BACKGROUND:Qinghai-Tibet Plateau (QTP) rape honey, recognized as a Protected Geographical Indication (PGI) product in China, has faced significant challenges due to fraudulent mislabeling of its origins in the market. To ensure the authenticity of PGI honey products and uphold market integrity, it is crucial to develop a rapid, precise, and efficient geographical traceability technology. OBJECTIVE:This study investigated the stable isotope signatures of rape honey from the Qinghai-Tibet Plateau (QTP) and the southern region (SR) for identifying key geographical indicators for the origin traceability of rape honey products in QTP. The research compared isotopic differences and elucidated their formation mechanisms across bulk honey, saccharides, and proteins. Finaly, multivariate discrimination models were established for specifically identifying QTP-origin rape honey, with optimized parameters to improve discrimination accuracy. METHODS:A total of 208 honey samples were collected from QTP (n = 71) and five provinces in the southern region (SR, n = 137) of China. Stable isotope ratios (δ13C, δ15N, δ2H, and δ18O) of bulk honey, endogenous proteins, and saccharides (glucose, fructose, and sucrose) were measured. One-way analysis of variance (ANOVA) was employed to analyze regional differences among the variables. Partial least-squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) models were constructed based on stable isotopic data to discriminate honey sample origins. RESULTS:ANOVA indicated the geospatial differences (P < 0.05) in δ2H and δ18O of bulk honey, as well as all four ratios of honey protein, are significant between QTP and SR. LDA exhibited superior discrimination performance, with leave-one-out cross-validation accuracies of 87.3% for QTP and 89.1% for SR. CONCLUSIONS:An integrated strategy combining stable isotope ratios analysis with multivariate modeling provides an accurate and effective verification method for geographical origin traceability of high-value honey from QTP. This approach provides a reliable tool to address the issue of fraudulent mislabeling of PGI rape honey. HIGHLIGHTS:Stable isotopic signatures of QTP rape honey were discussed. Bulk and component-specific isotopic ratios were informative geospatial indicators. Machine learning algorithms significantly enhanced honey origin discrimination. LDA accuracy for QTP honey samples reached up to 87.3%. This strategy was developed to combat origin mislabeling and ensure food integrity.

Abstract The traditional grazing system of the Qinghai-Tibet Plateau faces challenges such as feed shortages, despite the abundance of pastures during the warm season. However, the impact of supplemental feeding on yak meat quality during this period still requires further investigation. A total of 30 male yaks (with similar genetic backgrounds, aged 2.5–3 years, weighing 94.56 ± 3.9 kg) were evenly and randomly assigned to two groups: the traditional grazing group (G) and the supplemental feeding group (SF). This study evaluated the effects of supplementation on yak meat quality and metabolic characteristics, aiming to identify effective dietary strategies to improve the physical and nutritional quality of yak meat. Non-targeted metabolomics (UHPLC-QE-MS) was used to analyze biomarkers of meat quality. Results revealed that the SF group exhibited superior meat quality, with a 39.6% reduction in shear strength, a 22.4% reduction in cooking loss, a 15% increase in PUFA/SFA ratios, and an 18% increase in essential amino acid content. Metabolomic profiling indicated distinct differences between the two groups, with the SF group demonstrating significant upregulation of beneficial metabolites (e.g., pyruvic acid, L-tyrosine, and eicosapentaenoic acid) and downregulation of harmful metabolites (e.g., sulfates). These changes improved protein turnover, lipid metabolism, and glycolytic activity, enhancing meat tenderness, flavor, and nutritional value. This study provides novel insights into the metabolic mechanisms underlying feed-induced quality changes, highlighting the practical value of supplemental feeding in overcoming the limitations of traditional grazing systems and reducing ecological pressure on grasslands.

