Traditionally stability is analyzed using different models such as Eberhart-Russell etc.. Recently GGE Biplot has been used for this purpose. However, in the era of data mining and artificial intelligence, can we use data mining techniques for assessing stability for yield, variety selection and environment discrimination? I think it is quite possible. What are the possibilities? What are the pros and cons?
very good question but in your situation you can't refer to data mining because data mining is a term that refer for extracting hidden patterns from the data. For your situation it's better to use the term "Machine Learning (ML)" that refers to the ability of the machine to mimic human. Using ML you can assess the stability of the genotypes using different methods such as: data dependency, data correlation, data consistency,..
I suggest you to have a look on the Rough Set Theory proposed by professor Pawlak that is used as both feature selection and data dependency measure.
Hope this helps!
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