Stable isotopes and elemental fingerprints were employed as indicators to evaluate the vintage of French wine using climate factors and data-driven models. δ13C of wine ethanol and glycine, and δ18O of wine water and 16 elements were determined in wine from Bordeaux, Burgundy, and Languedoc-Roussillon. Results revealed that isotopic and elemental signatures from various vintages were influenced by precipitation and temperature. If there was less precipitation and higher temperatures during the grape ripening phase, isotopic and elemental signatures had a positive impact on the grapes, resulting in superior quality French wine. Data-driven models achieved excellent accuracy to identify vintages with the identification accuracy up to 72.0 %, and even higher accuracy (up to 95.0 %) from the Bordeaux region. Explainable methods were employed to select the top-5 and top-10 variables for each region under different data-driven models, yielding results comparable to those from a full set of variables.

A study of different grapevine tissues and organs (root, stem, leaf, fruit) water isotope fractionation models from high-quality wine grapes produced in the Helan Mountains, a key wine-producing area in northwestern China, was undertaken. Results showed that δ2H values of local groundwater sources were more negative than rivers and precipitation. Soil water δ2H and δ18O values were significantly higher than those of other environmental water sources. Water from the soil surface layer (0-30 cm, δ2H and δ18O values) was more positive than the deeper layer (30-60 cm), indicating that soil water has undergone a positive fractionation effect. δ2H and δ18O values of tissues and organs from different grape varieties followed a similar pattern but were more negative than the local atmospheric precipitation line (slope between 4.1 to 5.2). The 2H and 18O fractionation relationship in grapevine organs was similar, and 18O has a higher fractionation effect than 2H. δ2H and δ18O values showed a strong fractionation effect during the transportation of water to different grape organs (trend of stem > fruit > leaf). This study showed that 18/16O fractionation in grapes is more likely to occur under drought conditions and provides a theoretical basis to improve traceability accuracy and origin protection of wine production areas.

A comprehensive study of 96 bottled mineral water (BMW) samples consisting of 21 of the most popular origins and brands sourced from China (n = 38), France (n = 20), Italy (n = 10), New Zealand (n = 17) and Fiji (n = 12) has been undertaken. The 618O and 613C of dissolved inorganic carbon (DIC), 618O and 62H of water, mineral elements (Li, Na, Mg, K, Ca, Sr) and ions (Cl-, SO42-, F-, CO32-, HCO3-) were investigated and used for origin traceability. The origin of BMW was confirmed by applying Fisher discriminant analysis (Fisher -DA) and artificial neural network (ANN) models to these variables. 618ODIC, 613CDIC, 618O, 62H values of BMW showed significant deviations with origin. Mineral elements and anions varied widely due to different regional geology and hydrology characteristics. A discriminant model based on Fisher-DA showed that the identification accuracy of mineral water from different origins was in the range of 81 % to 100 %, whereas the discriminant accuracy was 100 % for the training samples and 96.0 % for the testing samples calculated by ANN. HCO3-, NO3-, 62H, delta 18O and F- were the most important variables that characterized BMWs from different origins. Using a combination of stable isotopes and different water chemical components, BMWs from China can be accurately distinguished from other origins using multivariate statistical models.

Rapid and quantitative biochemical analysis at points-of-need is imperative for food safety inspection. This work reports on: 1) a stand-alone smartphone-based "two-in-one" spectrophotometer (the SAFS) installed with a self-developed application (the SAFS-App) which can precisely collect both absorption spectra and fluorescence spectra in a reproducible manner within 5 s; and 2) a straightforward protocol for xanthine detection using fluorescent carbon nanodots and silver nanoparticles. The assay performed with the SAFS demonstrates high specificity towards xanthine, and a linear range of 1-60 μM with LODs of 0.38 and 0.58 μM for colorimetric and fluorometric readouts, respectively. The reliability and robustness of the SAFS are validated by on-site quantitation of xanthine in fish and serum samples, with comparable accuracy to HPLC method. More importantly, the SAFS presents itself as an appealing device which is accessible to everyone through the Internet of Things and can be tailored for diverse point-of-care testing applications.

