Application of NIR spectroscopy for rapid quantification of acid and peroxide in crude peanut oil coupled multivariate analysis

Suleiman A Haruna; Huanhuan Li; Muhammad Zareef; Md Mehedi Hassan; Muhammad Arslan; Wenhui Geng; Wenya Wei; Munir Abba Dandago; Selorm Yao-Say Solomon Adade; Quansheng Chen

doi:10.1016/j.saa.2021.120624

Application of NIR spectroscopy for rapid quantification of acid and peroxide in crude peanut oil coupled multivariate analysis

Spectrochim Acta A Mol Biomol Spectrosc. 2022 Feb 15;267(Pt 2):120624. doi: 10.1016/j.saa.2021.120624. Epub 2021 Nov 16.

Affiliations

¹ School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China; Department of Food Science and Technology, Kano University of Science and Technology, Wudil, P.M.B 3244, Kano, Kano State, Nigeria.
² School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China. Electronic address: jiona1044@ujs.edu.cn.
³ School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.
⁴ Department of Food Science and Technology, Kano University of Science and Technology, Wudil, P.M.B 3244, Kano, Kano State, Nigeria.
⁵ School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China; College of Food and Biological Engineering, Jimei University, Xiamen 361021, PR China. Electronic address: qschen@ujs.edu.cn.

PMID: 34824004
DOI: 10.1016/j.saa.2021.120624

Abstract

Two key parameters (acidity and peroxide content) for evaluation of the oxidation level in crude peanut oil have been studied. The titrimetric analysis was carried out for reference data collection. Then, near-infrared spectroscopy in combination with chemometric algorithms such as partial least square (PLS); bootstrapping soft shrinkage-PLS (BOSS-PLS); uninformative variable elimination-PLS (UVE-PLS), and competitive-adaptive reweighted sampling-PLS (CARS-PLS) were attempted and assessed. The correlation coefficients of prediction (Rp), root mean square error of prediction (RMSEP) and residual predictive deviation (RPD) were used to individually evaluate the performance of the models. Optimum results were noticed with CARS-PLS, 0.9517 ≤ Rc ≤ 0.9670, 0.9503 ≤ Rp ≤ 0.9637, 0.0874 ≤ RMSEP ≤ 0.5650, and 3.14 ≤ RPD ≤ 3.64. Therefore, this affirmed that the near-infrared spectroscopy coupled with CARS-PLS could be used as a simple, fast, and non-invasive technique for quantifying acid value and peroxide value in crude peanut oil.

Keywords: Acid value; Multivariate calibration; Non-destructive detection; Oxidation; Peroxide value; Titrimetric analysis.

MeSH terms

Algorithms
Arachis
Least-Squares Analysis
Multivariate Analysis
Peanut Oil
Peroxides
Petroleum*
Spectroscopy, Near-Infrared*

Substances

Peanut Oil
Peroxides
Petroleum