In order to improve the accuracy, objectivity and efficiency of data analysis, the CropWatch team has developed CropWatch GPT, which is designed to provide an automated analysis tool for each country's agricultural situation. Users simply go to the national agricultural monitoring interface and click on the “Generate Analysis” button, which will automate the task of analyzing the agricultural situation, climate, and crop growth in each country. Detailed information can be found at the following link: http://cloud.cropwatch.com.cn/web/report/graphlist?id=316.

CropWatch GPT is an API service based on a callable LLM (Large Language Model) designed for agricultural monitoring and data analysis. Built by the CropWatch team based on the Large Language Model (LLM), the system employs a “pre-training-prompting tuning” strategy to analyze data through contextual learning, command following, and thought chaining functions. CropWatch GPT has extensive background knowledge of the agricultural sector and offers a variety of analysis templates that allow you to customize the format and style of your analysis.

Figure 3.2  CropWatch GPT Automatically Generates Bulletin Analysis

If you are interested in contributing to the agricultural situation analysis of a specific country, you are warmly invited to join the CropWatch national analysis writing team. We look forward to collaborating with you on research and exchange.
If you are interested, please contact us via email: cropwatch@aircas.ac.cn