Advanced process analytical tools for identification of adulterants in edible oils – A review. (1st February 2022)

• Record Type: Journal Article
• Authors: Rifna, E.J.; Pandiselvam, R.; Kothakota, Anjineyulu; Subba Rao, K.V.; Dwivedi, Madhuresh; Kumar, Manoj; Thirumdas, Rohit; Ramesh, S.V.
• Is Part Of: Food chemistry. Volume 369(2022)
• Publication Date: 2022-02-01
• Subjects: Process analytical technology -- Spectroscopy -- Oil quality -- Adulteration of oils -- Chemometrics; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2021.130898
• Languages: English
• ISSNs: 0308-8146

Abstract

Graphical abstract: Highlights: Edible vegetable oil is recurrently adulterated with various low grade vegetable oils. Validation and control of edible oil quality is critical for the food oil processing industry. Process analytical spectroscopic tools was efficiently used for identification of adulterants. Advancements and fundamental notions of spectroscopic techniques are summarized. Application of chemometrics emphasizes the use of NIR, MIR, NMR, FT-IR, HIS and RS in discussed tools. 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.