Linear modeling analysis using for determining the factors affecting 305-day milk yield

Genc S., Mendes M.

ARQUIVO BRASILEIRO DE MEDICINA VETERINARIA E ZOOTECNIA, vol.73, no.4, pp.949-954, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 73 Issue: 4
  • Publication Date: 2021
  • Doi Number: 10.1590/1678-4162-12346
  • Journal Name: ARQUIVO BRASILEIRO DE MEDICINA VETERINARIA E ZOOTECNIA
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, CAB Abstracts, Food Science & Technology Abstracts, Veterinary Science Database, Directory of Open Access Journals
  • Page Numbers: pp.949-954
  • Keywords: 305-day milk yield, automatic linear modeling, prediction, dairy cows, GENETIC-PARAMETERS, BIRTH-WEIGHT, CLASSIFICATION
  • Çanakkale Onsekiz Mart University Affiliated: Yes

Abstract

The purpose of this study was to model the factors affecting the 305-day milk yield of dairy cows by using Automatic Linear Modeling Technique (ALM). The data set of this study consisted of eight different cow breeds grown in eight province of Turkey. Results of ALM showed that the accuracy of the model was 64.2 % means that 64.2% of the variation in the 305-day milk yield could be explained by the constructed model. Created model was consisted of four factors namely the Breed, Lactation Length, Parity, and Province. Therefore, those selected factors were more efficient than the others in predicting the 305-day milk yield