Sugarbeet is one of the major sugar crops in the world. China, as a sugarbeet producer leading the world in planting area and output, promoting the development of domestic sugarbeet production industry, which is significant to main tainand promote the prosperity of world’s sugar market. This article takes the agronomic technology of sugarbeet cultivation, planting, field management, harvesting and other production links as the starting point, focusing on the analysis and summary of the mechanical structure, working principle and existing problems of the frontier production equipment of sugarbeet at home and abroad. It is recommended that the cultivation method be universalized. Diversified sowing methods, refined field management, and combined harvesting methods are the main research directions for sugarbeet production machinery in the future, and expecting on the basis of deepening the understanding of mechanization of sugarbeet production, to provide support and assistance for promoting the domestic sugarbeet production mechanization process.

In order to improve the monitoring level of facility agricultural environment, a remote wireless monitoring system for agricultural greenhouse environment based on ESP32 module was designed. The system comprised of environmental information acquisition module, ESP32 control module, output module, and smartphone control terminal.The monitoring terminal APP was designed with blinker Internet of Things solution based on Android platform. Greenhouse environment temperature, humidity, light intensity, PM2.5 concentration, CO2 concentration, access control and other environmental information was collected through sensors and sent to the remote monitoring mobile phone via WiFi network.The environmental information of the greenhouse was viewed and the relevant greenhouse equipment was controlled remotely using a mobile APP. The system physical prototype was manufactured and an experiment was carried out. The results showed that the lowest success rate of data transmission of the terminal was 97.3% and the average networks packet loss rate was 2.17%. The system has many advantages such as stable operation low cost,good real⁃time, high communication security,high reliability and easy operation.

Fruit and vegetable picking is an important part of agricultural production, and it relies heavily on manual labor. The development and application of picking robots will greatly reduce labor dependence of picking operations. The picking robotic arm is a key part of the picking robot and a major focus of research on the picking robot. This paper classified the picking manipulators by the degree of freedom, and summarized the development process and research status of the picking manipulators in China and the rest of the world. Aiming at the problem of lack of standardized solutions in thechoice of freedom and configuration of the picking robotic arm for the same fruit and vegetable in the same cultivation mode, it is proposed that indepth integration of the picking manipulator research and agronomy is the key to solving the problem in future. At the same time, considering that the rigid body is difficult to adapt to the picking environment as well as the joint drive mode being single, it is believed that the flexible design of the picking manipulator body and the combined use of the drive mode will be the future development trend.

“Double carbon” has become the key task of Chinas agricultural green development. It is urgent to reduce agricultural greenhouse gas emissions in order to achieve the carbon neutral goal of 2060. This paper reviews the research progress and development trend of agricultural carbon emission in China in recent years, summarizes the research on the six major emission sources of agricultural materials, rice planting, carbon fixation of cultivated land, straw burning, livestock and poultry breeding and agricultural machinery, and publishes the suggestions and prospects for carbon emission reduction of the six major agricultural emission sources. The research shows that there are many empirical analysis on the agricultural carbon emission intensity of the five major agricultural emission sources of agricultural materials, rice planting, straw burning, livestock and poultry breeding and agricultural machinery, and the carbon emission reduction effect is significant, because of the effective regulation of its carbon emissions and the impact of strengthening the purchase subsidy policy. However, there is less empirical analysis on the carbon sequestration of arable land, and the process of carbon emission reduction is slow, mainly due to the greater impact of the subjective factors of farmers, so we should strengthen the publicity and learning of farmers. Although Chinas total agricultural carbon emissions fluctuate up and down, they tend to decline as a whole. In order to achieve green and sustainable development, the government and the whole people need to work together. The implementation of lowcarbon agriculture is conducive to achieving the 2060 carbon neutral goal.

Germplasm is the foundation of agriculture and a national strategic resource. The quality of seeds affects the production scale and potential of the overall planting industry. There are some problems in Chinast seed industry, such as incomplete and opaque industrial chain information and imperfect and unsafe seed traceability systems. This paper integrates blockchain technology into traditional seed information traceability and proposes a seed quality traceability model for distributed data storage. This paper uses Ethereum, Internet of Things, and terminal applications to design a threelayer architecture: application layer, Internet of things layer, and data storage layer. According to the characteristics of Ethereum and the requirements of system data storage and query, a distributed multidatabase storage mode is designed. The system stores the data information of each link from seed production to the circulation department. Combined with the characteristics of blockchain data information that cannot be tampered with, high transparency and traceability, it ensures that all data in the seed supply chain will not be changed or hidden by others to realize accurate traceability and rapid identification of seed quality. The system uses the smart contract algorithm to directly hit the source of the seed data to ensure the quality and safety of the purchased seeds and to provide information technology and service guarantees for safeguarding the rights and interests of seed consumers.