Verifying the geographical origin of soybeans (Glycine max [Linn.] Merr.) is a major challenge as there is little available information regarding non-parametric statistical origin approaches for Chinese domestic and imported soybeans. Commercially procured soybean samples from China (n = 33) and soybeans imported from Brazil (n = 90), the United States of America (n = 6), and Argentina (n = 27) were collected to characterize different producing origins using stable isotopes (δ2H, δ18O, δ15N, δ13C, and δ34S), non-metallic element content (% N, % C, and % S), and 23 mineral elements. Chemometric techniques such as principal component analysis (PCA), linear discriminant analysis (LDA), and BP–artificial neural network (BP-ANN) were applied to classify each origin profile. The feasibility of stable isotopes and elemental analysis combined with chemometrics as a discrimination tool to determine the geographical origin of soybeans was evaluated, and origin traceability models were developed. A PCA model indicated that origin discriminant separation was possible between the four soybean origins. Soybean mineral element content was found to be more indicative of origin than stable isotopes or non-metallic element contents. A comparison of two chemometric discriminant models, LDA and BP-ANN, showed both achieved an overall accuracy of 100% for testing and training sets when using a combined isotope and elemental approach. Our findings elucidate the importance of a combined approach in developing a reliable origin labeling method for domestic and imported soybeans in China.

Cost-effective and user-friendly quantitation at points-of-need plays an important role in food safety inspection, environmental monitoring, and biomedical analysis. This study reports a stand-alone smartphone-based fluorospectrophotometer (the SBS) installed with a custom-designed application (the SBS-App) for on-site quantitation of pesticide using a ratiometric sensing scheme. The SBS can collect fluorescence emission spectra in the wavelength range of 380-760 nm within 5 s. A ratiometric fluorescence probe is facilely prepared by directly mixing the blue-emissive carbon nanodots (the Fe3+-specific fluorometric indicator) and red-emissive quantum dots (the internal standard) at a ratio of 11.6 (w/w). Based on the acetylcholinesterase/choline oxidase dual enzyme-mediated cascade catalytic reactions of Fe2+/Fe3+ transformation, a ratiometric fluorescence sensing scheme is developed. The practicability of the SBS is validated by on-site quantitation of chlorpyrifos in apple and cabbage with a comparable accuracy to the GC-MS method, offering a scalable solution to establish a cost-effective surveillance system for pesticide pollution.

Stable isotopes (delta H-2, delta C-13, delta N-15 and delta O-18) of 232 milk powders and 88 fresh milk samples collected globally were used to distinguish fresh milk from reconstituted milk and qualitatively detect extraneous nitrogen in milk products. Nitrogen isotopes of six nitrogen-containing milk additives, including animal protein (peptone), soy protein, and four inorganic nitrogen additives (urea, melamine, ammonium chloride and biuret), were characterised to identify potential extraneous nitrogen (PENs) that could be fraudulently used to increase the protein N content of milk. Results showed that fresh milk and reconstituted milk can be distinguished by using stable isotopes combined with chemometrics (PCA, LDA and ANN) methods. LDA achieved accuracy rates of 94.9 % and 94.9 % for the testing and training sets respectively, while ANN had higher accuracy rates, up to 99.6 % for the training set, and 96.6 % for the testing set. Nitrogen stable isotopes were also found to be a useful tool to identify the addition of PENs in milk and could accurately detect the addition of inorganic nitrogen and soybean protein to less than 20 % of the total nitrogen in milk. The methods established in this paper are simple, efficient and fast, and can be used for the regulatory supervision of domestic and imported milk products by food safety testing agencies.

