Traditional plant disease diagnosis methods are mostly based on expert diagnosis, which easily leads to the backwardness of crop disease control and field management. In this paper, to improve the speed and accuracy of disease classification, a plant disease detection and classification method based on the optimized lightweight YOLOv5 model is proposed. We propose an IASM mechanism to improve the accuracy and efficiency of the model, to achieve model weight reduction through Ghostnet and WBF structure, and to combine BiFPN and fast normalization fusion for weighted feature fusion to speed up the learning efficiency of each feature layer. To verify the effect of the optimized model, we conducted a performance comparison test and ablation test between the optimized model and other mainstream models. The results show that the operation time and accuracy of the optimized model are 11.8% and 3.98% higher than the original model, respectively, while F1 score reaches 92.65%, which highlight statistical metrics better than the current mainstream models. Moreover, the classification accuracy rate on the self-made dataset reaches 92.57%, indicating the effectiveness of the plant disease classification model proposed in this paper, and the transfer learning ability of the model can be used to expand the application scope in the future.

Soil blocking and plant entanglement are the main challenges in Cyperus esculentus harvesting and excavating. The structure of the rotary blade is one of the critical factors affecting plant crushing and soil throwing performance. Inspired by the composite motion of longitudinal soil cutting and lateral soil throwing of the oriental mole cricket, a bionic rotary blade was designed with the contour curve of the excavation edge and excavation surface of its forefoot claw toe. The bionic rotary blade’s mechanical and kinematic analysis revealed its cutting mechanism. A flexible plant soil, bionic, rotary blade discrete element model was developed to simulate the Cyperus esculentus digging process. The optimal excavation edge and excavation surface were selected by a single factor experiment, and the optimal operating parameters of the bionic rotary blade were obtained by quadratic regression orthogonal rotational combination design. The results showed that the bionic rotary blade, based on the excavation edge and excavation surface of mole cricket first claw toe, had the longest throwing distance and the largest number of broken bonds. The best combination of operating parameters of the bionic rotary blade was 11.16 mm for blade spacing, 0.66 m/s for forward speed, and 300 rpm for shaft speed. The field experiment was carried out according to the best parameters. The results showed that the bionic rotary blade’s average soil throwing distance and plant crushing rate were 632.30 mm and 81.55%, respectively; thereby, not only meeting the requirements of Cyperus esculentus harvesting, but proving superior to the operation performance of the Chinese standard rotary blade IT245 and rotary blade with optimized cutting edge (IT245P). The results of this study can provide bionic design ideas and methods for the design of soil-cutting-based tillage machinery’s soil-engaging components, such as the rotary blade and returning blade.

Peanuts are prone to insect damage, breakage, germination, mildew, and other defects, which makes the quality of peanuts uneven. The difference in peanut pod quality makes the price and economic benefit also have a big difference. The classification of peanut pods according to quality is an important part of improving the product grade and market competitiveness. Real-time, accurate, and non-destructive quality detection of peanut pods can effectively improve the utilization and commercial value of peanuts. The strong subjectivity of manual detection and the low efficiency and low accuracy of mechanical detection have caused considerable wastage. Therefore, the present study proposed a new convolutional neural network for the peanut pod quality detection algorithm (PQDA) based on an improved ResNet. Compared to previous models, this model is more practical with high accuracy, lightweight, and easy nesting. Firstly, the detection and classification effects of ResNet18, AlexNet, and VGG16 are compared, and ResNet18 was determined to be the best backbone feature extraction network for model training. Secondly, three models were designed to optimize and improve the algorithm. The KRSNet module was added to the algorithm to make the model lightweight. The CSPNet module was added to the algorithm to improve the learning efficiency of each feature layer. The Convolutional Block Attention Module (CBAM) was added to the algorithm to improve its ability to capture more feature information about peanut pods. The experimental ablation results show that the precision of the improved model PQDA reaches 98.1%, and the size of parameters is only 32.63 M. Finally, the optimized model was applied to other peanut pod varieties for generalization experiments, and the accuracy reached 89.6% and 90.0%, indicating the effectiveness of the proposed peanut pod quality detection model. Furthermore, the model is suitable for deployment on embedded resource-limited devices, such as mobile terminals, to achieve the real-time and accurate detection of peanut pod quality.

