Agri-food supply and value chain markets have become increasingly complex due to the changes in consumers demands, the development of complex food standards associated with food safety and quality, advances in technology (e.g. big data, machine learning), and changes in the food industry structure. However, recent issues related to food authenticity, adulteration, fraud, mislabelling, traceability and provenance have added a new dimension to consumers’ concerns, and food industry and regulatory bodies worldwide. The incorporation of sensing technologies combined with data analytics, are determining a paradigm shift in the way food ingredients and foods are both evaluated and monitored. This chapter discusses the utilisation of data analytics and sensing technologies to address issues related with food authenticity, adulteration, fraud, traceability and provenance in the food supply and value chains. In particular, this chapter will focus on the use of rapid analytical methods based in vibrational spectroscopy in combination with data analytics.