Measures Of Residual Feed Intake Research Articles

Genetic parameters for measures of residual feed intake and growth traits in seven generations of Duroc pigs

Residual feed intake (RFI) represents the deviation of the actual feed consumption of an animal from that predicted from combination of growth traits. Data on 1642 Duroc (380 boars, 868 gilts, and 394 barrows) pigs in seven generations were used to estimate genetic parameters for measures of RFI, daily feed intake (FI), average daily gain (ADG), backfat (BF), and loin eye area (LEA). Four measures of RFI were estimated from models that included initial test age and weight, and ADG (RFI1); initial test age and weight, ADG, and BF (RFI2); initial test age and weight, ADG and LEA (RFI3); and initial test age and weight, ADG, BF, and LEA (RFI4). Genetic parameters were estimated using an animal model by the REML method. Heritability estimates for measures of RFI were moderate (ranged from 0.22 to 0.38). The corresponding estimates for FI, ADG, and LEA were also moderate (ranging from 0.45 to 0.49), while the estimate for BF was high (0.72). Genetic correlations of FI with ADG (0.84) and BF (0.67) were high. LEA negatively correlated with FI (− 0.42), ADG (− 0.11) and BF (− 0.44). Genetic correlations of BF with measures of RFI were higher when BF was not included in the estimation of RFI (0.77 with RFI1 and 0.76 with RFI3 vs. 0.11 with RFI2 and 0.07 with RFI4). Genetic correlations of LEA with measures of RFI were all negative (ranged from − 0.30 to − 0.60). Selection for ADG, LEA, BF, and intramuscular fat has resulted in small but favourable genetic changes in measures of RFI. Phenotypic correlations between measures of RFI were zero, and genetic correlations between them were low (0.17 to 0.23). FI was strongly correlated with all the measures of RFI, both genetically (ranged from 0.56 to 0.77) and phenotypically (ranged from 0.56 to 0.66). The results suggested that selection against RFI may cause a reduction in FI. BF should also decrease, and LEA should increase. The amount of change in BF or LEA would vary depending on whether RFI was adjusted for BF.

Identification of polymorphisms influencing feed intake and efficiency in beef cattle

Feed efficiency is an economically important trait in beef cattle. Net feed efficiency, measured as residual feed intake (RFI), is the difference between actual feed intake and the predicted feed intake required for maintenance and gain of the animal. SNPs that show associations with RFI may be useful quantitative trait nucleotides for marker-assisted selection. This study identified associations between SNPs underlying five RFI QTL on five bovine chromosomes (BTA2, 5, 10, 20 and 29) with measures of dry matter intake (DMI), RFI and feed conversion ratio (FCR) in beef cattle. Six SNPs were found to have effects on RFI (P < 0.05). The largest single SNP allele substitution effect for RFI was -0.25 kg/day located on BTA2. The combined effects of the SNPs found significant in this experiment explained 6.9% of the phenotypic variation of RFI. Not all the RFI SNPs showed associations with DMI and FCR even though these traits are highly correlated with RFI (r = 0.77 and r = 0.62 respectively). This shows that these SNPs may be affecting the underlying biological mechanisms of feed efficiency beyond feed intake control and weight gain efficiency. These SNPs can be used in marker-assisted selection but first it will be important to verify these effects in independent populations of cattle.

Genetic parameters for measures of the efficiency of gain of boars and the genetic relationships with its component traits in Duroc pigs1

Genetic parameters for the efficiency of gain traits on 380 boars and the genetic relationships with component traits were estimated in 1,642 pigs (380 boars, 868 gilts, and 394 barrows) in 7 generations of a Duroc population. The efficiency of gain traits included the feed conversion ratio (FCR) and residual feed intake (RFI) and their component traits, ADG, metabolic BW (MWT), and daily feed intake (FI). The RFI was calculated as the difference between the actual and expected FI. The expected FI was predicted by the nutritional requirement and by the residual of phenotypic (RFI(phe)) and genetic (RFI(gen)) regressions from the multivariate analysis for FI on MWT and ADG. The means for RFI(phe) and RFI(gen) were close to zero, and the mean for nutritional RFI was negative (-0.11 kg/d). The traits studied were moderately heritable (ranging from 0.27 to 0.53). The genetic and phenotypic correlations between ADG and FI were moderate to high, whereas the genetic correlation between MWT and FI was moderate, and the phenotypic correlation between them was low. The corresponding correlations between RFI(phe) and RFI(gen) were > 0.95, implying that they can be regarded as the same trait. The genetic and phenotypic correlations of FCR with measures of RFI were high but lower than unity. The RFI(phe) was phenotypically independent of its component traits, MWT (r(p) = 0.01) and ADG (r(p) = 0.03). The RFI(gen) was genetically independent of MWT (r(g) = -0.04), whereas there was a weak genetic relationship (r(g) = 0.15) between RFI(gen) and ADG. Residual FI was more heritable than FCR, and the genetic and phenotypic correlations of RFI(phe) and RFI(gen) with FI were positive and stronger than that of FCR with FI. These results provide evidence that RFI(phe) or RFI(gen) should be included in breeding programs for Duroc pigs to make genetic improvement in the efficiency of gain.

