التفاصيل البيبلوغرافية
العنوان: |
Profiling and classification of black tea, white tea, and green tea (Camellia sinensis L.) by Vis-NIR spectroscopy. |
المؤلفون: |
Rahmawati, Laila, Masithoh, Rudiati Evi, Pahlawan, Muhammad Fahri Reza, Zahra, Aryanis Mutia, Hariadi, Hari |
المصدر: |
AIP Conference Proceedings; 2024, Vol. 2957 Issue 1, p1-8, 8p |
مصطلحات موضوعية: |
TEA, GREEN tea, PRINCIPAL components analysis, NEAR infrared spectroscopy, SPECTROMETRY |
مستخلص: |
Green tea (GT), black tea (BT), and white tea (WT) are common tea which enjoyed immensely. The tea attributes include originality and chemical that are difficult to describe, evaluate and monitor. A traditional method of tea assessment has been sensory monitoring and evaluation, which lacks consistency and impartiality due to personal interest. To address these issues, visible and near-infrared (Vis-NIR) as a rapid, non-destructive, and simple methodology is developed to profiling and classify the GT, BT, and WT based on color and varieties. Vis-NIR spectroscopy with a 400–1,000 nm wavelength in original spectra and pre-processing analysis (SG-S, SG-1st, SNV, and MSC) were applied. Unsupervised analyses, such as Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA), were used in this research. PCA will lead the spectral information of the tea samples, which provides the grouping, classifying, and profiling. PCA result showed that the tea samples were grouped successfully. The dominant pattern shown at the spectral range of 600–700 nm was just corresponding to yellow or red. PLS-DA gave a reliable model, the Y-variables as predicted values were classified as y<1.5 of 1, 1.53.5. Model prediction of accuracy (ACC) was 100% on original spectra, SG-S, SNV, and MSC. Meanwhile, 91% on SG with nine samples were not classified. [ABSTRACT FROM AUTHOR] |
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قاعدة البيانات: |
Complementary Index |