Dissection of Koch's Residual Intake: Some Biological Implications

For 50 years residual feed intake (RFI) has remained a black box even though many researchers have touted it as more biological estimate of efficiency of feed utilization than feed conversion ratio (FCR). We have successfully dissected the efficiency of feed utilization to decompose the components of RFI and ascertained the contributions of its components. Currently, a fixed effect model is used to predict RFI as a deviation from a standard expected curve, which we term RFI_F. We used a random effect model to predict RFI_R which allowed the separate estimation of RFI for maintenance (RFI_M) and for growth (RFI_G) and also ascertain their respective efficiencies. The dissection of RFI into its contributing components (RFI_M and RFI_G) allows for a better understanding of the biological basis of the traits. In fact, while plasma triiodothyronine (T₃) level was correlated (P<0.05) with RFI_M but not RFI_G, insulin-like growth factor 1 (IGF1) level was correlated (P<0.03) with RFI_G and not with RFI_M. Single nucleotide polymorphisms (SNP) in insulin-like growth factor-1 (IGF1) [g.570A>C; M74176] was analyzed for associations with components of RFI in a random mating meat-type control population (n=448). The frequency of the IGF1 A allele was 0.19 and the genotypic classes of the population did not deviate from Hardy-Weinberg equilibrium (HWE) (X²_df=2=2.2755; P>0.05). Significant association of the IGF1 g.570A>C was found with RFI measured at days 28-35 (P<=0.05). The IGFI g.570A>C was significantly associated with RFI_M and not with RFI_G where C was the favorable allele.