Literature DB >> 33791859

Developing of a model to predict lying behavior of dairy cows on silvopastoral system during the winter season.

Karolini Tenffen de Sousa1,2, Matheus Deniz3,4, Matheus Fernando Moro4, Isabelle Cordova Gomes4, Marcos Martinez do Vale4, João Ricardo Dittrich3,4.   

Abstract

Lying behavior is an important indicator of the cows' welfare and health. In this study, we evaluate the effect of the physical environment on dairy cows' behaviors raised on a silvopastoral system through a predictive model. There was a difference (p<0.01) in soil surface temperature (SST) and black globe-humidity index (BGHI) between the shaded and sunny areas of the silvopastoral system. The BGHI was the variable most important to classify the cows' decision to seek shaded or sunny areas, while the soil surface temperature affected the choice for the area to perform the lying behaviors. In order to understand the influence of these parameters on cows' lying behavior, we developed another predictive model relating the SST and BGHI with cows lying at shaded and sunny areas. There was significance (p<0.01) for all model parameters. The odds of cows lying increased by approximately 2% with each degree of SST. In contrast, the probability of the cows lying in the shaded areas was 35% less than in sunny areas. The model developed in this study was efficient in identifying changes in the behavior of dairy cows in relation to physical environment. The BGHI influenced the areas used by cows to performing their standing behavior, while the areas used for lying behavior were influenced by the SST.

Entities:  

Keywords:  Animal welfare; Bioclimatology; Data mining; Decision tree; Probability

Year:  2021        PMID: 33791859     DOI: 10.1007/s00484-021-02121-0

Source DB:  PubMed          Journal:  Int J Biometeorol        ISSN: 0020-7128            Impact factor:   3.787


  1 in total

1.  Broiler behavior differs from males to females when under different light wavelengths.

Authors:  Sandro José Paixão; Angélica Signor Mendes; Marco Antonio Possenti; Rosana Reffatti Sikorski; Marcos Martinez do Vale; Cléverson de Souza; Bruno Evangelista Guimarães; Daniella Jorge de Moura; Irenilza de Alencar Nääs; Isadora Bischoff Nunes
Journal:  Trop Anim Health Prod       Date:  2022-05-17       Impact factor: 1.559

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.