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Dialogue on Intelligent Maize Breeding

On the evening of December 16, an academic gathering themed “Smart agriculture – intelligent breeding” was held at HZAU. Prof. Li Lin from the College of Plant Science & Technology shared with attendees new methods of intelligent breeding in maize and the application of biological big data in intelligent breeding.
“Smart agriculture has roughly experienced four stages of development: IT application, digitization, precision, and intelligence, each with its own emphasis but integrated function. The four coexist, with intelligence leading the way,” Prof. Li said. Then, he elaborated on them from the perspectives of disciplinary theories and technical application, and production objects respectively. Subsequently, he presented the emerging smart agriculture technology – intelligent breeding with biological big data. He stressed that classical genetics research has explored the genetic mechanisms of a multitude of agronomic traits, cloned a large number of important functional genes and analyzed numerous molecular networks, laying the foundation for molecular breeding and targeted improvement of crops. When talking about the key genes affecting maize yield, Prof. Li noted that different from rice and wheat, the green revolution driven by semi-dwarfing genes did not take place in maize. Therefore, the targeted improvement of maize plant type remains a big challenge given a variety of factors.
The development of biological big data provides new ideas for maize improvement. Li Lin’s team has conducted research on the mechanisms of plant type inheritance and key genes, developed artificial intelligence algorithms based on holographic functional mapping to systematically analyze the molecular mechanisms of maize plant type, yield, and flowering stage. Furthermore, the team built a prediction model for plant height, yield and flowering stage based on the intelligent prediction of big data. Prof. Li mentioned that the coding method could improve the prediction efficiency, and the precision design breeding approach developed by his team was better than the whole genomic selection breeding commonly used abroad.
“As the biological big data is widely applied, can Prof. Li give some advice for us students conducting microbiological research?” Feng Xin, a student from the College of Life Sciences and Technology asked. Then Prof. Li gave suggestions from the perspective of biological big data technology.
In the end, Prof. Li expressed that with the more frequent interdisciplinary integration driven by the rapid development of IT technology, the integration of crop science and informatics would spur the development of intelligent breeding. He also encouraged students to be fearless and persistent regardless of difficulties in their research, and that they need to learn interdisciplinary expertise to follow the trend of the time. By doing so, they can see their own research as part of the national technological development and make contributions to China’s socialist modernization.
“With numerous challenges to overcome, conducting academic research is not an easy task. However, when our own research results are published to help facilitate studies of other researchers, such a sense of achievement is incomparable,” Wu Qian, a student from the College of Life Science and Technology shared her opinion.

Translated by: He Fan
Proofread by: Li Xin
Supervised by: Xie Lujie