Search Results (46)

Tetrastigma hemsleyanum Diels et Gilg is a high-value edible and medicinal homologous plant, routinely grown under conventional field or greenhouse production systems across Asia. However, mislabeling of conventional products as the rarer (and more expensive) wild version may occur for financial gain. In this study, stable isotopes (δ¹³C, δ¹⁵N, δ²H, and δ¹⁸O) and metal contents (Cr, Cu, Ni, As, Cd, Pb) were used to characterize plant tissues (tuber root, stem, leaf) and corresponding soils originating from simulated-wild-cultivated (WC) and greenhouse-cultivated (GC) pot trials using the same soil. Carbon and nitrogen isotopes served as key indicators for distinguishing GC and WC products. Specifically, δ¹³C values of GC plant tissues were 1.4 to 2.4‰ more positive than those of WC plant tissues (p < 0.05), and δ¹⁵N values in GC tissues were 2.7 to 4.6‰ more positive than δ¹⁵N in WC tissues (p < 0.01). Lower δ¹⁵N values observed in WC products indicate slower nitrogen turnover compared with GC products. Soil metal concentrations had significant differences between the two cultivation systems, but only limited effects on metal bioconcentration factors (BCFs) and translocation factors (TFs) in T. hemsleyanum tissues. Pb and Cd concentrations in root tissues had large differences between cultivation systems, and carbon dynamics in GC plants were more negatively affected by Pb levels in soils. These findings provide the first investigation of T. hemsleyanum grown under different cultivation practices and establish a scientific basis for distinguishing other wild or simulated-wild labeled food and medicinal plant products from conventionally grown products in future studies. Full article

European pork production pursues traceability and authenticity to ensure animal welfare, food safety, and support products with geographical indications. This study reports a European survey integrating stable isotope ratios (δ¹³C, δ¹⁵N, δ³⁴S, δ¹⁸O, δ²H) and multi-element profiling using IRMS and ICP-MS, on 612 samples collected across Denmark, Poland, Italy, and Spain, with diverse production systems, breeds, feeding, and slaughter ages. Geographical and climatic gradients influenced δ²H and δ¹⁸O, which ranged from −111‰ to −89‰ in samples from Denmark and Spain and from 13.3‰ to 16.0‰ in samples from Italy and Spain, respectively. In selected farms, δ¹³C ranged from −22.7‰ to −17.0‰ depending on diet composition based on C₃ and C₄ plants. The wide variability in pig management practices suggested that δ¹⁵N (2.50 ÷ 4.96‰) increased with slaughter age and was positively correlated with Fe (3.38 ÷ 8.39 mg/kg) and Zn (9.39 ÷ 23.6 mg/kg). Most mineral components were mainly driven by feed formulation and supplementation. Principal component analysis (PCA) showed that samples were grouped based on their origin and husbandry system, confirming the key role of isotopic and elemental markers for the development of a database supporting the pork supply chains across Europe. Full article

Pacific white shrimp (Litopenaeus vannamei) is a major aquaculture product worldwide. For consumers, discriminating domestic from imported sources of shrimp meat, and individual domestic sources, can be highly desirable because of the different meat quality and environmental contamination from geographically different origins of shrimp. This study evaluated the potential of stable isotope analysis (δ¹³C, δ¹⁵N, δ²H, δ¹⁸O) with chemometric models to authenticate the origins of Pacific white shrimp sold in China. Shrimp samples from domestic (Guangxi, Fujian, Shandong, Inner Mongolia) and foreign (Ecuador) sources were analyzed, using statistical analyses. The four-isotope model achieved 89.3% cross-validation accuracy in distinguishing domestic and foreign shrimp, with an overall prediction Area Under the Curve (AUC) of 0.901 (95% CI: 0.819–0.983)—significantly outperforming single-isotope models. Differences in δ¹³C and δ¹⁵N reflected feed source variations, while δ²H and δ¹⁸O (Variable Importance in the Projection (VIP) > 1, key discriminatory indicators) mirrored geographic environmental difference. Although δ¹⁵N did not differ significantly among groups, the combination of all four isotopes reduced limitations of individual δ²H/δ¹⁸O use. This approach enhanced the precision, reliability, and applicability of stable isotope analysis for origin authentication by leveraging complementary isotopic data and robust statistical frameworks. These findings demonstrate the proposed model’s potential as a cost-effective, copyright-compliant framework for shrimp origin authentication, with implications for isotopic traceability across food science fields. Full article

