Sensitivity to dietary lysine: energy content in pigs divergently selected for components of efficient lean growth rate

Abstract

The sensitivity to dietary lysine: energy content of pigs from lines divergently selected over seven generations for components of efficient lean growth rate was quantified by the within-selection line regression of performance test traits on diet class. Large White pigs were performance tested over three 14-day test-periods starting at 30, 50 and 75 kg and offered, to appetite, isoenergetic diets differing in dietary total lysine: energy (0•59, 0•69, 0•81, 0•91, 1•01, 1•12 and 1•23 g/MJ digestible energy (DE)). Within each litter, full-sibs were performance tested on different diets. Pigs were also performance tested on a diet-choice procedure using diets with total lysine: energy of 0•69 and 1•12 g/MJ DE to determine the correlation between performance on phase-feeding and diet-choice.The study consisted of 578 animals with 459 pigs tested with phase-feeding and 119 tested on diet-choice procedures. The study detected significant selection line and dietary effects on performance test traits, but no significant between-selection line differences in sensitivity to dietary total lysine: energy. When combinations of performance test traits were transformed into predicted lysine and energy utilization traits there were significant selection line effects on predicted nutrient allocation, but not in responses to increasing dietary total lysine: energy. The lack of between-selection line differences in sensitivity to dietary total lysine: energy indicated that the consequences of changing dietary total lysine: energy will be broadly similar across a range of genotypes, as spanned by the selection lines of the study.Genetic correlations between performance traits of phase-fed and diet-choice pigs suggested that predictions of genetic merit will be similar with animals tested on either procedure between 30 and 75 kg but post 75 kg predicted genetic merit for growth rate and lysine intake should be estimated separately for performance on diet-choice or for performance on a given diet. In contrast, predicted genetic merit for fat deposition with performance testing on diet-choice will be highly correlated with predicted genetic merit with testing on a single diet.

Serum insulin‐like growth factor‐1 concentration in pigs divergently selected for daily food intake or lean growth rate

“…The mean (SD) weights at the start and end of test were 29.4 (1.5) and 89.1 (2.8) kg, respectively. The two diets, coded Q and S, were a subset of diets used in a phase‐feeding study with the selection lines ( Cameron et al. 2003) and diet coding has been retained to maintain consistency between studies.…”

“…In each of three generations prior to the current study, a different genotype with nutrition (GXN) study was performed, e.g. Cameron et al. (2003).…”

“…The mean (SD) weights at the start and end of test were 29.4 (1.5) and 89.1 (2.8) kg, respectively. The two diets, coded Q and S, were a subset of diets used in a phase-feeding study with the selection lines (Cameron et al 2003) and diet coding has been retained to maintain consistency between studies. Note that LGS animals were performance-tested on a restricted feeding regime during the selection phase in earlier generations of the lean growth experiment, while all animals were fed ad libitum in the current study.…”

“…In each of three generations prior to the current study, a different genotype with nutrition (GXN) study was performed, e.g. Cameron et al (2003). Inclusion of performance test data from the GXN studies in a multivariate analysis with IGF-1 data from the current study would require estimation of each diet-feeding regime effect for each GXN trial which may have contributed more noise than information to the genetic parameter estimates.…”

A resource allocation model describing consequences of artificial selection under metabolic stress

“…Animals tend to adapt to the environment they are selected in, which may result in the development of a genotype × environment (G × E) interaction. Results presented in the literature suggest that the size of difference between environments especially determines whether a G × E interaction will develop (e.g., Emanuelson et al, 1999;Cameron et al, 2000Cameron et al, , 2003.…”