Severe plant entanglement and high power consumption are the main problems of the up-cut rotary blade during Cyperus esculentus harvesting. Optimization of the rotary blade edge can enhance the soil-cutting and plant-crushing performance. In this study, the double-eccentric circle method was used to design the edge curve of the IT245 rotary blade. The edge curve’s dynamic sliding-cutting angle of equidistant points was analyzed to verify that the optimized rotary blade (IT245P) met the requirements of Cyperus esculentus harvesting. In order to accurately simulate the fragmentation of Cyperus esculentus plants after interaction with the rotary blade, the Hertz–Mindlin with Bonding contact model was selected to establish the flexible model of Cyperus esculentus plants. The plant–soil–rotary blade discrete element model was constructed to conduct simulation tests with power consumption and the plant-crushing ratio as evaluation indexes. The field experiment was carried out with tillage depth stability and power consumption as the experimental indexes. The results of the simulation test and field experiment showed that the power consumption of the IT245P rotary blade was reduced by 13.10%, and the plant-crushing rate was increased by 11.75% compared with the IT245 rotary blade. The optimal operating parameters were 1.08 m/s for forward speed, 107.11 mm for tillage depth, and 258.05 r/min for shaft speed. Under such a combination, the tillage depth stability and the power consumption were 94.63% and 42.35 kW. This study showed that a rotary blade with a double-eccentric circular curve could better realize plant-crushing and consumption reduction and meet the operation requirements of Cyperus esculentus and other Chinese medicinal materials’ harvesting.

Considering the problems of low soil fragmentation rates, high working resistance, and high energy consumption in the harvesting process of Cyperus esculentus in China, a method of Cyperus esculentus harvesting based on counter-rotation digging is proposed. The mechanism of interaction between the rotary tillage blade and Cyperus esculentus–soil is systematically investigated, and the vertical and horizontal disturbance performance of the positive and counter-rotating harvesting methods on soil and Cyperus esculentus is compared and analyzed. The results of the experiment showed that the intensity of soil and Cyperus esculentus disturbance by counter-rotation increased by 166.67% and 297.78%, respectively, and the effective disturbance time of soil and Cyperus esculentus increased by 133.33% compared to that of positive rotation. The working depth and rotation speed of the rotary tillage blade were the most significant for soil and Cyperus esculentus disturbance intensity. The working depth increased from 150 mm to 170 mm, and the soil disturbance intensity increased by 17.91% and 21.37% for positive and counter-rotating operation, respectively, and the rotation speed of the rotary tillage blade increased from 270 rpm to 330 rpm, and the soil disturbance intensity increased by 28.85% and 35.29%, respectively. Compared with the positive rotation operation, the Cyperus esculentus counter-rotation soil fragmentation rate increased by 4.09%, the Cyperus esculentus damage rate decreased by 10.69%, and the buried fruit rate decreased by 7.38%. This paper helps to understand the interaction mechanism between the rototiller and Cyperus esculentus–soil and lays a theoretical foundation for the subsequent design and optimization of the Cyperus esculentus digging device.

The layered soil crushing rotary tillage machine with L-shaped reclamation rotary blades and rotary-reclamation rotary blades combination was designed to deal with the problems of a low soil fragmentation rate, low straw mulching rate, and poor surface leveling after plowing in the traditional rotary tiller tillage mode in the coastal saline land of the Yellow River Delta. A dual active layered soil fragmentation tillage mode was proposed, and the key structural parameters, blade axis arrangement, and spatial layout of L-shaped reclamation rotary blades and rotary-reclamation rotary blades were determined based on the sliding cutting principle analysis. A discrete element model of soil straw tillage component aggregates suitable for coastal saline alkali land was constructed using EDEM, and the influence of L-shaped reclamation rotary blades and rotary-reclamation rotary blades on the soil tillage layer displacement performance and straw burial performance of saline alkali land was comprehensively analyzed from a microscopic perspective. Taking the rotation speed of the L-shaped reclamation rotary blades, the rotation speed of the rotary-reclamation rotary blades, and the forward speed as experimental factors, and using soil fragmentation rate and straw burial rate as evaluation indicators for experimental optimization analysis, the optimal parameters were obtained: the rotation speed of the L-shaped reclamation rotary blades was 295.04 r/min, the rotation speed of the rotary-reclamation rotary blades was 359.06 r/min, and the forward speed was 3.12 km/h. At this time, the theoretical soil fragmentation rate of saline alkali land was 94.67%, and the straw burial rate was 93.56%. Field experiments have shown that the average soil fragmentation rate of the L-shaped reclamation rotary blades and rotary-reclamation rotary blades combined layered soil crushing rotary tiller after cultivation is 94.37%, the straw burial rate is 95.68%, the surface flatness is 25.82 mm, and the stability of the tillage depth is 95.64%. The machine has shown increased performance in comparison to traditional single axis rotary tillers, meeting the needs of crop bed preparation in saline alkali land.