The chassis technology of agricultural machinery is the key technology of intelligent agricultural machinery and equipment， and also the key technology that affects agricultural and rural modernization. The inherent advantages of European and American farm based and intensive planting scenarios， as well as strong industrial foundations， make Europe and America ahead of China in the field of intelligent agricultural machinery， the adaptability of agricultural machinery chassis in our country is poor， the degree of intelligence is insufficient， the comfort is poor， and the safety factor is low. In response to the above issues， combined with the actual situation and characteristics of China's agricultural machinery development， this paper will think and look forward to the direction of intelligent development of agricultural machinery chassis in the future from three aspects of intelligent drive， high adaptability walking and independent operation. This paper focuses on summarizing the progress of new technologies such as hydraulic lifting， power shifting， continuously variable transmission， variable wheelbase， wire controlled steering， and unmanned driving applied to agricultural machinery chassis. Combining with the actual application situation in China， the basic principles and characteristics of various systems related to agricultural machinery chassis are elaborated. Finally， based on the research progress of agricultural machinery chassis at home and abroad and the gap between domestic and foreign countries， reference is provided for future research and design of intelligent agricultural machinery chassis and modernization of agriculture and rural areas from strengthening the research and upgrading of electro‑hydraulic technology and E-CVT， promoting the landing of multi‑directional walking and wire controlled steering technology， and realizing intelligent control and unmanned operation.

The problems such as grain yield reduction and fruit quality reduction caused by bird damage seriously restrict the development of agriculture and forestry economy, so the bird damage control has important research significance and application value in the process of agriculture and forestry management.This paper briefly summarized the classification and characteristics of bird damage control technology, focuses on the development history and current situation of laser bird repelling technology, sonic bird repelling technology, and integrated control technology with bird monitoring, and analyzes the development trend of agricultural and forestry bird repelling equipment from electronic to intelligent. In view of the existing problems of bird damage control equipment, such as easy adaptation by birds, poor coordination and poor versatility, it is proposed to establish a bird biological information database to provide a basis for the development of bird repellent equipment to weaken the adaptability of birds. Smart agriculture and forestry should be developed to promote the informatization and collaborative of bird repelling equipment. In the future, it is necessary to strengthen the cultivation of crops which are resistant to bird and develop advanced bird monitoring algorithms to improve the recognition rate to avoid bird damage in advance, so that bird damage control is the main, prevention is supplemented, governance first, prevention as a supplement.

Tea stripping technology is a key technology in the processing of flat tea and needle tea, which has an important influence on the appearance and quality of tea. To this end, this paper summarizes the research progress of tea stripping technology and machine in our country, focusing on the impact on tea stripping from four aspects: the transmission structure of the stripping machine, the Ushaped grooves structure design, the heating method, and the control mode, and points out the problems of the tea stripping machine in terms of institutional innovation, heat energy utilization, processing standards, etc. And it should increase the research and development of the stripping machine, selecting new heating materials and strengthening the construction of tea processing information and other related development trends, as a new type of tea stripping machine provide reference for innovative design and innovation of the structure.

In order to grasp the research status and industry trend of CVT and electric transmission technology in agricultural machinery,  the development history,  application status,  development bottleneck,  and development trend of CVT technology in agricultural machinery were analyzed and summarized. Firstly,  the development history of CVT and electric drive in agricultural machinery was reviewed,  and the principle of CVT and electric drive system in typical agricultural machinery was introduced. Secondly,  the application status of CVT and electric transmission in agricultural machinery was summarized,  and some typical agricultural machinery was listed. Finally,  in view of the problems existing in the collaborative development of power and transmission,  the research and development of lowpower continuously variable transmission systems,  the balance between technology and cost,  and suggestions for the followup research of CVT and electric drive are put forward. The development trend is discussed. The results show that electric transmission is not enough to replace CVT in the field of agricultural machinery in the foreseeable future. The application of electric drive in agricultural machinery mainly depends on the continuous change of battery and motor technology. The energy acquisition methods of the electric drive will be diversified,  such as solar energy,  wind energy,  and regenerative energy,  which may provide power for agricultural machinery. CVT and electric transmission technology may be widely used in unmanned agricultural machinery.

