The effective quantification of deposition rate is of vital importance in optimizing the application performance and the utilization of pesticides; meanwhile, the canopies of fruit tree orchards are large, with dense branches and leaves shading each other, making it difficult to quantify spraying efficiency. Therefore, it is imperative to develop a facile methodology for assessing the performance of different spraying techniques in terms of distribution and utilization rate in orchards. To evaluate spraying efficacy in orchards, a canopy segmentation method was developed in to be able to determine the spray deposition rate. The distribution and deposition rate of spray liquid applied using three kinds of orchard sprayer were measured in a pear orchard and a peach orchard. The test results showed that the trailer sprayer had the highest deposition rates, with values of 31.54% and 56.92% on peach and pear trees, respectively. The deposition rates of the mounted sprayer in the peach and pear canopies were 21.75% and 40.61%, and the rates of the hand-held sprayer were 25.19% and 29.97%, respectively. The spray gun had the best droplet distribution uniformity, with CVs of the spray in the peach and pear canopies of 20.54% and 25.06%, respectively. The CVs in the peach and pear canopies were 35.98% and 26.54% for the trailer sprayer, and the CVs of the mounted sprayer were 92.52% and 94.90%, respectively. The canopy segmentation method could effectively be used to calculate the deposition rate and drioplet distribution in orchard application, while a great deal of time was consumed by counting the number of leaves in the different areas of the fruit tree canopies. Therefore, research on the density of branches and leaves in fruit tree canopies should be carried out in order to improve the efficiency of fruit tree canopy information extraction.

To reduce the cutting force and cutting power consumption during harvest, the cutting mechanical properties of the root of little cabbage were studied. The cutting experiment was carried out using a texture analyzer, and the influence of the individual factors, the cutting bevel angle, the sliding angle, and the cutting gap on the maximum cutting stress and specific cutting energy were studied, respectively. On the basis of single factor experiments, multi-factor experiments were carried out using the central composite design scheme of the response surface method (RSM), and finally, the cutting parameters were optimized. The single factor test results showed that the maximum cutting stress and specific cutting energy first decreased and then increased with the increase in the cutting bevel angle, decreased with the increase in the sliding angle, and first dropped and then went up with the increase in the cutting gap. Response surface test results showed that the order of significance of factors affecting the maximum cutting stress of the root were the oblique angle, sliding angle, and cutting gap in sequence, and the order of the significance of factors affecting the specific cutting energy are cutting gap, oblique angle, and sliding angle. The interaction between the sliding angle and the cutting gap had a significant impact on the maximum cutting stress, and the interaction between the oblique angle and the cutting gap had a significant impact on the cutting energy. The optimal parameter combination is as follows: oblique angle of 9.1°, sliding angle of 30°, and cutting gap of 1.3 mm. At this time, the predicted maximum cutting stress was 7.43 × 104 Pa, and the specific cutting energy was 0.28 mJ mm⁻². Finally, a verification experiment was carried out, and the errors of the predicted and measured values of cutting under the optimal parameter combination were 6.9% and 10.8%, respectively, showing that the cutting parameter optimization results were reliable. This research can provide data support for the design and improvement in the cutting device of the little cabbage combine harvester.

To reduce pesticide pollution and promote sustainable agricultural development in China, we designed a pilot-scale biofilter system to treat residual imidacloprid wastewater in an orchard. The biofilter system demonstrated a high rate of removal of imidacloprid from the biodegradation wastewater, with removal rates from the outlet exceeding 99% at different concentrations of pesticides. Among environmental factors, imidacloprid concentration at the inlet and biomixture significantly affected the activity of imidacloprid-degrading bacteria. The dominant microbial communities during the stable operation of the biofilter system included Firmicutes, Actinobacteria, Proteobacteria, and Bacteroidetes at the phylum level and Bacillus, Methylobacter, and unclassified_f__Microbacteriaceae at the genus level. In future initiatives to improve biofilter performance and applicability, increasing attention should be paid to the dominant microbial communities, the number of biofilter units, and important environmental factors. Orchard workers in China should improve the existing treatment of residual pesticide wastewater to mitigate agricultural non-point source pollution.

The intelligent diagnosis key technology of orchard nutrients provides a decision-making basis for precision fertilization, which has important research significance. This article reviewed the recent research literature, compared and analyzed existing technologies, and summarized solved and unresolved problems. It aimed to find breakthroughs to further improve the level of intelligent diagnosis key technology for orchard nutrients, and promote the implementation and application of the technology. Research had found that the current rapid nutrient detection technologies were mostly based on spectral data, with a focus on preprocessing algorithms and regression models. Hyperspectral technology shows good performance in predicting tree and soil nutrients due to its large number of characteristic variables. Meanwhile, preprocessing algorithms such as filtering, transformation, and feature band selection had also solved the problem of data redundancy. However, there were few studies for small and trace elements, and field applications. Laser breakdown-induced spectroscopy has good prospects for soil nutrient detection, as it can simultaneously detect multiple nutrients. There had been some studies on the technology for generating suitable nutrient standards for orchards in terms of soil and tree nutrients, but it requires a long and extensive experiment, which is time-consuming and laborious. A universal and rapid method needs to be studied to meet the construction needs of suitable nutrient standards for different varieties of fruit trees.