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Li Y, Yang X, Zhao S, Zhang Z, Bai L, Zhaxi P, Qu S, Zhao Y. Effects of sampling time and location on the geographical origin traceability of protected geographical indication (PGI) Hongyuan yak milk: Based on stable isotope ratios. Food Chem 2024; 441:138283. [PMID: 38185048 DOI: 10.1016/j.foodchem.2023.138283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 12/21/2023] [Accepted: 12/24/2023] [Indexed: 01/09/2024]
Abstract
Hongyuan yak milk is a protected geographical indication (PGI) product of rich nutritional value, which is popular among consumers. Stable isotope ratio analysis (SIRA) is an effective way to protect the authenticity of the geographical origin of PGI products, and it is crucial to study the factors affecting stable isotopes. Firstly, we proved that the SIRA could be used to identify the geographical origin of Hongyuan yak milk, and that the identification accuracy in combination with δ13C and δ18O was 100 %. Secondly, we analyzed the effect of sampling selection on the stable isotopes of Hongyuan yak milk in practical applications, which showed that sampling time influenced the δ13C, δ2H, and δ18O, while the sampling locations did not. There were interactions between the effect of sampling time and location on δ2H and δ18O. These results provide a reliable method for identifying PGI products and also provide new guidance on sampling models.
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Affiliation(s)
- Yalan Li
- Institute of Quality Standards and Testing Technology for Agro-products, Key Laboratory of Agro-product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xiaoting Yang
- Institute of Quality Standards and Testing Technology for Agro-products, Key Laboratory of Agro-product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Shanshan Zhao
- Institute of Quality Standards and Testing Technology for Agro-products, Key Laboratory of Agro-product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Zixuan Zhang
- Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing 100081, China
| | - Lu Bai
- Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing 100081, China
| | - Pengcuo Zhaxi
- Hongyuan Yak Dairy Co., Ltd., Hongyuan 624400, China
| | - Song Qu
- Hongyuan Yak Dairy Co., Ltd., Hongyuan 624400, China
| | - Yan Zhao
- Institute of Quality Standards and Testing Technology for Agro-products, Key Laboratory of Agro-product Quality and Safety, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
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Varrà MO, Zanardi E, Serra M, Conter M, Ianieri A, Ghidini S. Isotope Fingerprinting as a Backup for Modern Safety and Traceability Systems in the Animal-Derived Food Chain. Molecules 2023; 28:molecules28114300. [PMID: 37298773 DOI: 10.3390/molecules28114300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 05/19/2023] [Accepted: 05/22/2023] [Indexed: 06/12/2023] Open
Abstract
In recent years, due to the globalization of food trade and certified agro-food products, the authenticity and traceability of food have received increasing attention. As a result, opportunities for fraudulent practices arise, highlighting the need to protect consumers from economic and health damages. In this regard, specific analytical techniques have been optimized and implemented to support the integrity of the food chain, such as those targeting different isotopes and their ratios. This review article explores the scientific progress of the last decade in the study of the isotopic identity card of food of animal origin, provides the reader with an overview of its application, and focuses on whether the combination of isotopes with other markers increases confidence and robustness in food authenticity testing. To this purpose, a total of 135 studies analyzing fish and seafood, meat, eggs, milk, and dairy products, and aiming to examine the relation between isotopic ratios and the geographical provenance, feeding regime, production method, and seasonality were reviewed. Current trends and major research achievements in the field were discussed and commented on in detail, pointing out advantages and drawbacks typically associated with this analytical approach and arguing future improvements and changes that need to be made to recognize it as a standard and validated method for fraud mitigation and safety control in the sector of food of animal origin.
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Affiliation(s)
- Maria Olga Varrà
- Department of Food and Drug, University of Parma, 43126 Parma, Italy
| | - Emanuela Zanardi
- Department of Food and Drug, University of Parma, 43126 Parma, Italy
| | - Matteo Serra
- Department of Food and Drug, University of Parma, 43126 Parma, Italy
| | - Mauro Conter
- Department of Veterinary Science, University of Parma, 43126 Parma, Italy
| | - Adriana Ianieri
- Department of Food and Drug, University of Parma, 43126 Parma, Italy
| | - Sergio Ghidini
- Department of Food and Drug, University of Parma, 43126 Parma, Italy
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Xu S, Zhao C, Deng X, Zhang R, Qu L, Wang M, Ren S, Wu H, Yue Z, Niu B. Multivariate analysis for organic milk authentication. J Chromatogr B Analyt Technol Biomed Life Sci 2021; 1186:123029. [PMID: 34798418 DOI: 10.1016/j.jchromb.2021.123029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Revised: 10/12/2021] [Accepted: 11/06/2021] [Indexed: 11/15/2022]
Abstract
To differentiate organic milk (OM) from conventional milk (CM), an orthogonal projection to latent structure-discriminant analysis (OPLS-DA) model was constructed using δ13C, δ15N, δ18O, 51 elements and 35 fatty acids (FAs) as the variables. So far, most reported studies barely use three or more types of variables, but more variables could avoid one-sidedness and get stabler models. Our multivariate model combines geographical and nutritional parameters and displays better explanatory and predictive abilities (R2X = 0.647, R2Y = 0.962 and Q2 = 0.821) than models based on fewer variables for differentiating OM and CM. In particular, δ15N, Se, δ13C, Eu, K and α-Linolenic acid (ALA) are found to be critical parameters for the discrimination of OM. These results show that the multivariate model based on stable isotopes, elements and FAs can be used to identify OM, and can potentially expand the global databases for quality and authenticity of milk.
