The application of stable isotope ratio analysis to determine the geographical origin of wheat

Luo, Da; Dong, Hao; Luo, Haoming; Xian, Yuezhong; Wan, Juan; Guo, Xiao‐Na; Wu, Yuluan

doi:10.1016/j.foodchem.2014.11.006

Cited by 87 publications

(45 citation statements)

References 24 publications

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“…While considering the results obtained here with the findings attained in a previous studies regarding the use of ICP‐MS and IRMS for the same purpose (Zhao et al ., ; Luo et al ., ; Dong et al ., ; Wadood et al ., ,b), it can be perceived that all techniques are effective and showed good potential for this kind of studies and applications. However, the application of one of them should consider a balance of advantages and disadvantages of each technique.…”

Section: Resultsmentioning

confidence: 98%

Geographical origin discrimination of wheat kernel and white flour using near‐infrared reflectance spectroscopy fingerprinting coupled with chemometrics

Wadood

Guo

Zhang

et al. 2019

Int J of Food Sci Tech

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Summary Wheat kernel and flour with three genotypes across 4 years procured from three different geographical areas of China were analysed using near‐infrared reflectance (NIR) spectroscopy coupled with chemometrics to better classify wheat according to the origin, production year and genotypes, respectively. For this purpose, principle component analysis‐linear discriminant analysis and multi‐way anova were applied to the NIR data. The best classification percentages were obtained for flour matrix both for geographical origin and production years with the correct percentages of 100% and 73%, respectively. For genotypes, wheat whole kernel showed better classification percentage (98.2%). All the samples were validated using external validation procedure and the obtained percentages were found satisfactory with the average prediction abilities of >85% in all regions indicating the suitability of the developed model. Multivariate anova showed that NIR fingerprints of wheat kernels and flours were significantly influenced by regions, years, genotypes and their interactions. In conclusion, white flour showed better performance in discriminating the geographical origin as compared to wheat whole kernel.

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Section: Resultsmentioning

confidence: 98%

Geographical origin discrimination of wheat kernel and white flour using near‐infrared reflectance spectroscopy fingerprinting coupled with chemometrics

Wadood

Guo

Zhang

et al. 2019

Int J of Food Sci Tech

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“…Therefore, the establishment of appropriate analytical methods to ensure geographical origin could play a key role in the verification system of food safety, which can effectively improve the government's regulatory capacity, facilitates the implementation of the policy to ensure food security and contributes to consumer confidence in the product quality (Chen et al ., ). Generally, it is widely acceptable to employ mineral elements and stable isotope for discrimination of geographical origin of food (Potortì et al ., ; Luo et al ., ,b) . The element analysers including inductively coupled plasma atomic emission spectroscopy (ICP‐AES), ICP‐MS and isotope ratio mass spectrometry (IRMS) are widely applied (Benincasa et al ., ; Li et al ., ).…”

Section: Introductionmentioning

confidence: 99%

Multiangle discrimination of geographical origin of rice based on analysis of mineral elements and characteristic volatile components

Fang

Shen

et al. 2018

Int J of Food Sci Tech

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Summary The aim of the study was to develop a multiangle discrimination method which combines mineral elements with volatile compounds to identify the geographical origin of rice. The levels of twenty‐four elements and characteristic volatile compositions of rice samples from different growing area (Panjin, Wuchang and Sheyang city of China) were measured by inductively coupled plasma mass spectrometer (ICP‐MS) and electronic nose (E‐nose), respectively. The obtained data were subject to the analysis of variance (anova), principal component analysis (PCA) and linear discriminant analysis (LDA). The twenty elements including B, Mg, Al, Ti, V, Cr, Mn, Fe, Ni, Zn, Ga, As, Sr, Cd, Sn, Sb, Ba, Pb, Bi and Tl and eleven sensors including LY2/LG,LY2/G, LY2/AA, LY2/GH, LY2/gCTL, LY2/gCT, P10/1, T30/1,T70/2, P10/2 and PA/2 were mainly contributed to discriminate the origin of the rice, and the average classification accuracy was 93.5%. Compared with one‐dimensional discrimination method, the multiangle analytical method of combining mineral elements with volatile compounds significantly improved the discrimination accuracy of origin of rice.

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“…6 For garlic, no databank for tracing its origin at national, continental or global scale has been set up yet, in spite of global utilization of garlic as a condiment in cuisine or for medicinal purposes. 7 Many authors have attempted to determine the geographical origin of different cereal grains, [8][9][10][11] Chinese teas 12 and honey 13 using only stable isotopes of light elements. Samples classification into groups according their geographical origin was relatively successful, indicating that better classification could be achieved by applying not only stable isotope ratios of one or two light elements, but by using multielement stable isotope ratio data.…”

Section: Introductionmentioning

confidence: 99%

Geographical Origin Characterization of Slovenian Organic Garlic Using Stable Isotope and Elemental Composition Analyses

Opatič¹,

Nečemer²,

Kocman³

et al. 2017

ACSi

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In the present research, the applicability of stable isotope (δ O) and multi-element (P, S, Cl, K, Ca, Zn, Br, Rb, Sr) data for determining the geographical origin of garlic (Allium sativum L.) at the scale of Slovenia was examined. Slovenia is a rather small country (20273 km 2 ) with significant geological and biological diversity. Garlic, valued for its medicinal properties, was collected from Slovenian farms with certified organic production and analyzed by elemental analyzer isotope ratio mass spectrometry combined with energy dispersive X-ray fluorescence spectrometry. Multivariate discriminant analysis (DA) revealed a distinction between four Slovenian macro-regions: the Alpine, Dinaric, Mediterranean and Pannonian. The model was validated through a leave-10%, 20% and 25% out cross validation. The overall success rate of correctly reclassified samples was 77% (on average), indicating that the model and the proposed methodology could be a promising tool for rapid, inexpensive and robust screening to control the provenance of garlic samples.

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The application of stable isotope ratio analysis to determine the geographical origin of wheat

Cited by 87 publications

References 24 publications

Geographical origin discrimination of wheat kernel and white flour using near‐infrared reflectance spectroscopy fingerprinting coupled with chemometrics

Geographical origin discrimination of wheat kernel and white flour using near‐infrared reflectance spectroscopy fingerprinting coupled with chemometrics

Multiangle discrimination of geographical origin of rice based on analysis of mineral elements and characteristic volatile components

Geographical Origin Characterization of Slovenian Organic Garlic Using Stable Isotope and Elemental Composition Analyses

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