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In view of the problems such as frequent fluctuation of garlic price, lack of efficient forecasting means and difficulty in realizing the steady development of garlic industry, combined with the current situation of garlic industry and the collected data information. Taking Big Data platform of garlic industry chain as the core, using the methods of correlation analysis, smoothness test, co-integration test, and Granger causality test, this paper analyzes the correlation, dynamic, and causality between garlic price and young garlic shoot price. According to the current situation of garlic industry, the garlic industry service based on Big Data is put forward. It is concluded that there is a positive correlation between garlic price and young garlic shoot price, and there is a long-term stable dynamic equilibrium relationship between young garlic shoot price and garlic price fluctuation, and young garlic shoot price can affect garlic price. Finally, it is proposed to strengthen the infrastructure construction of garlic Big Data, increase the technological innovation and application of garlic Big Data technology, and promote the safety and security ability of the whole industry to promote the development of garlic industry.

In order to solve the hidden regional relationship among garlic prices, this paper carries out spatial quantitative analysis of garlic price data based on ArcGIS technology. The specific analysis process is to collect prices of garlic market from 2015 to 2017 in different regions of Shandong Province, using the Moran's Index to obtain monthly Moran indicators are positive, so as to analyze the overall positive relationship between garlic prices; then using the geostatistical analysis tool in ArcGIS to draw a spatial distribution Grid diagram, it was found that the price of garlic has a significant geographical agglomeration phenomenon and showed a multi-center distribution trend. The results showed that the agglomeration centers are Jining, Dongying, Qingdao, and Yantai. At the end of the article, according to the research results, constructive suggestions were made for the regulation of garlic price. Using Moran's Index and geostatistical analysis tools to analyze the data of garlic price, which made up for the lack of position correlation in the traditional analysis methods and more intuitively and effectively reflected the trend of garlic price from low to high from west to east in Shandong Province and showed a pattern of circular distribution.

In view of the frequent fluctuation of garlic price under the market economy and the current situation of garlic price, the fluctuation of garlic price in the circulation link of garlic industry chain is analyzed, and the application mode of multidisciplinary in the agricultural industry is discussed. On the basis of the big data platform of garlic industry chain, this paper constructs a Garch model to analyze the fluctuation law of garlic price in the circulation link and provides the garlic industry service from the angle of price fluctuation combined with the economic analysis. The research shows that the average price rate of the price of garlic shows “agglomeration” and cyclical phenomenon, which has the characteristics of fragility, left and a non-normal distribution and the fitting value of the GARCH model is very close to the true value. Finally, it looks into the industrial service form from the perspective of garlic price fluctuation.

Background Cow manure is not only an agricultural waste, but also an organic fertilizer resource. The application of organic fertilizer is a feasible practice to mitigate the soil degradation caused by overuse of chemical fertilizers, which can affect the bacterial diversity and community composition in soils. However, to our knowledge, the information about the soil bacterial diversity and composition in tea plantation applied with cow manure fertilization was limited. In this study, we performed one field trial to research the response of the soil bacterial community to cow manure fertilization compared with urea fertilization using the high-throughput sequencing technique of 16S rRNA genes, and analyzed the relationship between the soil bacterial community and soil characteristics during different tea-picking seasons using the Spearman’s rank correlation analysis. Results The results showed that the soil bacterial communities were dominated by Proteobacteria, Bacteroidetes, Acidobacteria and Actinobacteria across all tea-picking seasons. Therein, there were significant differences of bacterial communities in soils with cow manure fertilization (CMF) and urea fertilization (UF) in three seasons: the relative abundance of Bacteroidetes in CMF was significantly higher than that in UF and CK in spring, and the relative abundance of Proteobacteria and Bacteroidetes in CMF was significantly higher than that in UF and CK in autumn. So, the distribution of the dominant phyla was mainly affected by cow manure fertilization. The diversity of bacterial communities in soils with cow manure fertilization was higher than that in soils with urea fertilization, and was the highest in summer. Moreover, soil pH, OM and AK were important environmental properties affecting the soil bacterial community structure in tea plantation. Conclusions Although different fertilizers and seasons affect the diversity and structure of soil microorganisms, the application of cow manure can not only improve the diversity of soil bacteria, but also effectively regulate the structure of soil bacterial community in tea plantation. So, cow manure fertilization is more suitable for tea plantation.