Background: Stable isotope-based analytical methods have brought about a significant transformation in the study of energy nutrient metabolism, enabling precise in vivo measurement of metabolic fluxes at systemic, tissue, and organ-specific levels in both healthy and diseased states. The regulation of these metabolic fluxes is governed by dynamic interactions between proteins, lipids, carbohydrates, and their precursors—such as glucose, fatty acids, and amino acids—as well as final metabolic products. Discussion: Advanced analytical technologies, including nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), which can offer enhanced precision, have been developed for investigating nutrient metabolism and fluxes in humans, providing precise information on metabolic pathways. These techniques have primarily utilized stable isotopes, such as ²H, ¹³C, ¹⁵N, and ¹⁸O, which have largely replaced radioactive isotopes and are now central to metabolic research. These isotopes have been used to label glucose, fatty acids, or amino acids—the main biomolecular precursors—enabling detailed investigation at systemic, tissue, and organ-specific levels of carbohydrate, lipid, and protein metabolism, and revealing pathway alterations associated with diseases conditions, such as diabetes, non-alcoholic fatty liver disease, cardiovascular disorders, and cancer. The use of deuterium oxide (D₂O) has allowed for long-term metabolic studies, providing a cost-effective and less invasive means to monitor metabolic changes over days to months. Total daily energy expenditure can be measured in free living conditions by the doubly stable isotopes ²H- and ¹⁸O-labeled water method. Stable isotope tracing, combined with advanced imaging and modeling, has also been instrumental in assessing body composition, energy expenditure, and nutrient bioavailability. Collectively, these methods have expanded our understanding of human physiology and disease, supporting the development of novel diagnostic tools, the identification of new biomarkers, and the tailoring of nutritional and therapeutic interventions. Conclusions: This review aimed to provide an overview of the applications of stable isotopes for the study of energy nutrient metabolic pathways. The ongoing integration of stable isotope approaches with artificial intelligence, omics technologies, and miniaturized detection techniques could promise to further refine our understanding of human metabolism and drive advances in personalized medicine. Full article

Accurately tracing the geographical origin of Zanthoxylum schinifolium Sieb. et Zucc. is important for brand authentication, quality control, and food safety assurance. In this study, the stable isotope ratios (δ¹³C, δ¹⁵N, δ²H, δ¹⁸O) and the contents of 20 elements were analyzed in samples from three major production regions. Significant differences (p < 0.05) were observed in δ¹³C, δ²H, δ¹⁸O and most elemental profiles across origins. Chemometric methods—including principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), and linear discriminant analysis (LDA)—were applied to classify samples by geographical origin. OPLS-DA identified key discriminators (VIP > 1) such as Ca, δ¹³C, Mg, δ²H, B, δ¹⁸O, Cr, Ni, Na, Pb, As, Co, Se, and Zn, achieving a classification accuracy of 96.8%. LDA based on the combined isotope and element datasets showed even higher performance, with an original discrimination rate of 98.4% and a cross-validated rate of 92.8%. The results demonstrate that integrating stable isotope and multi-element fingerprints with supervised classification models provides a reliable and effective approach for verifying the geographical origin of Zanthoxylum schinifolium, supporting its use in traceability systems and fair trade practices. Full article

China, as the primary importer of Thailand’s high-quality rice (Oryza sativa L.), has an urgent need for effective origin discrimination methods between premium aromatic rice from China and Thailand to prevent origin mislabeling issues. In this study, stable isotope and elemental multivariate analysis combined with partial least squares discriminant analysis (PLS-DA) were used to build an origin traceability model for Chinese and Thai rice from different production areas. Multivariate analysis of variance revealed that Thai rice exhibited significantly higher δ¹³C (−26.4 ± 0.4‰) and δ¹⁸O (25.9 ± 1.1‰) values, but a significantly lower δ¹⁵N value (3.5 ± 0.8‰) compared to the three major producing regions of China. These differences are directly related to geographical and climatic factors such as latitude, precipitation, and temperature. A PLS-DA model demonstrated high performance in the classification of different Chinese indica rice and Thailand rice origins. Through cross-validation, the classification accuracy for the training set reached 97.3%. For the independent testing set, the classification accuracy was recorded to be 95.0%. Furthermore, external blind sample verification was conducted, and the classification accuracy achieved was 100%. Ca, K, Na, δ¹⁸O, Zn and δ²H were found to be important variables to discriminate between Chinese indica rice and Thai rice. Finally, for country of origin labelling claims, this rice study provides the basis for a suitable regulatory method to detect mislabeled Thai origin rice and prevent fraud. Full article

