Authentication of the Geographical Origin of Shandong Scallop Chlamys farreri Using Mineral Elements Combined with Multivariate Data Analysis and Machine Learning Algorithm-Reference-Cited by-同舟云学术

Authentication of the Geographical Origin of Shandong Scallop Chlamys farreri Using Mineral Elements Combined with Multivariate Data Analysis and Machine Learning Algorithm

Published:2022-06-21 Issue:11 Volume:15 Page:2984-2993
ISSN:1936-9751
Container-title:Food Analytical Methods
language:en
Short-container-title:Food Anal. Methods

Author:

Kang Xuming,Zhao Yanfang,Peng Jixing,Ding Haiyan,Tan Zhijun,Han Cui,Sheng Xiaofeng,Liu Xiyin,Zhai Yuxiu

Funder

Central Public-interest Scientific Institution Basal Research Fund, YSFRI, CAFS

Open task of Key Laboratory of Testing and Evaluation for Aquatic Product Safety and Quality, Ministry of Agriculture and Rural Affairs

Key Projects of Intergovernmental International Cooperation in Science and Technology Innovation

Central Public-interest Scientific Institution Basal Research Fund, CAFS

China Agriculture Research System of MOF and MARA

Publisher

Springer Science and Business Media LLC

Subject

Safety Research,Safety, Risk, Reliability and Quality,Applied Microbiology and Biotechnology,Food Science,Analytical Chemistry

Link

https://link.springer.com/content/pdf/10.1007/s12161-022-02346-8.pdf

Reference56 articles.

1. Bennion M, Morrison L, Brophy D, Carlsson J, Abrahantes JC, Graham CT (2019) Trace element fingerprinting of blue mussel (Mytilus edulis) shells and soft tissues successfully reveals harvesting locations. Sci Total Environ 685:50–58. https://doi.org/10.1016/j.foodcont.2020.107515

2. Bevilacqua M, Bucci R, Magrì AD, Magrì AL, Nescatelli R, Marini F (2013) Classification and class-modelling. In: Marini F (ed) Chemometrics in food chemistry, 1st edn., 28. Elsevier, Amsterdam, pp 171–233. https://doi.org/10.1016/B978-0-444-59528-7.00005-3

3. Breiman (2001) Statistical modeling: the two cultures. Stat Sci 16(3):199–231. https://doi.org/10.1214/ss/1009213726

4. Callao MP, Ruisánchez I (2018) An overview of multivariate qualitative methods for food fraud detection. Food Control 86:283–293. https://doi.org/10.1016/j.foodcont.2017.11.034

5. Canizo BV, Escudero LB, Pellerano RG, Wuilloud RG (2019) Data mining approach based on chemical composition of grape skin for quality evaluation and traceability prediction of grapes. Comput Electron Agr 162:514–522. https://doi.org/10.1016/j.compag.2019.04.043

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