Plant Imaging Expert Group: Application of Infrared Spectroscopy and Image Fusion Technology in Non-Destructive Quality Inspection of Individual Grains

Please join us on Wednesday, March 25, at 13:00 CET, for a session featuring the Application of Infrared Spectroscopy and Image Fusion Technology in Non-Destructive Quality Inspection of Individual Grains.

The application of infrared spectroscopy and image fusion technology has emerged as a powerful approach for the non-destructive quality inspection of individual grains, addressing the growing demand for rapid, accurate, and objective assessment in modern agriculture and food industries. Traditional grain quality evaluation methods are often labor-intensive, destructive, and limited in their ability to capture internal chemical composition. In contrast, infrared spectroscopy, particularly near-infrared (NIR) and mid-infrared (MIR) techniques enables the rapid detection of key physicochemical properties such as moisture, protein, starch, and lipid content without damaging the sample.

When combined with advanced imaging systems, infrared spectroscopy provides both spectral (chemical) and spatial (structural) information at the single-grain level. Image fusion technology further enhances this capability by integrating data from multiple imaging modalities, improving feature extraction, defect detection, and classification accuracy.

Through the synergistic use of spectral analysis and image fusion, researchers and industry professionals can achieve more precise grading, contamination detection, and varietal identification, ultimately improving quality control, reducing waste, and supporting sustainable grain management practices.

We will welcome Qixing Tang from College of Electronic and Electrical Engineering, Anhui Agricultural University who will showcase the fusion of cross-source spectral data with component-driven analysis for maize grain quality detection; a small-sample crop seed quality detection system based on spectral-image bimodal fusion technology; and hyper-spectral imaging for seed viability assessment.

Join us to explore the significant potential of spectral and imaging techniques in advancing grain quality evaluation and precision agriculture.