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With the continuous development of information technology, various industries continue to use information technology to promote industrial upgrading and optimize the industrial structure. Agricultural informatization, as the only way for future agricultural development, will become an inevitable direction for the rejuvenation of traditional industries. The proposal of the development concept of "Mass Entrepreneurship, Mass Innovation" marks that my country has gradually entered an innovative society, and the development of public services and service products will become a powerful guarantee for promoting the construction of the agricultural informatization industry chain. This paper starts from the application of cloud computing and 5G in agriculture, considers the impact of big data on agriculture, and combines the business requirements and functional requirements of agricultural social services. The design of agricultural socialization service platform is realized, and finally, the service effect of the platform is evaluated by neural network. The following is a summary of the work done in this paper: (1) The research background and significance of the development concept of agricultural informatization services are expounded. Finally, the research content and method of this paper are discussed. (2) The technical principle and optimization algorithm of BPNN are introduced, and the evaluation index of the service effect of agricultural information platform is designed. (3) Select the appropriate parameters to build the experimental model and then train it, then compare the experimental effects of the traditional BP algorithm and the optimized three algorithms, and comprehensively evaluate the LM-BP model with the best performance. [ABSTRACT FROM AUTHOR]

With the rapid development of agricultural economy, people are paying more and more attention to how to apply high-efficiency technologies that save resources to improve agricultural production efficiency, so water-saving irrigation technology has gradually developed. China's agricultural irrigation technology is relatively backward. In addition to the inappropriate irrigation methods and irrigation systems, problems such as siltation, seepage, and frost heave damage in irrigation canals have seriously affected the durability and service life of the canals. The backward irrigation technology seriously restricts the development of agricultural water-saving irrigation. Compared with large irrigation channels, the fabricated reinforced concrete small irrigation channels studied in this paper are less prone to frost heave damage and infiltration problems, and have the advantages of standardized production, simple transportation and installation, and convenient maintenance. In order to study the durability issues such as the basic characteristics, frost heave damage, and service life of fabricated irrigation channels, this paper takes the channel concrete and the formed channel as the research objects, and discusses the research on the properties of the channel concrete through theoretical research, numerical analysis, experiments, and other methods. Strength properties, water penetration resistance, cyanide ion penetration resistance and frost resistance; simulate the seasonal frost heave failure process of the channel; finally, on the basis of the test data, the service life aims to explore the safety and applicability of the fabricated reinforced concrete irrigation channel during the design use period. [ABSTRACT FROM AUTHOR]

Agriculture is the basic industry of the national economy, and the transformation of agricultural economic growth mode is of great significance to ensure the supply of agricultural products and improve the quality of agricultural products. Therefore, it is the only way to solve this problem to change the way of agricultural economic growth through scientific and technological investment, industrial structure adjustment, and other methods. Based on the fuzzy comprehensive evaluation method, this paper analyzes various factors of agricultural economic development and establishes a multilevel fuzzy comprehensive evaluation model of the development status of agricultural economic system. The stochastic frontier production function model of the fuzzy control comprehensive model is applied to decompose the agricultural labor productivity, and the counterfactual thinking and distribution method are used to analyze the influence of these factors on the evolution of provincial agricultural labor productivity differences. The value inequality decomposition method measures the contribution of each factor to the provincial agricultural labor productivity difference as well as the contribution of exogenous explanatory variables to the provincial agricultural technical efficiency difference. It is concluded that the relative contribution rate of nonagricultural activities to the difference in agricultural technical efficiency is the largest, and the average relative contribution rate reaches 74%. The improvement of agricultural labor productivity cannot rely solely on the increase in the input of agricultural material factors, but should rely on science and technology. [ABSTRACT FROM AUTHOR]

The green development of the entire agricultural industry chain is not only an important way to enhance the competitiveness of agricultural products and promote the value-added of the agricultural industry but also an inevitable choice to improve the efficiency of resource utilization and ensure sustainable economic development from the perspective of the ecological environment. This paper defines the connotation and characteristics of the green development of the whole agricultural industry chain and deeply analyzes the development status, major challenges, and feasible paths of the whole agricultural industry chain in China. It has built a whole industry chain development model of "Internet + modern agriculture" and proposed a decentralized agricultural data management system based on the IoT to solve the problem of untraceable of traditional agricultural products and other data. The agricultural IoT system is designed with a unique blockchain double-chain structure, using the global hash chain and the mutual verification between the transaction chains in each partition. It proposes the PMCP protocol, which improves the performance of the system by producing blocks in parallel for several consensus groups in each consensus cycle. The experimental results show that the proposed model is queryable, traceable, and trustworthy for whole-life agricultural data, and the proposed model outperforms other schemes in terms of throughput and delay. [ABSTRACT FROM AUTHOR]

