Initial breeding value prediction on Manchego sheep by using rule-based systems

Abstract

In this paper we present an application of rule-based expert systems to a farming problem. Concretely the prediction of the breeding value in Manchego ewes is studied for the early stage of their life in which the standard (BLUP) methodology cannot be applied. In this case the pedigree index (arithmetical mean between parents’ breeding value) is used to make the estimation. An alternative to this method is presented here, which is based on the use of two different types of rule-based systems: regression rules and linguistic fuzzy rules. The approach proposed is data-driven in the sense that the rules are learnt from data. The results obtained show that the learnt systems are more accurate than the pedigree index, especially for the regression rules case. On the other hand, the linguistic fuzzy rules systems are more easier to understand for human experts, and this is a point to be take into account because of the nature of the problem we are dealing with.