Effects of Water Isotope Composition on Stable Isotope Distribution and Fractionation of Rice and Plant Tissues.

Rice origin authenticity is important for food safety and consumer confidence. The stable isotope composition of rice is believed to be closely related to its water source, which affects its origin characteristics. However, the influence of water availability on the distribution of rice stable isotopes (δ2H and δ18O) is not clear. In this study, three irrigation waters with different isotopic values were used to investigate isotopic water use effects of Indica and Japonica rice, using pot experiments. Under three different water isotope treatments, the δ2H values of Indica polished rice showed significant differences (-65.0 ± 2.3, -60.5 ± 0.8 and -55.8 ± 1.7‰, respectively, p < 0.05) compared to δ13C and δ15N, as did Japonica polished rice. The values of δ2H and δ18O of rice became more positive when applying more enriched (in 2H and 18O) water, and the enrichment effect was higher in rice than in the corresponding plant tissue. In addition, the δ2H and δ18O values of Indica rice leaves decreased at the heading stage, increased at the filling stage, and then decreased at the harvest stage. Japonica rice showed a similar trend. δ2H changes from stem to leaf were more negative, but δ18O changes were more positive, and δ2H and δ18O values from leaf to rice were more positive for both brown and polished rice. The results from this study will clarify different water isotopic composition effects on rice and provide useful information to improve rice origin authenticity using stable isotope-based methods.

Stable isotope and elemental profiles determine geographical origin of saffron from China and Iran.

Origin verification of high-value saffron is essential for fair trade and to protect consumers' interests and rights. A traceability method using elemental content (% C and % N) and stable isotopes (δ13C, δ2H, δ18O, and δ15N) combined with chemometrics was developed to discriminate saffron from Iran and China and classify major domestic production areas in China. Results showed that Iranian samples had lower % C and % N contents but higher δ13C values than Chinese origin saffron, with δ13C acting as an important variable for origin discrimination. Moreover, δ2H and δ13C isotopes were found to be important variables to classify Chinese regional saffron origin. Two supervised pattern recognition models (PLS-DA) developed to classify Iranian and Chinese saffron, and regional Chinese saffron had a discrimination accuracy of 85.0 % and 80.2 %, respectively. These models provide the basis for a new regulatory inspection procedure to verify saffron origin and label claims, minimizing fraudulent mislabeling and adding value to saffron from specific regions.

Stable isotope and photosynthetic response of tea grown under different temperature and light conditions.

The stable isotope and photosynthesis response of tea (Camellia sinensis) is determined under different light and temperature conditions. The results showed that isotopes of young tea leaves were more enriched with increasing light intensity (31 ~ 411 µmol m-2∙s-1). However, the value of δ13C and δ15N seemed depleted, while δ2H and δ18O became enriched as temperature increasing from 15 to 35 °C. Significant isotope differences were found in tea leaves harvested between early growth (0 ~ 10 days) and later growth (10 ~ 21 days) periods (p < 0.05). Pearson's correlation showed a negative correlation between isotopes (δ13C, δ15N and δ2H) and photosynthetic parameters (EVAP and CI) ranging from 0.497 to 0.872, under 25 °C/203 µmol m-2∙s-1. But δ18O had a weak correlation with all photosynthetic parameters under the same conditions. These distinctive correlations between isotopes and photosynthetic parameters provide new insights which could be used to predict tea isotope responses arising from subtle seasonal or climate change conditions.

Stable Isotope Effects of Biogas Slurry Applied as an Organic Fertilizer to Rice, Straw, and Soil.

