Deep in the mountains along the border between Hubei and Chongqing, an agricultural cooperative named 'Youyoucao Eyu' is attempting to answer a cutting-edge question in the most down-to-earth way: Can AI really help farmers earn more money?
This cooperative, rooted in the border region of Hubei and Chongqing, has spent the past decade focusing on the cultivation and primary processing of alpine wild vegetables and medicinal herbs. But this spring, they did something that left neighboring farmers feeling 'a bit mystified'—they installed a machine vision-based AI monitoring system in a seedling greenhouse at an altitude of 1,200 meters.
'Before, raising seedlings relied entirely on experienced farmers reading the sky, the soil, and the leaves. Now, with a camera scan, the system can tell you which seedling bed is short of water and which leaf looks off,' said Lao Zhou, the cooperative's head, pointing to a palm-sized screen on the wall of the greenhouse. On the screen, temperature, humidity, and light intensity were updating in real time, along with a set of 'health indices' he couldn't fully decipher.
The system, provided by a Chongqing-based AI startup, has its core algorithm trained on thousands of images of local plant diseases. It can not only identify common gray mold and downy mildew but also, based on changes in leaf color, issue early warnings of potential nutrient deficiencies three days in advance. Lao Zhou did the math: last spring, a late cold snap caused losses of nearly 20% of seedlings using traditional methods; this year, with the AI early warning system, they covered the seedlings with thermal film in advance, reducing losses to below 5%.
But this is only the first step in Youyoucao Eyu's 'AI transformation.' What has drawn even more attention is their attempt to apply AI to the supply chain—by analyzing historical order data, weather forecasts, and search trends on e-commerce platforms to predict what to plant and how much in the next season. In the past, the cooperative often found itself in the dilemma of 'planting too much and failing to sell, or planting too little and failing to meet demand.' Now, the planting suggestions generated by AI have already increased order matching rates by 30% this spring.
'Many people think AI is high-tech and far removed from rural life. But Youyoucao Eyu shows us that as long as you pinpoint the pain points, AI can become just another tool like a hoe,' said an agricultural technology researcher involved in the project's implementation. He specifically noted that the biggest challenge in promoting the system was not the technology itself, but gaining the trust of the farmers. 'They didn't believe a machine could be more accurate than their own eyes—until one time, the system identified a batch of fritillaria that was about to be infected with root rot. When they dug them up, the roots were indeed starting to turn black. That's when they became convinced.'
The story of Youyoucao Eyu is a microcosm of the current wave of agricultural intelligence in China. According to data from the Ministry of Agriculture and Rural Affairs, over 200 counties and districts across the country have introduced AI-assisted decision-making in planting and breeding. However, cases that achieve a full-chain closed loop 'from prediction to sales' at the cooperative level remain rare. What makes Youyoucao Eyu's experiment noteworthy is that it didn't opt for a high-concept 'unmanned farm' approach, but instead focused on solving the most concrete, 'earthy' problems—when to water, whether to apply pesticides, and what to plant this year to ensure a market.
Of course, there are still concerns along this path. Lao Zhou admitted that the system's maintenance costs are not low, with server and network fees alone exceeding 20,000 yuan a year. For a high-altitude agricultural cooperative with thin profit margins, this money has to be earned by selling the yield from an extra three acres of medicinal herbs. Furthermore, the accuracy of the AI model is highly dependent on local data accumulation. In the event of extreme weather or new crop diseases, the system could 'fail.'
Nevertheless, Youyoucao Eyu has taken its first step. This autumn, they plan to roll out the AI system to 50 partner farming households and attempt to replace traditional farming logs with AI-generated 'planting calendars.' Lao Zhou said, 'The machine may not know how to farm, but at least it can tell me when I need to go check the fields.'
A bottom-up experiment in agricultural intelligence is quietly taking root and growing in the mountains along the Hubei-Chongqing border.