Using plant physiological stable oxygen isotope models to counter food fraud

Cueni, Florian and Nelson, Daniel B. and Boner, Markus and Kahmen, Ansgar. (2021) Using plant physiological stable oxygen isotope models to counter food fraud. Scientific reports, 11 (1). p. 17314.

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Official URL: https://edoc.unibas.ch/84975/

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Fraudulent food products, especially regarding false claims of geographic origin, impose economic damages of $30-$40 billion per year. Stable isotope methods, using oxygen isotopes (δ 18 O) in particular, are the leading forensic tools for identifying these crimes. Plant physiological stable oxygen isotope models simulate how precipitation δ 18 O values and climatic variables shape the δ 18 O values of water and organic compounds in plants. These models have the potential to simplify, speed up, and improve conventional stable isotope applications and produce temporally resolved, accurate, and precise region-of-origin assignments for agricultural food products. However, the validation of these models and thus the best choice of model parameters and input variables have limited the application of the models for the origin identification of food. In our study we test model predictions against a unique 11-year European strawberry δ 18 O reference dataset to evaluate how choices of input variable sources and model parameterization impact the prediction skill of the model. Our results show that modifying leaf-based model parameters specifically for fruit and with product-independent, but growth time specific environmental input data, plant physiological isotope models offer a new and dynamic method that can accurately predict the geographic origin of a plant product and can advance the field of stable isotope analysis to counter food fraud.
Faculties and Departments:05 Faculty of Science > Departement Umweltwissenschaften > Integrative Biologie > Physiological Plant Ecology (Kahmen)
UniBasel Contributors:Kahmen, Ansgar and Cueni, Florian and Nelson, Daniel
Item Type:Article, refereed
Article Subtype:Research Article
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:24 Feb 2022 14:23
Deposited On:27 Jan 2022 12:57

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