Food supply chain involves many operations and processes with so-called critical control points where inspection of food is required to assess and thus ensure safety, but also to achieve certain specifications and sensory attributes. Traditional methods of food inspection include analytical procedures, and also expert/human evaluation, which are generally destructive, time-consuming, laborious and expensive. In order to improve efficiency and productivity, non-destructive, automatic, rapid and cost-effective methods of food inspection are continuously required to replace such traditional methods. In this regard, hyperspectral imaging (HSI) has emerged as a promising technique for food industry. In this chapter, we present a review about implementation at industrial scale of HSI technology for food safety and quality inspection. We consider both classification and quantification models and tasks, and discuss some key examples and applications to illustrate the use of HSI for solving industrial problems. Overall, there is still work to do to translate laboratory scale research into effective implementation of HSI at industrial scale.