In this study, a three-year experiment on the fragrant pear orchard was conducted to investigate the effects of different varieties of green manure on the Korla fragrant pear fruit quality, with a view to finding a suitable green manure planting mode for Korla fragrant pear orchard. Green manures were planted in spaces among rows of pear trees, and then smashed and pressed into the soil as fertilisers by the agricultural machinery equipment in their full bloom period. In the experiment, four planting modes of green manure had been set for comparison: SA: Leguminosae green manures alfalfa (Medicago sativa L.), SP: Poaceae green manures oats (Avena sativa L.), ST: Cruciferae green manures oilseed rape (Brassica napus L.), and S: orchard authigenic green manures (Chenopodium album L., Mulgedium tataricum (L) DC., and Phragmites australis (Cav.) Trin. ex Steud.). Apart from that, eleven fruit quality indicators were analyzed to evaluating the effects of different green manure planting mode on the quality of fragrant pear. According to analysis of variance (ANOVA) results, there were significant differences among four planting modes in terms of nine fruit quality indicators (PSP>ST>S.

A chlorophyll content prediction model for predicting chlorophyll content in the pericarp of Korla fragrant pears was constructed based on harvest maturity and storage time. This model predicts chlorophyll content in the pericarp of fragrant pears after storage by using the error backpropagation neural network (BPNN), generalized regression neural network (GRNN) and adaptive neural fuzzy inference system (ANFIS). The results demonstrate that chlorophyll content in the pericarp of fragrant pears decreased gradually as the harvest time lengthened. The chlorophyll content in the pericarp of fragrant pears with different maturity levels at harvest decreased continuously with the increase in storage time. According to a comparison of the prediction performances of the BPNN and ANFIS models, it was discovered that the trained GRNN and ANFIS models could predict chlorophyll content in the pericarp of fragrant pears. The ANFIS model showed the best prediction performances when the input membership functions were gasuss2mf (RMSE = 0.006; R² = 0.993), dsigmf (RMSE = 0.007; R² = 0.992) and psigmf (RMSE = 0.007; R² = 0.992). The findings of this study can serve as references for determining the delivery quality and timing of Korla fragrant pears.

For the issues of the poor stability of the furrow opener depth, large soil backfill depth, and inconsistent furrow shape on a no-till seeder for planting green manure between rows of orchards in South Xinjiang, a double-disc, corrugated furrow opener is designed. This paper analyzes the law of soil movement between corrugated double-disc and traditional double-disc furrow openers using the discrete element method (DEM) and concludes that the corrugation width and number of corrugations on the corrugated double-disc furrow opener are the primary factors affecting furrowing operation. When the number of corrugations is sixteen, the forward speed is six kilometers per hour, and when the corrugation width is seventeen and a half millimeters, the simulation operation parameters are optimal. The soil-bin validation experiment results are as follows: Under the condition of an 80 mm furrow depth, the stability of the average furrow depth is enhanced by 3.54%, the working resistance and the average disrupted soil area are increased by 26.16 N and 220 mm², respectively, and the backfill depth is decreased by 10.98 mm. The operation effect of a double-disc furrow opener with corrugated discs is enhanced by the high stability of the furrow depth, low working resistance, and small backfill depth. This study provides a theoretical foundation for the design and optimization of the furrow opener components of a no-till seeder for planting green manure between rows of orchards.

Today, China’s orchard area covers 11,874,850 ha. With China’s progress in implementing the strategy of “quality-based and environmental-friendly agricultural development”, green manure has been developed as a modernized green soil management method for use in orchard areas. Green manure shows the highest decomposition rate with a ploughing depth of 150 mm. To efficiently utilize green manure in orchard areas, a “separated burying device” was designed, which can realize “stalk falling and soil falling” simultaneously. The device was composed of rotary blades, an iron chain separation curtain, soil retaining board and compacting machine. The cooperation parameters of different parts of the proposed device were designed through a discrete element simulation test, and a cooperative parameter model of the proposed device was constructed. According to the simulation test, the highest coverage of the prototype (95.16%) was achieved only when the knife roller center of rotary tillage moved to the point where it had a horizontal distance of 378.76 mm from the root of the “iron chain separation curtain”, the width of the transverse soil retaining board was 187.78 mm and the included angle of the soil retaining board θ was 116.48°. Based on a model verification test, the burying rate was found to be 94.36%, which differed slightly from the simulation test results. The burying rate increased by 4.84% upon the application of a “separated burying device”. The “separated burying device” was able to increase the burying rate of green manure between rows in the orchard area. It is conducive to the full utilization of green manure resources and lays good sowing foundations for green manure resowing. The construction of a “separated burying device” and its cooperative parameter model can provide insight into the research, development and optimization of relevant machines, such as the stalk returning machine.

In order to solve the problems of traditional orchard-specific green manure crushing and returning machines, such as the single operation effect, root system damage, unsustainable green manure growth, and low utilization rate, an offset crushing–furrowing–burying–straw-returning machine was designed for green manures in orchards. Based on quadratic regression combination experiments, the Discrete Element Method (EDEM) was used to construct a discrete element model simulating the deep furrowing and burying processes of the furrowing and soil-covering device, where the advance speed, plow-shaped furrowing blade rotation speed, and furrowing depth were considered as experimental factors and the coverage rate was taken as an evaluation index, and then simulation analyses were carried out to obtain experimental data; Design-Expert was used to perform ANOVA and RSM analyses, thus finding that its optimal working parameter portfolio consists of the advance speed of 42 m/min, the furrowing blade rotation speed of 300 r/min, and the furrowing depth of 190 mm, and that the coverage rate is 95.82% when this parameter portfolio is applied. Field experiments were conducted to validate the optimal parameter portfolio. The experimental results show that with an average coverage rate of 90.87% (4.95% away from the optimal value based on the simulation experiments on average), an average crushing length qualification rate of 91.24%, and an average root system damage rate of 5.6%, this device is applicable for its operation conditions. The development of this machine and the construction of its parameter model can provide a certain reference value for developing and optimizing related machines including green manure-returning machines.