Greenhouse is playing an increasingly important role in agricultural production by creating suitable planting conditions to effectively improve the utilization rate of agricultural resources.  Greenhouse climate change is a highly coupled nonlinear process with multiple factors, which is easily affected by external climate environment interference, thereby affecting the stability of the entire control system. How to stably, efficiently and intelligently control the climate variables inside the greenhouse is a practical problem that urgently needs to be solved. This article summarizes the current research status of greenhouse environmental control methods at home and abroad, starting from four aspects such as fuzzy control, decoupling control, energysaving control and neural network, it elaborates on the current application status and advantages and disadvantages of mainstream greenhouse intelligent control methods, and points out the problems of single environmental control factors, low energy utilization efficiency, and poor dynamic adjustment ability of control models. This paper puts forward some suggestions for future greenhouse environmental control, including system multivariable control, sustainability and energysaving of control, optimization of control models, and integration of agronomy and environmental control,  so as to provide reference and guidance for the healthy development and refined management of greenhouse agriculture.

The low post‑production processing capacity of fruits and vegetables leads to the lack of core competitiveness of fruits and vegetables in the international market. The most important step of post‑processing is fruit and vegetable sorting, and the fruit and vegetable sorting equipment can effectively improve the sorting efficiency and liberate the labor force. This paper expounds the current situation of fruit and vegetable sorting equipment at home and abroad from the market and scientific research, and also analyzes the problems existing in the current fruit and vegetable sorting equipment, discusses the research trend of fruit and vegetable sorting in the future, and points out that the external quality sorting technology of fruit and vegetable combined with artificial intelligence and machine vision and the internal quality sorting technology of near‑infrared spectrum analysis will be the recent research focus. At the same time, a mechanical arm grabbing sorting equipment scheme is proposed for the post‑harvest sorting scene of vulnerable fruits and vegetables, which provides a reference for solving the sorting problem of delicate, vulnerable and high‑quality fruits and vegetables in the later stage.

Yam planting in China has a long history and a wide range. Due to its own growth characteristics, geographical environment and planting mode, the mechanization degree of yam harvesting is relatively low, and manual harvesting is mostly used. With the development of industrial structure, the development degree of yam harvesting mechanization directly affects the economic benefits of farmers. This paper analyzes the planting characteristics of several yams in China, summarizes the main harvesting methods of several yams in China, expounds the research status and progress of main harvesting equipment and technology of yams such as walking system, transmission system, trenching system, soil turning vibration mechanism and positioning system, and briefly discusses the research on yam harvester in foreign countries. On this basis, it is pointed out that the mechanization of yam harvesting in China faces problems such as insufficient integration of agricultural machinery and planting environment, inconsistent planting mode, poor quality of harvesting machines and tools, lack of innovation and imperfect harvesting function, and relevant suggestions are put forward for the problems faced by the mechanized harvesting equipment of Yam as follows: developing the mechanized harvesting equipment of yam according to local conditions. Promoting the construction of planting regulations, learning from the development experience of developed countries, improving the innovation ability of core components, and developing combine harvesters.

Precision sowing can effectively reduce the number of seeds used, save costs and money, and the quality of crops grown through precision sowing is high. In order to grasp the development level of electronically controlled precision sowing technology at home and abroad, this paper carries out research from precision sowing online detection technology, sowing volume control technology and seed replenishment technology, focusing on the advantages and disadvantages of photoelectric sensor detection, piezoelectric sensor detection, capacitive sensor detection, visual image detection and precision sowing control technology; and points out the lack of standardization of precision sowing machines in China, insufficient research and development of high precision sensors, and immature intelligent control technology. Finally, combined with the current development situation at home and abroad, the development trend of Chinas precision sowing technology in the direction of multimachine collaboration, remote control and intelligent control is to provide some reference for future researchers to understand electronically controlled precision sowing technology in China.

In order to classify and locate different walnut varieties,  a walnut detection method based on deep learning was proposed. First of all,  this paper took the three kinds of walnut mainly produced in the southern Xinjiang region as the object for image acquisition and made the walnut data set by flipping,  clipping,  denoising,  lighting transformation,  and other operations of the image. Then,  the YOLOv5based detection model was used for experiments and compared with the detection results of YOLOv3,  YOLOv4,  and Faster RCNN algorithms. The results showed that the mean average accuracy (mAP) of the YOLOv5 model for walnut detection of Xin2,  Xinguang,  and Wen185 was 99.5%,  98.4%,  and 97.1%,  respectively,  and the detection time of a single image was 7 ms. Under the same data set and the same experimental environment,  the detection speed of the model is 7 times that of Faster RCNN,  the detection accuracy of the model is 2.8% higher than that of Yolov4,  and the model size is only 1/14 of that of YOLOv4. The test results showed that the model based on YOLOv5 of walnut detection was the highest in terms of detection accuracy and speed among all the comparison algorithms,  which was suitable for the detection requirements of this research,  which could provide a research basis for robot automatic walnut sorting.

