How to Integrate Agricultural Big Data Thinking into Animal Husbandry

Recently, the second Global Internet Finance Conference, hosted by the Internet Finance Thousand-Person Forum, was held in Beijing. This conference took "Internet + Finance + Industry" as its theme and proposed that the next outlet for the industrial internet is agriculture. At the sub-forum on big data driving finance, Wen Fujiang, president of Shandong Agricultural University, delivered a keynote speech titled "The Application of Agricultural Big Data in Modern Agriculture."

At the meeting, Wen Fujiang shared with attendees their cases in the use of big data. He introduced: the Agricultural Big Data Center established by Shandong Agricultural University in May 2013 uses big data thinking, methods, and so on to solve related agriculture-related problems. They independently developed a digital precision dairy cattle breeding system and related equipment. This system can collect relevant data in real time during the dairy cattle breeding process and store it, analyze historical data to build models, and through monitoring of these data and model analysis, achieve the goal of improving the technical management level of dairy cattle breeding.

Through this system, the following points can be achieved: First, through timely recording of milk yield, activity level, and body weight, the system analyzes and provides the individual nutritional requirements of each dairy cow, and performs quantitative supplemental feeding for each cow in the milking parlor, achieving precise nutritional management of dairy cows; Second, by recording the timely activity level of dairy cows and comparing it with an estrus diagnosis model established from historical data, cows in estrus are identified. The detection rate of this system is >90%, and the false detection rate is <3%, more than 1 times higher than the detection rate of manual estrus diagnosis; Third, through real-time data monitoring and analysis of milk yield, milk electrical conductivity, body weight, activity level, and so on, suspected sick cows are promptly identified to assist disease diagnosis. Fourth, a sorting gate is set at the exit of the milking parlor, automatically identifying the cow number, and through software settings for sorting parameters to control the opening and closing of the sorting gate, cows in estrus, suspected sick cows, and so on are separated individually from the herd, achieving automatic sorting. Fifth, through analysis of the temperature data of the monitored barn, automatic control of fans and spray equipment is achieved, realizing automatic cooling control in the barn, alleviating heat stress of dairy cows in summer, and letting the dairy cows live more comfortably.

Wen Fujiang said that this system was independently developed by Shandong Agricultural University. The equipment used was previously imported from Israel, and now it has also been successfully developed. Using this system, one person can manage a dairy farm of several thousand cows.