Algorithm for generating matrices of estimated effects for breeding evaluation of small cattle using a mixed biometric model

Abstract

The use of a mixed biometric model for breeding evaluation of small cattle has been discussed in the article. This model of breeding evaluation involves a large number of matrix operations. At the same time, the volumes of the formed matrices are directly proportional to the number of animals in the evaluated sample as well as to the number of their off spring. An algorithm for generating matrices of estimated effects that have a large dimension has been presented in the paper. This task is the most time-consuming when using a mixed biometric model. Currently, there are the large number of mathematical packages that provide ample opportunities for performing calculations. A special place in this series is occupied by the integrated mathematical package MATLAB has been designed specifically for performing matrix operations. The authors rely on the use of this package in their work. At the same time the algorithm presented in this paper has the property of universality and can be applied by users in any other software product. Since the matrices of the estimated effects consist of zeros and ones we propose the two-step procedure for forming these matrices. At the first stage, a zero matrix of the required dimension is created. At the second stage, in accordance with the data on the number of evaluated animals, the number of herds for which off spring are distributed, the number and affiliation of evaluated animals to genetic groups, the elements of the matrix are determined, in which zeros are replaced by ones. The advantage of the proposed algorithm is its versatility, and the representation of the algorithm in the form of a block diagram will allow you to design it as a separate proceduresubroutine.