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Shiv K, Singh A, Kumar S, Prasad LB, Gupta S, Bharty MK. Evaluation of different regression models for detection of adulteration of mustard and canola oil with argemone oil using fluorescence spectroscopy coupled with chemometrics. Food Addit Contam Part A Chem Anal Control Expo Risk Assess 2024; 41:105-119. [PMID: 38180769 DOI: 10.1080/19440049.2023.2297869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 12/10/2023] [Indexed: 01/06/2024]
Abstract
Mustard and canola oils are commonly used cooking oils in Asian countries such as India, Nepal, and Bangladesh, making them prone to adulteration. Argemone is a well-known adulterant of mustard oil, and its alkaloid sanguinarine has been linked with health conditions such as glaucoma and dropsy. Utilising a non-destructive spectroscopic method coupled with a chemometric approach can serve better for the detection of adulterants. This work aimed to evaluate the performance of various regression algorithms for the detection of argemone in mustard and canola oils. The spectral dataset was acquired from fluorescence spectrometer analysis of pure as well as adulterated mustard and canola oils with some local and commercial samples also. The prediction performance of the eight regression algorithms for the detection of adulterants was evaluated. Extreme gradient boosting regressor (XGBR), Category gradient boosting regressor (CBR), and Random Forest (RF) demonstrate potential for predicting adulteration levels in both oils with high R2 values.
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Affiliation(s)
- Kunal Shiv
- Department of Chemistry, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Anupam Singh
- Department of Chemistry, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Sachin Kumar
- Department of Chemistry, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Lal Bahadur Prasad
- Department of Chemistry, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Seema Gupta
- Department of Chemistry, Institute of Science, Banaras Hindu University, Varanasi, India
| | - Manoj Kumar Bharty
- Department of Chemistry, Institute of Science, Banaras Hindu University, Varanasi, India
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Zhang Z, Li Y, Zhao S, Qie M, Bai L, Gao Z, Liang K, Zhao Y. Rapid analysis technologies with chemometrics for food authenticity field: A review. Curr Res Food Sci 2024; 8:100676. [PMID: 38303999 PMCID: PMC10830540 DOI: 10.1016/j.crfs.2024.100676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 12/15/2023] [Accepted: 01/07/2024] [Indexed: 02/03/2024] Open
Abstract
In recent years, the problem of food adulteration has become increasingly rampant, seriously hindering the development of food production, consumption, and management. The common analytical methods used to determine food authenticity present challenges, such as complicated analysis processes and time-consuming procedures, necessitating the development of rapid, efficient analysis technology for food authentication. Spectroscopic techniques, ambient ionization mass spectrometry (AIMS), electronic sensors, and DNA-based technology have gradually been applied for food authentication due to advantages such as rapid analysis and simple operation. This paper summarizes the current research on rapid food authenticity analysis technology from three perspectives, including breeds or species determination, quality fraud detection, and geographical origin identification, and introduces chemometrics method adapted to rapid analysis techniques. It aims to promote the development of rapid analysis technology in the food authenticity field.