The Chinese mitten crab (Eriocheir sinensis) from Yangcheng Lake is a globally renowned geographical indication product. To characterize changes in stable isotopic signatures in this species in Yangcheng Lake during the year-round culture period, this study investigated the dynamic changes in stable isotopic fingerprints (δ¹³C, δ¹⁵N, δ²H and δ¹⁸O) of the third pereiopod across an annual aquaculture cycle. Isotopic ratios were analyzed via one-way ANOVA, principal component analysis (PCA), linear discriminant analysis (LDA) and Pearson correlation analysis. Results demonstrated that δ¹³C stabilized after six months of cultivation, showing no significant temporal variation (p > 0.05). Multivariate statistical analysis further revealed that the samples cultured in the initial period could be clearly differentiated in both PCA and LDA plots. However, after six months, the monthly sample points became highly overlapping and indistinguishable, indicating that the crabs had developed stable and consistent isotopic “fingerprints” by that time. Pearson correlation analysis indicated significant correlations among all other isotope pairs, with the exception of δ¹⁵N and δ²H. This study confirms that isotopic signatures require prolonged cultivation (≥6 months) to reflect authentic geographical traits. In addition, our findings provide a basis for verifying the origin of Chinese mitten crab and other aquatic taxa in Yangcheng Lake. Full article

Grapevine water relations are increasingly influenced by drought under climate change, with significant implications for yield, fruit composition and wine quality. Stable isotopes of hydrogen, oxygen, carbon and nitrogen (δ²H, δ¹⁸O, δ¹³C and δ¹⁵N) provide sensitive tracers of plant water sources and physiological responses to stress. Here, we combined dual water isotopes (δ²H, δ¹⁸O), carbon and nitrogen isotopes (δ¹³C, δ¹⁵N), and high-resolution micrometeorological/soil observations to diagnose drought dynamics in Vitis vinifera cv. Sauvignon blanc (Orlești, Romania; 2023–2024). Dual-isotope relationships delineated progressive evaporative enrichment along the soil–plant–atmosphere continuum, with slopes LMWL ≈ 6.41 > stem ≈ 5.0 > leaf ≈ 2.2, consistent with kinetic fractionation during transpiration (leaf) superimposed on source-water signals (stem). Weekly leaf δ¹⁸O covaried strongly with relative humidity (RH; r = −0.69) and evapotranspiration (ET; r = +0.56), confirming atmospheric control of short-term enrichment, while stem isotopes showed buffered responses to soil water. We integrated Δ¹⁸O (leaf–stem), RH, ET, and soil matric potential at 60 cm (Soil₆₀) into an Isotopic Drought Index (IDI), which captured the onset, intensity, and persistence of the July–August 2024 drought (IDI_0–100 > 90; RH < 60%, ET > 40 mm wk⁻¹, Soil₆₀ > 100 cb). Carbon and nitrogen isotopes provided complementary, integrative diagnostics: δ¹³C increased (less negative) with drought (r = −0.52 with RH; +0.49 with IDI), reflecting higher intrinsic water-use efficiency, whereas δ¹⁵N rose with soil dryness and IDI (leaf: r ≈ +0.48 with Soil₆₀; +0.42 with IDI), indicating constraints on N acquisition and enhanced internal remobilization. Together, multi-isotope and environmental data yield a mechanistic, field-validated framework linking atmospheric demand and edaphic limitation to vine physiological and biogeochemical responses and demonstrate the operational value of an isotope-informed drought index for precision viticulture. Full article

