What is the new model of order agriculture?

The "order agriculture" big data tool of JD.com is to know about it

1. Taking the opportunity of land transfer, we collect land data, crop data, and user data from the field. And through external procurement to obtain market data, thus establishing the four major data chains

2, the system from the above databases are automatically captured and compared and analyzed, to find the "order agriculture" supply and demand parties

3, in the next production process, the figure of big data is everywhere!

Case study

After analyzing the data, we found the order demand for green beetroot from Li Ji Pressure Vegetable, Fuling Pressure Vegetable Group and other enterprises.

Found a group of counties and cities in the country that can meet the conditions for growing green beetroot in terms of historical climate, soil pH value and other indicators. Among them, Gyunlian County in Yibin City, Sichuan Province, which is adjacent to Chongqing, has part of its land left idle from September of the year after the tobacco purchase to April of the following year, which is just right for growing green beetroot.

Polysoil.com found the Agricultural Bureau of Yunlian County to realize the order of planting green beetroot.

After a winter of storage, the beetroots buried in the soil become full and crisp, and are sent to processing companies to be sliced, air-dried and pickled before becoming a globally-acclaimed Chongqing delicacy - squash.

Chongqing squash with about 700,000 acres of planting area and large and small nearly a hundred processing enterprises, become the city's largest production value of one of the largest characteristics of agricultural products.

However, like most agricultural products, Chongqing squash also exists in a cycle: the abundance of the year to sell off, the following year farmers to reduce the planting area, resulting in the downstream collection of raw materials and not enough to raise the price, and then the next year we all swarmed to expand production, and lead to the sale of off ...... so the formation of a vicious circle.

The five paths of the rural revitalization strategy, industrial revitalization ranked first. The foundation of the industry is the planting industry. Breaking the agriculture, especially the planting industry in the prevalence of production and marketing disconnect problem, in the end, what tricks to use?

Chongqing, an Internet company called poly earth network, through big data means, for the implementation of "order agriculture" to explore a new road.

Squeeze beet enterprises for what to go abroad to buy beetroot

Municipal Agricultural Commission, deputy director of the Market Information Office of the Gao Baochun that, from the experience of developed countries, to crack the disconnect between production and marketing of the best way to process agricultural products to the farmers under the orders of the farmers to produce according to the single enterprise in accordance with the about the pricing of the purchase, the upstream and downstream to achieve a close and seamless docking.

But the reality is not so. Even if enterprises are willing to place orders, most farmers are unwilling or even afraid to take. Still take the mustard industry as an example, Fuling Zhenxi Town, vegetable head growers Liu Xianzu said, planting risks everywhere, once encountered a drought or pests, vegetable head to reduce production, can not meet the order, may also be compensated. And, in the year of harvest failure, foreign enterprises to Yu snapped up, the purchase price may be higher, sold to foreign enterprises, may be more cost-effective.

To ensure the yield and quality of crops, you need to use advanced planting techniques for large-scale planting, but the transfer of land, purchase of agricultural materials, remediation of land, where does the money come from? Liu Xianzu said he repeatedly applied to the bank and never got a loan.

Banks also have difficulties, Chongqing Rural Commercial Bank, a grass-roots creditors said the city's planting industry is generally small-scale, low loan amount, unit management costs are high. What's more, most of the agricultural loans are credit loans without collateral, and it's not easy for banks and farmers to establish a relationship of trust. Once the loan out, encounter crop failure, farmers can not repay, it is easy to form bad and doubtful debts.

It is understood that, due to the difficulty of realizing the order production, for a long time, the city has been a small-scale cultivation of green beetroot to a family. Farmers usually sell the beetroot to vegetable vendors, who in turn sell it to vegetable press enterprises. The middlemen make a difference in price, but the farmers have a meager income.

Fuling mustard industry, a business owner, due to the unstable supply of raw materials, mustard processing enterprises in Chongqing will often "no rice to cook", can only go to Sichuan, Jiangxi and Zhejiang and other places to buy high prices of beetroot. He revealed that such a situation, in the city and even most of the country's agricultural products in general.

So, this situation can be changed in the context of today's big data?

One "order agriculture" is how to realize

And poly earth network approach is: through big data means, the implementation of "order agriculture".

Like most Internet platforms engaged in the transfer of land and the trading of agricultural materials and products, Jutu has accumulated a huge amount of land information, user information and transaction data through years of operation. After automatically capturing and comparing and analyzing the data, this website has discovered many user needs. One of them is the demand for orders of green beetroot from enterprises such as Li Ji Squash and Fuling Squash Group.

Who can meet the demand? Also based on big data analysis, Jutu.com found a group of counties and cities across the country that could meet the conditions for growing beetroot in terms of historical climate, soil pH and other indicators.