为保护高值热带作物榴莲的原产地信息,采集马来西亚、泰国、柬埔寨和越南共4个产区73份不同品种榴莲样本,利用电感耦合等离子体质谱法测定榴莲果核与榴莲果肉中28种矿物元素含量,结合方差分析、主成分分析、Fisher逐步判别分析和BP人工神经网络,建立基于矿物元素的榴莲产地判别模型并验证其准确率.结果 表明,榴莲果核和果肉中分别有16种和13种矿物元素在4个产区存在显著差异;主成分分析中前6个主成分累计贡献率为85.207％,代表矿物元素含量的主要信息;将有显著差异的元素代入Fisher逐步判别方程,结果发现单一榴莲果核及榴莲果肉判别准确率较低,榴莲果核和榴莲果肉耦合指标显著提高判别准确率,筛选出果核中Li、Be、Mg、Mn、Rb元素和果肉中Be、Ag、Ba元素8项指标构建榴莲产地溯源模型,模型的初始验证准确率为91.8％,交叉验证准确率为90.4％;将有显著差异的元素代入BP人工神经网络模型,榴莲果核As、Ag、Al、Rb和果肉中Ag元素为BP人工神经网络前5重要元素,模型训练验证准确率为96.1％,检验验证准确率为95.5％.初步证明利用矿物元素指纹特征结合化学计量学方法对东南亚产地榴莲判别具有可行性.

Not-from-concentrate (NFC) juice has better nutrition, flavor and higher price than reconstituted juice. Accordingly, NFC juice is prone to adulteration and is an ongoing industry problem that has not yet been resolved. Undeclared addition of water and sugar are the main forms of NFC juice adulteration. This paper investigates the carbon and oxygen stable isotope ratios (δ13C and δ18O values) of the bulk juice and different juice components from 21 fruit and vegetable juices, and qualitatively and quantitatively analyzes the addition of water and sugar in NFC juices. The results show that the use of fruit pulp can help to qualitatively and quantitatively indicate the presence of C4 plant sugars in NFC juice, and can reliably detect added C4 plant sugars above 7 %. Sugar-specific isotope analysis (SSIA) technology was used to determine the δ13C values of different sugars (sucrose, glucose and fructose) and carbon content to qualitatively infer C3 plant sugar addition. Pulp extracted from juice had a good linear relationship with the juice water δ18O values (R2 >0.90). The addition of water to NFC juice can also be determined by comparing δ18O values of extraneous water, pulp and filtered juice. Stable isotope technology confirmed NFC juice adulteration of in-market samples using the pulp as an internal reference and was found to be a useful tool to detect adulteration of in-market NFC juice.

本文介绍了微波消解法对奶粉进行消解,全自动间断化学分析仪对奶粉中磷含量进行测定的分析方法.文章对该方法的检出限、定量限、线性、准确性、重复性等进行分析.结果 表明,该方法的检出限为7 mg/100g,定量限为23 mg/100g,在0～40 mg/L范围内吸光度与磷含量呈良好的线性关系(R2=0.9997),相对标准偏差小于3％(n=7),与国标钒钼黄分光光度法相比差异无显著性,测定奶粉标准物质的测定值均在标准参考值范围内.建立的分析方法自动化程度高,准确度、灵敏度、精密度高,方法简便、快速,适用于奶粉中磷含量的分析研究.

本研究从深圳口岸获取我国三文鱼主要进口国(法罗群岛、挪威、智利、加拿大以及澳大利亚)的三文鱼样品共16份,并采集中国产三文鱼(虹鳟)样品2份,分析三文鱼肌肉、表皮、鳞片以及骨骼中的碳、氮、氢、氧、硫稳定同位素比值,比较不同产地以及不同部位同位素分布差异,采用判别分析对不同产地进行判别.三文鱼的碳、硫以及氢、氧稳定同位素具有显著的产地差异.不同组织之间同位素呈现明显的同位素分馏效应.鳞片以及表皮同位素比值对产地的指示效果优于肌肉和骨骼,结果表明采用稳定同位素能完全将以上产地的样品区分开,且还能将中国的虹鳟与进口的三文鱼进行区分.对市场随机购买的6份三文鱼样品的产地鉴别结果表明,稳定同位素技术能有效鉴别市场中三文鱼的产地造假行为,可用于对市场上三文鱼的产地追溯,以期为我国食品安全提供技术保障.

