Sentence examples for rates of genetic progress from inspiring English sources

The identification of QTL and investigation of genetic and molecular mechanisms underlying those QTL may result in more efficient animal selection and increased rates of genetic progress.

Expected rates of genetic progress (Δ G) are combined with expected rates of inbreeding (Δ F) in a linear objective function (Φ = Δ G - λΔ F) which is maximised.

It is progressively being used to increase rate of genetic progress for production traits that are measured late in life (e.g. meat yield and quality), expensive to measure (e.g. RFI) and are sex linked (e.g. milk production and quality).

When selection was most intensive (highest ranking) the rate of genetic progress per annum was 1.51 to 1.73 as great as when it was least intensive (from top sixth or top third).

The benefits of marker assisted selection (MAS) are evaluated under realistic assumptions in schemes where the genetic contributions of the candidates to selection are optimised for maximising the rate of genetic progress while restricting the accumulation of inbreeding.

Family-based predictions of genetic values have been used successfully for selection in plants and animals for many decades; however, there is a limit on the annual rate of genetic progress that can be attained with family-based prediction.

Optimum breeding schemes for maximising the rate of genetic progress with a restriction on the rate of inbreeding (per year or per generation) are investigated for populations with overlapping generations undergoing mass selection.

These results show that a high rate of genetic progress in growth can be achieved with an acceptable increase of less than 1% F per generation, at least in the short term.

Traditional self-pollinating crop breeding programs have long cycle times, historically 6 to 10 yr (Kannenberg and Falk 1995), and this limits the rate of genetic progress for grain yield and other complex traits.

Genomic information from dense single nucleotide polymorphism (SNP) chips provides the opportunity to increase the rate of genetic progress in breeding programs, if a sufficient number of markers and animals with phenotypes (or pseudo-phenotypes such as estimated breeding values, EBV) are genotyped [ 1].

Both simulation and empirical studies have systematically shown higher prediction accuracy of GS relative to standard pedigree-based predictions and it is now clear that GS offers great opportunities to further increase the rate of genetic progress achieved in plant and animal breeding.