Optical imaging for food grain quality evaluation–recent advances and future perspectives

Abstract

Optical imaging techniques have gained widespread popularity in grain quality evaluation due to their non-destructive nature, rapid analysis, and ability to provide detailed information about various grain properties. This review highlights recent advancements in optical imaging technologies, including hyperspectral imaging (HSI), multispectral imaging (MSI), RGB imaging, fluorescence imaging (FI), thermal imaging (TI), and ultraviolet imaging (UVI) along with their future perspectives. These techniques are discussed in terms of their principles, applications, and potential for non-destructive assessment of grain quality parameters such as composition, defects, and contamination. A comparative analysis of these techniques is provided, emphasizing their precision, application areas, and limitations. Challenges such as calibration model development, illumination variability, and the complexity of image analysis are critical for widespread adoption to construct robust and generalised models. Despite these challenges, integrating these imaging techniques offers significant opportunities for improving grain sorting, storage, and processing. By providing comprehensive and objective data, these technologies have the potential to revolutionize grain quality monitoring and enhance postharvest management practices, enabling greater efficiency and reduced costs.