Building an interoperable space for smart agriculture

The digital transformation in agriculture introduces new challenges in terms of data,knowledge and technology adoption due to critical interoperability issues,and also challenges regarding the identification of the most suitable data sources to be exploited and the information models that must be used.DEMETER(Building an Interoperable,Data-Driven,Innovative and Sustainable European Agri-Food Sector)addresses these challenges by providing an overarching solution that integrates various heterogeneous hardware and software resources(e.g.,devices,networks,platforms)and enables the seamless sharing of data and knowledge throughout the agri-food chain.This paper introduces the main concepts of DEMETER and its reference architecture to address the data sharing and interoperability needs of farmers,which is validated via two rounds of 20 large-scale pilots along the DEMETER lifecycle.This paper elaborates on the two pilots carried out in region of Murcia in Spain,which target the arable crops sector and demonstrate the benefits of the deployed DEMETER reference architecture.

Development and Application of Meteorological Disaster Monitoring and Early Warning Platform for Characteristic Agriculture in Huzhou City Based on GIS

Based on the needs of characteristic agricultural production for meteorological services in Huzhou City,we use C# programming language to develop the meteorological disaster monitoring and early warning platform for characteristic agriculture in Huzhou City. This platform integrates the functions of meteorological and agricultural information monitoring,disaster identification and early warning,fine weather forecast product display,and data query and management,which effectively enhances the capacity of meteorological disaster monitoring and early warning for characteristic agriculture in Huzhou City,and provides strong technical support for the meteorological and agricultural departments in the agricultural meteorological services.

China National Engineering Research Center for Information Technology in Agriculture

China National Engineering Research Center for Information Technology in Agriculture （NERCITA） was established in 2001 with the approval of the Ministry of Science and Technology of China. As a national research institution, it mainly engages in research and development of agricultural and rural informatization engineering technology. Based on the requirements of agricultural and rural development of China, the major mission of NERCITA is to make key technology innovation, establish technical platform and develop significant products for agriculture, which focus on five aspects： intelligent information processing technology, remote sensing and geographic information system, precision agriculture, biological environment control engineering and automation technology as well as fast detection techniques of agricultural product security and the monitoring technology of farmland environmental quality. The ultimate goal is to provide a powerful technological support for agricultural modernization and rural development.

Construction of Smart Library Based on the Agricultural Information from Metaverse Horizon

Metaverse is a virtual world,but it is possible and even becomes a trend that metaverse interacts with the real world along with the sci-tech and social development.Smart library is a main direction of modern library development,from informatization to digitization and then intelligent-based,modernization of library has been improved qualitatively.Emergence of metaverse brings a brand-new horizon to the generation and application of agricultural information,this paper made primary explorations the requirements and action mechanism of agricultural information on the construction of smart library within the external constraint of metaverse.

Agricultural remote sensing big data:Management and applications

Big data with its vast volume and complexity is increasingly concerned, developed and used for all professions and trades. Remote sensing, as one of the sources for big data, is generating earth-observation data and analysis results daily from the platforms of satellites, manned/unmanned aircrafts, and ground-based structures. Agricultural remote sensing is one of the backbone technologies for precision agriculture, which considers within-field variability for site-specific management instead of uniform management as in traditional agriculture. The key of agricultural remote sensing is, with global positioning data and geographic information, to produce spatially-varied data for subsequent precision agricultural operations. Agricultural remote sensing data, as general remote sensing data, have all characteristics of big data. The acquisition, processing, storage, analysis and visualization of agricultural remote sensing big data are critical to the success of precision agriculture. This paper overviews available remote sensing data resources, recent development of technologies for remote sensing big data management, and remote sensing data processing and management for precision agriculture. A five-layer-fifteen- level （FLFL） satellite remote sensing data management structure is described and adapted to create a more appropriate four-layer-twelve-level （FLTL） remote sensing data management structure for management and applications of agricultural remote sensing big data for precision agriculture where the sensors are typically on high-resolution satellites, manned aircrafts, unmanned aerial vehicles and ground-based structures. The FLTL structure is the management and application framework of agricultural remote sensing big data for precision agriculture and local farm studies, which outlooks the future coordination of remote sensing big data management and applications at local regional and farm scale.

