Modelling the Impact of Climate Variables on Agriculture through the F-Transform

This paper investigates the bidirectional relationship between climatic variables and agricultural production in the United States, focusing on the reciprocal interactions among precipitation data, temperature data, and annual agricultural output (specifically corn, soybean, and wheat) in the most productive counties of Illinois. The aim is to assess the impact that weather conditions may have on agricultural productivity. The study is performed using quantile and expectile F-transform (and, more generally, Lp-norm-based fuzzy-valued F-transforms) in modeling time series. Graphical examples and pictures accompany the presentation.