A study of methods for cultivating innovative talent relying on multi-disciplinary integration in Grassland science: Taking "Grassland Science + Information Technology Science" as an example

China faces comprehensive and complex practical problems in developing grassland agriculture and keeping up with global trends in informatization and intelligence. This paper explores a multi-disciplinary approach to training innovative grassland science talent proficient in utilizing big data, artificial intelligence, and other information technology sciences, aiming to cultivate professional and technical talents in the field of grassland agriculture to meet the developmental needs of China. Using combined survey data from 187 students at the College of Pastoral Agriculture Science and Technology, Lanzhou University, secondary data about the college’s graduates between 2014 and 2019, and statistics on student recruitment by agricultural and animal husbandry enterprises among China’s top 500 companies in recent years, we identified several problems in our current Chinese talent training methods, including outdated training programs and insufficient consideration of industry development needs. We thus discuss the necessity of exploring a multi-disciplinary talent training program for grassland science, and suggest a novel grassland agricultural talent training process. We refer to this innovative talent training program as “Grassland Science +”, and discuss aspects of implementation of this innovative grassland science talent training program in detail, including teaching staff, curriculum system, innovative practice platform and assessment, and evaluation standards.