Research on Development of Agricultural Geographic Information Ontology

This paper first analyzes the reason that agricultural geographic information gives rise to semantic heterogeneity and solution thereof. Although OWL （web ontology language） is the standard of ontology representation language in semantic web, it is insufficient in representing spatial characteristics, especially spatial relationship. Consequently it is pointed out to build geo-ontology by virtue of three theories such as mereology, location theory and topology in this paper. This paper introduces mereology, location theory and topology, and then discusses how to adopt these three theories to build geo-ontology. The outcome of experiment shows that solution put forward by this paper is feasible.

A Dairy Industry Information Cooperative Service System Based on a Production Process Ontology

Agricultural information cooperative services （AICS） are now becoming an important aspect of agriculture informatization. This study offers an ontological conception of the agricultural production process, establishing operational divisions corresponding to both the stages and the fundamental information requirements of the dairy industry production process in China, yielding a process ontology for the dairy industry as well as a business chain model. A framework for a dairy industry information cooperative service system was established, with service functions realized in a prototype system. The resulting agricultural process ontology built on the basis of biological characteristics has advantages as a classification standard for agricultural information; whereas the business chain model based on this agricultural process ontology allows for an effective distribution of agricultural information cooperative services. This study outlines a concept and demonstrates a prototype of a cooperative service capable of integrating diverse online agricultural information relevant to the dairy industry in China.

Research and application of real-time monitoring and early warning thresholds for multi-temporal agricultural products information

Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background of big data,improving the capacity to monitor agricultural products is of great significance for macroeconomic decision-making.Agricultural product information early warning thresholds are the core of agricultural product monitoring and early warning.How to appropriately determine the early warning thresholds of multi-temporal agricultural product information is a key question to realize real-time and dynamic monitoring and early warning.Based on the theory of abnormal fluctuation of agricultural product information and the research of substantive impact on the society,this paper comprehensively discussed the methods to determine the thresholds of agricultural product information fluctuation in different time dimensions.Based on the data of the National Bureau of Statistics of China(NBSC)and survey data,this paper used a variety of statistical methods to determine the early warning thresholds of the production,consumption and prices of agricultural products.Combined with Delphi expert judgment correction method,it finally determined the early warning thresholds of agricultural product information in multiple time,and carried out early warning analysis on the fluctuation of agricultural product monitoring information in 2018.The results show that:(1)the daily,weekly and monthly monitoring and early warning thresholds of agricultural products play an important early warning role in monitoring abnormal fluctuations with agricultural products;(2)the multitemporal monitoring and early warning thresholds of agricultural product information identified by the research institute can provide effective early warning on current abnormal fluctuation of agricultural product information,provide a benchmarking standard for China's agricultural production,consumption and price monitoring and early warning at the national macro level,and further improve the application of China's agricultural product monitoring and early warning.

ANALYSIS ON AGRICULTRUAL INFORMATION DEMAND——Case of Jilin Province

With the rapid development of agricultural informalization in the world, the demand of agricultural information has been a focus in the international agriculture and information fields. Based on the investigation, this paper presented the four characteristics of the demand of agricultural information in China, includingregionality, seasonality, great potential demand and variation in kind and level. The factors infuencing the demand of agricultural information were analyzed by the Optimized Less Square （OLS） method. The result shows that, of all factors influcing agricultural information demand, the most important one is economy, the second is facility of information pass, and knowledge and education of user, credit of agricultural information service system and production situation follow. Taking Jilin Province as an example, this article also elaborated the agricultural information demand status, and deduced the regression model of agricultural information demand and verified it by the survey in rural Jilin.

Construction of Agricultural Information Service System in China——under the Eyeshot of Communication Science

The paper aims to study the current communication condition,configuration,characteristic and regulation of Chinese agricultural information in terms of the eyeshot of communication studies,and provide reference to build Chinese agricultural information service system based on the analysis of their advantages and disadvantages.

Research on Web-GIS Based Intelligent Management Decision-Making System for Soybean

The design of Web-GIS based intelligent management decision-making system for soybean follows the life cycle standard of software engineering. Based on the analysis of the flow of soybean growth technology, the data flow chart was protracted and the function from chart was brought in the course of the designing and realizing the system. By making use of the directed program tool such as VC, Java and multi-media technique the fimctions of decision-making system were realized. It will do a lot of for the theoretical and practical development of intelligent technology of agricultural information of Heilongjiang Province.