China is a large agricultural country. With the development of industrial production, mechanized harvesting has become an inevitable development trend of agricultural material harvesting. In this paper, based on the latest technology of polycrystalline ferroelectric composite materials in the design of the shovel frame of the harvester's vibrating excavating shovel, the relevant theories of the polycrystalline ferroelectric composite material and the shovel frame of the harvester's vibrating excavating shovel are based on the literature. After understanding, the shovel frame structure of the vibrating excavating shovel of the harvester was designed, and the latest technology of polycrystalline ferroelectric composite material was introduced in the design of the shovel frame of the vibrating excavating shovel of the harvester to make the vibration system have better performance. The designed shovel frame structure is tested, and the test results show that the horizontal output force received by the shovel designed in this paper increases with the increase of speed and is minimized at 0.26 m/s. The vertical output force decreases first and then increases with the increase of speed. It is the smallest when the running speed is 0.39 m/s. The horizontal working resistance is always greater than the vertical working resistance, and it can be seen that the design of the shovel frame structure can be realized in actual work. [ABSTRACT FROM AUTHOR]

As a large agricultural country, the three rural areas have always been one of the key areas of concern for national economic development. Among them, agricultural products finance is not only related to the development of agricultural economy, but also related to the poverty alleviation and wealth of thousands of farmers. With the rapid development of big data, cloud computing, blockchain, and other financial technologies, it will be important to build a new model of agricultural products supply chain finance and a special agricultural products O2O cloud service platform by relying on new technologies. Therefore, this paper conducts a study on the operation of agricultural products e-commerce platform based on cloud computing. This paper firstly introduces the advantages and key technologies of cloud computing. Secondly, this paper constructs the revenue models of e-merchants, farmers, and leading enterprises under insurance and risk-sharing modes and analyzes the optimal decisions of e-merchants, farmers, and leading enterprises under each mode and the influencing factors of the optimal decisions, so as to provide a new way of thinking for the construction of agricultural supply chain finance mode. [ABSTRACT FROM AUTHOR]

The agricultural mechanization development can promote the high-quality development of agriculture, but the agriculture which faces the huge environmental pressure also needs to transform to the green sustainable development. Based on agricultural panel data of 30 provinces in China from the year 2008 to 2017, this paper measures the level of agricultural green transformation using the Malmquist–Luenberger (ML) index. Furthermore, the spatial panel econometric model is used to empirically investigate the impact of agricultural mechanization development on this green transformation. It concludes that the agricultural green transformation in western China shows an upward trend in fluctuations, with its overall transformation level still lower than the national average level. Besides, the agricultural mechanization operation level in the western region has a positive role in promoting the green transformation of agriculture, while the agricultural mechanization equipment level shows the opposite force. Compared with southwest China, the agricultural mechanization operation level in northwest China has a more positive impact. The improvement of farmers' income and agricultural technology has positive impacts on agriculture green transformation in the whole western region, while agricultural human capital shows an opposite impact on the northwest and southwest. [ABSTRACT FROM AUTHOR]

Agricultural modernization has gradually become the direction of future agricultural development. With the improvement of the technical capacity of the Internet of things, a new agricultural development model, namely, intelligent agriculture, has gradually emerged. It can not only improve the production efficiency of agriculture but also improve the efficiency of resource utilization. The main work of the software design of the terminal node is the IoT network connection, the sensor work acquisition, and the packaging of the collected data for transmission and acceptance control to fundamentally alleviate the pressure on food security and ensure the sustainable development of China's agriculture. The experiment demonstrates that the curve temperature cycle of the agricultural greenhouse monitored by the system in this paper is normal, and the maximum temperature has been constant under different time cycles. For example, the maximum values of 5, 15, and 20 are all 0.67. [ABSTRACT FROM AUTHOR]

The digitalization of agricultural planting and breeding enterprises is the only way for agricultural development. Now with the development of various technologies, the digitalization of agricultural enterprises is becoming faster and faster. Today, the development of intelligent sensors provides platform support for the digitalization of agricultural enterprises. This article is aimed at introducing the application of intelligent sensors in agriculture to provide strategic research for the digital development of agricultural planting and breeding enterprises. This paper proposes the establishment of a system platform for network intelligent sensors and proposes the establishment of an agricultural short message management publishing platform. And the existing public information transmission methods are used to provide a cheap, simple, and fast way for agricultural producers to quickly obtain agricultural information, so as to provide a feasible plan for solving the agricultural "last mile of agriculture" problem. After inspection and analysis, the information management release platform can meet the design requirements, and the processing rate of short-term interest is above 98%, which can pave the way for the digital industrialization of agricultural enterprises. [ABSTRACT FROM AUTHOR]

