- Home
- Knowledge library
- FEC and CT support
FEC and CT support
Summary
About this project
The Problem:
CT is a successful tool for identifying outstanding animals within a breed, but it also has an important wider impact on breeding improvement. The use of CT has enhanced our understanding of the relationship between on-farm ultrasonic measurements and lean and fat in the carcase. This has helped superior animals to be identified more quickly and efficiently, using on-farm ultrasound. It also strengthens the breeding evaluations produced across a breed.
Faecal Egg Counts (FEC) can identify animals that need worming, but can also be used to detect variation in immunity against worms between individual sheep. This information can then be used to produce EBVs that indicate animals that have improved resistance to worms, forming a selection criterion in a breeding programme.
Project Aims:
- To promote the use of Computed Tomography (CT) scanning of ram lambs
- To increase the use of faecal egg count sampling for production of EBVs
Approach:
CT scanning specific animals provides a highly accurate assessment of total fat, muscle and bone yield within the carcase and provides an assessment of gigot muscularity. This enables leading breeders to pinpoint truly unique individuals with superior breeding for specific traits. All of the CT information collected is used to enhance the EBVs and Indexes of animals that are analysed within the national terminal sire breeding evaluations. Breeds currently using CT scanning include Charollais, Suffolk, Texel, Meatlinc, Hampshire Down and Beltex.
Individual FEC are collected from performance recorded animals, and the information can be incorporated into a EBV and used to select animals that shed fewer eggs. Breeds currently collecting FECs for EBVs include Charollais, Suffolk, Texel, Lleyn, Blackface, Blue Face Leicester and Wiltshire Horn.
Deliverables :
Breed societies can report information from animals with CT or FEC results.
The extra information from these techniques help to make the analyses more accurate.