An innovative approach for real-time authentication of cocoa butter using a combination of rapid evaporative ionization mass spectrometry and chemometrics. (March 2022)

• Record Type: Journal Article
• Authors: Chang, Yuwei; Chan, Li Yan; Kong, Fanzhou; Zhang, Guangtao; Peng, Hong
• Is Part Of: Food control. Volume 133:Part B(2022)
• Publication Date: 2022-03
• Subjects: Cocoa butter -- Cocoa butter equivalents -- Rapid evaporative ionization mass spectrometry -- Real-time authentication -- Chemometrics -- One-class classification; Food -- Quality -- Periodicals; Food -- Analysis -- Periodicals; Food handling -- Periodicals; Food industry and trade -- Quality control -- Periodicals; Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques; Aliments -- Qualité -- Périodiques; Aliments -- Analyse -- Périodiques; Hygiène alimentaire -- Périodiques; Food -- Analysis; Food handling; Food -- Quality; Periodicals; Electronic journals; 664.07
• DOI: 10.1016/j.foodcont.2021.108617
• Languages: English
• ISSNs: 0956-7135

Abstract

Abstract: Cocoa butter (CB) is one of the most valuable raw materials in the chocolate industry, and its authenticity is essential to guarantee the safety and quality of chocolate products. For the first time, a real-time and high-throughput method using rapid evaporative ionization mass spectrometry (REIMS) was developed to determine the authenticity of CB. Various types of CB and cocoa butter equivalents (CBEs), as well as CB adulterated by the addition of CBEs, were measured, and different chemometric approaches were implemented for different adulteration scenarios. Hierarchical cluster analysis (HCA) was performed to obtain an overview of the dataset, exploring similarities and differences between CB and CBEs. An orthogonal partial least squares-discriminant analysis (OPLS-DA) model was developed to differentiate between authentic and adulterated CB. A classification accuracy of 100% was achieved, and CBEs could be detected at a level of 10%. A one-class support vector machine (OCSVM) model capable of detecting unsuspected adulterants was successfully built. This model had 95% specificity and 100% sensitivity. Single-origin CB was successfully differentiated from blended CB. This study demonstrated that REIMS could be used as a rapid and sensitive approach for authentication and adulteration analysis of CB. The methodology could enhance the ability of chocolate manufacturers in ensuring the authenticity of their products, helping to avoid complex and ever-changing fraudulent activities. Highlights: A REIMS method was developed for the real-time authentication of cocoa butter. The OPLS-DA model developed can detect CBEs as an adulterant at a level of 10%. The OCSVM model developed can detect unsuspected adulterants. The method can distinguish single-origin cocoa butter from blended cocoa butter. Discriminatory markers in CBEs and single-origin cocoa butter were identified.