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    This topic mainly displays the research and technology of the integration of Internet of Things technology and traditional agriculture published in Chinese Agricultural Science Bulletin and Journal of Agricultural Science, such as the use of sensors and software to control agricultural production through mobile platform or computer platform, and make traditional agriculture more "smart".

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    Monitoring of Powdery Mildew in Winter Wheat Based on HJ Satellite
    ZHUANG Dongying, YIN Ming, GENG Anhong, LI Weiguo, CUI Bibo
    Chinese Agricultural Science Bulletin    2023, 39 (28): 137-141.   DOI: 10.11924/j.issn.1000-6850.casb2022-0738
    Abstract + (80)    HTML (1)    PDF (1622KB) (20)      

    The disease index (DI) survey of powdery mildew for winter wheat at flowering stage was carried out in different regions. Canopy spectral measurement and field sampling were conducted simultaneously during this process. Three factors that played an important role in wheat growth were selected, namely leaf chlorophyll content, leaf water content and air temperature. These factors were statistically analyzed with DI to build a prediction model of wheat powdery mildew and obtained a thematic map. The results showed that there was a certain correlation between the three factors and DI. Leaf chlorophyll content and leaf water content were negatively correlated with DI with correlation coefficients of 0.6316 and 0.633 respectively, and leaf area index (LAI) and air temperature were positively correlated with DI with correlation coefficients of 0.6372 and 0.561 respectively. The change of wheat powdery mildew disease index can be obtained through changes of leaf chlorophyll content, leaf water content, air temperature and LAI (converted by NDVI), which proves that it is feasible to monitor the disease index based on remote sensing technology, and the constructed model can better retrieve the disease index of wheat powdery mildew. On this basis, this study drew the thematic map of wheat powdery mildew disease index monitored by remote sensing technology.
    Wheat Disease Recognition Model Integrating Attention Mechanism and Multi-scale Convolution
    LU Xiaowei, MENG Zhiqing
    Chinese Agricultural Science Bulletin    2023, 39 (25): 147-154.   DOI: 10.11924/j.issn.1000-6850.casb2023-0216
    Abstract + (86)    HTML (3)    PDF (2290KB) (38)      

    Classification and recognition techniques based on deep convolutional neural networks are proposed to solve the wheat disease identification problem. In this paper, the proposed method is compared and analyzed against existing wheat disease recognition models, and the promising results of applying deep learning technology in agricultural disease identification and monitoring are discussed. The experimental results show that the method based on the deep convolutional neural network is 3%, 4%, 5%, and 5% higher than the traditional EfficientNet network in terms of accuracy, precision, recall, and F1, and can effectively identify wheat disease. We verified the effectiveness of the proposed components by ablation experiments, and the convergence speed of the model was significantly better than the existing models. The proposed identification model provides strong support for agricultural production and is expected to become one of the main technical tools in the field of agricultural disease identification and monitoring in the future.
    Faster R-CNN Detection Method for Citrus Pests Based on Dilated Convolution and Feature Pyramid
    CEN Xiao
    Chinese Agricultural Science Bulletin    2023, 39 (22): 158-164.   DOI: 10.11924/j.issn.1000-6850.casb2023-0194
    Abstract + (88)    HTML (2)    PDF (1992KB) (18)      

    The four common pests in the citrus planting process were analyzed, and the detection problems of the pests with different sizes and low contrast features were improved on the basis of the Faster R-CNN model. Aiming at the problem that the down-sampling of the pooling layer leads to a decrease in the resolution of the detected image, which in turn leads to the loss of feature information in the image, the hole convolution method is used to capture more deep-level features in the image and increase the receptive field. Combined with the feature pyramid network FPN to fuse the features of different scales in the data, enhance the robustness of the features, and solve the problem that the original RPN network only uses a single final output layer for detection, and the detection accuracy is low. Compared with the original Faster R-CNN model, YOLOv4 and other classic target detection models, the mAP of the improved scheme is 91.72%, and the detection accuracy is improved. The experimental results prove that the proposed improvement scheme can meet the demand of identifying citrus pests in natural environments.
    Knowledge Graph Construction and Visualization in Soil Fertility and Scientific Crop Fertilizer Management
    ZHANG Caili, WU Saisai, LI Wei, WANG Hui, CHEN Lei
    Journal of Agriculture    2023, 13 (7): 80-86.   DOI: 10.11923/j.issn.2095-4050.cjas2022-0067
    Abstract + (150)    HTML (11)    PDF (1741KB) (122)      