The Chuankou deposit is a super-large W deposit formed during the Indosinian collision event in South China, and its mineralization is suggested to be related to the Indosinian muscovite granite. However, two types of W mineralizations were discovered in the Caledonian granite porphyry in the Chuankou W deposit: disseminated scheelite and quartz-wolframite-scheelite vein mineralizations. The genesis of W mineralization in the Caledonian granite porphyry is not yet clear. This paper focuses on fluid microthermometry and stable isotopes (C, H, O, S) analysis of the quartz and scheelite in the ores in the Caledonian granite porphyry in the Chuankou W deposit. The aims are to determine the nature and evolution of the ore-forming fluids, the origin of the ore-forming materials involved in the two types of W mineralization in the Caledonian granite porphyry, and to provide a detailed discussion of the deposit’s genesis. Microthermometry results of fluid inclusions with scheelite and quartz from two stages show that the average homogenization temperature in the quartz-veins within the Caledonian granite porphyry is 248 °C, and the average salinity is 6.31 wt.% NaCl eq (n = 85), the average homogenization temperature in the quartz-veins within the slate is 219 °C, and the average salinity is 5.57 wt.% NaCl eq (n = 49). The ore-forming fluids experienced an evolution from high temperature and high salinity to low temperature and low salinity. Sulfur isotope compositions show that the δ³⁴S values of pyrite and arsenopyrite in the quartz-veins within the Caledonian granite porphyry are 2.06 to 3.28‰ and −0.38 to 0.21‰, respectively, and the δ³⁴S value of pyrite in the quartz-veins within the slate is −1.72 to 0.47‰. The δ³⁴S values of each stage are close to 0‰, indicating that the origin of sulfur mainly from magma. The H-O isotope compositions of the quartz indicate that the ore-forming fluid was primarily magmatic water. The low δ¹⁸O_H2O values (1.74 to 1.58‰) are influenced by fluid–rock interactions or the incorporation of atmospheric precipitation. The carbon isotopes (δ¹³C = −9.5 to 8.3‰) indicate a magmatic origin, but the C isotopes of quartz in the quartz-veins within the slate shift toward sedimentary rocks, reflecting the incorporation of rock components in the late mineralization period. These isotopic differences indicate that the fluid–rock interaction gradually strengthened during fluid evolution. Full article

The Chinese mitten crab (Eriocheir sinensis) industry is currently facing the challenges of origin fraud, as well as a lack of precision and interpretability of existing traceability methods. Here, we propose a high-precision origin traceability method based on a combination of stable isotope analysis and interpretable machine learning. We sampled Chinese mitten crabs from six origins representing diverse aquatic environments and farming practices, and analyzed their δ¹³C, δ¹⁵N, δ²H, and δ¹⁸O stable isotope compositions in different sexes and tissues (hepatopancreas, muscle, and gonad). By comparing the classification performance of Random Forest, XGBoost, and Logistic Regression models, we found that the Random Forest model outperformed the others, achieving high accuracy (91.3%) in distinguishing samples from different origins. Interpretation of the optimal Random Forest model, using SHAP (SHapley Additive exPlanations) analysis, identified δ²H in male muscle, δ¹⁵N in female hepatopancreas, and δ¹³C in female hepatopancreas as the most influential features for discriminating geographic origin. This analysis highlighted the crucial role of environmental factors, such as water source, diet, and trophic level, in origin discrimination and demonstrated that isotopic characteristics of different tissues provide unique discriminatory information. This study offers a novel paradigm for stable isotope traceability based on explainable machine learning, significantly enhancing the identification capability and reliability of Chinese mitten crab origin traceability, and holds significant implications for food safety assurance. Full article

Stable isotope analysis is a powerful tool for inferring and quantifying transformation processes, but its effectiveness relies on understanding the magnitude and variability of isotopic fractionation associated with specific reactions. Potassium permanganate (KMnO₄) is widely used as an efficient oxidant for the degradation of trichloroethylene (TCE); however, the influence of environmental factors on the isotope fractionation during this process remains unclear. In this study, compound-specific isotope analysis (CSIA) was conducted to investigate the variability in carbon isotope effects during the KMnO₄-mediated degradation of TCE under varying conditions, including initial concentrations of KMnO₄ and TCE, the presence of humic acid (HA), pH levels, and inorganic ions. The results showed that the overall carbon isotope enrichment factors (ε) of TCE ranged from −26.5 ± 0.5‰ to −22.8 ± 0.9‰, indicating relatively small variations across conditions. At low KMnO₄/TCE molar ratio (n(KMnO₄)/n(TCE)), incomplete oxidation and/or MnO₂-mediated oxidation of TCE likely resulted in smaller ε. For dense, non-aqueous phase liquid (DNAPL) TCE, which represents extremely high concentrations, the ε value was −13.0 ± 1.7‰ during KMnO₄ oxidation. This may be attributed to the slow dissolution of isotopically light TCE from the DNAPL phase, altering the δ¹³C signature of the reacted TCE and resulting in a significantly larger ε value than observed for dissolved-phase TCE oxidation. The ε values increased with rising pH, probably due to the decrease in oxidation potential (E₀) of KMnO₄ from pH ~2 to ~12, as well as the emergence of different degradation pathways and intermediates under varying pH conditions. Both SO₄²⁻ and NO₃⁻ slightly influenced the ε values, potentially due to the formation of H₂SO₄ and HNO₃ at lower pH, which may act as auxiliary oxidants and contribute to TCE degradation. A high concentration (50 mM) of HA led to a decrease in ε values, likely due to competitive interactions between HA and TCE for KMnO₄, which reduced the effective oxidation of TCE. Overall, the carbon isotope enrichment factors for KMnO₄-mediated TCE degradation are relatively stable, although certain environmental conditions can exert minor influences. These findings highlight the need for caution when applying quantitative assessment based on CSIA for KMnO₄ oxidation of TCE. Full article

