Non-destructive and rapid detection of the internal chemical composition of granules samples by spectral transfer

Near-infrared spectroscopy (NIRS) analysis has been widely used in various industries, but the stability and accuracy of the final analysis results rely on the sample uniformity, limiting the application of the technique in the analysis of granules samples. In this work, the protein and amylose of rice as research objects, and proposed to transform the spectrum of the granules into the spectrum of its corresponding powder through spectral transfer based on direct standardization (DS), successfully, followed by using the powder model to predict the new spectrum. After the spectral transfer, the root mean square of validation (RMSEV) values of protein were reduced from 0.3293, 0.6890, and 0.6815 to 0.2602, 0.5106, and 0.4436, respectively. and the RMSEV values of amylose were reduced from 0.9587, 1.0601, 2.8952 to 0.7094, 0.8317, and 2.4090, respectively. After using key variables for spectral transfer, the RMSEV values of protein were 0.2410, 0.5336 and 0.4605, respectively, while the RMSEV values of amylose were 0.6760, 0.8442 and 2.3392, respectively. These results clearly show that spectral transfer can ameliorate the problem of large error and poor stability of analytical results due to the irregular sample and uneven component distribution, which will promote the NIRS technique to achieve real-time and accurate online supervision in agricultural production.