Advances in Hyperspectral Imaging Technology for Grain Quality and Safety Detection: A Review

This review provides an overview of recent advancements in hyperspectral imaging (HSI) technology for grain quality and safety detection, focusing on its impact on global food security and economic stability. Traditional methods for grain quality assessment are labor-intensive, time-consuming, and destructive, whereas HSI offers a non-destructive, efficient, and rapid alternative by integrating spatial and spectral data. Over the past five years, HSI has made significant strides in several key areas, including disease detection, quality assessment, physicochemical property analysis, pesticide residue identification, and geographic origin determination. Despite its potential, challenges such as high costs, complex data processing, and the lack of standardized models limit its widespread adoption. This review highlights these advancements, identifies current limitations, and discusses the future implications of HSI in enhancing food safety, traceability, and sustainability in the grain industry.