Dissection of Koch's residual feed intake: Implications for selection

For 50 yr, residual feed intake (RFI) has remained a black box even though many researchers have touted it as a more biological estimate of efficiency of feed utilization than feed conversion ratio (FCR). We successfully dissected the efficiency of feed utilization by decomposing the components of RFI and ascertained the contributions of its components. Currently, a fixed effect model is used to predict RFI, which we term RFIF. We used a random effect model to predict RFIR, which allowed a separate estimation of RFI for maintenance (RFIM) and for growth (RFIG) and also ascertained their respective efficiencies. Judged by residual variance, R-2 and deviance information criterion, the random effect model was superior to the traditional fixed effect model used to generate RFIF. Under the traditional method, the h(2) of RFIF was 0.13 but h(2) of RFIR was 0.35. The heritability of RFIM and RFIG were moderate (similar to 0.50), but the genetic correlation between them was highly negative (-0.95), suggesting that these 2 efficiencies contribute in an opposing way toward RFI. As a result, there should be caution in ascribing a biological basis to RFI. Under the current methodology, a biological basis can be ascribed to RFIM and RFIG. Selecting on RFIM will lead to smaller but efficient birds. The genetic gains in feed efficiency will be achieved by reductions in feed required for maintenance. The RFIG is not an efficiency parameter and should not be used as a sole criterion for selection. The ability of the current method to estimate efficiency values for metabolic BW and BW gain provides geneticists with additional parameters to use to discriminate between animals with similar RFIR. It also provides the flexibility to impose weights on RFIM and RFIG to meet a desired objective.