Data fusion by ratio modulation of stable isotope, multi-element, and fatty acids to improve geographical traceability of lamb

Combining stable isotopes and multi-elements with machine learning chemometric models to identify the geographical origins of Tetrastigma hemsleyanum Diels et Gilg

Tetrastigma hemsleyanum Diels et Gilg (T. hemsleyanum) is an edible plant with considerable medicinal properties, the quality of which varies depending on its origin. Therefore economically motivated adulteration has emerged. So there is an urgent need to develop effective techniques for determining the origin of T. hemsleyanum. This study combined stable isotopes and multiple elements with machine learning chemometric models (SVM, RF and FNN models) for T. hemsleyanum origin traceability. The results showed that this approach successfully distinguished T. hemsleyanum form different regions with the SVM, RF and FNN models all displaying a 100 % prediction accuracy and the FNN model exhibiting superior performance. This study provides a technical and theoretical basis for research on the origin traceability of T. hemsleyanum.

Isotope Fingerprinting as a Backup for Modern Safety and Traceability Systems in the Animal-Derived Food Chain

In recent years, due to the globalization of food trade and certified agro-food products, the authenticity and traceability of food have received increasing attention. As a result, opportunities for fraudulent practices arise, highlighting the need to protect consumers from economic and health damages. In this regard, specific analytical techniques have been optimized and implemented to support the integrity of the food chain, such as those targeting different isotopes and their ratios. This review article explores the scientific progress of the last decade in the study of the isotopic identity card of food of animal origin, provides the reader with an overview of its application, and focuses on whether the combination of isotopes with other markers increases confidence and robustness in food authenticity testing. To this purpose, a total of 135 studies analyzing fish and seafood, meat, eggs, milk, and dairy products, and aiming to examine the relation between isotopic ratios and the geographical provenance, feeding regime, production method, and seasonality were reviewed. Current trends and major research achievements in the field were discussed and commented on in detail, pointing out advantages and drawbacks typically associated with this analytical approach and arguing future improvements and changes that need to be made to recognize it as a standard and validated method for fraud mitigation and safety control in the sector of food of animal origin.

A New and Effective Method to Trace Tibetan Chicken by Amino Acid Profiling

As a "rare bird on the plateau", the Tibetan chicken is rich in nutrition and has high medicinal value. In order to quickly and effectively identify the source of food safety problems and to label fraud regarding this animal, it is necessary to identify the geographical traceability of the Tibetan chicken. In this study, Tibetan chicken samples from four different cities in Tibet, China were analyzed. The amino acid profiles of Tibetan chicken samples were characterized and further subjected to chemometric analyses, including orthogonal least squares discriminant analysis, hierarchical cluster analysis, and linear discriminant analysis. The original discrimination rate was 94.4%, and the cross-validation rate was 93.3%. Moreover, the correlation between amino acid concentrations and altitudes in Tibetan chicken was studied. With the increase in altitude, all amino acid contents showed a normal distribution. For the first time, amino acid profiling has been comprehensively applied to trace the origin of plateau animal food with satisfactory accuracy.

Direct analysis in real time high-resolution mass spectrometry for authenticity assessment of lamb

In comparison to more traditional methods of determining food authenticity, such as gas chromatography analysis, the primary advantages of DART-HRMS include its high speed and throughput of analysis. This study used a non-targeted metabolomics method based on real-time high-resolution mass spectrometry combined with chemometric analysis to distinguish lamb samples from four regions. Orthogonal least squares-discriminant analysis revealed a distinct difference between these four lamb regions. The potential markers were chosen based on the variable's importance in projection values, variance, and fold change. A total of 79 markers were identified using the matching chemistry database. These markers differed significantly between lambs in four regions according to heatmap analysis. The linear discriminatory analysis model had an initial classification rate of 100.0% and a cross-validation accuracy of 82.50% on the identified markers. The research demonstrates that DART-HRMS can perform a rapid authentication evaluation of lamb samples.

Proposing Two Local Modeling Approaches for Discriminating PGI Sunite Lamb from Other Origins Using Stable Isotopes and Machine Learning

For the protection of Protected Geographical Indication (PGI) Sunite lamb, PGI Sunite lamb samples and lamb samples from two other banners in the Inner Mongolia autonomous region were distinguished by stable isotopes (δ¹³C, δ¹⁵N, δ²H, and δ¹⁸O) and two local modeling approaches. In terms of the main characteristics and predictive performance, local modeling was better than global modeling. The accuracies of five local models (LDA, RF, SVM, BPNN, and KNN) obtained by the Adaptive Kennard–Stone algorithm were 91.30%, 95.65%, 91.30%, 100%, and 91.30%, respectively. The accuracies of the five local models obtained by an approach of PCA–Full distance based on DD–SIMCA were 91.30%, 91.30%, 91.30%, 100%, and 95.65%, respectively. The accuracies of the five global models were 91.30%, 91.30%, 91.30%, 100%, and 91.30%, respectively. Stable isotope ratio analysis combined with local modeling can be used as an effective indicator for protecting PGI Sunite lamb.

Health risk assessment of heavy metals contamination in selenium-enriched eggs

This study aims to quantify the amount of selenium (Se) generally consumed in the Chinese diet via Se-enriched eggs, as well as the levels of lead (Pb), arsenic (As), cadmium (Cd), chromium (Cr), and mercury (Hg) in such eggs, and to assess the health risks associated with their consumption in China. As would be expected, Se was found to present significantly higher geometric mean levels in the Se-enriched eggs (0.464 mg/kg) than in normal eggs (0.304 mg/kg); however, Se concentrations were also closely related to the Cr and Pb in the eggs, with the Pb levels found to exceed the Chinese standard limit. Therefore, the quantity of Pb in Se-enriched eggs requires attention. According to estimated daily intake (EDI) evaluations of Se and heavy metals, levels were found to be highest via children for all metals in the eggs, In adults, the total target hazard quotient (TTHQ) for Se, Pb, Cd, As, Hg, and Cr contamination in eggs were calculated to be below the standard limit of 1, thus confirming that Se-enriched eggs may be considered safe for consumption by adults. However, the THQ of as was higher than 1 in the children aged of 2-4 years, and the TTHQ values were higher than 1 in boys aged 2-9 and girls aged 2-8, indicating a significant non-carcinogenic health risk due to the intake of maximum metals in the eggs samples. Thus, the safety of selenium-enriched eggs for children should be of wide concern. In conclusion, while Se-enriched eggs offer high levels of selenium, their health safety is concerning.