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

The Application of Multi-Parameter Multi-Modal Technology Integrating Biological Sensors and Artificial Intelligence in the Rapid Detection of Food Contaminants

Against the backdrop of continuous socio-economic development, there is a growing concern among people about food quality and safety. Individuals are increasingly realizing the critical importance of healthy eating for bodily health; hence the continuous rise in demand for detecting food pollution. Simultaneously, the rapid expansion of global food trade has made people's pursuit of high-quality food more urgent. However, traditional methods of food analysis have certain limitations, mainly manifested in the high degree of reliance on personal subjective judgment for assessing food quality. In this context, the emergence of artificial intelligence and biosensors has provided new possibilities for the evaluation of food quality. This paper proposes a comprehensive approach that involves aggregating data relevant to food quality indices and developing corresponding evaluation models to highlight the effectiveness and comprehensiveness of artificial intelligence and biosensors in food quality evaluation. The potential prospects and challenges of this method in the field of food safety are comprehensively discussed, aiming to provide valuable references for future research and practice.

Using isotopic fingerprints in gastropod shells to validate commercial production pathway and geographic provenance

Growing demand for high-value seafood is fuelling provenance fraud, which threatens the sustainability of wild fisheries while posing biosecurity and human health risks. Here, we investigated carbon (δ 13C) and oxygen (δ 18O) isotopes in abalone shells (Haliotis sp.) to determine the production method and geographical provenance. Using X-ray diffraction and isotope ratio mass spectrometry, we found that shell mineralogy did not influence isotope values. Isotope values between wild and farmed sectors were statistically different, with 64% of individuals correctly classified as farmed or wild. Subsequently, we successfully distinguished the provenance of abalone collected from farms (with 83% of individuals correctly classified), as well as wild-caught abalone collected from four state jurisdictions (with 88% correctly classified). Carbon isotopes were strongly correlated to longitude, with both isotopes correlated to latitude. Overall, this study demonstrates the potential of isotopic fingerprints in gastropod shells to track the provenance of commercially valuable species.

Innovation to limit seafood fraud post-COVID-19

Seafood is an important source of protein and micronutrients, but fishery stocks are increasingly under pressure from both legitimate and illegitimate fishing practices. Sustainable management of our oceans is a global responsibility, aligning with United Nations Sustainable Development Goal 14, Life Below Water. In a post-COVID-19 world, there is an opportunity to build back better, where locally sourced food via transparent supply chains are ever-more important. This article summarises emerging research of two innovative case studies in detecting and validating seafood provenance; and using alternative supply chains to minimise the opportunity for seafood fraud in a post-COVID-19 world.