In order to effectively solve the problems which affect the stable and healthy development of garlic industry, such as the uncertainty of the planting scale and production data, the influence factors of price fluctuation is difficult to be accurately analyzed, the difficult to predict the trend of price change, the uncertainty of the market concentration, and the difficulty of the short-term price prediction etc., the big data platform of the garlic industry chain has been developed. Combined with a variety of data acquisition technology, the information collection of influencing factors for garlic industry chain is realized. Based on the construction of the big data technology platform, the real-time synchronous acquisition, efficient storage and analysis of the planting, market, storage, processing, export and logistics information in five provinces and seven counties are realized. The application of the big data platform for garlic industry chain has realized the accurate acquisition of garlic planting area, the price and trend of market circulation and the information of export information, analyzed the fluctuation regulation of garlic price, and also realized the short-term precision prediction of garlic price.

To explore the conducive to China’s agricultural science and technology park of input and output of the related strategy and promote agricultural supply side structural reform in China, we use cobb-douglas production function model, combined with stepwise regression and principal component regression method, the analysis of 2015–2017 China national agricultural science and technology park enterprise data. We summarized the relationship between the input and output by cobb-douglas production function. The investment of labor force and capital investment and the annual output value were positive correlation, but the elasticity coefficient of labor input three years to show the trend of increasing year by year. Elasticity coefficient of capital in three years presents a decreasing trend year by year. By stepwise regression and principal component regression method, you can see that is not the total amount of investment. The greater the output, the more technology innovation factors will become the future main factors influencing the development of the national agricultural science and technology park. Therefore, China should strengthen agricultural science and technology innovation, cultivate agricultural science and technology talents. Develop agricultural science and technology innovation projects, so as to promote China’s agricultural supply-side structural reform.

In response to the increasing food safety problems of the meat product in the industry chain of livestock and poultry, and the actual demand of enterprises and consumers, combining the development status of the enterprises, considering the safety factors of animal breeding and product processing, this paper designed a food safety traceability system, based on modern internet of things technologies such as RFID, QR code, sensor technology and wireless communication technology, of which the traceability information covers all links of the whole industry chain. Compared with other traceability systems, the system in this paper has improved greatly in terms of its breadth, depth, and accuracy, which is an effective way to solve the food safety problem. The system provides the customers, enterprises, and the government department with multi-channel information traceability service, which has the real significance of the reduction food safety risk and improvement of recall efficiency of defective products.

In response to various problems existing in the current duck product industry chain. For example, decentralized of the industry chain, lack of data exchange between each link, lack of unified information collection equipment, and so on. An intelligent information management platform for duck product chain was developed, based on the specific needs of each link of the duck and poultry industrial chain. The platform is mainly composed of the information collection equipment and the intelligent management systems. The information acquisition equipment comprehensively uses the current well-perceived and reliable transmission technology of the Internet of Things to achieve the seamless collection of information in each link of the duck product industry chain and the seamless convergence of information in each link. The intelligent management system utilizes big data analysis technology to realize internal automation and digital management. The long-term test of the system shows that the data in each link of the system seamlessly connects. The data collected by the system is accurate and reliable. Its operation is simple and convenient. The system is highly scalable and suitable for use in production.

Traffic accident hidden behind a lot of factors, although the rapid development of China’s transportation infrastructure, traffic management level is increasing, but the development of social economy and daily living travel traffic caused by the supply and demand contradiction is prominent. The traffic safety management situation is still grim, needs to be based on existing management, through the analysis of massive traffic the management of data mining, finding the underlying changes in the law, for the transportation departments to effectively carry out the administration of road traffic safety, more in-depth mining the potential causes of traffic accidents. In this paper, we first use the Baidu map API interface to transform the street information to the specific latitude and longitude. Then we divide the morning and evening peak and non peak hours, working days and non working days, and analyze the time characteristics of the accidents based on the MATLAB 3D data imaging principle. Secondly, the stability analysis is carried out after the data collection, and the occurrence trend and periodic law of the accident are obtained by using the Holt - Winters filter prediction and test and STL decomposition. Finally, in view of the above analysis, the reasonable countermeasures are given in order to reduce the incidence of traffic accidents and build a harmonious travel environment.