The stable carbon (C) and nitrogen (N) isotopic ratios and their concentrations in green tea were ascertained across distinct harvest periods within a microclimate setting. The findings revealed statistically significant variations in the delta N-15 (1.67 f 2.60 %o to 4.47 f 0.68 %o), N% (4.59 f 0.38 % to 6.18 f 0.48 %), and (SC)-C-13 (-27.91 f 0.65 %o to -25.99 f 0.95 %o) values among tea samples collected at different harvest periods (p < 0.05). Typically, these isotopic parameters exhibited an initial depletion indicative of climatic influence, succeeded by an enrichment phase. In contrast, C% demonstrated minimal variation across harvest periods (p > 0.05), which consistently ranged from 45.93 f 4.02 % to 47.44 f 1.01 %. Redundancy analysis and Pearson correlation elucidated the impact of climatic variability on isotopic fractionation within the tea samples. Specifically, S15N values displayed a significant positive correlation with temperature and solar irradiance but a negative correlation with other climatic elements. Conversely, N% exhibited an inverse correlational trend relative to S15N under identical conditions. For S13C, a predominantly negative correlation with climatic factors was observed. The study has delineated the influence of climatic fluctuations on the isotopic composition of tea, offering a valuable theoretical basis for enhancing traceability through stable isotope-based methodologies.

The mislabeling of kiwifruit origin frequently disturbs market competition and governmental supervision, significantly undermines brand reputation and consumer rights. In this work, a total of 370 kiwifruits from 8 different countries in global were collected, and 6 stable isotope ratios (SIRs), 10 mineral elements (MEs), and 16 rare earth elements (REEs) were determined for origin traceability study. One-way analysis of variance (ANOVA) showed that regional differences of 32 variables are at significant level (P value =0.00). Supervised methods, partial least squares-discriminant analysis (PLS-DA) and its derivative algorithm (OPLS-DA), linear discriminant analysis (LDA), enhanced identification performance and finally elevated the accuracies to 100 % for all kiwifruit origins. Lu, Tb, Eu, Ho, Pm, Y, δ34S, δ2H, δ15N, Mg, Se were main contributive variables for LDA modeling (AUC value >0.5). A blind test was conducted using 63 samples randomly selected from Chinese market. The predicted result indicated a significantly high probability of origin mislabeling of imported kiwifruit products, with percentages ranging from 30.0 % to 90.0 %. This study may provide technical supports for combating origin mislabeling conduct, and ensuring food authenticity of kiwifruit in global trade.

Mycotoxin in grape and its products (wine, raisin) is a widely concerned issue of food safety, it closely associated with consumers’ health. In this study, an analytical strategy by combining second-order calibration method with excitation-emission matrix (EEM) fluorescence detection followed photo derivatization (PD) was explored for rapid and sensitive analysis of aflatoxin B1 (AFB1), ochratoxin A (OTA), zearalenone (ZEA) in grape, raisin and wine. Except simple solvent extraction by ethyl acetate and concentration by vacuum distillation, samples don’t need other complicated treatment steps any more. With the aid of predominant second-order advantages of alternative trilinear decomposition (ATLD) algorithm, ‘pure’ spectra and quantitative signals of targeted mycotoxins can be resolved from the heavily interfered EEM profile of sample even in the presence of spectral overlaps and unknown backgrounds. The recoveries of AFB1, OTA and ZEA in four kinds of samples are in the range of 90

Astragalus membranaceus (AM), a well-known traditional Chinese medicine (TCM), has been found to exhibit significant therapeutic effects on T2DM. The mechanism of AM (root) extract ameliorating diabetes and its medicinal components were deep inverstigated in this work. A mouse oral trial, LC-HRMS-based untargeted metabolomics, quantitative spectrum effect relationship analysis (QSERA), and network pharmacology was integrated for this studying. With the aid of data-mining by AntDAS (Automatic Data Analysis Strategy) platform, 59 bioactive compounds involved in the Leprdb/db mouse model of T2DM therapy were screened from LC-HRMS fingerprints of AM (root) extract even in the presence of heavily interfered background. The key bioactive AM (root) metabolites, astragaloside and l-arabinose, influence T2DM targets including IL2 and HSP90AA1. Molecular docking experiment revealed high-affinity binding between astragaloside and l-arabinose and these core targets. QSERA predicted the specific regulatory effects of bioactive compounds on T2DM in mice. This integrated approach provides a novel strategy for interpreting the pharmacodynamic effects of AM (root) extract in T2DM, which may facilitate the clinical application of traditional Chinese medicine.