China is the largest importer of infant formula. However, monitoring the authenticity of infant formula has long been a problem in China. The origin of infant formula is more difficult to trace than fresh milk because it contains many foreign additives that cannot be correlated to a specific country. In this study, stable isotope ratios (δ15N, δ13C, δ34S, δ2H and δ18O) of bulk infant formula milk powder and fresh milk from 6 origins (Netherlands, Switzerland, France, Denmark, New Zealand and China) were compared to establish geographical origin isotopic characteristics. N, C and S elemental contents were also investigated to improve origin verification. Artificial Neural Network (ANN) and Linear Discriminant Analysis (LDA) were used to establish origin verification models of imported infant formula and fresh milk. Overall, results showed that infant formula had higher δ18O, δ2H, δ15N and δ34S values, and lower δ13C values than fresh milk. δ18O and δ2H values of infant formula varied more than in fresh milk, as the additives are not necessarily sourced from the same country, while δ15N, δ13C and δ34S values were more negative, most likely due to the presence of numerous additives probably from non-dairy sources such as fats, sugars, amino acids and proteins. This study showed a combination of isotopes and elemental contents could completely discriminate the origin of infant formula imported into China, with a discrimination accuracy of 100% using ANN.

Origin verification of 240 French wines from four regions of France was undertaken using isotope and elemental analyses. Our aim was to identify and differentiate the geographical origin of these red wines, and more importantly, to build a classification tool that can be used to verify geographic origin of French red wines using machine learning models. Multivariate analyses of the isotopic and elemental data revealed that it is possible to determine the geographical origin of French wines with a high level of confidence for most regions analyzed in this study. The wine verification accuracy of four French wine producing regions of Bordeaux, Burgundy, Languedoc-Roussillon and Rhone using an Artificial Neural Network (ANN) method was 98.2%. The results also show that ANN is more suitable than Discriminant Analysis for this verification purpose. The most important variables for French wine regional traceability were Mg, Mn, Na, Sr, Ti and Rb.

Determining the geographical origin of specialty fruits imported into China is important to protect the legitimate rights and interests of consumers against mislabeled origin fruits and may provide a regulatory tool to verify fruit sold into international markets. This study aims to establish an accurate and effective method to identify the geographical origin of south-east Asian durian, which could be further used to improve the traceability of similar imported fruits. In this study, 73 durian were collected from Malaysia, Thailand, Cambodia and Vietnam. We analyzed durian core and pulp using five stable isotopes (delta 15N, delta 13C, delta 34S, delta 2H and delta 18O) and elemental contents: nitrogen (% N), carbon (% C) and sulfur (% S). Two way-ANOVA (two-way analysis of variance) was used to identify major origin differences for each variable. Linear Discriminant Analysis (LDA) and Artificial Neural Network (ANN) models were used as exploratory techniques and classification parametrics. Two way-ANOVA showed significant differences (p < 0.05) between the geographical origin and durian tissue type. The durian core afforded better origin traceability than durian pulp. LDA achieved durian origin accuracy rates of 98.6 % and 97.3 % for the testing and training sets respectively by combining stable isotopes and elemental contents. ANN gave higher accuracy rates than LDA, correctly identifying durian origin with an accuracy of 100 % for the training set, and 94.4 % on the testing set. This research found stable isotopes and elemental compositions could be used to potentially discriminate the geographical origins of durian from four south-east Asian countries.

乳品掺假鉴别是目前我国乳品质量控制的难题之一,相关部门特别是进口监管部门急需快速且准确鉴别乳制品掺假以及原产地来源的新技术和方法.本文综述我国乳制品掺假现状,总结掺假乳制品的常见鉴别技术,重点阐述目前国内外稳定同位素技术在乳制品真实性鉴别研究中的进展,主要介绍C、H、O、N和S稳定同位素的相关应用,并指出该技术在乳品掺假鉴别和产地溯源中的技术优势、存在的问题以及未来发展的方向.

