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NIR Spectroscopy Coupled Chemometric Algorithms for Rapid Antioxidants Activity Assessment of Chinese Dates (Zizyphus Jujuba Mill.)

Arslan, Muhammad, Xiaobo, Zou, Tahir, Haroon Elrasheid, Xuetao, Hu, Rakha, Allah, Zareef, Muhammad, Seweh, Emmanuel Amomba, Basheer, Sajid
International journal of food engineering 2019 v.15 no.3-4
Ziziphus jujuba, algorithms, antioxidant activity, antioxidants, chemometrics, models, near-infrared spectroscopy, prediction, statistical analysis
In this work, near-infrared spectroscopy coupled the classical PLS and variable selection algorithms; synergy interval-PLS, backward interval-PLS and genetic algorithm-PLS for rapid measurement of the antioxidant activity of Chinese dates. The chemometric analysis of antioxidant activity assays was performed. The built models were investigated using correlation coefficients of calibration and prediction; root mean square error of prediction, root mean square error of cross-validation and residual predictive deviation (RPD). The correlation coefficient for calibration and prediction sets and RPD values ranged from 0.8503 to 0.9897, 0.8463 to 0.9783 and 1.86 to 4.88, respectively. In addition, variable selection algorithms based on efficient information extracted from acquired spectra were superior to classical PLS. The overall results revealed that near-infrared spectroscopy combined with chemometric algorithms could be used for rapid quantification of antioxidant content in Chinese dates samples.