    Aiming to improve the function of artificial intelligence in agriculture, and to search the knowledge organization and application in field of soil fertility, the soil fertility ontology of Anhui Province was built with manual construction method as well as the Protégé application software. Then the structured data, semi-structured data and unstructured data related to soil fertility in Anhui Province were first cleaned and then processed by inverse distance weighted (IDW) interpolation. Based on deep learning model of ERNIE-BiLSTM-CRF and PCNN-Attention, the tasks of named entity recognition and relationship extraction were realized, and all the triplet data were stored in Neo4j graph database. And the visual knowledge graph of soil fertility was successfully constructed. This study can provide reference for the construction of other agricultural knowledge graph in the aspects of ontology construction, entity relationship extraction model and graph visualization.
    The Application of Digital Agriculture Technology in Intelligent Management of Agro-Product Quality and Safety
    YANG Ling
    Journal of Agriculture    2023, 13 (6): 97-100.   DOI: 10.11923/j.issn.2095-4050.cjas2022-0152
    Abstract + (174)    HTML (14)    PDF (1025KB) (160)      

    Digital agriculture is the development trend of agricultural modernization. Based on the current situation of management of agro-product quality and safety, this paper expounds that digital agricultural technology can be applied in the quality control of the production process, improvement of supervision efficiency and market information services to promote management of agro-product quality and safety. The realistic challenges are analyzed in this paper, and some suggestions are put forward, including unified information management of agro-product producers, emphasizing key points, developing classified guidance of agro-product producers and strengthening technical support.
    Smart Crop Cultivation: A New Agricultural Science Toward Deep Integration of Information, Agronomy and Machinery
    GU Shenghao, WEN Weiliang, LU Xianju, Wang Chuanyu, GUO Xinyu
    Journal of Agriculture    2023, 13 (2): 67-76.   DOI: 10.11923/j.issn.2095-4050.cjas2021-0217
    Abstract + (286)    HTML (16)    PDF (1550KB) (184)      

    Human society has developed into a new era of intelligent connection of everything, agricultural science has entered a new stage of data-intensive knowledge discovery, and smart agriculture has become an important part to support the implementation of the Rural Revitalization Strategy. Under this background, the traditional theoretical and technical system of crop cultivation could no longer meet the needs of the development of smart crop cultivation, and it is urgent to accelerate the deep integration and collaborative innovation with other related disciplines to develop smart crop cultivation. This study first elaborates the connotation and characteristics of smart crop cultivation, then clarifies the concept, research content and key technologies and the corresponding disciplinary system, and finally proposes the development trend, challenges, and countermeasures of crop cultivation. To implement major scientific discoveries, frontier technology breakthroughs and industrial model innovations around the four key aspects of connection, perception, cognition and control in smart cultivation, to build a theoretical and technological system of smart cultivation, and to promote the transformation and upgrading of traditional cultivation to smart cultivation will help achieve sustainable development of crop production and accelerate agricultural modernization.
    Control System in Smart Facility Agriculture: Research Progress
    XU Peng, ZHANG Guanzhi, LI Yang, XU Xiaodong, YANG Zhenchao
    Chinese Agricultural Science Bulletin    2023, 39 (3): 156-154.   DOI: 10.11924/j.issn.1000-6850.casb2022-0136
    Abstract + (144)    HTML (8)    PDF (1260KB) (40)      