The growing consumption of Volvariella volvacea has heightened concerns regarding its geographical authenticity. This study analyzed the proteins, 16 common amino acids, and 10 mineral elements (Ca, Cu, Fe, K, Mn, Mg, Na, Se, Sr, Zn) in samples from Fujian, Guangdong, Hubei, Jiangsu, Jiangxi, Shanghai, and Zhejiang, China, along with regional variations in stable isotope ratios. PCA and PLS-DA were applied for origin authentication. The results showed an average protein content of approximately 30 g/100 g (dry basis), with Guangdong samples being the highest. Amino acids exhibited significant regional differences, but the total essential amino acid and total amino acid contents did not. Mineral elements varied significantly by region, except for Cu and K. The Fujian, Hubei, Jiangxi, and Zhejiang samples exhibited significantly higher δ¹³C and δ¹⁵N values, while Shanghai samples had significantly higher δ²H and δ¹⁸O values. These differences enabled PCA to classify the samples into two groups: FHJZ (Fujian, Hubei, Jiangxi, Zhejiang) and GJS (Guangdong, Jiangsu, Shanghai). The PLS-DA model achieved 93.60% accuracy in distinguishing these two groups. Pairwise accuracy within the GJS group exceeded 80%, whereas that within the FHJZ group requires further improvement. These findings support the feasibility of stable isotope analysis for authenticating the geographical origin of Volvariella volvacea. Full article

High-value products, such as hazelnuts, are particularly vulnerable to fraud due to their price dependence on geographical origin. Guaranteeing hazelnuts’ authenticity is essential for consumer trust and safety. Stable isotope analysis has become a reference method for origin authentication as it is reliable, robust, and easily transferable across laboratories. However, multiple isotopic markers coupled with chemometric techniques are often needed to authenticate food provenance accurately. In this study, we focused on assessing the potential of bulk δ¹⁸O, along with δ²H and δ¹³C of the main fatty acids, as hazelnut-origin authenticity markers. PLS-DA classification models were developed to differentiate samples (n = 207) according to their region of origin. This multi-isotopic approach provided promising external validation results, achieving a 94% global correct classification rate in discriminating hazelnuts from regions with distinct geographical and environmental conditions. This study lays the groundwork for further model development and evaluation across additional production areas and harvest years. Full article

Rheum tanguticum is one of the primary rhubarb species used for food and medicinal purposes, and it has recently been gaining more attention and recognition. This research represents the first attempt to use stable isotopes and elemental analysis via IRMS to identify the geographical origin of Rheum tanguticum. A grand total of 190 rhubarb samples were gathered from 38 locations spread throughout the provinces of Gansu, Sichuan, and Qinghai in China. The carbon content showed a decreasing trend in the order of Qinghai, followed by Sichuan, and then Gansu. Nitrogen content was notably higher, with Qinghai and Sichuan displaying similar levels, while Gansu had the lowest nitrogen levels. Significant differences were noted in the δ¹³C (−28.9 to −26.5‰), δ¹⁵N (2.6 to 5.6‰), δ²H (−120.0 to −89.3‰), and δ¹⁸O (16.0‰ to 18.8‰) isotopes among the various rhubarb cultivation areas. A significant negative correlation was found between %C and both longitude and humidity. Additionally, δ¹³C and δ¹⁵N isotopes were negatively correlated with longitude, and δ¹⁵N showed a negative correlation with humidity as well. δ²H and δ¹⁸O isotopes exhibited a strong positive correlation with latitude, while significant negative correlations were observed between δ²H and δ¹⁸O isotopes and temperature, precipitation, and humidity. The LDA, PLS-DA, and k-NN models all exhibited strong classification performance in both the training and validation sets, achieving accuracy rates between 82.1% and 91.7%. The combination of stable isotopes, elemental analysis, and chemometrics provides a reliable and efficient discriminant model for accurately determining the geographical origin of R. tanguticum in different regions. In the future, the approach will aid in identifying the geographical origin and efficacy of rhubarb in other studies. Full article

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. Full article