Biogas slurry (BS) is now increasingly used for organic rice production in China. However, the isotopic response and fractionation of different BS application rates to characterize organic rice cultivation have not yet been investigated. In this study, different fertilizer treatments were applied to rice paddy soil including urea, BS with five different application rates and a control with no fertilizer added. Multiproxy analyses (% C, % N, δ13C, δ15N, δ2H, and δ18O) of rice, rice straw, and soil were undertaken using elemental analyzer-isotope ratio mass spectrometry. Rice, straw, and soil showed only minor isotopic and elemental variations across all fertilizer treatments except for δ15N. δ15N values of rice and straw became more positive (+6.1 to +11.2‰ and +6.1 to +12.2‰, respectively) with increasing BS application rates and became more negative with urea fertilization (+2.8 and +3.0‰, respectively). The soil had more positive δ15N values after BS application but showed no significant change with different application rates. No obvious δ15N isotopic differences were found between the control soil and soils fertilized with urea. 15N fractionation was observed between rice, straw, and soil (Δrice-soil -2.0 to +4.3‰, Δstraw-soil -1.9 to +5.3‰) and their isotopic values were strongly correlated to each other (r > 0.94, p < 0.01). Results showed that % C, % N, δ13C, δ2H, and δ18O in rice displayed only minor variations for different fertilizers. However, δ15N values increased in response to BS application, confirming that BS leaves an enriched 15N isotopic marker in soil, straw, and rice, indicating its organically cultivated status. Results from this study will enhance the stable isotope δ15N databank for assessing organic practices using different fertilizer sources.

Isotope chemometrics determines farming methods and geographical origin of vegetables from Yangtze River Delta Region, China.

Shanghai city has encountered possible food fraud regarding the geographical mislabeling of vegetables for economic gain. A combination of δ13C, δ15N, δ2H and δ18O values and partial least squares discrimination analysis and support vector machine (SVM) methods were used for the first time to assess farming methods and determine the origin of vegetables from Shanghai city, Anhui and Zhejiang provinces. The results showed that 65.8% of Shanghai vegetables, 38.2% of Anhui vegetables and 23.6% of Zhejiang vegetables appeared to be grown using green or organic farming methods. The optimal discriminant model was obtained using SVM with a predictive accuracy of 100% for Shanghai vegetables. Zhejiang vegetables had a predictive accuracy of 91.7%, while it was difficult to distinguish Anhui vegetables from Shanghai or Zhejiang vegetables. Therefore, this study provided a useful method to identify vegetable farming methods and discriminate vegetables from Shanghai and Zhejiang.

Differentiating wild, lake-farmed and pond-farmed carp using stable isotope and multi-element analysis of fish scales with chemometrics.

Stable carbon (δ13C) and nitrogen (δ15N) isotope ratios and multi-element signatures of pooled fish scales were used to differentiate wild, lake-farmed and pond-farmed carp from Dongting Lake, China. Fish scales were found to be important archives for the dietary history and trophic level of wild and farmed fish, indicating their food sources. δ13C and δ15N values of pond-farmed carp scales were comparatively enriched to wild and lake-farmed carp due to their animal protein-derived feeds. Multi-element compositions of fish scales also showed significant differences between wild and farmed fish. A partial least squares discriminant analysis (PLS-DA) model correctly discriminated the three carp groups. Discrimination accuracies of wild, lake-farmed and pond-farmed carp were 100%, 95%, and 100% for the training set, and 100% for the testing set. This strategy provides a promising non-lethal alternative method to combat mislabeling of freshwater carp from different farming methods.

Differentiating Westlake Longjing tea from the first- and second-grade producing regions using ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry-based untargeted metabolomics in combination with chemometrics.

There are numerous articles published for geographical discrimination of tea. However, few research works focused on the authentication and traceability of Westlake Longjing green tea from the first- and second-grade producing regions because the tea trees are planted in a limited growing zone with identical cultivate condition. In this work, a comprehensive analytical strategy was proposed by ultrahigh performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based untargeted metabolomics coupled with chemometrics. The automatic untargeted data analysis strategy was introduced to screen metabolites that expressed significantly among different regions. Chromatographic features of metabolites can be automatically and efficiently extracted and registered. Meanwhile, those that were valuable for geographical origin discrimination were screened based on statistical analysis and contents in samples. Metabolite identification was performed based on high-resolution mass values and tandem mass spectra of screened peaks. Twenty metabolites were identified, based on which the two-way encoding partial least squares discrimination analysis was built for geographical origin prediction. Monte Caro simulation results indicated that prediction accuracy was up to 99%. Our strategy can be applicable for practical applications in the quality control of Westlake Longjing green tea.

