Skip to main content
ARS Home » Research » Publications at this Location » Publication #199296
Title: ESTIMATES OF GENETIC PARAMETERS USING RANDOM REGRESSION MODELS FOR GASTROINTESTINAL HELMINTHOID DATA IN ANGUS CATTLE

Author
item SILVA, M - EMBRAPA
item Van Tassell, Curtis - Curt
item Sonstegard, Tad
item COBUCI, J - UNIV OF RIO GRANDE DO SUL
item Gasbarre, Louis

Submitted to: World Congress of Genetics Applied in Livestock Production
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/26/2006
Publication Date: 10/10/2006
Citation: Silva, M.V., Van Tassell, C.P., Sonstegard, T.S., Cobuci, J.A., Gasbarre, L.C. 2006. Estimates of genetic parameters using random regression models for gastrointestinal helminthoid data in angus cattle. World Congress of Genetics Applied in Livestock Production. 8:15-34.

Interpretive Summary: Accurate genetic evaluation of livestock is based on appropriate modeling of phenotypic measurements. Sometimes these phenotypes are measured several times over the life of the animal, so called longitudinal data. Fecal egg count (FEC), a type of longitudinal data, is commonly used to measure resistance to nematodes in ruminants. An infection curve can be calculated by mathematical functions for each animal using weekly FEC measurements. Consequently, the objectives of the present study were to determine the efficiency of random regression models in analyzing FEC data and determining FEC heritability. Results indicated FEC infection curves to be a moderately heritable characteristic.

Technical Abstract: Genetic evaluation of livestock is based on appropriate modeling of phenotypic measurements. In ruminants, fecal egg count (FEC) is commonly used to measure resistance to nematodes. A series of repeated FEC measurements may provide information about the population dynamics. A total of 6,378 FEC measures were determined for 409 animals between 1992 and 2003 from BARC Wye Angus herd. Original data were transformed using Box-Cox transformation to approach normality. The database was analyzed using Random Regression Models (RRM), by the REML method. RRM may be used as a new tool for genetic and non-genetic studies of FEC. Within the different orders of Legendre polynomials used, those with more parameters (order 4) adjusted FEC data best. Results indicated FEC to be a moderately heritable characteristic.