Yun Liu

Buckwheat grains will suffer varying degrees of damage during the threshing process. Damaged grains are prone to changes in nutritional quality during storage. To explore the relationship between the threshing damage mechanism and nutritional quality, the mechanical properties of buckwheat with different moisture contents were determined through compression and friction tests, obtaining some conventional mechanical property indicators. On this basis, a 3D collision model of buckwheat–nail tooth was established, and the dynamic process of collision was simulated with LS-DYNA. During collision, the changes in energy, von Mises stress, and critical damage velocity of grains with different moisture contents were analyzed. After the threshing test, the grains were observed and classified according to the degree of damage. The differences in nutritional components of different types of grains were analyzed through physicochemical experiments. The experimental results showed that the failure force, elastic modulus, and ultimate strength of buckwheat grains were negatively correlated with moisture content, while the deformation and friction coefficient were positively correlated with moisture content. During collision, the von Mises stress of the grains showed a pattern of increase and then decrease. The maximum stress value occurred at the contact area center, spreading along the periphery and gradually decreasing. The maximum von Mises stress decreased with increasing moisture content and increased with increasing collision velocity. The critical damage velocities of grains at moisture contents of 11.98%, 15.77%, 18.04%, 20.82%, and 25.22% were 13.07, 11.72, 10.94, 10.55, and 10.15 m/s, respectively. After threshing, grains were divided into three types: undamaged, surface cracked, and shell damaged. The nutritional quality of the last two damaged grains decreased during the storage process. These results are of great significance for optimizing buckwheat threshing parameters, reducing buckwheat damage, and improving the economic performance of the buckwheat industry.

For buckwheat, the optimal harvest period is difficult to determine—too early or too late a harvest affects the nutritional quality of buckwheat. In this paper, physical and chemical tests are combined with a method using near-infrared spectroscopy nondestructive testing technology to study buckwheat harvest and determine the optimal harvest period. Physical and chemical tests to determine the growth cycle were performed at 83 days, 90 days, 93 days, 96 days, 99 days, and 102 days, in which the buckwheat grain starch, fat, protein, total flavonoid, and total phenol contents were assessed. Spectral images of buckwheat in six different harvest periods were collected using a near-infrared spectral imaging system. Four preprocessing methods (SNV, S-G, DWT, and the normaliz function) and three dimensionality reduction algorithms (IVSO, VCPA, VISSA) were used to process the raw buckwheat spectral data, and the full and eigen spectra were established as a random forest (RF). Random forest (RF) and Least Squares Support Vector Machine (LS-SVM) classification models were used to determine the full and eigen spectra, respectively, and the optimal model for the buckwheat single harvest period was determined and validated. Through physical and chemical tests, it was concluded that the 90-day harvest buckwheat grain protein, fat, and starch contents were the highest, and that the total flavonoid and total phenolic contents were also high. The SNV preprocessing method was the most effective, and the feature bands extracted using the IVSO algorithm were more representative. The IVSO-RF model was the best discriminative model for the classification of buckwheat in different harvest periods, with the correct rates of the training and prediction sets reaching 100% and 96.67%, respectively. When applying the IVSO-RF model to the buckwheat single harvest period to verify the classification, the correct rate of the training set for each harvest period reached 96%, and that of the prediction set reached 100%. Near-infrared spectroscopy combined with the IVSO-RF modeling method for buckwheat harvest period detection is a rapid, nondestructive classification method. When this was combined with physical and chemical analyses, it was determined that a growth cycle of 90 days is the best harvest period for buckwheat. The results of this study can not only improve the quality of buckwheat crops but also be applied to other crops to determine their optimal harvest period.

Mechanical threshing can cause damage to oats, and the nutritional quality of the damaged kernels easily changes during storage. The current research on oats with regard to threshing damage and nutritional quality falls into two separate research areas, but they are inextricably linked. It is necessary to combine these two types of studies. In order to explore the damage mechanism of oat threshing and its effect on the nutritional components, a three-dimensional model of oat–nail-tooth impact was established, and a finite element analysis of the dynamic impact process was performed using LS-DYNA. The changes in the von Mises stress, contact force, energy, critical velocity, and damage characteristics during impact on different surfaces of the kernel were analyzed. A threshing test was carried out, and the kernels were classified according to their different damage types. The differences in the nutrient compositions and contents of oats with different damage types were analyzed by means of near-infrared spectroscopy and physicochemical testing. The results showed that the von Mises stress and contact force tended to first increase and then decrease during impact. When the impact velocity was 12 m/s, for the top, bottom, front, back, and left sides of the oat impacted by the nail tooth, the maximum von Mises stresses were 10.05, 10.46, 8.60, 9.28, and 8.49 MPa, respectively. The maximum contact forces were 25.09, 18.57, 34.29, 38.37, and 35.19 N, respectively. The critical velocities of impact damage were 13.38, 13.10, 13.40, 14.64, and 16.00 m/s, respectively. The threshing damage could be divided into four typical types: transverse fracture, bottom breakage, side fracture, and back crack. The chemical compositions of oat kernels with different damage types were basically the same, but their nutrient contents were different. These results provide a theoretical basis for optimizing oat threshing devices, reducing threshing damage, and improving oat quality.