    With the evolution of science and technology, the development of agriculture is of more informatization and modernization, and smart agriculture is the inevitable trend of agricultural development in the future. Greenhouse control system is the core of smart facility agriculture and the key to realize large-scale development and intensive production of facility agriculture. This paper reviewed the research progress of greenhouse control system, aiming to provide reference for future study on smart facility agriculture. The greenhouse control system has become more and more mature since the 1970s. This study compared the control algorithm, master control chip and various sensors of greenhouse control system, reviewed research in recent years on the components of the control system which included perception layer, transmission layer and application layer, and introduced the mainstream sensors, network transmission technology and master control chip in the market, in order to provide a scheme for the design of greenhouse control system. This study also analyzed problems existing in greenhouse facility agriculture and discussed its future development direction.
    Monitoring Forest Insect Pests by Different Remote Sensing Sensors: Research Progress and Prospect
    MA Lei, HUANG Xiaojun, GANBAT Dashzebegd, MUNGUNKHUYAG Ariunaad, TSAGAANTSOOJ Nanzadd, ALTANCHIMEG Dorjsuren, BAO Gang, TONG Siqin, BAO Yuhai, ENKHNASAN Davaadorj
    Chinese Agricultural Science Bulletin    2022, 38 (26): 91-99.   DOI: 10.11924/j.issn.1000-6850.casb2021-0872
    Abstract + (340)    HTML (4)    PDF (1114KB) (57)      

    As an important part of the global ecosystem, forests account for about a quarter of the world’s land area. In recent years, pests have caused a large number of forest deaths, and the ecological security has been damaged. Thus, it is urgent to explore a simple and efficient forest pest monitoring method. Referring to the research of domestic and foreign scholars and relevant books, this paper analyzes and summarizes the advantages and disadvantages of multispectral, hyperspectral and microwave remote sensing sensors in forest pest monitoring. It is found that the spatial resolution of multispectral remote sensing is high, but the spectral resolution is poor, making it difficult to perceive subtle changes in the forest. Instead, the hyperspectral remote sensing has high spectral resolution, but its spatial resolution is low and the data is large and difficult to calculate. Lastly, the microwave remote sensing has strong penetration, it is able to monitor throughout the day, and is not susceptible to weather. However, its spatial resolution is low and it is difficult to obtain forest spectral information. In the future, the ability of pest differentiation, the ability of early monitoring, and the construction of forest pest remote sensing monitoring system based on multi-source data should be improved. This paper provides a new idea for remote sensing of forest pests.
    Climate-smart Grassland Management Technology Helps the Revitalization of Pastoral Areas
    ZHOU Chengyang, LIU Hao, HUANG Ding, WANG Jie, LI Tingyu, WANG Mingli, ZHANG Yingjun, LI Chengyu, ZHAI Xiyue, YANG Wuteng
    Chinese Agricultural Science Bulletin    2022, 38 (20): 156-164.   DOI: 10.11924/j.issn.1000-6850.casb2022-0006
    Abstract + (176)    HTML (3)    PDF (2277KB) (225)      

