The deliberately origin mislabeling of sweet cherry causes significantly disruptions to market integrity and consumers' trust. In this study, 153 cherry samples from five provinces in China and the corresponding irrigation water and soil samples were collected. 5 stable isotope ratios (δ13C, δ15N, δ2H, δ18O, 87Sr/86Sr) and 8 multi-element contents (Na, Mg, P, K, Ca, Fe, Zn, Se) of cherry were determined by EA-IRMS and ICP-MS to study isotopic fractionation and elemental enrichment mechanisms for origin traceability. The results show the δ2H and δ18O of cherry exhibit a strong correlated with its irrigation water (r2 > 0.85), while δ15N, 87Sr/86Sr, Fe, Zn and Se contents are related to its cultivated soil (r2 > 0.75), and the δ13C is related to the local microclimate. ANOVA reveals that the regional differences of δ13C, δ2H, δ18O, 87Sr/86Sr as well as Na, Mg, Ca contents of cherry are significant (P < 0.05), and are important geographical indicators. Various multivariate modeling methods, HCA, PLS-DA, and LDA, were employed with the overall accuracy exceeding 90%. This strategy provides an effective mean to verify the label authenticity of cherry origin in Chinese market.

A strategy combining stable isotope and multi-element analysis with chemometrics was developed for origin traceability of cherry products from five provinces of China (Liaoning, Shandong, Hebei, Sichuan, Shannxi). The relationships of stable isotope and multi-element signatures of cherry with irrigation water and cultivated soil in its origin are discussed. One-way analysis of variance (ANOVA) indicates that the regional differences of δ13C, δ2H, δ18O, 87Sr/86Sr, Na, Mg, Ca, Fe, Zn and Se are significant (P<0.05) and can be as indicators for cherry origin traceability. Multivariate modeling of stable isotope and multi-element data of cherry using hierarchical cluster analysis (HCA), partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA) was conducted and compared. The discriminant accuracy of PLS-DA was unsatisfactory for all origins of China, but it was significantly improved by LDA, in which 153 cherry samples from five provinces can be accurately identified with accuracy higher than 90%.

Endogenous SEM (SEMend) naturally occurs in crustacea aquatic products, it confuses the legal verdict of exogenous SEM (SEMex) degraded by antibiotic nitrofurazone abuse. In the present study, compound-specific gas phase chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) analysis coupled with a two-step pre-column derivatization was developed for determining the nitrogen stable ratio (815N) of SEM in shrimp and crab. The optimal derivatization and solid phase extraction (SPE) condition of SEM were screened by Plackett-Burman design and central composite design (CCD) experiment. The nitrogen isotope ratio analysis (NSIRA) of SEM in two types of crustaceans proved that its 815N values significantly decreased from 7.0 parts per thousand to 2.0 parts per thousand once nitrofurazone being used. Analytical results found that the 815N value of SEMex in vivo was consistent its nitrofurazone precursor but the value of SEMend was dependent on N-containing components (e.g., tissue protein), ANOVA showed significant difference between two types of SEM (p < 0.05). Based on the 815N vari-ations between SEM itself and its nitrofurazone precursor, tissue protein of crustaceans, the percentages of SEMex and SEMend can be calculated for its source apportionment in vivo. The limit of detection of SEM is down to 0.21 mu g kg- 1 and 0.54 mu g kg -1, and the identification lower limit of SEMex are accurate at 6.27% and 0% for two types of crustaceans. The strategy first realized the independent determination of SEMex and SEMend in crustacea aquatic products, which explained that high-level SEM in crustaceans can't as the legal verdict of nitrofurazone abuse in aquaculture.

Multi-stable isotope ratio analysis (δ13C, δ15N, δ34S, δ2H, δ18O) of shrimp tail shell was first explored for the origin traceability and farming pattern authentication of shrimp products in Chinese market. Relative to shrimp tail meat, tail shell was found to be more excellent material for stable isotope analysis, it did not need of complicated degreasing pretreatment and can closely reflect the diet source and trophic level of shrimp during the latest growth cycle after molting. The study proved that δ15N and δ34S values of shrimp tail shell highly correlated with its feedstuff and habitat environment, and can be as the most important geographical indexes for origin traceability and authentication purpose. Multivariate modeling of 5 stable isotope ratios discriminates 320 shrimp samples of three farming patterns (wild-caught, coast-pond and freshwater farming) with accuracies close to 100%, 192 coast-pond farming shrimp samples from five countries with accuracies higher than 90%, respectively.

1H nuclear magnetic resonance (NMR)-based untargeted metabolomics has been extensively used for the geographical discrimination of food samples. In analyzing complex samples, this technique faces the challenges of baseline drift and NMR peak position shifts, resulting in inaccurate geographical discrimination by current chemometric models, like partial least squares. To address this problem, we provide a novel automatic untargeted chemometrics strategy named AntDAS-NMR in this work. AntDAS-NMR utilizes the originally acquired NMR spectra as inputs to automatically perform baseline drift correction, NMR peak detection, NMR peak-based spectrum alignment, and geographical discrimination analysis. The developed strategy is used for the geographical discrimination of Goji honey samples from the northwest zones of China. Results indicate that with the aid of AntDAS-NMR, the artifacts of baseline drifts and NMR peak shift that influence the geographical discrimination model can be reasonably resolved and that Goji honey samples from various provinces of China can be satisfactorily classified. Additionally, the performance of AntDAS-NMR is comparable with classic NMR data analysis tools, like COW, icoshift, PAFFT, and RAFFT. In conclusion, the AntDAS-NMR may be used as a candidate for 1H NMR-based untargeted metabolomics.