Physiological index data and low-field nuclear magnetic resonance (LF-NMR) spectral data of rice seed samples from three varieties harvested in different years were collected through a combination of the standard germination test and an LF-NMR test. Three parameters of seed vigor: germination energy, germination percentage, and germination index, were calculated based on the physiological index data of the rice seed samples to determine their vigor over the years after harvest. LF-NMR Carr-Purcell-Meiboom-Gill (CPMG) sequence echo-peak data were used as the input, and rice seed vigor was used as the output to establish discriminative models using principal component analysis, support vector machine, logistic regression, K-nearest neighbor, artificial neural network, and Fisher’s linear discriminant. The results showed that models constructed using any algorithm, except for principal components analysis-algorithm distinguished between seeds with high and low vigor, while models constructed using Fisher’s linear discriminant algorithm gave the best results. This study provided a rapid, accurate, and non-destructive method to test rice seed vigor, offering theoretical support and a reference for rice seed-sorting and storage research.

This study aimed to investigate the effect of low-frequency high-voltage pulsed electric field (LFHV-PEF) treatment on the germination of aged rice seeds. Aged rice seeds were subjected to LFHV-PEF treatment with different electric field strengths, and low-field nuclear magnetic resonance (LF-NMR) was performed to acquire the LF-NMR data of rice seeds at different germination periods during a standard seed germination test to analyze their internal patterns of water state and distribution. Optimal treatment conditions were determined based on the physicochemical data collected during germination, and the improvements in seed vigor were verified. The findings indicated that during germination, the contents of bound and semi-bound water within the aged rice seeds initially increased and then decreased, whereas free water and total water contents increased continuously and rapidly. Side peaks were also observed within the seeds. Under the LFHV-PEF treatment, the semi-bound water within the seeds was more easily converted to free water, and the water absorption rate, germination potential, germination rate, germination index, and vigor index of these seeds improved. Further, the optimal electrical field strength was 12 kV. By analyzing the internal patterns of water state and distribution in seeds, the mechanism by which electric field treatment improved seed vigor was elucidated, thus, providing theoretical support and data evidence for research on water absorption during the germination of rice seeds, and methods for improving seed vigor.

To clarify the quantitative relationship between tempering drying parameters and the physicochemical properties of paddy rice, and to optimize the paddy rice drying process, a quadratic regression orthogonal rotational combination test was applied in this study. The initial tempering moisture content of paddy rice, tempering temperature, and tempering duration were the test factors, and the amylose starch content, alkali spreading value, and gel consistency were the test indicators. It was shown that under the conditions of the initial tempering moisture content of paddy rice of 20.5%, the tempering temperature of 43°C, and the tempering duration of 3.39 hr, the amylose starch content, alkali spreading value, and gel consistency were 17.83%, 7.08 grade and 86.4 mm, respectively. The average error between the actual value and the optimized theoretical value was 4.06%, indicating that the regression model was accurate and the physicochemical properties of rice were improved under the optimal process conditions. Then, the visual prediction model for the physicochemical properties of rice was established based on BP (Back Propagation) and GA-BP (Genetic Algorithm-BP) neural networks, respectively, and was compared with the regression model established by Design-Expert software. The results showed that the root mean square error, mean absolute error, and mean absolute percentage error of GA-BP were lower. Practical applicationsDrying is a significant primary process performed during the grain post-harvest period, and it has a significant impact on the qualities of appearance, nutrition, and consumption. Traditional hot air drying has many problems such as low drying efficiency and high crack percentage, while tempering drying can alleviate those by reducing the gradient difference between the inside and outside of the grain, and this has become a hot spot for paddy rice drying research. To meet the current market demand for grain quality, most researchers have discussed the effects of tempering temperature and duration on the milling and nutrition qualities of rice. However, research on the initial tempering moisture content of paddy rice, tempering way, and its effect on the physicochemical properties of rice has rarely been reported. Therefore, it is important to study the influence of tempering drying process parameters on the physicochemical properties of paddy rice.