التفاصيل البيبلوغرافية
| العنوان: |
Determination of the Betacyanin and Betaxanthin Contents of Red Beet (Beta Vulgaris) Powder Using Partial Least Square Regression Based on Visible-Near Infrared Spectra. |
| المؤلفون: |
Masithoh, Rudiati Evi, Fahri Reza Pahlawan, Muhammad, Arifani, Erlina Nur, Zuhrotul Amanah, Hanim, Byoung Kwan Cho |
| المصدر: |
Trends in Sciences; May2024, Vol. 21 Issue 5, p1-8, 8p |
| مصطلحات موضوعية: |
BEETS, INFRARED spectra, LEAST squares, STANDARD deviations, POWDERS |
| مستخلص: |
Red beet (Beta vulgaris) contains betalain, which comprises red-violet betacyanin and yellow betaxanthin with esthetic and health benefits. Betacyanin and betaxanthin are usually detected using common chemical analysis, which requires a long time, skilled analysts, and sample destruction. For fast and accurate measurement, this study utilized a portable low-cost Visible-Near Infrared Spectra (Vis-NIR) spectrometer at 350 - 1000 nm combined with partial least square regression to predict the betacyanin and betaxanthin contents of red beet powder. The best calibration models for betacyanin and betaxanthin had R² c of 0.89 and 0.919, respectively, and standard error of calibration SEC of 0.108 and 0.037 mg/g, respectively. The models were able to predict the contents of both pigments with R² p of 0.87, standard error of prediction SEP of 0.108 mg/g, and the ratio of prediction to deviation RPD of 2.52 for betacyanin and R² p of 0.84, SEP of 0.056 mg/g, and RPD of 2.47 for betaxanthin. When applied to external unknown data, the models predicted the contents of betacyanin and betaxanthin with R² of 0.98 and root mean square error of 0.107 and 0.055 mg/g. Moreover, the predicted values were not significantly different at 95 % confidence. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