The present study aimed to investigate the variations in the nutritional composition, antioxidant capacity, and metabolite profile of lilies subjected to different drying treatments, including vacuum freeze drying (VFD), hot air drying (HAD), vacuum drying (VD), and infrared drying (ID). The results show that VFD provided better preservation of the original coloration and displayed the highest levels of total amino acid content, total phenolic content, total flavonoid content, and polysaccharide and alkaloid content. Our results reveal that VFD treatment can be employed to obtain high-quality lilies with desirable appearance characteristics and nutrient compositions. Metabolomics analysis identified a total of 464 metabolites from various dried lilies. Differential metabolite screening found 150 differential metabolites across all pairwise comparisons. Hierarchical clustering analysis (HCA) indicated that lilies subjected to VFD treatment exhibited a higher abundance of steroids, saponin, flavonoids, and phenolic glycoside, whereas those subjected to HAD, VD, or ID treatments showed relatively elevated levels of specific amino acids or derivatives. This study elucidates the significant impact of various drying treatments on the quality and metabolic profile of lilies, thereby providing valuable insights for enhancing the nutritional quality of processed lilies.

The farming pattern of crayfish significantly impacts their quality, safety, and nutrition. Typically, green and ecologically friendly products command higher economic value and market competitiveness. Consequently, intensive farming methods are frequently employed in an attempt to replace these environmentally friendly products, leading to potential instances of commercial fraud. In this study, stable isotope and multi-element analysis were utilized in conjunction with multivariate modeling to differentiate between pond-intensive, paddy-ecologically, and free-range cultured crayfish. The four stable isotope ratios of carbon, nitrogen, hydrogen, and oxygen (δ13C, δ15N, δ2H, δ18O) and 20 elements from 88 crayfish samples and their feeds were determined for variance analysis and correlation analysis. To identify and differentiate three different farming pattern crayfish, unsupervised methods such as hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used, as well as supervised multivariate modeling, specifically partial least squares discriminant analysis (PLS-DA). The HCA and PCA exhibited limited effectiveness in classifying the farming pattern of crayfish, whereas the PLS-DA demonstrated a more robust performance with a predictive accuracy of 90.8%. Additionally, variables such as δ13C, δ15N, δ2H, Mn, and Co exhibited relatively higher contributions in the PLS-DA model, with a variable influence on projection (VIP) greater than 1. This study is the first attempt to use stable isotope and multi-element analysis to distinguish crayfish under three farming patterns. It holds promising potential as an effective strategy for crayfish authentication.

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.

Atractylodes macrocephala Koidz (AMK) is an expensive edible Chinese herb with medicinal properties. Its economic value and medicinal properties are closely related to its geographical origin. In this study, a method based on stable isotopes and multiple elements combined with chemometrics was developed to identify the geographical origin of AMK. Five stable isotope ratios, including δ2 H, δ18 O, δ13 C, δ15 N, and δ34 S, and 41 elements in 281 AMK samples from 10 regions were analyzed. An analysis of variance of stable isotope ratios and elements revealed that the δ2 H, δ18 O, Mg, Ca, and rare-earth element concentrations in AMK from different geographical regions were significantly different. Orthogonal partial least squares discriminant analysis proved that Ca, K, Mg, and Na can be used for classifying (variable importance >1) and accurately identifying AMK from Panan, Xianfeng, and other areas with 100% discrimination accuracy. In addition, we achieved a good identification of protected geographic indication products of similar quality. This method realized the geographical discrimination of AMK from different producing areas and could potentially control the fair trade of AMK. PRACTICAL APPLICATION: The quality of AMK is highly dependent on its geographical origin. Confusion over the origin of AMK impacts consumer rights. This study developed an accurate and effective classification method based on stable isotopes and multiple elements to ascertain the geographical origin of AMK, thereby providing an effective method for determining its quality.