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Affiliation(s)
- Zixuan Zhang
- Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing, China
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-Product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yalan Li
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-Product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shanshan Zhao
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-Product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Mengjie Qie
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-Product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lu Bai
- Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Zhiwei Gao
- Hangzhou Nutritome Biotech Co., Ltd., Hangzhou, China
| | - Kehong Liang
- Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Yan Zhao
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-Product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing, China
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Rodrigues N, Peres F, Casal S, Santamaria-Echart A, Barreiro F, Peres AM, Alberto Pereira J. Geographical discrimination of olive oils from Cv. ‘Galega Vulgar’. Food Chem 2023; 398:133945. [DOI: 10.1016/j.foodchem.2022.133945] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 08/08/2022] [Accepted: 08/10/2022] [Indexed: 01/18/2023]
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Zaroual H, Chèné C, Mestafa El Hadrami E, Karoui R. Comparison of four classification statistical methods for characterising virgin olive oil quality during storage up to 18 months. Food Chem 2022; 370:131009. [PMID: 34509151 DOI: 10.1016/j.foodchem.2021.131009] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 07/29/2021] [Accepted: 08/29/2021] [Indexed: 11/25/2022]
Abstract
This study examines the ability of fluorescence spectroscopy for monitoring the quality of 70 Moroccan virgin olive oils belonging to three varieties and originating from three regions of Morocco. By applying principal component analysis and factorial discriminant analysis to the emission spectra acquired after excitation wavelengths set at 270, 290, and 430 nm, a clear differentiation between samples according to their storage time was observed. The obtained results were confirmed following the application of four multivariate classification methods: partial least squares regression, principal component regression, support vector machine, and multiple linear regression on the emission spectra. The best prediction model of storage time was obtained by applying partial least squares regression since a coefficient of determination (R2) and a root mean square error of prediction (RMSEP) of 0.98 and 24.85 days were observed, respectively. The prediction of the chemical parameters allowed to obtain excellent validation models with R2 ranging between 0.98 and 0.99 for free acidity, peroxide value, chlorophyll level, k232, and k270.
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Affiliation(s)
- Hicham Zaroual
- Univ. Artois, Univ. Lille, Univ. Littoral Côte d'Opale, Univ. Picardie Jules Verne, Univ. de Liège, INRAE, Junia, UMR-T 1158, BioEcoAgro, F-62300, Lens, France; Univ. Sidi Mohamed Ben Abdellah, Faculty of Sciences and Technologies, Applied Organic Chemistry Laboratory, Fez M-30000, Morocco
| | | | - El Mestafa El Hadrami
- Univ. Sidi Mohamed Ben Abdellah, Faculty of Sciences and Technologies, Applied Organic Chemistry Laboratory, Fez M-30000, Morocco
| | - Romdhane Karoui
- Univ. Artois, Univ. Lille, Univ. Littoral Côte d'Opale, Univ. Picardie Jules Verne, Univ. de Liège, INRAE, Junia, UMR-T 1158, BioEcoAgro, F-62300, Lens, France.
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Rifna EJ, Pandiselvam R, Kothakota A, Subba Rao KV, Dwivedi M, Kumar M, Thirumdas R, Ramesh SV. Advanced process analytical tools for identification of adulterants in edible oils - A review. Food Chem 2022; 369:130898. [PMID: 34455326 DOI: 10.1016/j.foodchem.2021.130898] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 07/16/2021] [Accepted: 08/16/2021] [Indexed: 12/16/2022]
Abstract
This review summarizes the use of spectroscopic processes-based analytical tools coupled with chemometric techniques for the identification of adulterants in edible oil. Investigational approaches of process analytical tools such asspectroscopy techniques, nuclear magnetic resonance (NMR), hyperspectral imaging (HSI), e-tongue and e-nose combined with chemometrics were used to monitor quality of edible oils. Owing to the variety and intricacy of edible oil properties along with the alterations in attributes of the PAT tools, the reliability of the tool used and the operating factors are the crucial components which require attention to enhance the efficiency in identification of adulterants. The combination of process analytical tools with chemometrics offers a robust technique with immense chemotaxonomic potential. These involves identification of adulterants, quality control, geographical origin evaluation, process evaluation, and product categorization.