    Climate warming and human activities have brought unprecedented challenges to the alpine grassland ecosystem on the Qinghai-Tibet Plateau. In order to enhance the Qinghai-Tibet pastoral area’s ability to cope with climate change, rationally utilize alpine grassland resources, reduce greenhouse gas emissions from natural animal husbandry, and increase herdsmen’s income and livelihood resilience, this research team implemented the Ministry of Agriculture and Rural Affairs (MARA)-World Bank (WB)-Global Environment Facility (GEF) climate-smart grassland management technology research. In Mole Town of Qilian County in Qinghai Province, we worked with herdsmen to implement the natural grassland management technology of non-spring grazing and no-tillage seeding, monitored grassland vegetation diversity and productivity, calculated the normalized vegetation index (NDVI) of vegetation in the study area through satellite images, and investigated the social impacts and herdsmen’s satisfaction and economic conditions resulting from climate-smart grassland management. The pilot application and investigation of climate-smart grassland management technology has achieved rich results in Mole Town. Grassland productivity has been increased by 34.1% and 50.0% respectively under non-spring grazing and no-tillage seeding, and both of these two restoration measures have increased the grassland vegetation diversity to a certain extent. NDVI showed that the vegetation growth under the restoration measures is better than that of the control land. In addition, 88.6% of the herdsmen are satisfied with the climate-smart grassland management technology. The implementation of the management technology directly or indirectly increased the income of the project households and herdsmen. And the scientific literacy of about 80.0% of local herdsmen has been improved. Climate-smart grassland management technology can improve the grassland vegetation diversity, productivity and green coverage, increase herdsmen’s income, improve herdsmen’s living environment, promote herdsmen’s scientific literacy, and enhance herdsmen’s ability to cope with climate change, thereby helping the revitalization of pastoral areas.
    Technology Research and System Design of Automatic Forage Observation
    CHONG Yang, ZHAO Jiankai, MA Xiucai
    Chinese Agricultural Science Bulletin    2022, 38 (22): 126-133.   DOI: 10.11924/j.issn.1000-6850.casb2022-0299
    Abstract + (180)    HTML (1)    PDF (3081KB) (21)      

    In view of the ecological observation needs of Inner Mongolia Autonomous Region, especially the grassland ecosystem observation needs, forage observation was selected as the research content, and the idea of real-time remote controllable and visual forage observation automation technology based on embedded technology and parallel computing technology were proposed. The characteristic pixel image recognition method was used to realize the automatic measurement of forage coverage and the automatic recognition of forage growth image. The image height to object height transformation algorithm was obtained by using photogrammetry technology and image processing technology to realize the automatic measurement of layer height and plant height. Combined with modern electronic technology, DSP technology and image processing technology, an intelligent sensor for forage automatic observation was designed, which completed image acquisition, processing and pattern recognition at the observation front end, and then transmitted the processed results to the server through the network. Users could access the server through smartphone or PC to view the observation data remotely. The system realized the automatic observation of forage coverage and layer (plant) height and forage growth period. The test results show that the image processing is significantly correlated with the measured coverage value, with the test R0.05>0.90, and significantly correlated with the measured plant height, with the test R0.05>0.85. Compared with the image processing in the back-end PC system, the intelligent sensor for forage automatic observation can not only improve the data operation and processing speed of the observation system, but also have good robustness. At the same time, the intelligent sensor for forage automatic observation can greatly reduce the pressure of data transmission, and is suitable for tasks with high requirements of volume, power consumption, working environment and stability.
    The Integrated Development Mode and Mechanism of Agriculture, Forestry, Culture, Tourism and Health Industry from the Perspective of New Industry Form and New Function——Taking Zezhou County of Shanxi Province as an Example
    WANG Wenlei, LI Qian
    Journal of Agriculture    2022, 12 (5): 70-76.   DOI: 10.11923/j.issn.2095-4050.cjas2021-0114
    Abstract + (356)    HTML (5)    PDF (1167KB) (204)      