Stable isotopes verify geographical origin of yak meat from Qinghai-Tibet plateau.

High-value yak meat from Qinghai-Tibet Plateau was investigated using stable isotopes (δ13C, δ2H, δ18O, δ15N and δ34S) to identify attributes which could verify and protect its geographical origin. Supervised PLS-DA was applied to the isotope data to discriminate four geographical locations. δ13C, δ2H, and δ18O values showed significant differences according to origin while δ15N and δ34S values did not show any change across the different regions. Isotope values of different body tissues from the same animal showed no statistical difference for the five stable isotopes. In addition, the δ2H and δ18O values of defatted yak meat was highly correlated to farm altitude and associated drinking water. This yak meat traceability method is particularly useful to protect the Product of Geographical Indication (PGI) status of Gannan yak meat and verify the farming origin of yak meat sold in markets for food safety purposes, especially when excessive hormones, pesticides or heavy metals are found.

Long-Term Agricultural Effects on the Authentication Accuracy of Organic, Green, and Conventional Rice Using Isotopic and Elemental Chemometric Analyses.

Organically farmed rice is believed to be healthier, safer, and eco-friendlier than its conventionally farmed counterparts and sells for a premium price in global markets. Deliberate mislabeling of organic rice has become a critical consumer concern in China and elsewhere, and there is an increased risk of buying fraudulent organic rice in the market place. In this study, stable isotopic and multielemental analysis combined with chemometrics was used to differentiate organically farmed rice from green and conventional rice in a 4-year experimental field trial from 2014 to 2017. A total of 108 rice samples and their associated soils were collected during the study from three farming (fertilization) systems to investigate whether there are long-term changes in the rice farming classification accuracy from climate effects. Stable carbon and nitrogen isotopic ratios (i.e., δ13C and δ15N) and 27 elemental contents (e.g., Na, K, Ca, Fe, and Zn) of rice and soil samples were determined and then evaluated using statistical analysis [i.e., one-way analysis of variance, multivariable correlation analysis, and modeling of partial least-squares discriminant analysis]. Although δ15N values can be an effective indicator for organic rice authentication during one crop rotation, both δ13C and δ15N values of rice were easily affected by rice cultivar and interannual soil fertilization and localized agroclimatic variations. These two isotopes were not able to separate organic rice from green and conventional rice accurately. Elemental contents of green and conventional rice (especially K and Ca) were found at higher levels due to the abundant application of synthetic fertilizers (e.g., KNO3, KH2PO4, and CaHPO4), unlike organically farmed rice, which primarily used animal manure and composts. Partial least-squares discriminant analysis modeling combined isotopic and elemental signatures to correctly differentiate organic rice from green and conventional counterparts, with an accuracy up to 100% over the 4-year study. Therefore, this multi-isotope and -element strategy proposes a more rigorous, alternative tool to combat fraudulent mislabeling of organic rice, increasing the trust of organically labeled rice products and supporting the integrity of the organic sector worldwide.

Influence of leaf age, species and soil depth on the authenticity and geographical origin assignment of green tea.

