A two-tiered system of analysis to tackle rice fraud: The Indian Basmati study.

Demand for high quality Basmati rice has increased significantly in the last decade. This commodity is highly vulnerable to fraud, especially in the post COVID-19 era. A unique two-tiered analytical system comprised of rapid on-site screening of samples using handheld portable Near-infrared NIR and laboratory confirmatory technique using a Head space gas chromatography mass spectrometry (HS-GC-MS) strategy for untargeted analysis was developed. Chemometric models built using NIR data correctly predicted nearly 100% of Pusa 1121 and Taraori, two high value types of Basmati, from potential adulterants. Furthermore, rice VOC profile fingerprints showed very good classification (R2 >0.9, Q2 > 0.9, Accuracy > 0.99) for these high quality Basmati varieties from potential adulterant varieties with aldehydes identified as key VOC marker compounds. Using a two-tiered system of a rapid method for on-site screening of many samples alongside a laboratory-based confirmatory method can classify Basmati rice varieties, protecting the supply chain from fraud.

Food Fingerprinting: Using a Two-Tiered approach to Monitor and Mitigate Food Fraud in Rice.

BACKGROUND: Rice is an important staple food that is consumed around the world. Like many foods, the price of rice varies considerably, from very inexpensive for a low-quality product to premium pricing for highly prized varieties from specific locations. Therefore, like other foods it is vulnerable to economically motivated adulteration through substitution or misrepresentation of inferior-quality rice for more expensive varieties. OBJECTIVE: In this article we describe results of a research project focused on addressing potential food fraud issues related to rice supplies in China, India, Vietnam, and Ghana. Rice fraud manifests differently in each country; therefore, tailored solutions were required. METHOD: Here we describe a two-tiered testing regime of rapid screening using portable Near Infrared technology supported by second tier testing using mass spectrometry-based analysis of suspicious samples. RESULTS: Portable Near Infrared spectroscopy models and laboratory-based Gas Chromatography-Mass Spectrometry methods were developed to differentiate between: high-value Basmati rice varieties and their potential adulterants; six Geographic Indicated protected rice varieties from specific regions within China; various qualities of rice in Ghana and Vietnam; and locally produced and imported rice in Ghana. Furthermore, an Inductively Coupled Plasma-Mass Spectrometry method was developed to support the Chinese rice varieties methods as well as a Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry method for quality differentiation in Vietnam. CONCLUSIONS/HIGHLIGHTS: This two-tier approach can provide a substantially increased level of testing through rapid screening outside of the laboratory with the reassurance of corroborating mass spectrometry-based laboratory analysis to support decision making.

Metabolomic fingerprinting of volatile organic compounds for the geographical discrimination of rice samples from China, Vietnam and India.

Rice is one of the most important cereals for human nutrition and is a basic staple food for half of the global population. The assessment of rice geographical origins in terms of its authenticity is of great interest to protect consumers from misleading information and fraud. In the present study, a head space gas chromatography mass spectrometry (HS-GC-MS) strategy for characterising volatile organic compounds (VOCs) profiles to distinguish rice samples from China, India and Vietnam is described. Partial Least Square Discriminant Analysis (PLS-DA) model exhibited a good discrimination (R2 = 0.98182, Q2 = 0.9722, and Accuracy = 1.0) for rice samples from China, India and Vietnam. Moreover, Data-Driven Soft Independent Modelling of Class Analogy (DD-SIMCA) and K-nearest neighbors shown good specificity 100% and accuracy 100% in identifying the origin of samples. The present study established VOC fingerprinting as a highly efficient approach to identify the geographical origin of rice.

Effect-based proteomic detection of growth promoter abuse.

Unregulated growth promoter use in food-producing animals is an issue of concern both from food safety and animal welfare perspectives. However, the monitoring of such practices is analytically challenging due to the concerted actions of users to evade detection. Techniques based on the monitoring of biological responses to exogenous administrations have been proposed as more sensitive methods to identify treated animals. This study has, for the first time, profiled plasma proteome responses in bovine animals to treatment with nortestosterone decanoate and 17ß-oestradiol benzoate, followed by dexamethasone administration. Two-dimensional fluorescence differential in-gel electrophoresis analysis revealed a series of hepatic and acute-phase proteins within plasma whose levels were up- or down-regulated within phases of the treatment regime. Surface plasmon resonance (SPR) immuno-assays were developed to quantify responses of identified protein markers during the experimental treatment study with a view to developing methods which can be used as screening tools for growth promoter abuse detection. SPR analysis demonstrated the potential for plasma proteins to be used as indicative measures of growth promoter administrations and concludes that the sensitivity and robustness of any detection approach based on plasma proteome analysis would benefit from examination of a range of proteins representative of diverse biological processes rather being reliant on specific individual markers.