    To further promote the transformation and upgrading of county level agricultural economy, optimize agricultural structure and increase farmers’ income, based on the combination of agriculture, forestry, culture, tourism and health industry, this study focused on the organizational form of the differentiation, convergence and integration of agriculture, forestry, culture, tourism and health industry, and constructed the new industry form and new function of the organizational form. The integration of agriculture, forestry, culture, and tourism and health industry is the mutual penetration, intersection and integration among agriculture, forestry, cultural industry, tourism industry and health care industry. The integration among the five industries could promote the development of the new industry form and new function. This study took Zezhou County of Shanxi Province as the research object, based on the county’s resources and terrain characteristics, established the development modes of ‘plain + modern agriculture’, ‘hilly area+ cultural tourism’ and ‘mountain area+ forest health’ from the perspective of the new industry form and new function, as well as the cultivation mechanism of new agricultural business entities, the strengthening mechanism of interest connection, the guarantee mechanism of policy and the expansion mechanism of industrial development. This study could have a practical role in promoting the development of the new industry form and new function of the integration of agriculture, forestry, culture, and tourism and health industry.
    The Construction Strategies of Rural Tourism Destinations in the Era of Mobile Internet
    ZHOU Hui
    Journal of Agriculture    2022, 12 (5): 96-100.   DOI: 10.11923/j.issn.2095-4050.cjas2021-0200
    Abstract + (242)    HTML (6)    PDF (1091KB) (191)      

    In the pre-digital era when the mobile internet has not yet become popular, a set of relatively fixed rules and traditions have been formed on the construction strategy of rural tourism destinations. However, with the advent of the mobile internet era, numerous rural tourism destinations, as important potential regions for rural revitalization and industrial support, urgently need to be guided by construction ideas that conform to the logic of the new era. At present, the lack of integration with the needs of the internet era has led to unclear construction countermeasures, which has become one of the important reasons for the lack of enthusiasm for rural tourism destinations. Under the opportunity of a new round of policy support and rapid development of new media technology, this study starts with the regular characteristics of tourism communication in the mobile internet era, deeply interprets the new characteristics of rural tourism development such as ‘beauty face-based economy, web celebrity phenomenon, and data dominance’, and puts forward the construction strategies of strengthening the construction of traditional rural landscapes and scenes, trying more new elements of rural industries, and advancing the construction of rural smart facilities like data collection and management platform, in order to promote the development of rural tourism and rural revitalization.
    Performance Comparison Between New Automatic Soil Moisture Sensor and Traditional FDR Sensor
    CHEN Yajun, AN Xuewu, YANG Yuhui
    Chinese Agricultural Science Bulletin    2022, 38 (11): 123-128.   DOI: 10.11924/j.issn.1000-6850.casb2021-1139
    Abstract + (242)    HTML (9)    PDF (1418KB) (34)      

    Based on the traditional FDR automatic soil moisture sensor, we developed a new type of automatic soil moisture sensor by redesigning the measuring circuit. In the laboratory, the electrical performance, measurement performance, resistance to temperature changes and resistance to saline and alkali of the new automatic soil moisture sensor were compared with those of the traditional FDR automatic soil moisture sensor. The comparison results showed that: the new automatic soil moisture sensor could realize continuous monitoring of soil moisture and meet the measurement performance requirements; the calibration process of the new automatic soil moisture sensor was relatively simple, the measurement accuracy was higher, the anti-interference ability was stronger, and the stability was better. The new automatic soil moisture sensor could improve the accuracy and stability of soil moisture monitoring, and provide technical support for upgrading the automatic soil moisture observation instrument.
    Agricultural Science Popularization Supporting Rural Revitalization An Empirical Study on Liaoning 12316 Sannong Comprehensive Information Service Platform
    CHEN Qiufei, JIA Guoqiang
    Chinese Agricultural Science Bulletin    2022, 38 (11): 160-164.   DOI: 10.11924/j.issn.1000-6850.casb2021-1187
    Abstract + (259)    HTML (3)    PDF (1266KB) (77)      

