Climate change, the growth in world population, high levels of food waste and food loss, and
the risk of new disease or pandemic outbreaks are examples of the many challenges that …

In considering the need of people all over the world for high-quality food, there has been a
recent increase in interest in the role of nondestructive and rapid detection technologies in …

It has been reported that quantum generative adversarial networks have a potential
exponential advantage over classical generative adversarial networks. However, quantum …

Abstract Machine learning (ML) has proven to be a useful technology for data analysis and
modeling in a wide variety of domains, including food science and engineering. The use of …

Food waste is a global issue with significant economic, social, and environmental impacts.
Addressing this problem requires a multifaceted approach; one promising avenue is using …

Artificial Intelligence (AI) technologies have been powerful solutions used to improve food
yield, quality, and nutrition, increase safety and traceability while decreasing resource …

Despite extensive commercial and regulatory interventions, food spoilage and
contamination continue to impose massive ramifications on human health and the global …

With advances in artificial intelligence (AI) technologies, the development and
implementation of digital food systems are becoming increasingly possible. There is …

Background Immunochromatographic test strip (ICTS) has become one of the most widely
used rapid diagnostics platforms for the point-of-care testing of various contaminant residues …

To enhance the resilience of food systems to food safety risks, it is vitally important for
national authorities and international organizations to be able to identify emerging food …