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Affiliation(s)
- E J Rifna
- Department of Food Process Engineering, National Institute of Technology, Rourkela 769008, Odisha, India
| | - R Pandiselvam
- Physiology, Biochemistry and Post-Harvest Technology Division, ICAR - Central Plantation Crops Research Institute, Kasaragod 671 124, Kerala, India.
| | - Anjineyulu Kothakota
- Agro-Processing & Technology Division, CSIR-National Institute for Interdisciplinary Science and Technology (NIIST), Trivandrum 695 019, Kerala, India.
| | - K V Subba Rao
- Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur, West Bengal 721302, India
| | - Madhuresh Dwivedi
- Department of Food Process Engineering, National Institute of Technology, Rourkela 769008, Odisha, India
| | - Manoj Kumar
- Chemical and Biochemical Processing Division, ICAR-Central Institute for Research on Cotton Technology, Matunga, Mumbai 400019, India
| | - Rohit Thirumdas
- Department of Food Process Technology, College of Food Science and Technology, PJTSAU, Telangana, India
| | - S V Ramesh
- Physiology, Biochemistry and Post-Harvest Technology Division, ICAR - Central Plantation Crops Research Institute, Kasaragod 671 124, Kerala, India
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Ghnimi H, Ennouri M, Chèné C, Karoui R. A review combining emerging techniques with classical ones for the determination of biscuit quality: advantages and drawbacks. Crit Rev Food Sci Nutr 2021:1-24. [PMID: 34875937 DOI: 10.1080/10408398.2021.2012124] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
The production of biscuit and biscuit-like products has faced many challenges due to changes in consumer behavior and eating habits. Today's consumer is looking for safe products not only with fresh-like and pleasant taste, but also with long shelf life and health benefits. Therefore, the potentiality of the use of healthier fat and the incorporation of natural antioxidant in the formulation of biscuit has interested, recently, the attention of researchers. The determination of the biscuit quality could be performed by several techniques (e.g., physical, chemical, sensory, calorimetry and chromatography). These classical analyses are unfortunately destructive, expensive, polluting and above all very heavy, to implement when many samples must be prepared to be analyzed. Therefore, there is a need to find fast analytical techniques for the determination of the quality of cereal products like biscuits. Emerging techniques such as near infrared (NIR), mid infrared (MIR) and front face fluorescence spectroscopy (FFFS), coupled with chemometric tools have many potential advantages and are introduced, recently, as promising techniques for the assessment of the biscuit quality.
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Affiliation(s)
- Hayet Ghnimi
- INRAE, Junia, Université d'Artois, University of Lille, Université du Littoral Côte d'Opale, Université de Picardie Jules Verne, Université de Liège, Lens, France.,Higher Institute of Biotechnology of Monastir, University of Monastir, Monastir, Tunisia.,National Engineering School of Sfax, University of Sfax, LR11ES45, Sfax, Tunisia
| | - Monia Ennouri
- Olive Tree Institute, University of Sfax, LR16IO01, Sfax, Tunisia
| | - Christine Chèné
- Tilloy Les Mofflaines, Adrianor, Tilloy-lès-Mofflaines, France
| | - Romdhane Karoui
- INRAE, Junia, Université d'Artois, University of Lille, Université du Littoral Côte d'Opale, Université de Picardie Jules Verne, Université de Liège, Lens, France
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Zaroual H, Chénè C, El Hadrami EM, Karoui R. Application of new emerging techniques in combination with classical methods for the determination of the quality and authenticity of olive oil: a review. Crit Rev Food Sci Nutr 2021; 62:4526-4549. [DOI: 10.1080/10408398.2021.1876624] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Affiliation(s)
- Hicham Zaroual
- Université d'Artois, UMRT 1158 BioEcoAgro, ICV-Institut Charles VIOLLETTE, Lens, France
- Sidi Mohamed Ben Abdellah University, Applied Organic Chemistry Laboratory, Fez, Morocco
| | | | - El Mestafa El Hadrami
- Sidi Mohamed Ben Abdellah University, Applied Organic Chemistry Laboratory, Fez, Morocco
| | - Romdhane Karoui
- Université d'Artois, UMRT 1158 BioEcoAgro, ICV-Institut Charles VIOLLETTE, Lens, France
- INRA, USC 1281,Lille, France
- Yncréa, Lille, France
- University of the Littoral Opal Coast (ULCO), Boulogne sur Mer, France
- University of Lille, Lille, France
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