RATIONALE: Stable isotope fractionation occurring during leaf growth provides internal characteristics for identifying the geographical origin, traceability and authentication of tea. Studying the influence of leaf age, species and the relationship with the cultivated soil may reveal previously undocumented stable isotope fractionation mechanisms, and provide a deeper understanding of the physiological isotopic effects on the tractability and authentication accuracy of green tea to combat mislabeling and fraudulent conduct. METHODS: A total of 36 pairs of young (one bud with one leaf) and mature growth (older leaf) samples from two species of Longjing tea (Longjing #43 and Colonial cultivar) and corresponding cultivation soil samples from two different depth layers (0-20 cm and 20-40 cm) were collected in Westlake district, Hangzhou, Zhejiang province, China. Four stable isotope ratios (δ13 C, δ15 N, δ2 H, and δ18 O values) were measured using an elemental analyzer coupled with an isotope ratio spectrometer. Linear correlation and one-way analysis of variance (ANOVA) statistical analyses were performed to investigate isotopic fractionation mechanisms during plant growth, and reflect the dynamic physiological processes from soil to leaf. RESULTS: The carbon and nitrogen isotope ratios (δ13 C and δ15 N values) reflected the absorption, migration and fractionation of carbon dioxide and nitrogenous nutrients during photosynthesis, nutrient uptake, nitrogen fixation and leaf respiration. The water isotope ratios (δ2 H and δ18 O values) reflected the use and fractionation of water by tea plants at different growth stages. CONCLUSIONS: Considerable differences were found for hydrogen and oxygen isotope ratios according to leaf age, revealing complex isotopic fractionation mechanisms and possible interference factors. Leaf maturity effects should be considered, as they will influence the precision and accuracy of models when assigning the geographical origin, traceability and authentication of tea.

Differentiating Organically Farmed Rice from Conventional and Green Rice Harvested from an Experimental Field Trial Using Stable Isotopes and Multi-Element Chemometrics.

Chemometric methods using stable isotopes and elemental fingerprinting were used to characterize organically grown rice from green and conventionally grown rice in experimental field trials in China. Carbon, nitrogen, hydrogen, and oxygen stable isotopes as well as 26 other elements were determined. Organic rice was found to be more depleted in 13C than green or conventionally grown rice because of the uptake of enriched 13C from carbon dioxide and methane respiring bacteria and more enriched in 15N because of the volatilization of the nitrogen from the urea and ammonium of the animal manures used to manufacture the organic composts. Chemometrics (principal-component analysis and linear-discriminant analysis) were used to separate the three farming methods and provided a promising scientific tool to authenticate the farming methods of different rice cultivars fertilized with animal manures, green composts, and synthetic fertilizers in China or elsewhere.

Improved Discrimination for Brassica Vegetables Treated with Agricultural Fertilizers Using a Combined Chemometric Approach.

Multielement and stable isotope (δ(13)C, δ(15)N, δ(2)H, δ(18)O, (207)Pb/(206)Pb, and (208)Pb/(206)Pb) analyses were combined to provide a new chemometric approach to improve the discrimination between organic and conventional Brassica vegetable production. Different combinations of organic and conventional fertilizer treatments were used to demonstrate this authentication approach using Brassica chinensis planted in experimental test pots. Stable isotope analyses (δ(15)N and δ(13)C) of B. chinensis using elemental analyzer-isotope ratio mass spectrometry easily distinguished organic and chemical fertilizer treatments. However, for low-level application fertilizer treatments, this dual isotope approach became indistinguishable over time. Using a chemometric approach (combined isotope and elemental approach), organic and chemical fertilizer mixes and low-level applications of synthetic and organic fertilizers were detectable in B. chinensis and their associated soils, improving the detection limit beyond the capacity of individual isotopes or elemental characterization. LDA shows strong promise as an improved method to discriminate genuine organic Brassica vegetables from produce treated with chemical fertilizers and could be used as a robust test for organic produce authentication.

Using second-order calibration method based on trilinear decomposition algorithms coupled with high performance liquid chromatography with diode array detector for determination of quinolones in honey samples.

A novel strategy that combines the second-order calibration method based on the trilinear decomposition algorithms with high performance liquid chromatography with diode array detector (HPLC-DAD) was developed to mathematically separate the overlapped peaks and to quantify quinolones in honey samples. The HPLC-DAD data were obtained within a short time in isocratic mode. The developed method could be applied to determine 12 quinolones at the same time even in the presence of uncalibrated interfering components in complex background. To access the performance of the proposed strategy for the determination of quinolones in honey samples, the figures of merit were employed. The limits of quantitation for all analytes were within the range 1.2-56.7 µg kg(-1). The work presented in this paper illustrated the suitability and interesting potential of combining second-order calibration method with second-order analytical instrument for multi-residue analysis in honey samples.