Advanced Hyperspectral Imaging for Macronutrient Analysis in Glutinous Rice Under Varying Drying Conditions

Original Title: Hyperspectral Imaging Spectroscopy for Non-Destructive Determination of Grape Berry Total Soluble Solids and Titratable Acidity

Jimoh et al. Current Research in Food Science 2025, 10, 100963; https://doi.org/10.3390/rs16101655

Glutinous rice (GR) is a widely consumed variety in Asia, known for its sticky texture after cooking due to its high amylopectin content. Beyond its culinary significance, assessing its nutritional composition—including moisture, protein, fat, and ash content—is essential to ensuring its quality.

For this reason, the use of hyperspectral imaging in the visible and near-infrared spectrum was studied as a non-invasive tool to analyze the composition of GR under different drying conditions. Advanced data processing techniques and wavelength selection methods were applied to enhance the accuracy of macronutrient detection.

The results showed that using the Savitzky-Golay (SG1D) method and the VISSA algorithm significantly improved analysis precision, achieving 100% accuracy in quality parameters prediction. This confirms that combining hyperspectral imaging with advanced data processing is an effective strategy for assessing the nutritional quality of GR in the food industry.

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