Establishment of Non-Destructive Methods for the Detection of Amylose and Fat Content in Single Rice Kernels Using Near-Infrared Spectroscopy

For the efficient selection of high-quality rice varieties, near-infrared spectroscopy (NIRS) technique has been widely applied to detect constituents in single kernels. Compared with other constituents, amylose content (AC) and fat (FC) are key parameters that can affect quality rice. Based on two modified AC FC trace detection methods, NIRS methods kernels were developed. Using proposed groups kernel datasets measured. The collected spectrometers different sample movement states (static dynamic) measurement modes (diffuse reflectance (NIRr) diffuse transmission (NIRt)). By optimizing pre-treatment method spectral range, determination coefficients cross-validation (R2cv) prediction (R2p) models under conditions all above 0.6. results indicated applicable rapid, non-destructive sorting individual seeds FC, it was shown these meet requirements rough screening seed varieties.