Genetic and phenotypic relationships among different measures of growth and feed efficiency in young Charolais bulls

Performance and progeny test data on young Charolais bulls in France were used to estimate genetic and phenotypic variation, and correlations among postweaning growth and feed efficiency traits. Records on 510 performance test bulls born from 1985 to 1989 and 792 progeny test bulls born from 1988 to 1997 were used, plus available pedigree information (total n=5493). Feed intake for performance test bulls was restricted to achieve growth rate of 1.5 kg/day, while that for progeny test bulls was ad libitum. Nine growth and feed efficiency traits were studied. (Co)variances were estimated by multivariate REML analysis using an animal model. The focus of the study was on the progeny test bulls but all analyses were done simultaneously with two performance test traits which were used to select most of the sires of the progeny test bulls. All the traits to 15 months of age were moderately heritable (0.31–0.48), highlighting the fact that genetic improvement can potentially be made in any of these traits. Feed conversion ratio (FCR) was highly correlated genetically with relative growth rate ( r=−0.90) and Kleiber ratio ( r=−0.81), two traits which do not require measurement of feed intake. The measure of residual feed intake (RFI) where the expected feed intake (EFI) was calculated from the dataset was highly correlated genetically ( r=0.89) with RFI where EFI was calculated from feeding standards formulae. Both RFI measures were highly correlated genetically ( r≥0.85) with FCR.

Genetic parameters for production traits and measures of residual feed intake in large white swine.

The purpose of this study was to estimate genetic parameters for ADG, backfat thickness and loin eye area (LEA), and measures of feed intake and efficiency for purebred Large White boars born from 1990 to 1997. Boars from 60% of the litters were culled at weaning based on a maternal breeding value (index) of the dam, and remaining boars (n = 26,706) were grown to 100 d of age. Selection of boars for individual pen testing was based on a combination of growth and maternal indices. Boars were fed a corn-soybean meal diet that was 1.14% lysine, 19% protein, and 3,344 kcal/kg ME for approximately 77 d. Boars were weighed at the beginning and end of the test, and feed intake was recorded. Daily feed intake (DFI), ADG, and feed:gain ratio (FG) were computed. Four measures of residual feed intake (RFI) were estimated as the difference between actual feed intake and that predicted from models that included 1) initial test age and weight and test ADG (RFI1); 2) initial test age and weight, test ADG, and backfat (RFI2); 3) initial test age and weight, test ADG, and LEA (RFI3); and 4) initial test age and weight, test ADG, backfat, and LEA (RFI4). Genetic parameters were estimated using an animal model and single- or multiple-trait DFREML procedures. Models included fixed effects of contemporary groups and initial test age as a covariate and random animal and litter effects. Heritability estimates for test ADG, DFI, FG, backfat, LEA, RFI1, RFI2, RFI3, and RFI4 were .24, .23, .16, .36, .24, .17, .11, .15, and .10, respectively. Genetic correlations between ADG and backfat, ADG and LEA, ADG and DFI, and ADG and FG were .37, .36, .82, and -.32, respectively. Genetic correlations between ADG and measures of residual feed intake ranged from .11 to .18. Genetic correlations of backfat with LEA, DFI, and FG were -.27, .64, and .40, respectively. Genetic correlations of backfat with RFI measures were higher when backfat was not included in the estimation of RFI. Genetic correlations for LEA with DFI and FG were 0 and -.52, respectively. Genetic correlations for LEA with RFI measures were all negative and ranged from -.31 to -.51. Genetic correlations indicate that selection for reduced RFI could be made without adversely affecting ADG. Backfat should also decrease, and LEA should increase. The amount of change in backfat or LEA would depend on the measure of RFI used.