A study of starch content detection and the visualization of fresh-cut potato based on hyperspectral imaging
Fuxiang Wang, Chunguang Wang, Shiyong Song
Abstract
) value of 0.9467, root mean square error of prediction of 1.63, and RPD of 2.95. The starch content in fresh-cut potatoes was visualized using the best model in combination with pseudocolor technology. The results indicate that hyperspectral imaging is effective for mapping the spatial distribution of starch content; thus, a solid theoretical basis is obtained for the grading and online monitoring of fresh-cut potato slices.
Topics & Concepts
Hyperspectral imagingStarchVisualizationContent (measure theory)Potato starchChemistryComputer scienceFood scienceMathematicsArtificial intelligenceMathematical analysisSpectroscopy and Chemometric AnalysesWater Quality Monitoring and AnalysisAdvanced Chemical Sensor Technologies