    This study aims to explore the new model, path and methodology of the informatization service for farmers’ science popularization in the background of implementing the Rural Revitalization Strategy, and to provide reference for constructing agricultural informatization service system and supporting rural revitalization at all levels nationwide. Based on the literature research of agricultural science popularization and its new model and methodology, the authors analyzed the experience of building 12316 Sannong (namely agriculture, rural community and farmers) Comprehensive Information Service Platform in Liaoning Province and the platform’s actual role in supporting rural revitalization. Liaoning 12316 Sannong Comprehensive Information Service Platform has created a new ‘five in one’ model of science popularization informatization service for farmers, with a structure of 5 levels of national, provincial, municipal, county and township. From 2019 to 2021, the platform provided 11.3071 million cases of science popularization service within Liaoning Province, and it has now become a typical model of ‘Internet + Agriculture’ application in the province and a key brand of agricultural informatization. The platform can provide reference for local agricultural departments to improve their informatization service system construction, and the basic infrastructure construction should be highlighted for building agricultural information network to cultivate farmers with high capacity. It is suggested that the provincial level agricultural information service platform should establish a ‘galaxy’ model of science popularization service system to carry out cross-region science popularization activities, and agricultural information service platforms at all levels should actively explore diversified informatization service models to support rural revitalization.
    Leaf Area Measurement System Based on Digital Image Processing Technology
    SONG Yingbo
    Journal of Agriculture    2022, 12 (2): 73-75.   DOI: 10.11923/j.issn.2095-4050.cjas2020-0218
    Abstract + (255)    HTML (5)    PDF (1123KB) (336)      

    In view of the time consuming and low efficiency of the traditional method of leaf area measurement, and the high cost and inconvenient maintenance of the leaf area meter method, this study used the image processing technology to measure the leaf area. The computer vision technology reference method was used to solve the limitations of image threshold segmentation, leaf shadow removal and leaf edge detection algorithm, and the threshold was obtained by OTSU method, the median filtering method was used to remove residual impurities in the image, and the Roberts operator was used for edge extraction. Leaf areas are calculated and compared with those obtained by leaf area meter and paper-cutting method. The leaf area determined by the leaf area meter method and the image processing method had the correlation coefficient R2 of 0.962, and the leaf area determined by the paper cutting method and the image processing method had the correlation coefficient R2 of 0.949. The digital image processing method is validated to be suitable for large amount of leaf area measurement, and has fast speed, accurate data and high precision.
    Research on the Construction of Agricultural Big Data Information Collection Platform
    LI Tingting, MA Juanjuan, ZHANG Jianhua
    Chinese Agricultural Science Bulletin    2022, 38 (3): 158-164.   DOI: 10.11924/j.issn.1000-6850.casb2021-0245
    Abstract + (181)    HTML (5)    PDF (2896KB) (56)      

    Agricultural big data has become an important means to promote agricultural transformation and upgrading and improve production decision-making. Based on the comprehensive analysis of the significance and objectives of the construction of agricultural big data information collection platform, this paper puts forward the construction idea and overall framework of agricultural big data information collection platform, describes the information collection mode and content mode of the platform, and designs the core functions of the system. The study aims to promote the construction of agricultural information resource system by building agricultural big data information collection platform, and lay the foundation for the development and application of agricultural big data industry.
    Development of an Expert Diagnosis System for Jujube Diseases and Pests Based on WeChat Public Platform
    ZHAI Yingyan, ZHANG Feng, REN Bowen, JING Yangping, XIE Yufen, HAO Zhe, HONG Bo
    Chinese Agricultural Science Bulletin    2022, 38 (1): 149-154.   DOI: 10.11924/j.issn.1000-6850.casb2021-0058
    Abstract + (193)    HTML (3)    PDF (2690KB) (33)      