With the continuous development of facilities vegetable industry and the increasing demand for facilities vegetable, the realization of mechanization and intelligent operation production has become the necessary link in the modernization process of facilities vegetable industry. Although facilities vegetable area, output and production value are expanding, there is still a big gap with facilities agriculture developed countries such as Europe and the United States. In order to improve the level of industrial mechanization of facilities in China and develop reliable mechanical equipment, this paper summarizes the research status and development trends of modern facilities of vegetable operating machinery in America, Japan, Holland and other countries, and summarizes the types, advantages and disadvantages of facilities of vegetable operating machinery. It is pointed out that some problems exist in the process of vegetable production, such as mechanization, low degree of automation, poor adaptability of machines and machines, and relatively backward application of agricultural robots. Combining with the situation of Chinese facilities, this paper puts forward some countermeasures to strengthen research and development of intellectualized facilities, informationized facilities agricultural equipment, and promote the application of new materials and new agricultural robot technology, which will point out the direction and provide reference for the development of Chinese facilities vegetable mechanization.

The behavior of sheep can reflect its health status and physiological stages. Automatic tracking of the objects for sheep in the farm environment is a prerequisite for statistics and analysis of its behavior. In this paper, captive sheep were used as the experimental subjects, and then a multiple object tracking method for sheep based on StrongSORT algorithm was proposed. It used YOLOv5-CBAM as the front⁃end detector, then combined the currently advanced StrongSORT tracker. The experimental results showed that, in the short video tracking, the multiple object tracking accuracy, multiple object tracking precision, the total number of identity switches and IDF1 of 10 sheep reached 91.6%, 0.269, 52 and 70.7%, respectively. Compared with the YOLOv5+StrongSORT algorithm, the multi‑object tracking accuracy of the YOLOv5-CBAM+StrongSORT algorithm proposed in this paper was improved by 0.4%, the multi‑object precision tracking was basically unchanged, the number of identity switching times was reduced by 17.5%, and the IDF1 value was increased by 3.2%. In the long video tracking, the above evaluation indicators were 57.3%, 0.244, 21 and 47.9%, respectively, and the advantages of YOLOv5-CBAM+StrongSORT were mainly reflected in the number of identity switches, which were reduced by 13, 10 and 12 times compared with YOLOv5+ByteTrack, YOLOv5+DeepSORT, and YOLOv5+OCSORT, respectively.

 Accurate crop classification and recognition based on machine vision is the premise of agricultural automation and intelligent operation. Convolution neural network (CNN) is one of the most widely used algorithms in crop image classification and recognition. The complexity of crop phenotypic characteristics and growth environment determines the diversity of crop image acquisition platforms. Through the analysis of crop classification and recognition research based on CNN at home and abroad from 2020 to 2022, the image acquisition platforms can be divided into two categories such as general platform and self‑built platform, among which the general platform hardware products are mature and easy to deploy, but equipment selection and environment construction should be done well. The self‑built platform is divided into fixed and mobile ones, which can obtain experimental data efficiently, but the hardware integration is more complicated. The advantages and disadvantages of various platforms and their applicable scope are compared and analyzed in detail. The future trends of crop image acquisition platforms will include high‑throughput, high‑efficiency, automated universal image acquisition devices, multi‑modal data acquisition and fusion applications integrating a variety of sensors, intelligent cameras with built‑in computing processing, etc. The more refined image acquisition platforms will effectively support in‑depth research on crop phenotypes.

To address the problems of low efficiency, high cost, and low accuracy in manual detection of citrus diseases, this article combines artificial intelligence technology to classify and identify diseased citrus leaves. Firstly, a dataset of citrus disease leaves under simulated complex environments is established. Secondly, an improved Swin Transformer model for citrus disease leaf classification is proposed, which includes a Local Perception Channel Enhanced Attention Module (LPCE) to enhance the models receptive field and feature representation capabilities. Through weighted correlation between channels, the model is made to extract key features more easily. Experiments demonstrate that the classification accuracy of the proposed model reaches 98.52%, with Precision, Recall, and F1score reaching 98.17%, 98.24%, and 98.28% respectively, all exceeding the baseline model. It providing technical support for the detection of citrus diseases.