In this chapter, the role of hyperspectral imaging (HSI) as a non-destructive technique for rapid and simultaneous assessment of food quality parameters is explored. Hyperspectral imaging provides the combined benefits of spectroscopy and machine vision, thereby capturing the chemical information at each pixel in the sample. This chapter starts with the theory and principles of hyperspectral imaging, along with the imaging and processing approaches that are used to transform hyperspectral imaging into a useful tool for food quality analysis. It also delves into the applications of spectral imaging, particularly in meat, fruits and vegetables, grains and cereals, and dairy products such as for the detection of contaminants and defects, assessment of freshness and nutritional composition, and sorting and grading applications. Ultimately, it covers the future trends in HSI which include the advancement in optical sensing and machine learning techniques.