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Near-infrared spectroscopy coupled chemometric algorithms for prediction of antioxidant activity of black goji berries (Lycium ruthenicum Murr.)

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Abstract

In this study, near-infrared (NIR) spectroscopy coupled with partial least-squares (PLS) regression and various efficient variable selection algorithms, synergy interval-PLS (Si-PLS), backward interval PLS (Bi-PLS) and genetic algorithm-PLS (GA-PLS) were applied comparatively for the prediction of antioxidant activity in black wolfberry (BW). The eight assays were used for quantification of antioxidant content. The developed models were assessed using correlation coefficients (R2) of the calibration (Cal.) and prediction (Pre.); root mean square error of prediction, RMSEP; standard Error of Cross-Validation, RMSECV and residual predictive deviation, RPD. The performance of the built model greatly improved by the application of Si-PLS, Bi-PLS and GA-PLS compared with full spectrum PLS. The R2 values determined for calibration and prediction set ranged from 0.8479 to 0.9696 and 0.8401 to 0.9638, respectively. These findings revealed that NIR spectroscopy combined with chemometric algorithms can be used for quantification of antioxidant activity in BW samples.

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Acknowledgements

The authors appreciatively acknowledge financial support provided by the International Science and Technology Cooperation Project of Jiangsu Province (BZ2016013); The Natural Science Foundation of Jiangsu Province (BK20160506, BE2016306); China Postdoctoral Science Foundation (2016M590422, 2017M611736); The National Natural Science Foundation of China (31671844, 31601543, 31750110458) and The National Key Research and Development Program of China (2016YFD0401104). We also would like to thank our colleagues in School of Food and Biological Engineering who helped in this study.

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Authors and Affiliations

  1. School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., Zhenjiang, 212013, Jiangsu, China

    Muhammad Arslan, Zou Xiaobo, Haroon Elrasheid Tahir, Hu Xuetao, Sajid Basheer & Zhao Hao

  2. National Institute of Food Science & Technology, University of Agriculture, Faisalabad, 38000, Pakistan

    Allah Rakha

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  1. Muhammad Arslan
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  2. Zou Xiaobo
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  3. Haroon Elrasheid Tahir
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  4. Hu Xuetao
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  7. Zhao Hao
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Correspondence to Zou Xiaobo.

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Arslan, M., Xiaobo, Z., Tahir, H.E. et al. Near-infrared spectroscopy coupled chemometric algorithms for prediction of antioxidant activity of black goji berries (Lycium ruthenicum Murr.). Food Measure 12, 2366–2376 (2018). https://doi.org/10.1007/s11694-018-9853-x

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  • DOI: https://doi.org/10.1007/s11694-018-9853-x

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