It is difficult to find out if agricultural big data lacks resources and is not shared.

In the current pattern of global scientific and technological and economic development, data has become a kind of productivity and competitiveness. At present, big data has rapidly developed into a new generation of information technology and service industry, and has become a national basic strategic resource. Agriculture and countryside is one of the important fields of big data's production and application. Big data in agriculture and countryside has become a new resource element of modern agriculture.

In recent years, agricultural big data is in hot demand. However, compared with other industries, the collection, release and application of big data in agricultural and rural areas are still faced with a variety of dilemmas to be resolved.

China's agricultural big data has not yet been formed.

Big data, which involves a wide range of agriculture, is particularly large and complex, and can be said to be the largest big data.

According to the characteristics of agriculture and the segmentation of the whole agricultural industry chain, Agricultural big data can be divided into agricultural environment and resources big data, agricultural production big data, agricultural market big data and agricultural management big data. From the perspective of industry, big data of agriculture can be divided into planting, agricultural materials and aquaculture and other different industries, which can also be subdivided into different varieties and products.

Li Daoliang, a professor at the School of Information and Electrical Engineering of China Agricultural University, pointed out at the China big data Industry Summit in May this year. Agricultural big data mainly comes from four aspects: Internet of things, bioinformation data, resources and environmental data, and agricultural statistics. From the perspective of application, Agricultural big data is mainly in five aspects: the first is basic research, the second is agricultural intelligent production, the third is agricultural product market forecast and logistics, the fourth is agricultural product quality and safety, and the fifth is agricultural resources integration, sharing and service platform.

Li Daoliang told the China Science Daily that at present, there are two broad categories of big data in China, one is micro, mainly from enterprises, and the other is macro, from government departments.

With big data's strategic resource status becoming more and more prominent, many agricultural enterprises have laid out deep ploughing big data, and even transformed from this. The president of Monsanto China revealed in the first half of this year that Monsanto's strategic direction in recent years is the application of data science in agriculture. In 2014, Dabinong Group put forward the strategy of "Wisdom Dabinong" and launched "three networks and one link". It is understood that it has distributed tens of thousands of salespeople across the country to record pig farm production and collect customer information in order to constantly update data.

But Li Daoliang also said that at present, China's agricultural big data "has not yet been formed", either from the government level or from the enterprise level.

"this is the biggest problem at the moment." Li Daoliang told reporters that this is a situation that has been formed for a long time and is difficult to change in a short time. This has something to do with the fact that we did not attach importance to accumulation in the past, as well as our scientific research mechanism and the working system of government departments.

In 2013, Zhang Xin, then director of the Department of Market and Economic Information of the Ministry of Agriculture, wrote that there is a big gap between China's data collection, release, application and decision-making needs, and that data collection and release are still in the initial stage. there is an urgent need for reform at the institutional level.

The root cause lies in the lack of a complete data system

"at present, domestic agricultural enterprises are consciously involved in big data, but there are only a handful of enterprises that can do the whole industrial chain." Li Xia, manager of animal husbandry industry group of Shandong Zhuochuang Capital Inquiry Group, said in an interview with China Science Daily.

She said that taking the animal husbandry industry group as an example, being big data of the whole industry chain means starting with the supply and demand of feed raw materials, to breeding and circulation, and then to downstream slaughtering and processing links, so as to realize the citation and corroboration of data. "most of the big data done by many enterprises are areas that they are familiar with and good at." Li Xia told reporters.

In Li Daoliang's view, at present, the most "hot" thing to do big data is in the enterprise, to create a big data platform, which can not only provide a decision-making basis for enterprise production and operation, but also help to grasp the right to speak of data. Only large enterprises in the industry can really form and master big data.

At the China big data Industry Summit Forum, Li Daoliang summarized the problems faced by big data: the lack of agricultural big data, the lack of long-term accumulation of big data model, the lack of integration with industry by big data, and the lack of necessary norms by big data.

Li Daoliang told China Science Daily that due to block management and other reasons, data was not shared among departments, resulting in a lack of agricultural big data. "now, from the government level, in fact, we are trying to break this situation and achieve resource sharing. Only with resource sharing can we form big data and reanalyze big data."

Speaking of the accumulation of data, Li Xia also said, "the workload of data collection is very huge, and it needs to be constantly screened, screened and updated, and the data accumulated over a long period of time is valuable."

An industry insider, who spoke on condition of anonymity, told China Science Daily that at present, the demand and use of big data in China's market industry, especially in agriculture, is far lower than that of foreign countries. "in the final analysis, a solid, highly accurate and complete data system is needed."

The talent gap needs to be filled urgently.

About half a month ago, the Ministry of Agriculture issued the second batch of pilot programs for agricultural information analysis and early warning of the whole industry chain, which aims to set up an agricultural information analysis and early warning team of the whole industry chain through pilot projects. to form a work pattern with rapid analysis response, comprehensive information content, and accurate prediction and judgment.

The reporter learned that at present, the country's personnel in agricultural information collection and analysis "have a large gap" and are "not professional."

Ming Junren, of the School of Management of Wuhan Engineering University, pointed out that at present, there are mainly the following problems in the contingent of agricultural information talents: a serious shortage of professional agricultural information talents, an imbalance in the structure of agricultural information talents, a non-standard work flow of agricultural information activities, and an imperfect salary management system for agricultural information talents.

On the other hand, Li Xia uses "fault" to describe the current situation of talents in related fields. "there are leading experts and scholars in the industry and national information warning analysts," she explained, "but there is no further down."

According to Li Xia, who has been in the front line of agricultural information collection and analysis for many years, information collection and analysis should be "approachable" and really understand relevant industries and industries through on-the-spot visits. "I believe that in terms of methods, information collection and analysts must be familiar with it, but what is more important to do this work is the understanding of the industry and the resources accumulated in the field." Li Xia said.

In addition, Li Xia believes that there is also a need to form a good organizational structure and collection process, "to put it simply, how to collect, when to update, and how to inspect and supervise, which all require a series of matching."

Ming Junren suggested that the training of agricultural information talents should be brought into the discipline training system of higher education in our country, and the multi-training system of agricultural information talents should be constructed.

Song Changqing, executive deputy director of the Agricultural big data Research Center of Shandong Agricultural University, once pointed out in an article that it is necessary to formulate a training plan for agricultural big data technology and application personnel according to the development of agricultural big data and the needs of modern agricultural applications. to establish a collaborative innovation team with the integration of multi-disciplines.