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 …

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 …

The massive rise of Big Data generated from smartphones, social media, Internet of Things
(IoT), and multimedia, has produced an overwhelming flow of data in either structured or …

Big data analysis has found applications in many industries due to its ability to turn huge
amounts of data into insights for informed business and operational decisions. Advanced …

Technology is being developed to handle vast amounts of complex data from diverse
sources. The terms" Big Data" and" Decision Support Systems"(DSS) refer to computerised …

Agriculture stands on the cusp of a digital revolution, and the same technologies that created
the Internet and are transforming medicine are now being applied in our farms and on our …

Food Traceability 4.0 refers to the application of fourth industrial revolution (or Industry 4.0)
technologies to ensure food authenticity, safety, and high food quality. Growing interest in …

Blockchain technology is a distributed ledger technology and is expected to face some
difficulties and challenges in various industries due to its transparency, decentralization …

Food safety continues to threaten public health. Machine learning holds potential in
leveraging large, emerging data sets to improve the safety of the food supply and mitigate …

We ask how European food law impacts the transformative potential of alternative proteins,
including single-cell proteins, plant-based novel proteins, cultured meat, macroalgae, and …