Suhandy, Diding and Yulia, Meinilwita (2017) Peaberry coffee discrimination using UV-visible spectroscopy combined with SIMCA and PLS-DA. Taylor & Francis, International Journal of Food Properties.
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Abstract
Ultraviolet-visible (UV-Vis) spectral information (190–400 nm) was used to classify coffee samples into either pure peaberry or pure normal coffee classes using two chemometric methods: soft independent modelling of class analogy (SIMCA) and partial least squares discriminant analysis (PLSDA). The spectral data of peaberry and normal coffee were acquired using a UV-Vis spectrometer (Genesys™ 10S UV-Vis, Thermo Scientific, USA). For both supervised discrimination methods, SIMCA and PLS-DA, all samples were correctly classified into their corresponding classes. The SIMCA model classified all samples accurately (100%) into either the peaberry or normal coffee class, even at a 5% confidence level; however, the PLS-DA model also correctly classified all samples (100%). Investigation of the major wavelengths contributing to the classifications using x-loading weights and loading of latent variables (LVs) indicated wavelengths at 230, 250, 270, 310, and 350 nm were important for determination of the coffee types. These wavelengths were closely related to the absorbance wavelengths of several important chemical components in roasted coffee: caffeine, caffeic acid, and chlorogenic acids (CGA). These results provided the basis for developing a simple and reliable method for peaberry coffee authentication (including more complex samples where peaberry coffee is blended with normal coffees) based on UV-Vis spectra.
| Item Type: | Other |
|---|---|
| Subjects: | S Agriculture > S Agriculture (General) |
| Divisions: | Fakultas Pertanian (FP) > Prodi Teknik Pertanian |
| Depositing User: | Dr. Diding Suhandy |
| Date Deposited: | 10 May 2021 01:23 |
| Last Modified: | 10 May 2021 01:23 |
| URI: | http://repository.lppm.unila.ac.id/id/eprint/30071 |
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