In order to improve the pineapple mechanized planting ability, based on the analysis of the existing fruit and vegetable transplanting technology and pineapple planting technology, a 2ZBL-90 double row pineapple planter was designed and trial produced, which can complete the fertilization, rotary tillage, ridging, film mulching, transplanting, and other operation procedures for pineapple seedlings at one time. The morphological parameters of pineapple seedlings were measured and statistically analyzed, the key components of fertilization and rotary tillages and transplant parts were optimized. The results showed that the length of pineapple seedling was 15-30 cm, the width was 10-15 cm, the conic angle of seedling type was 21°-30°, the diameter of spiral blade was 100 mm, the pitch was 60 mm, and the rotation speed was controlled at 15 r/min. The planting spacing and depth of the 2ZBL-90 pineapple seedling transplanter met the planting requirements. The qualified rate was more than 95%, and the seedlings were in a good upright state, which could meet the planting requirements.

 The autonomous navigation technology of agricultural machinery has always been the key technology in the development of modern agriculture. The existing machine vision navigation had some shortcomings, such as poor robustness and weak adaptability. To solve these problems, a field path navigation algorithm based on the convolutional neural network was proposed. In this study, an improved segmentation network FCNVGG14 was obtained based on the mainstream semantic segmentation model FCNVGG16, which was used for the pretreatment of crop row segmentation tasks in the field. Then, feature points were classified by the unsupervised point clustering method. Finally, navigation lines were fitted by the improved Hough Transform (PKPHT). The analysis results show that, compared with the mainstream algorithms such as U-Net, the IOU index of the image segmentation algorithm based on the FCNVGG14 network model was improved by 2% in the multichannel input and 4% in the singlechannel input, achieving good segmentation effects. Compared with the traditional image threshold segmentation algorithm, it overcame the inevitable problems of false detection and large deviation in the line fitting caused by the defects of crop loss, excessive weeds in the field, and uneven illumination. 
The field path navigation experiment proves that the detection accuracy of the improved model path recognition algorithm based on FCNVGG16was no less than 92%, the detection time of single frame was less than 100 ms, and the speed of the operating platform was no more than 0.5 m/s under the condition that the field illumination was consistent with human eyes. The maximum lateral deviation was 9.84 cm and the average deviation was less than 6.68 cm, indicating that it was feasible for machine vision navigation. This provides a new method and idea for field visual navigation with low computational power.

Under the background of fully implementing the rural revitalization strategy and promoting the highquality development of animal husbandry, in order to accurately identify the shortcomings in the continuing education methods and methods of smart breeding technology for poultry breeding practitioners, timely improve the teaching mode in time to enhance the ability of poultry practitioners to apply smart breeding technology, a questionnaire survey was conducted on the front line breeding and production management practitioners in the poultry breeding industry, and the urgency of the teaching needs of smart breeding technology in the main production links, the teaching method, the teaching key content, and the production links were investigated and statistically analyzed. The results showed that the demand for intelligent poultry breeding technology was relatively high among practitioners; In the education and training mode, the classification report teaching and field teaching methods were accepted by more people, while the attention and interest in online teaching were relatively low; The focus of continuing education was mainly focused on the use of facilities and equipment in smart breeding, safety matters and practical practices, etc., and the attention of practitioners to the principles of smart breeding technology and the progress of new technologies was relatively low; In view of the production links involved in education and training, practitioners paid more attention to the intelligent control of poultry breeding environment and abnormal behavior monitoring. According to the deficiencies found in the survey results, the education and training mode of poultry intelligent breeding practitioners is further discussed from 5 aspects, and the improvement measures of the continuing education mode of practitioners are given.

In view of the limitations of existing macadamia nut peeling machines, such as the first classification and then peeling, as well as the disadvantages such as semiautomation, the requirement of nut diameter consistency, low efficiency, low qualified rate, and high peeling damage rate, a new type of peeling machine based on double helix adaptive extrusion of roller type was developed. 885 samples were used and the diameters in three directions of macadamia nuts with husk or peeled were measured. It was confirmed by statistical tests that the nut diameters of 3 directions obeyed normal distribution at 0.05 level and were correlated with each other significantly at 0.000 1 level. The average roundness of nuts with skin was 0.975 3-1.048 6. The appearance of macadamia nut was spheroid. Based on the measured nut diameters and their distribution, the designed peeling device consisted of a structure of double helix rollers extrusion. Roundness nut model force analysis of the compression device was used on the macadamia nuts and the parameter design constraint and force balance equation were obtained. The final design of the peeling device was determined. The parameters of the two rollers were as follows: 76 mm in diameter, 75 mm in screw pitch, 1 100 mm in effective length, 400 r/min in rotating speed, and 4-12 mm in the gap. In addition, the spring stiffness of the peeling device was 2.71 N/mm. The performance test showed that the qualified rate of peeling reached 97.73%, the rate of peeling damage was only 1.13%, and the average productivity was 495.54 kg/h, which was highly consistent with the design values. The effect of productivity on working quality was not significant at 0.05 level. All of the above results confirm that structure form selection and parameter design were reasonable and valid. While the diameter of macadamia nuts with skin was in the range of 24.21-38.97 mm, the developed peeling device was suitable for these macadamia nuts to perform peeling work with continuously automatic feedstock.

In order to meet the development needs of high-quality farmers' education and training in the new era, we should use information means to improve the participation of high-quality farmers in online training. In this paper, the training quality of high-quality farmers is analyzed in detail by the analytic hierarchy process. Aiming at the current needs of high-quality farmers, the training quality evaluation algorithm is proposed, and the training quality comprehensive model is constructed. An experiment is conducted to verify the effectiveness of the proposed method. Finally, this paper focuses on applying the Collaborative Filtering Recommendation Algorithm based on student course scores to the training course recommendation module and gives the implementation method of key parts of the course recommendation system.