    To quickly popularize the knowledge of jujube diseases and insect pests, this study used an agricultural expert system to improve the diagnosis and management efficiency of jujube diseases and insect pests. Based on the WeChat platform, the jujube expert diagnosis system ‘JujubaExpert2020’ was developed using php script language and mysql database. The system includes three functional modules: disease and pest diagnosis, cultivation history, and news on jujube planting. The core function is the database query and expert diagnosis forums of jujube pests and diseases. Users can query in two ways of keywords or the list of diseases and insect pests, to obtain information about the occurrence rules, hazard characteristics and prevention methods of related diseases and pests quickly and easily; the expert diagnosis forum provides a communication platform for users and experts, and experts can diagnose jujube diseases and pests online and answer the questions raised by users. In addition, the system also integrates the jujube industry distribution and agro-meteorological information of related producing areas nationwide, so that users can understand the development status of the national jujube industry better. The development of this system is beneficial to improving the early identification, diagnosis and scientific management ability of farmers on jujube diseases and pests, and could promote the IT application in jujube industry.
    Research Advances on the Application of the Internet of Things Technology in Kelp Seedling Cultivation
    WANG Haimo, YU Hang, ZHU Shaozhang, ZHANG Qiyu, LIU Feng, WANG Chengguo
    Journal of Agriculture    2022, 12 (1): 74-79.   DOI: 10.11923/j.issn.2095-4050.cjas2021-0081
    Abstract + (293)    HTML (18)    PDF (1284KB) (262)      

    Kelp (Laminaria japonica) is a large perennial edible algae variety, and the cultivation of its seedlings is the basic step in kelp production. It is an inevitable choice to achieve the transformation and upgrading of kelp seedling cultivation by combining it with the Internet of Things (IoT) technology. Based on related research results, the concept and key technologies of the IoT technology are described to elaborate the development status of agricultural IoT and the typical framework of kelp seedling cultivation monitoring system, and the application of the IoT technology in the process of kelp seedling cultivation of the past few years are summarized. Based on the discussion and analysis of the existing problems, the countermeasures are put forward, such as improving the informatization level of kelp seedling industry, reinforcing the research and development ability of related technologies and hardware and software facilities, and strengthening the guiding and promoting role of the government, which can provide reference for the development of intelligent production mode of kelp seedling.
    The National Agricultural and Rural Personnel Information Service Platform: Research on the Construction Path
    Wu Junze
    Journal of Agriculture    2021, 11 (11): 104-107.   DOI: 10.11923/j.issn.2095-4050.cjas2021-0103
    Abstract + (232)    HTML (6)    PDF (1118KB) (233)      

    Strengthening the information construction of rural human resource work is an important measure to improve the identification standard of rural talents, carry out classified statistics on rural talents, and improve the service and guarantee ability of rural talents. Constructing the national agricultural and rural personnel information service platform is an effective way to enhance the information construction of rural human resource work. This paper introduces the basic principles for constructing the national agricultural and rural personnel information service platform, and expounds the main functions provided by the platform from the aspects of classified storage, classified collection, evaluation and identification, dynamic management, and service development. To improve the information service quality for agricultural and rural talents, this paper puts forward suggestions aiming at the weak types of talents by making full use of the advantages of the platform resources.
    Application of Internet of Things and PLC Technology in Fish Vegetable Symbiosis System
    Zheng Guangzhi, Zhang Shan, Guo Haitao, Shi Wenfeng, Lu Qisheng, Wang Wei
    Chinese Agricultural Science Bulletin    2021, 37 (30): 133-138.   DOI: 10.11924/j.issn.1000-6850.casb2020-0239
    Abstract + (341)    HTML (5)    PDF (1433KB) (105)      

    As the core of industry 4.0, Internet of Things technology has become a hot word around the world. As a large agricultural country, in agricultural production, China needs to introduce new technologies to construct a production mode with less consumption, pollution avoidance, low cost and mass production in limited resources. This paper introduces IOT technology combined with Siemens S7-1500 controller, node-red and other Internet of Things tools, connecting sensors and PC station to form a set of PLC controlled fish vegetable symbiosis system. TIA portal serves as the programming configuration software to configure and test the sensor and controlled object, to design the electrical system, to assemble the electrical cabinet of the external control system, and to realize the automatic control of the fish vegetable symbiosis system. The design changes the traditional high-density farming mode, and could act as another type of integrated farming mode imitating nature. It holds the characteristics of low energy consumption, high yield, high profit, good product and no pollution.