Studies on Agricultural Scientific and Technical Information Core Metadata Register System

To construct the Agricultural Scientific and Technical Information Core Metadata （ASTICM） standard and its expanding principles, and to develop a register system based on ASTICM, the policy and methods of DC （Dublin Core） and SDBCM （Scientific Database Core Metadata） were studied. The construction of ASTICM has started from the proposed elements of the DCMI （Dublin Core Metadata Initiative）, and has expanded the DC and SDBCM with related expanding principles. ASTICM finally includes 75 metadata elements, five expanded principles, and seven application profile creation methods. According to the requirement analysis of a large number of users of agricultural information, a register system based on ASTICM was developed. The ASTICM standard framework and its register system supported the search, sharing, integration exchange and other applications, effectively.

Constraints of Women Farmer’s Access to Information and Communication Technologies (ICTs) for Agricultural Information in Oyo State, Nigeria

The study investigated constraints of women farmers access to ICTs for agricultural information in Oyo State.A total of 120 respondents were sampled.Data were retrieved using interview schedule and were analysed using descriptive and inferential statistics.Statistics reveal respondents average age,average household size and average monthly income as x=45.8,x=10.6 and x=₦7,800.34 respectively,majority(86.7%)were married,58.3%representing respondents with primary education.Mobile phone(x=0.98)was the most available among the respondents while poor ICTs infrastructure(x=1.55)and difficulty in the utilization of ICTs gadgets(x=1.62)ranked highest as constraints access to ICTs for agricultural information.Significant relationship existed between respondents average monthly income(r=0.492,p=0.000),educational level(χ^(2)=4.726,p=0.021)and the constraints access to ICTs for agricultural information.Scaling up the ICTs infrastructure base around farming clusters and capacity building like training on ICTs to access agricultural information retrieval is advocated for women farmers.

Visual Design Solving the Last Mile Problem of Agricultural Science and Technology Informatization

Agricultural science and technology is a collective name of the agricultural science information and agricultural technology information, which belongs to different activity fields, pursuing the use of nature and laws of things. In the process of transmission, it has a lot of data and pro^ams, thus, facing the audience groups of accepting different information ability, it often appears information transmission distort or misunderstanding. Information visualization design will represent a lot of agricultural science and technology information with complex structure and level, making use of the graphics relationship, by using the concise, easily browsing and searching method. How to make use of the information visualization design to solve the large capacity structure of agricultural science and technology information is the content that this paper analyzes.

Factors Influencing the Success of Agricultural Information System （AIS）： A Factor Analysis

This study aims at investigating the AIS （Agricultural Information System） in Hamedan province, Iran, benefiting from the list of criteria for well functioning AISs that were identified in earlier researches. For this purpose, a survey method with multi-stage stratified random sampling technique was used to select 31 agricultural researchers, and 62 extension workers in the province. The data were acquired by questionnaire and structured interviews. The instrument for data collection was subjected to pre-testing, validation and reliability tests. The results of the factor analysis revealed that the criteria could be categorized into four overarching groups based on their inter-correlation. The analysis of mentioned criteria in Hamedan province AIS showed less efficiency and effectiveness than studies conducted in other areas. But among these, two desirable criteria existed. It is recommended that the ecological knowledge system （EKS） should be integrated with AIS, and some ecological and sustainable development criteria should be added to the existing ones.

Novel encoder for ambient data compression applied to microcontrollers in agricultural robots

Agricultural robots are flexible to obtain ambient information across large areas of farmland. However, it needs to face two major challenges: data compression and filtering noise. To address these challenges, an encoder for ambient data compression, named Tiny-Encoder, was presented to compress and filter raw ambient information, which can be applied to agricultural robots. Tiny-Encoder is based on the operation of convolutions and pooling, and it has a small number of layers and filters. With the aim of evaluating the performance of Tiny-Encoder, different three types of ambient information (including temperature, humidity, and light) were selected to show the performance of compressing raw data and filtering noise. In the task of compressing raw data, Tiny-Encoder obtained higher accuracy (less than the maximum error of sensors ±0.5°C or ±3.5% RH) and more appropriate size (the largest size is 205 KB) than the other two auto-encoders based convolutional operations with different compressed features (including 20, 60, and 200 features). As for filtering noise, Tiny-Encoder has comparable performance with three conventional filtering approaches (including median filtering, Gaussian filtering, and Savitzky-Golay filtering). With large kernel size (i.e., 5), Tiny-Encoder has the best performance among these four filtering approaches: the coefficients of variation with the large kernel (i.e., 5) were 8.6189% (temperature), 10.2684% (humidity), 57.3576% (light), respectively. Overall, Tiny-Encoder can be used for ambient information compression applied to microcontrollers in agricultural information acquisition robots.