By collecting theoretical research and practical cases on the application of big data in agricultural production and management at home and abroad, this article is based on the actual production and management of rural farmers, deeply analyzes the current situation of big data construction, and finds a model suitable for the development of local agricultural big data. We establish an agricultural big data system suitable for rural characteristics and provide suggestions and suggestions. First of all, this article is based on actual research. Through interviews and questionnaires on the occupational differentiation and agricultural production management of local farmers, the relevant theoretical connections are made, through descriptive statistical analysis of data, and Stata is used for intersectionality. This study uses modular construction methods to build a complete industrialized farm house system and, on this basis, combines the nature of family industry and family intergenerational relationship to divide the unit types and combinations of industrialized modular farm houses. In corresponding analysis and discussion, the test shows that the professional differentiation of farmers is related to the willingness of agricultural production management and agricultural production management behavior. Secondly, this paper uses logistic model to carry out empirical analysis of influencing factors and conducts research on the influencing factors of agricultural production management willingness and agricultural production management behaviors of farmers with different occupational differentiation degrees and models agricultural production management willingness and agricultural production management behaviors, respectively, for empirical testing. Farmers' professional differentiation has related influence factors on agricultural production management willingness and land transfer behavior. After analyzing the results of the model, this article concludes that the occupational differentiation of farmers has a significant impact on the willingness of agricultural production management, and the specific manifestations are significant in many aspects such as farmers' age, education level, whether they have nonagricultural employment skills, and the number of family agricultural labors. The professional differentiation of farmers also has a significant impact on agricultural production management behavior, which is specifically manifested in many aspects such as farmers' age, education level, nonagricultural employment skills, and geographical location of land. [ABSTRACT FROM AUTHOR]

Agriculture is one of Ethiopia's economic cornerstones, although its production remains low. Since then, the implementation of modern agricultural technologies has remained a promising strategy in Ethiopia for increasing agricultural production, achieving food security, and reducing poverty. The objective of the study is to examine the determinants of modern agricultural technology adoption for teff production in Minjar Shenkora woreda. The data were collected from the representatives of 362 rural households. This study employed both descriptive statistics and multinomial logit model. The estimations of the multinomial logit model revealed that sex, age, marital status, tropical livestock units, educational level of household head, distance to market, extension contact, active household members, access to credit, off-farm activities participation, and cultivated land size are the determinants of modern agricultural technology adoption for teff production in Minjar Shenkora woreda, North Shewa Zone, Amhara Region, Ethiopia. Therefore, this study recommended that the country's federal and regional governments, agricultural development offices, nongovernmental organizations, and donor agencies should collaborate with farm households to improve access to information, access to credit, encourage off-farm participation and provide training and consulting services to increase the adoption of modern agricultural technologies. [ABSTRACT FROM AUTHOR]

Inclusive finance can help rural low-income groups, township small and microenterprises, and other groups in China to improve their living and economic standards and can meet the relevant credit needs of relevant rural personnel under the condition of risk prevention. The integration of AI and HP finance has built a more professional information and data platform for customers with different credit needs in the agricultural economy. Based on the development and integration of agricultural economy, this study makes effective analysis and judgment on poor customers with credit needs through the artificial intelligence system platform under the application of inclusive finance, so as to scientifically and effectively identify and screen the big data of different credit data of customers and finally select the most qualified high-quality credit customers, so as to effectively improve the overall economic income of customers with agricultural credit needs. It has laid a foundation for the development of agricultural economy and more effectively extracting high-quality credit customers, so that the development of agricultural economy has been widely used. [ABSTRACT FROM AUTHOR]

With the integration and development of the Internet, the Internet of Things, cloud data, and communication technology, data has grown rapidly. Although science and technology have promoted the upgrade and modernization of the modern agricultural system, it has also brought about the problem of a sharp increase in data, making it difficult to grasp the direction of agricultural development. At the same time, in order to better grasp the development of agricultural modernization, this article has carried out research on the agricultural modernization development index data system based on network big data and raised the problem that agricultural modernization based on network big data can accurately grasp the development direction of agricultural modernization. Experiments show that the index data system studied in this article has a good grasp of the state of agricultural modernization development and is the basis for judging and formulating correct agricultural policies. Among them, the indicator data on the rate of change of the national agricultural policy needs to be maintained between 1.84 and 2.01. The research in this article is of great significance to the development of agricultural modernization. [ABSTRACT FROM AUTHOR]

The inappropriate dumping of agricultural residues (ARs) can result in environmental pollution and the waste of valuable energy resources. The process of converting ARs to energy has been considered an important step for regional energy, agricultural development, and environmental sustainability and recently, many sustainable bioenergy technologies (BETs) have been developed for ARs. Since the assessment of ARs‐to‐energy conversion technologies contains several alternatives concerning multiple criteria with imprecise information, it is deliberated as an uncertain multicriteria decision‐making (MCDM) problem. The Pythagorean fuzzy set (PFS) is an important and effective way to tackle the uncertainty present in real‐life decision‐making problems. To select a suitable conversion technology from a set of options and upgrade the ARs‐to‐energy industries, the present study develops a combined approach to PFSs based on weighted discrimination‐based approximation (WDBA). This method extends the classical WDBA approach using an improved score function and discrimination measure within the PFS context, to evaluate MCDM problems with partial information on the criteria weights. To estimate the weights of the unknown attributes, a score function‐based linear programming model is developed. A new ranking method is extended to grade the options using the proposed discrimination measure within the PFS environment. Further, a case study assessing ARs‐to‐energy conversion technologies is conducted to illustrate the practicality and feasibility of this method. A comparative analysis shows that the approach developed is more effective and proficient in facilitating decision experts' selection of desirable BETs for ARs. [ABSTRACT FROM AUTHOR]