Against the historical backdrop of synchronizing industrialization, informationization, urbanization and agricultural modernization in China, it is of a material immediate significance to clearly define research priorities and development orientations for the future in the field of information-based agriculture. This article, through summarizing the status quo and the latest developments in the field of China’s research into the information-based agriculture, specifically proposes certain scientific problems and key technologies for future research in the area of information-based agriculture, and gives a systematic analysis on major items for research in the area of China’s information-based agriculture for the next 5 to 10 years.
Abstract The breeding environment of laying hens has an important influence on the growth of laying hens, the prevention and control of diseases, and the yield and quality of eggs. Therefore, the real-time collection and utilization of the environment information of laying hens is the key point of breeding laying hens. In this study, the environmental information monitoring and control equipment and systems for egg-breeding laying hens were integrated and developed. The real-time monitoring of the environment information of the laying hens and the information query function on the webpage and mobile devices was realized. The stability and versatility testing of equipment and systems were completed through the pilot deployment of equipment and systems in a laying hen farm in Beijing. The design and development of the equipment and system can provide technical support for the modernization, mechanization and information management of laying hens.
This paper established the application level evaluation index system of agricultural IoT (Internet of Things) in the whole industrial chain of agriculture by means of the application of agricultural IoT in agricultural production, agricultural circulation, agricultural service and agricultural management.It determined the weight of each index by using the analytic hierarchy process, and then established the comprehensive evaluation model.The evaluation index was scored, and the practical application of the method was carried out by an example, which not only provides a scientific and comprehensive evaluation basis for the application level evaluation of IoT, but also provided a way for continuous optimization of the index system in the future.
Abstract Ensuring the balance between supply and demand of agricultural products and keeping the basic price of agricultural products are the preconditions of reducing market fluctuation. According to the situation of production and supply of agricultural products and price fluctuation of agricultural products market in Inner Mongolia and Xing’an League, this paper condenses the primal problems existing in the agricultural products market in Inner Mongolia, studies the causes of these problems, makes overall plans for the structural reform of the supply side of agricultural products at present and in the future, in an effort to put forward reasonable countermeasures and suggestions for realizing effective docking of production and marketing of agricultural products and reasonable price fluctuation
In the actual cotton planting environment, rapid change of light within a day, reflection from different backgrounds and different weather conditions can affect the imaging of cotton. Therefore, the crop object segmentation is difficult. Images which were captured in 12 natural scenes during cotton planting, including three weather conditions, such as sunny, cloudy and rainy and four soil cover conditions, such as white mulch film, black mulch film, straw and bare soil were regarded as the research objects. This paper presents the cotton leaf segmentation method based on Immune algorithm and pulse coupled neural networks (PCNN). First, 17 color components of white mulch film, black mulch film, straw, bare soil and cotton under the conditions of sunny, cloudy and rainy days were analyzed by using statistical method. Three high feasible and anti-light color components were selected by histogram statistical with mean gray value. Second, the optimal parameters of PCNN model and the optimal number of iterations were determined by using immune algorithm optimization theory, and the method in this paper was tested by using 1200 cotton images which were captured under 12 natural scenes. Finally, the test results showed that this method can distinguish cotton target region from soil and other background regions. Meanwhile, for reflection of mulch film, crop shadow, dark light, complex background, noise, etc. which are often appeared in natural scene, four image segmentation methods of Otsu algorithm, [Formula: see text]-Means algorithm, FCM algorithm and PCNN were compared with the proposed method in this paper. The segmentation result showed that the proposed method has good resistance to change of light and complex background. The average [Formula: see text] of the proposed method is 6.5%, significantly lower than that of other four methods and the performance is better than other four methods. This method can segment cotton images in different weather conditions and different backgrounds accurately under complex natural conditions. It will contribute to the subsequent growth status determination and pest diagnosis of cotton.
Forest biomass could quantify the complex relationship between the change of forest carbon storage and the carbon cycle in the environment. The accurate estimation results of forest biomass are the basis for the analysis and evaluation of forest ecosystem structure, function, quality and benefit. The distribution of forest biomass is the result of the interaction of structural factors and random factors. A typical data flow processing framework had been adopted, and a new ecological tool: Multi-factor assisted forest biomass spatial interpolation software tool (MFA-SIS) had been designed and implemented. The MFA-SIS had implemented complex algorithm logic in the underlying code, and simplified the pre-processing process of multi-factor assisted modeling data and forest biomass sample data. And the visualization interface could provide a good software module for forest biomass estimation that is easy to learn, practical and has great application potential, and provide a good underlying model algorithm tool support for the "double carbon" strategy proposed by China.
A clear grasp of vegetable price transmission mechanism and the ability to make early warning for vegetable price are important for guaranteeing the effective supply and stabilizing the market price of vegetables.Therefore, it is of great significance to conduct a research on vegetable price transmission and the early warning considering the associations with non-target areas.The implementation plan for the research was expounded from the research methods, technical route, key technologies and innovations.
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