a diode array. Light sources of 300, 375 nm were used to excite the samples by light-emitting diodes. The acquired spectral information was used to classify the coffee samples into peaberry and normal coffee using the chemometric method of partial least squares discriminant analysis (PLS-DA). The results showed that all coffee samples were discriminated as corresponding classes by PLS-DA. In the PLS-DA model, investigation of the main wavelengths contributing to classification using all sample VIP showed that excitation/emission wavelengths at 300/470, 300/670 375/470, 375/670 nm are important for coffee type determination. These wavelengths were closely related to the excitation-emission wavelengths of several important chemical components in raw coffee beans (caffeine, caffeic acid, and chlorogenic acid (CGA), tocopherol). These results will be useful as basic knowledge to contribute to the labor-saving and automation of coffee bean sorting in the future.

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