Catalogo Articoli (Spogli Riviste)

OPAC HELP

Titolo:
SELECTION OF FARM-ANIMALS FOR NONLINEAR TRAITS AND PROFIT
Autore:
MEUWISSEN THE; GODDARD ME;
Indirizzi:
UNIV NEW ENGLAND,ANIM GENET & BREEDING UNIT ARMIDALE NSW AUSTRALIA
Titolo Testata:
Animal Science
, volume: 65, anno: 1997,
parte:, 1
pagine: 1 - 8
SICI:
1357-7298(1997)65:<1:SOFFNT>2.0.ZU;2-N
Fonte:
ISI
Lingua:
ENG
Soggetto:
NONLINEAR PROFIT; INDEXES;
Keywords:
FARM ANIMALS; NONLINEAR TRAITS; PROFITS; SELECTION;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Science Citation Index Expanded
Science Citation Index Expanded
Citazioni:
12
Recensione:
Indirizzi per estratti:
Citazione:
T.H.E. Meuwissen e M.E. Goddard, "SELECTION OF FARM-ANIMALS FOR NONLINEAR TRAITS AND PROFIT", Animal Science, 65, 1997, pp. 1-8

Abstract

According to animal breeding theory, profit after, say, 10 generations of selection is maximized when the usually non-linear profit function is approximated by a linear breeding goal where the linearization isat the population mean in generation 10 and the linear breeding goal is subsequently predicted by a linear index for which the animals are selected. The prediction of the population mean at generation 10 requires linear relationships among the traits that constitute the non-linear profit, because otherwise this prediction becomes very complicated. A non-linear index is proposed that simply estimates the non-linear goal H = f(u) by (H) over cap = f((u) over cap), where u = vector of genetic values for the traits and (u) over cap is its (BLUP) estimate. This non-linear index does not require predictions of (future) population means and does not require linearly related traits. To test these indices a simple meat production example was constructed where the non-linearity between the traits was clue to the competition between weight and probability of survival for the same resources from food intake. In the model selection for weight and, in particular, for weight overcosts (mainly food) led to reduced profits due to large reductions ofsurvival rates. Although, the example was oversimplified, this shouldprovide a warning for the use of oversimplified breeding goals, e.g. fitness traits may reduce by more than expected from base population genetic parameters. When probability of survival and weight were measured, a non-linear index of these non-linear traits gave the greatest generic gains. Failure to update genetic parameters each generation severely reduced genetic gain and, if linear indices were used, it was also important to update the economic weights. When probability of survival was measured, profit could be calculated on each animal and included as a trait in the calculation of estimated breeding value. This yielded high genetic gain and did not require updating of genetic parameters or economic weights.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 27/09/20 alle ore 22:49:34