Soil organic matter is an important component that reflects soil fertility and promotes plant growth. The soil of typical Chinese tea plantations was used as the research object in this work, and by combining soil hyperspectral data and image texture characteristics, a quantitative prediction model of soil organic matter based on machine vision and hyperspectral imaging technology was built. Three methods, standard normalized variate (SNV), multisource scattering correction (MSC), and smoothing, were first used to preprocess the spectra. After that, random frog (RF), variable combination population analysis (VCPA), and variable combination population analysis and iterative retained information variable (VCPA-IRIV) algorithms were used to extract the characteristic bands. Finally, the quantitative prediction model of nonlinear support vector regression (SVR) and linear partial least squares regression (PLSR) for soil organic matter was established by combining nine color features and five texture features of hyperspectral images. The outcomes demonstrate that, in comparison to single spectral data, fusion data may greatly increase the performance of the prediction model, with MSC + VCPA-IRIV + SVR (R²C = 0.995, R²P = 0.986, RPD = 8.155) being the optimal approach combination. This work offers excellent justification for more investigation into nondestructive methods for determining the amount of organic matter in soil.

Soil fertility is vital for the growth of tea plants. The physicochemical properties of soil play a key role in the evaluation of soil fertility. Thus, realizing the rapid and accurate detection of soil physicochemical properties is of great significance for promoting the development of precision agriculture in tea plantations. In recent years, spectral data have become an important tool for the non-destructive testing of soil physicochemical properties. In this study, a support vector regression (SVR) model was constructed to model the hydrolyzed nitrogen, available potassium, and effective phosphorus in tea plantation soils of different grain sizes. Then, the successful projections algorithm (SPA) and least-angle regression (LAR) and bootstrapping soft shrinkage (BOSS) variable importance screening methods were used to optimize the variables in the soil physicochemical properties. The findings demonstrated that soil particle sizes of 0.25–0.5 mm produced the best predictions for all three physicochemical properties. After further using the dimensionality reduction approach, the LAR algorithm (R²_C = 0.979, R²_P = 0.976, RPD = 6.613) performed optimally in the prediction model for hydrolytic nitrogen at a soil particle size of 0.25~0.5. The models using data dimensionality reduction and those that used the BOSS method to estimate available potassium (R²_C = 0.977, R²_P = 0.981, RPD = 7.222) and effective phosphorus (R²_C = 0.969, R²_P = 0.964, RPD = 5.163) had the best accuracy. In order to offer a reference for the accurate detection of soil physicochemical properties in tea plantations, this study investigated the modeling effect of each physicochemical property under various soil particle sizes and integrated the regression model with various downscaling strategies.

To address the inefficient use of pruned grape branches and the high cost of orchard management, an integrated machine for collecting and crushing grape branches was developed, tailored to the distinctive viticulture methods in Xinjiang, China, and the physical properties of the branches. Based on a unified design scheme, the structural parameters of the collection mechanism and the suitable operating width were optimized through systematic theoretical analysis. The crushing unit was designed with attention to blade shape, quantity, and spatial distribution, while critical operational parameters—including blade dimensions, speed range, and key factors influencing crushing quality—were identified using kinetic analysis. A three-factor, three-level response surface experiment was designed via Design Expert software, incorporating crushing roller speed, pickup roller speed, and ground clearance of the pickup device as test variables. Pickup rate and acceptable fragment ratio were employed as evaluation indicators. Field tests showed that at a crushing roller speed of 2185 r/min, pickup roller speed of 105 r/min, and ground clearance of 10 mm, the pickup rate was 95.93% and the qualified fragmentation rate reached 97.19%, the machine met the operational requirements of achieving over 95% efficiency for both collection and crushing. This study provides a theoretical foundation and technical support for the mechanized treatment of pruned grape branches in Xinjiang.

Using numerical simulation method, combined with the pre-branch material characteristics of the measurement results, based on the LS-DYNA software to simulate the branch crushing process, the analysis found that not only the existence of the cutter cutting in the branch destruction process, there is also the cutting of the opposing surface of the bending fracture, with the increase in the speed of the knife rollers, the cutter cutting resistance increases, the cutting resistance reaches 2690 N when the cutter at 2500 r/min, the cutter cutting resistance is the smallest in the cutting simulation at the blade angle of 55°, the blade angle is more suitable for the cutting of the branch. In the cutting simulation under different cutting edge angles, the cutting resistance of the tool is the smallest when the edge angle is 55°, which is 1860 N. This edge angle is more suitable for branch crushing and cutting. Using Fluent software to analyse the airflow characteristics of the crushing device, it was found that with the increase of the knife roller speed, the inlet flow and negative pressure of the crushing chamber are increasing, the speed of 2500 r/min, the inlet flow and negative pressure were 1.92 kg/s and 37.16 Pa, which will be conducive to the feeding of branches, but the speed is too high and it will also lead to the enhancement of the vortex of part of the area in the crushing device, which will affect the feeding of branches and the throwing of the crushed material. affect the feeding of branches and the throwing out of crushed materials, and finally determined the speed range of the crushing knife roller is 1800 ~ 2220 r/min. Based on ANSYS/Model module modal analysis of the crushing knife roller, the knife roller of the first six orders of the intrinsic frequency and vibration pattern, crushing knife roller of the lowest order of the modal intrinsic frequency of 137.42 Hz, much larger than the crushing knife roller operating frequency of 37 Hz, the machine will not resonate during operation.

Aiming at the problem of the low rate of resource utilization of large amounts of grape branch pruning and the high cost of leaving the garden, we design a kind of grape branch picking and crushing collection machine that integrates the collection of strips, the picking up, crushing, and collecting operations. The crushing and collecting parts of the machine are simulated, analyzed, and tested. Using the method of numerical simulation, combined with the results of the pre-branch material properties measurement, the branch crushing process is simulated based on LS-DYNA software. Our analysis found that in the branch destruction process, not only does knife cutting exist, but the bending fracture of the opposite side of the cutting place also exists. With the increase in the knife roller speed, the cutting resistance of the tool increases, reaching 2690 N at 2500 r/min. In the cutting simulation under different tool edge angles, the cutting resistance of the tool is the smallest when the edge angle is 55°, which is 1860 N, and this edge angle is more suitable for branch crushing and cutting. In the cutting simulation under different cutting edge angles, the cutting resistance of the tool is the smallest when the edge angle is 55°, which is 1860 N, and this edge angle is more suitable for branch crushing and cutting. Using Fluent software to analyze the characteristics of the airflow field of the pulverizing device, it was found that with the increase in the knife roller speed, the inlet flow and negative pressure of the pulverizing chamber increase. When the knife roller speed is 2500 r/min, the inlet flow rate and negative pressure are 1.92 kg/s and 37.16 Pa, respectively, which will be favorable to the feeding of the branches, but the speed is too high and will also lead to the enhancement of the vortex in some areas within the pulverizing device, which will in turn affect the feeding of the branches as well as the throwing out of pulverized materials. Therefore, the speed range of the pulverizing knife roller was finally determined to be 1800~2220 r/min. Based on the ANSYS/Model module modal analysis of the crushing knife roller, the knife roller of the first six orders of the intrinsic frequency and vibration pattern, the crushing knife roller of the lowest order had a modal intrinsic frequency of 137.42 Hz, much larger than the crushing knife roller operating frequency of 37 Hz, above which the machine will not resonate during operation. The research results can provide a theoretical basis and technical support for other similar crops to be crushed and collected.