目的 建立蔬菜水果中31种不同类别农药残留的QuEChERS-分散液液微萃取-气相色谱串联质谱检测方法.方法 蔬菜水果中的农药残留经QuEChERS萃取及净化后,使用分散液液快速微萃取浓缩,用气相色谱串联质谱仪检测.对分散液液微萃取相关的影响因素,如萃取溶剂种类与体积、分散溶剂的体积、盐的浓度等进行了优化.结果 在香蕉和西红柿2个基质中开展基质加标实验,添加水平为1.0 μg/kg、5.0 μg/kg、10.0 μg/kg.本方法的最大线性范围为0.1μg/kg ～ 20.0 μg/kg,方法回收率为73.3％～126.8％,相对标准偏差为3.6％ ～23.6％,方法的检出限为0.001 μg/kg～0.22 μg/kg,定量限为0.002 μg/kg～0.73 μg/kg.结论 本方法结合了QuEChERS的快速萃取、净化能力与分散液液微萃取的快速、高倍浓缩能力.方法 前处理过程简单、快速、灵敏度极高、定量结果准确,适合于蔬菜水果中31种农药残留的检测与确证.

Multi-isotope and multi-elemental analyses were performed on 600 red wine samples imported into China from 7 different countries and compared with Chinese wine. Carbon and oxygen isotopes and 16 elements were used to determine origin traceability. Our goal was to build a classification tool using data modeling that can verify the geographic origin of wines imported into China. Multivariate analyses of the isotopic and elemental data revealed that it is possible to determine the geographical origin for most imported wines with a high level of confidence (>90%). The results show that Artificial Neural Network method had a high discrimination accuracy and is more suitable than Discrimination Analysis and Random Forest methods when it comes to classifying wine origin on a global scale. In conclusion, stable isotope and trace element analyses followed by multivariate processing of the data is a fast and efficient technique suitable for global wine traceability.

利用元素分析法对3个产地的香米进行鉴别,利用电感耦合等离子体质谱法(ICP-MS)和电感耦合等离子体光谱法(ICP-OES)对来自泰国、江西、湖南3个地区的180份香米进行包括钙、铁、钾、镁、锌、硼、铝、铬、锰、钴、镍、铜、砷、锶、硒、镉、铯、钡、铅19种元素在内的含量分析,通过判别分析建立判别模型.判别模型对泰国香米自校验交叉校验准确率100％,拥有极高的准确率.

A method of ultra performance liquid chromatography-tandem mass spectrom-etry(UPLC-MS/MS)was developed for determination of 8 kinds of dinitroaniline herbi-cides(trifluralin,pendimethalin,butralin,isopropalin,dinitramine,nitralin,oryzalin, prodiamine)in spinach,apple and soybean.Afer homogenization,5.0 g sample was soaked with 7 mL water for 1 h.Then 3 g NaCl was added,and the sample was extrac-ted twice by 25 mL hexane saturated acetonitrile solution.After concentration,the extract was put through C18 column and eluted by 5 mL acetonitrile.The eluated was then concentrated and dissolved with 2.0 mL hexane-acetone mixture(2:8,V/V).The preparation was cleaned by Envi-Carb column and eluted with 5.0 mL hexane-acetone. The residue was dissolved by 50% acetonitrile aqueous solution(contain 0.1% formic acid),and determined by UPLC-ESI/MS/MS.Under the optimized chromatographic conditions,8 target compounds were obtained.Confirmation was achieved using electro-spray ionization(ESI)in positive mode with multiple reaction monitoring(MRM),and external standard method was used for quantification.The results show that 8 dinitroa-niline herbicides have good linearity,the linearity is more than 0.99.T he limits of quantification(LOQs)are 10 μg/kg.The mean recoveries are between 70.0% and 120%at the spiked levels of 10-200 μg/kg.The RSD of the method are between 0.56% and 23.0%.T he method is precise,sensitive and accurate,which is suitable for confirma-tion and quantification of dinitroaniline herbicides in vegetables,fruits and grains.

利用元素分析建立四个产地香米的鉴别方法.利用电感耦合等离子体质谱法和电感耦合等离子体光谱法对来自泰国、越南、柬埔寨、巴基斯坦四个地区的220份香米进行包括钙、铁、钾、镁、锌、硼、铝、铬、锰、钴、镍、铜、砷、锶、硒、镉、铯、钡、铅19种元素在内的含量分析.通过判别分析建立判别模型.判别模型自校验交叉校验准确率100％,拥有极高的准确率.