Read this article in:

Predicting tail biting risk using classification and regression tree analysis

Tail biting in pigs has been an identified behavioural, welfare and economic problem for decades, and requires appropriate but sometimes difficult on-farm interventions.

Wednesday 27 December 2017 (9 months 25 days ago)

The aim of the paper is to introduce the Classification and Regression Tree (CRT) methodologies to develop a tool for prevention of acute tail biting lesions in pigs on-farm. A sample of 60 commercial farms rearing heavy pigs were involved; an on-farm visit and an interview with the farmer collected data on general management, herd health, disease prevention, climate control, feeding and production traits.

Results suggest a value for the CRT analysis in managing the risk factors behind tail biting on a farm-specific level, showing 86.7% sensitivity for the Classification Tree and a correlation of 0.7 between observed and predicted prevalence of tail biting obtained with the Regression Tree. CRT analysis showed five main variables (stocking density, ammonia levels, number of pigs per stockman, type of floor and timeliness in feed supply) as critical predictors of acute tail biting lesions, which demonstrate different importance in different farms subgroups. The model might have reliable and practical applications for the support and implementation of tail biting prevention interventions, especially in case of subgroups of pigs with higher risk, helping farmers and veterinarians to assess the risk in their own farm and to manage their predisposing variables in order to reduce acute tail biting lesions.

Scollo A, Gottardo F, Contiero B, Edwards SA. A cross-sectional study for predicting tail biting risk in pig farms using classification and regression tree analysis; Prev Vet Med. 2017 Oct 1;146:114-120. doi: 10.1016/j.prevetmed.2017.08.001. Epub 2017 Aug 2. PMID: 28992915

Article Comments

This area is not intended to be a place to consult authors about their articles, but rather a place for open discussion among users.
Leave a new Comment

Access restricted to 333 users. In order to post a comment you must be logged in.

Not a registered user of 333?sign upand access swine prices, the search engine, ...
It is fast and free
Are you registered in 333?LOGINIf you've forgotten your password we'll send it to you here