Quantitative assessment of phytochemicals in chickpea beverages using NIR spectroscopy

Nana Adwoa Nkuma Johnson; Selorm Yao-Say Solomon Adade; Suleiman A Haruna; John-Nelson Ekumah; Yongkun Ma

doi:10.1016/j.saa.2023.123623

Quantitative assessment of phytochemicals in chickpea beverages using NIR spectroscopy

Spectrochim Acta A Mol Biomol Spectrosc. 2024 Feb 15:307:123623. doi: 10.1016/j.saa.2023.123623. Epub 2023 Nov 8.

Authors

Nana Adwoa Nkuma Johnson¹, Selorm Yao-Say Solomon Adade², Suleiman A Haruna³, John-Nelson Ekumah⁴, Yongkun Ma⁵

Affiliations

¹ College of Ocean Food and Biological Engineering, Jimei University, Xiamen 361021, PR China; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Road, Zhenjiang, 202013, Jiangsu, China.
² College of Ocean Food and Biological Engineering, Jimei University, Xiamen 361021, PR China; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Road, Zhenjiang, 202013, Jiangsu, China; Department of Nutrition and Dietetics, Ho Teaching Hospital, Ho, Ghana. Electronic address: syadade@gmail.com.
³ School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Road, Zhenjiang, 202013, Jiangsu, China; Department of Food Science and Technology, Kano University of Science andTechnology, Wudil, P.M.B 3244 Kano, Kano State, Nigeria.
⁴ School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Road, Zhenjiang, 202013, Jiangsu, China; Department of Nutrition and Food Science, College of Basic and Applied Sciences, University of Ghana, P. O. Box LG 134, Legon, Ghana.
⁵ School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Road, Zhenjiang, 202013, Jiangsu, China. Electronic address: mayongkun@ujs.edu.cn.

PMID: 37989004
DOI: 10.1016/j.saa.2023.123623

Abstract

The prospects of near-infrared (NIR) spectroscopy combined with effective variable selection algorithms for quantifying phytochemical compounds in chickpea beverages were investigated in this study. As reference measurement analysis, the phytochemicals were extracted and identified via high-performance liquid chromatography. Multivariate algorithms were then applied, analyzed, and evaluated using correlation coefficients of validation set (R_p), root mean square error of prediction (RMSEP), and residual predictive deviations (RPDs). Accordingly, the competitive adaptive reweighted sampling-partial least squares (CARS-PLS) model achieved superior performance for biochanin A (R_p = 0.933, RPD = 3.63), chlorogenic acid (R_p = 0.928, RPD = 3.52), p-coumaric acid (R_p = 0.900, RPD = 2.37), and stigmasterol (R_p = 0.932, RPD = 3.15), respectively. Hence, this study demonstrated that NIR spectroscopy paired with CARS-PLS could be used for nondestructive quantitative prediction of phytochemicals in chickpea beverages during manufacture and storage.

Keywords: CARS-PLS; Chickpea beverages; HPLC; Multivariate calibration; Near-infrared spectroscopy; Phytochemicals.

MeSH terms

Algorithms
Chlorogenic Acid
Cicer*
Least-Squares Analysis
Spectroscopy, Near-Infrared* / methods

Substances

Chlorogenic Acid