Abstract: 【Objective】 analyze cognition and application status of Generative Generative Artificial Intelligence (Generative AI), tools. 【Methods】 Based on a questionnaire survey of 208 researchers from the Xinjiang Academy of Agricultural Sciences, this study analyzed the cognition and application status of generative AI tools in agricultural research. 【Results】 Agricultural researchers' cognition of generative AI remains at a basic level, with information primarily obtained through non-systematic channels.In terms of application, generative AI is concentrated in information retrieval and literature organization in the early stages of research, but its penetration in value-creation stages of mid-to-late research is insufficient.Notably, it is rarely applied in fields directly related to Xinjiang's agricultural production practices, such as field management plan generation.Key obstacles to its adoption include AI hallucinations, inadequate professional knowledge bases, poor localization adaptation, and privacy/data security risks inherent in AI tools.Additionally, researchers face challenges in technical training and organizational support. 【Conclusion】 1.Accelerate localized deployment and development by creating region-specific agricultural large language models and establishing localized knowledge bases.2.Standardize AI applications in agricultural research by formulating application guidelines and establishing a data classification protection system.3.Strengthen research integrity and data security by establishing research integrity committees and increasing investments in data security technologies. These measures can promote the deep integration of generative AI into agricultural research in Xinjiang, facilitating the region's agricultural modernization.