A multi-functional nanoflares biosensor of spherical gold nanoparticle (Au NP) modified by fluorophore-labeled oligonucleotides (ONS) was designed for ultra-sensitive multi-target mycotoxin analysis in food. Au NP was densely modified with multiplex highly oriented hairpins of oligonucleotides (ONS), each ONS was hybridized to a reporter with a distinct fluorophore label and specifically affiliative to its corresponding mycotoxin target. The fluorescent signals of reporters were pre-quenched by Au NP based on ONS hairpin structures and recovered when exposed to ONS's targets. Excitation-emission matrix (EEM) fluorescence detection was performed in EX and EM wavelength of 200-800 nm. Heavily overlapping spectra of fluorophores, mycotoxins and backgrounds were resolved by alternative trilinear decomposition (ATLD) algorithm, pure spectra of specific fluorophore responding to mycotoxin target can be extracted out for quantitative analysis. Four mycotoxins (Aflatoxin B1, zearalenone, Fumonisins B1, ochratoxin A) were simultaneously quantified at extremely low level with limit of detection <0.02 mu g kg-1, the average recovery accuracies were higher than 91.7 % in various matrices of cereals, nuts, edible oils. This study realized an important breakthrough of the application of nanoflares biosensor and maybe promising to be as an alternative strategy for onsite mycotoxins monitoring of food.

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.

In this study, an accurate, rapid, green, and environment friendly method for the extraction and quantitative analysis of flavonoids in honey was established by using the aqueous two-phase extraction combined with the chemometrics-assisted HPLC-DAD. The first purpose of this study was to extract seven flavonoids in five different types of honey using alcohol/salt aqueous two-phase system (ATPS). The system with 2.82 mL sodium citrate (30%), 1.58 mL water, and 3.10 mL isopropanol, showed the highest flavonoids extraction yields in the top phase (87.66–101.50%). Additionally, the three-way array of honey samples based on HPLC-DAD was decomposed mathematically by the alternating trilinear decomposition (ATLD) algorithm to obtain reasonable chromatograms, spectra, and concentration profiles for each analyte. Compared with the traditional solid-phase extraction method, the ATPS-ATLD-based method showed satisfactory spiked recoveries, lower limit of detection, and higher sensitivity, further verifying its accuracy and stability.

In this paper, a combination of non-targeted metabolomics and multi-element analysis was used to investigate the impact of five different cultivars on the sensory quality of QTMJ tea and identify candidate markers for varietal authenticity assessment. With chemometric analysis, a total of 54 differential metabolites were screened, with the abundances significantly varied in the tea cultivars. By contrast, the QTMJ tea from the Yaoshan Xiulv (XL) monovariety presents a much better sensory quality as result of the relatively more abundant anthocyanin glycosides and the lower levels of 2′-o-methyladenosine, denudatine, kynurenic acid and L-pipecolic acid. In addition, multi-elemental analysis found 14 significantly differential elements among the cultivars (VIP > 1 and p < 0.05). The differences and correlations of metabolites and elemental signatures of QTMJ tea between five cultivars were discussed using a Pearson correlation analysis. Element characteristics can be used as the best discriminant index for different cultivars of QTMJT, with a predictive accuracy of 100%.

