Using classification algorithms for predicting durum wheat yield in the province of Buenos Aires.

Highlights: [•] Several machine learning algorithms for the classification of yield components were compared. [•] Rules to infer yields at harvest of durum wheat with data from Buenos Aires Province were found it. [•] A priori method obtains the best performance for all locations. [•] More relevant traits for yield levels prediction were identified. [•] Thousand grain weight is the most relevant trait for predicting durum wheat yield. [Copyright &y& Elsevier]