Who is the most suitable for the areas where the conditions are met? Big data shows that the government of Yunlian County in Yibin, a provincial-level poverty-stricken county in Sichuan province adjacent to Chongqing, is making every effort to advocate the development of tobacco-based farming in the hope of increasing farmers' incomes.

Digging further into the big data, JD.com made an even more surprising discovery: the county's land is idle from September of the year after tobacco purchases to April of the following year, which is the best time to plant green beetroot. Jutu.com found the Gyunlian County Agricultural Bureau, and the two sides hit it off.

In fact, the precise matching of production and marketing is only the first step in the role of big data. In the next step of the production process, the figure of big data is everywhere. For example, based on crop growth data and market supply and demand data, JD.com has designed a crop growth model, a disease diagnosis model, and a price prediction model.

The crop growth model, that is, using the fit of the standard growth curve and the real growth curve, monitors the growth of crops; the disease diagnosis model, on the other hand, translates the facts of the disease into a specific probability of illness and combines them with the condition thresholds to accurately confirm the name of the disease and match the precise treatment plan. With the support of these two data models, the system will automatically warn technicians on their cell phones of poor crop growth or disease, thus prompting them to take countermeasures.

The market supply and demand model is used to predict price fluctuations of crops, with which Jutu.com can offer a suitable order price to buyers and sellers of "order agriculture", so that no one suffers.

Agricultural finance is a typical scenario for the application of big data. JTN first collects information and data on farmers' behavior, family background, personal background and crop growth cycle, market supply and demand, and then through quantitative analysis of the data, reduces it to a farmer's real balance sheet and expected balance sheet, forming a standard big data user profile. Through the latter, it is easy for financial institutions to recognize whether they can lend or not, and whether they dare to lend or not.

Nearly one million small farmers and nearly 2,000 enterprises "hand in hand"

Through big data to find buyers and sellers, summarize the transaction, and then through the means of big data to provide technology, finance, agricultural centralized purchasing and other full-process services to ensure that the orders are completed in a quality and quantity, Jutubu.com has done.

In 2013, the Chongqing Zhongxian young entrepreneur Tian Jinglong returned home from Shanghai to the rural areas of the land transfer, and then hung on 58 Tongcheng or Catch.com to find the next home, and soon had more than a million dollars in profit.

After getting a taste of the sweet spot, Tian Jinglong founded Jutu.com, trying to be like his peers by opening up data ports to absorb national city- and county-level franchisees, expanding the number of customers and the scale of transactions. But he soon found this traditional model industry "ceiling": even if you run across the country, but the market size of a few hundred million dollars.

During the process of redesigning the business model, Tian Jinglong discovered the market pain point of order agriculture. The market is not short of orders, but the upstream production organization has been a problem. Can Jutu.com go to the upstream organization, directly hosting the farmers' land, intensive management?

But they do not know the technology, how to go to the hosting land to organize production?2016, Jingdong Finance and Jutu network reached a strategic cooperation, the former through the big data to establish a financial risk control model approach, to Tian Jinglong brought revelations.

He found that big data can quantify and visualize every detail of production and business activities. The data can generate models that allow the planting industry to have and industry-like standardized processes, so that large-scale planting and trading has a technical basis.

Tian Jinglong began to rebuild the large database of Jutu.com. The source of data on similar sites is usually uploaded by users, making authenticity difficult to recognize. His solution was to get back into the land transfer business, taking the opportunity to personally collect land data, user data and crop data in the field. Since then, he has built up a market database by sourcing from professional organizations and other means.

A few years down the road, Jutu.com has formed a four-level big data chain of land data, user data, crop data, and market data, and has established a series of application models, such as the aforementioned crop growth model, disease diagnosis model, and price prediction model.

Earlier this year, Jutu.com's first order of agriculture based on big data allowed farmers in Gyunlian and businesses in Chongqing to realize a ****win. Dozens of large trucks took turns constantly traveling to and from Sichuan and Chongqing, and the squash enterprises received a high-quality supply of raw materials at a price more than 10% cheaper than that of vegetable vendors. Gyunlian county-wide income increased by nearly 40 million yuan, and the per capita income of growers increased by more than 6,000 yuan.

Similar business, poly earth network is currently being carried out in nine, involving wheat, rice, corn, soybeans, mustard, ginger, lemon, lobster and other nearly 20 agricultural varieties, as well as more than 10 provinces and municipalities in Guizhou, Sichuan, Anhui and other provinces. Nearly one million dispersed small farmers and nearly 2,000 enterprises, through big data, the successful realization of "hand in hand". The land hosted by the poly soil network amounted to more than 30,000 acres, the most in central China, the farthest in the northeast, more and more agriculture-related enterprises began to cooperate with the poly soil network.