https://www.frontiersin.org/articles/10.3389/fpls.2023.11283...
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That's a simple application of machine learning algorithms you might find in scikit-learn. Here is a special issue of another alleged "predatory journal" that is full of papers on the subject
https://www.mdpi.com/journal/agronomy/special_issues/E18K759...
The OP did not suggest machine learning in generally, they suggested LLMs specifically, which time and time again have been shown to be incapable of this task as a matter of fundamental design. Worse, because LLMs can't understand the their training data, the output of an LLM must be verified, which in situations like this would probably take more time than simply conducting novel research in the form of random experimentation.
Also, you really need to read your citations. The first one found that machine learning was unsuited for the task of agricultural prediction...
There are computer programs that do the kind of thing you're thinking about, for example, for protein structure analysis. They're incredibly complicated and generally require a lot of processing power.