The husbandry pattern of yak meat is a crucial factor for its market price and competitiveness; deliberately mislabeling of the production information will cause consumer confidence crisis. In this work, stable isotope signatures of free-range grass-fed (FRG) and captive grain-fed (CG) yak meat were analyzed for their discrimination. δ13C, δ2H, δ18O, δ15N, δ34S of bulk muscle and δ13C of six fatty acids were respectively determined by EA–IRMS and GC–C–IRMS. ANOVA and correlation analysis of stable isotope ratios of yak muscle and fatty acids against its feed indicated that their δ13C, δ15N, δ34S significantly are related, which provides the evidence of diet and trophic information. δ13C of six fatty acids (FAs) are significantly different (p < 0.05) between two patterns; all FAs of FRG yak meat are highly related to grass silage (R > 0.70), but saturated and unsaturated FAs of CG yak meat are respectively related to soybean silage (R > 0.70) and maize silage (R > 0.56). PLS-DA and LDA modeling based on stable isotope ratios of yak muscle and FAs together discriminate yak meat from these two husbandry patterns with accuracies of 100 %. This strategy may be promising as a feasible method for confirming the husbandry patterns of yak meat, ensuring label authenticity and food safety.

Samples of New Zealand (NZ) butter (20), Australian butter (2) and USA butter (1), all with assured traceability, were characterised using stable isotopes. A further 45 butter samples from a range of geographical origins sold in Chinese supermarkets were compared for traceability evaluation purposes. Supervised PLS-DA of bulk butter and protein isotopes accurately distinguished genuine NZ butter from China, USA and European labelled butter. Carbon (bulk and protein) and sulphur (protein) isotopes of NZ butter had the highest discrimination ability due to characteristic isotope signatures arising from C3 pastoral feed and coastal proximity of NZ's farming regions; NZ butter was not completely discriminated from Australian or Irish butter due to similar dairy farming practices and environmental conditions. Nonetheless, stable isotopes could reliably identify NZ butter from Chinese, USA and European labelled products offering a useful tool to recognise mislabelled premium NZ butter in several key international export markets.

Abstract Mycotoxin risks in grape and its products (wine, raisin) are widely concerned food safety issues, it closely associated with consumers’ health. In this study, an analytical strategy by combining second-order calibration method with excitation-emission matrix (EEM) fluorescence detection followed photo derivatization (PD) was explored for rapid and sensitive analysis of aflatoxin B1 (AFB1), ochratoxin A (OTA), zearalenone (ZEA) in grape, raisin and wine. Except simple solvent extraction by ethyl acetate and concentration by vacuum distillation, samples don’t need other complicated treatment steps any more. With the aid of predominant second-order advantages of alternative trilinear decomposition (ATLD) algorithm, ‘pure’ spectra and quantitative signals of targeted mycotoxins can be resolved from the heavily interfered EEM profile of sample even in the presence of spectral overlaps and unknown backgrounds. The recoveries of AFB1, OTA and ZEA in four kinds of samples are in the range of 90–110%, the limits of detection (LODs) were low to 0.1 µg kg− 1, 0.5 µg kg− 1 and 0.8 µg kg− 1, respectively. This analytical strategy may be as an alternative method for improving mycotoxin analysis in complex food matrices and ensuring food safety in grape industry.

Stable isotope and multi-element analytical techniques with chemometrics were developed to trace the origin authenticity of rice in China market. In the long-term study from 2017 to 2020, a total of 115 batches of rice samples from 8 main producing areas of 7 Asian countries were determined 5 stable isotope ratios and 18 elemental contents. One-way analysis of variance (ANOVA) and various multivariate modeling methods were performed for the origin discrimination. Supervised multivariate modeling including partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) can realize more satisfactory identifica-tion of 8 rice origins than ANOVA comparison and unsupervised methods, their leave-one-out cross-validation accuracies approach 85.0 % and 90.9 %, respectively. delta 2H, delta 13C, Ba, Al, Mg, delta 34S, Pb and delta 18O were screened as the most important variables for rice origin traceability (VIP > 1 or AUC > 0.5). This analytical strategy combining maybe promising to ensure the origin authenticity and combat illegal mislabeling in rice trade.