Spatial fingerprinting: horizontal fusion of multi-dimensional bio-tracers as solution to global food provenance problems

Cazelles, Kevin; McCann, Kevin; Zemlak, Tyler; Gutgesell, Marie; Myles-Gonzalez, Emelia; Hanner, Robert

doi:10.5061/dryad.95x69p8jd

Cited by 2 publications

References 2 publications

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Spatial fingerprinting: horizontal fusion of multi-dimensional bio-tracers as solution to global food provenance problems

Cazelles

Zemlak

Gutgesell

et al. 2020

Preprint

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Building the capacity of efficiently determining the provenance of food products represents a crucial step towards the sustainability of the global food system. Whether it is for enforcing existing egislation or providing reliable information to consumers, technologies to verify geographical origin of food are being actively developed. Biological tracers (bio-tracers) such as DNA and stable isotopes have recently demonstrated their potential for determining provenance. Here we show that the data fusion of bio-tracers is a very powerful technique for geographical provenance discrimination. Based on 90 individuals of Sockeye salmon that originate from 3 different areas for which we measured 17 bio-tracers, we demonstrate that increasing the combined bio-tracers results in stronger the discriminatory power. The generality of our results are mathematically demonstrated under simplifying assumptions and numerically confirmed in our case study using three commonly used supervised learning techniques.

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Spatial fingerprinting: horizontal fusion of multi-dimensional bio-tracers as solution to global food provenance problems

Cazelles

Zemlak

Gutgesell

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

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Spatial Fingerprinting: Horizontal Fusion of Multi-Dimensional Bio-Tracers as Solution to Global Food Provenance Problems

Cazelles

Zemlak

Gutgesell

et al. 2021

Foods

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Building the capacity of efficiently determining the provenance of food products represents a crucial step towards the sustainability of the global food system. Despite species specific empirical examples of multi-tracer approaches to provenance, the precise benefit and efficacy of multi-tracers remains poorly understood. Here we show why, and when, data fusion of bio-tracers is an extremely powerful technique for geographical provenance discrimination. Specifically, we show using extensive simulations how, and under what conditions, geographical relationships between bio-tracers (e.g., spatial covariance) can act like a spatial fingerprint, in many naturally occurring applications likely allowing rapid identification with limited data. To highlight the theory, we outline several statistic methodologies, including artificial intelligence, and apply these methodologies as a proof of concept to a limited data set of 90 individuals of highly mobile Sockeye salmon that originate from 3 different areas. Using 17 measured bio-tracers, we demonstrate that increasing combined bio-tracers results in stronger discriminatory power. We argue such applications likely even work for such highly mobile and critical fisheries as tuna.

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Spatial fingerprinting: horizontal fusion of multi-dimensional bio-tracers as solution to global food provenance problems

Cited by 2 publications

References 2 publications

Spatial fingerprinting: horizontal fusion of multi-dimensional bio-tracers as solution to global food provenance problems

Spatial fingerprinting: horizontal fusion of multi-dimensional bio-tracers as solution to global food provenance problems

Spatial Fingerprinting: Horizontal Fusion of Multi-Dimensional Bio-Tracers as Solution to Global Food Provenance Problems

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