AI is simply about finding correlations in large data sets. Computers don't understand anything, they just shuffle symbols. So training an LLM on agricultural research will likely uncover patterns that would not be obvious to people and these patterns could point to new techniques and processes for increasing yields like scheduled flooding (as explained in the article). LLMs don't understand code but they consistently can complete code fragments which end up being correct more often than not. A model for yield optimization doesn't have to understand farming to suggest techniques and processes for increasing yields just like LLMs do for code fragments.