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Affiliation(s)
- Siyan Xu
- School of Life Sciences, Shanghai University, Shanghai 200444, China; Technical Center for Animal, Plant and Food Inspection and Quarantine, Shanghai Customs, Shanghai 200135, China
| | - Chaomin Zhao
- Technical Center for Animal, Plant and Food Inspection and Quarantine, Shanghai Customs, Shanghai 200135, China.
| | - Xiaojun Deng
- Technical Center for Animal, Plant and Food Inspection and Quarantine, Shanghai Customs, Shanghai 200135, China
| | - Runhe Zhang
- Technical Center for Animal, Plant and Food Inspection and Quarantine, Shanghai Customs, Shanghai 200135, China
| | - Li Qu
- Technical Center for Animal, Plant and Food Inspection and Quarantine, Shanghai Customs, Shanghai 200135, China
| | - Min Wang
- Technical Center for Animal, Plant and Food Inspection and Quarantine, Shanghai Customs, Shanghai 200135, China
| | - Shuo Ren
- Technical Center for Animal, Plant and Food Inspection and Quarantine, Shanghai Customs, Shanghai 200135, China
| | - Hao Wu
- Food Inspection and Quarantine Center, Shenzhen Customs, Shenzhen 518000, China
| | - Zhenfeng Yue
- Food Inspection and Quarantine Center, Shenzhen Customs, Shenzhen 518000, China
| | - Bing Niu
- School of Life Sciences, Shanghai University, Shanghai 200444, China
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Xu S, Zhao C, Deng X, Zhang R, Qu L, Wang M, Ren S, Wu H, Yue Z, Niu B. Determining the geographical origin of milk by multivariate analysis based on stable isotope ratios, elements and fatty acids. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2021; 13:2537-2548. [PMID: 34013914 DOI: 10.1039/d1ay00339a] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
To construct a reliable discrimination model for determining milk geographical origin, stable isotope ratios including δ13C, δ15N and δ18O, 51 elements and 35 fatty acids (FAs) in milk samples from Australia, New Zealand and Austria were detected and analyzed. It is found that all of the stable isotope ratios in the milk samples of Australia are the highest, followed by those of the samples from New Zealand and Austria. In addition, 14 elements and 8 FAs show different contents in the samples of different countries at the significance level of P < 0.05. Based on these results, a multivariate model with good robustness and predictive ability for authenticating milk origin (R2X = 0.693, Q2 = 0.854) was successfully constructed. Element contents and stable isotope ratios are more reliable variables for milk origin discrimination and Rb, δ18O, Tl, Ba, Mo, Sr, δ15N, Cs, As, Eu, C20:4n6, Sc, C13:0, K, Ca and C16:1n7 are the critical markers in the multivariate model for verifying milk origin.
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Affiliation(s)
- Siyan Xu
- School of Life Sciences, Shanghai University, Shanghai 200444, China
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Ogrinc N, Camin F. Special Issue "Isotopic Techniques for Food Science". Molecules 2020; 26:molecules26010134. [PMID: 33396761 PMCID: PMC7796104 DOI: 10.3390/molecules26010134] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 12/28/2020] [Indexed: 11/16/2022] Open
Abstract
Today, the analytical verification of food safety and quality together with authenticity and traceability plays a central role in food analysis [...].
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Affiliation(s)
- Nives Ogrinc
- Department of Environmental Sciences, Jožef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia
- Jožef Stefan International Postgraduate School, Jamova 39, 1000 Ljubljana, Slovenia
- Correspondence: ; Tel.: +386-1-588-5387
| | - Federica Camin
- Department of Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach, via Mach 1, 38010 San Michele all’Adige, Italy;
- Center Agriculture Food Environment (C3A), University of Trento, via Mach 1, 38010 San Michele all’Adige, Italy
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