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Haruna SA, Li H, Zareef M, Mehedi Hassan M, Arslan M, Geng W, Wei W, Abba Dandago M, Yao-Say Solomon Adade S, Chen Q. Application of NIR spectroscopy for rapid quantification of acid and peroxide in crude peanut oil coupled multivariate analysis. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 267:120624. [PMID: 34824004 DOI: 10.1016/j.saa.2021.120624] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Revised: 10/11/2021] [Accepted: 11/10/2021] [Indexed: 06/13/2023]
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.
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Affiliation(s)
- Suleiman A Haruna
- 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
| | - Huanhuan Li
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.
| | - Muhammad Zareef
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China
| | - Md Mehedi Hassan
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China
| | - Muhammad Arslan
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China
| | - Wenhui Geng
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China
| | - Wenya Wei
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China
| | - Munir Abba Dandago
- Department of Food Science and Technology, Kano University of Science and Technology, Wudil, P.M.B 3244, Kano, Kano State, Nigeria
| | | | - Quansheng Chen
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China; College of Food and Biological Engineering, Jimei University, Xiamen 361021, PR China.
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Evaluation of Quality Parameters of Açaí Oil During Thermal Oxidation Using NIRS and Chemometrics. FOOD ANAL METHOD 2021. [DOI: 10.1007/s12161-021-02054-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Kalogianni EP, Georgiou D, Marinopoulou A, Exarhopoulos S, Petridis D, Dimitreli G. A novel rapid method for the determination of frying oil quality: development of prototype and equations and examination with respect to legislation criteria. Int J Food Sci Technol 2020. [DOI: 10.1111/ijfs.14919] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Affiliation(s)
- Eleni P. Kalogianni
- Department of Food Science and Technology International Hellenic University P.O. Box 141 Thessaloniki57400Greece
| | - Despoina Georgiou
- Department of Food Science and Technology International Hellenic University P.O. Box 141 Thessaloniki57400Greece
| | - Anna Marinopoulou
- Department of Food Science and Technology International Hellenic University P.O. Box 141 Thessaloniki57400Greece
| | - Stylianos Exarhopoulos
- Department of Food Science and Technology International Hellenic University P.O. Box 141 Thessaloniki57400Greece
| | - Dimitrios Petridis
- Department of Food Science and Technology International Hellenic University P.O. Box 141 Thessaloniki57400Greece
| | - Georgia Dimitreli
- Department of Food Science and Technology International Hellenic University P.O. Box 141 Thessaloniki57400Greece
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Borghi FT, Santos PC, Santos FD, Nascimento MH, Corrêa T, Cesconetto M, Pires AA, Ribeiro AV, Lacerda V, Romão W, Filgueiras PR. Quantification and classification of vegetable oils in extra virgin olive oil samples using a portable near-infrared spectrometer associated with chemometrics. Microchem J 2020. [DOI: 10.1016/j.microc.2020.105544] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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Gu H, Huang X, Sun Y, Chen Q, Wei Z, Lv R. Intelligent evaluation of total polar compounds (TPC) content of frying oil based on fluorescence spectroscopy and low-field NMR. Food Chem 2020; 342:128242. [PMID: 33069532 DOI: 10.1016/j.foodchem.2020.128242] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 09/08/2020] [Accepted: 09/26/2020] [Indexed: 10/23/2022]
Abstract
The purpose of this study was to construct a fusion model using probe-based and non-probe-based fluorescence spectroscopy and low-field nuclear magnetic resonance spectroscopy (Low-field NMR) for rapid quality evaluation of frying oil. Iron tetraphenylporphyrin (FeTPP) was selected as the probe to detect polar compounds in frying oil samples. Non-probe-based fluorescence spectroscopy and low-field NMR were employed to determine the fluorescence changes of antioxidants, triglycerides and fatty acids in frying oil samples. Compared to the models constructed using non-fusion data, the fusion-data models achieved a better regression prediction performance and correlation coefficients with values of 0.9837 and 0.9823 for the training and test sets, respectively. This study suggested that the multiple data fusion method was capable to construct better regression models to rapidly evaluate the quality of frying oil and other food with high oil contents.
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Affiliation(s)
- Haiyang Gu
- School of Bio and Food Engineering, Chuzhou University, Chuzhou 239000, China; School of Food Science and Engineering, Hefei University of Technology, Hefei 230000, China.
| | - Xingyi Huang
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Yanhui Sun
- School of Bio and Food Engineering, Chuzhou University, Chuzhou 239000, China
| | - Quansheng Chen
- School of Bio and Food Engineering, Chuzhou University, Chuzhou 239000, China; School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
| | - ZhaoJun Wei
- School of Food Science and Engineering, Hefei University of Technology, Hefei 230000, China
| | - Riqin Lv
- School of Bio and Food Engineering, Chuzhou University, Chuzhou 239000, China
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