Neglect of lactation stage leads to naive assessment of residual feed intake in dairy cattle

Residual feed intake (RFI) is a candidate trait for feed efficiency in dairy cattle. We investigated the influence of lactation stage on the effect of energy sinks in defining RFI and the genetic parameters for RFI across lactation stages for primiparous dairy cattle. Our analysis included 747 primiparous Holstein cows, each with recordings on dry matter intake (DMI), milk yield, milk composition, and body weight (BW) over 44 lactation weeks. For each individual cow, energy-corrected milk (ECM), metabolic BW (MBW), and change in BW (ΔBW) were calculated in each week of lactation and were taken as energy sinks when defining RFI. Two RFI models were considered in the analyses; RFI model 1] was a 1-step RFI model with constant partial regression coefficients of DMI on energy sinks (ECM, MBW, and ΔBW) over lactation. In RFI model 2], data from 44 lactation weeks were divided into 11 consecutive lactation periods of 4 wk in length. The RFI model 2] was identical to model 1] except that period-specific partial regressions of DMI on ECM, MBW, and ΔBW in each lactation period were allowed across lactation. We estimated genetic parameters for RFI across lactation by both models using a random regression method. Using RFI model 2], we estimated the period-specific effects of ECM, MBW, and ΔBW on DMI in all lactation periods. Based on results from RFI model 2], the partial regression coefficients of DMI on ECM, MBW, and ΔBW differed across lactation in RFI. Constant partial regression coefficients of DMI on energy sinks over lactation was not always sufficient to account for the effects across lactation and tended to give roughly average information from all period-specific effects. Heritability for RFI over 44 lactation weeks ranged from 0.10 to 0.29 in model 1] and from 0.10 to 0.23 in model 2]. Genetic variance and heritability estimates for RFI from model 2] tended to be slightly lower and more stable across lactation than those from model 1]. In both models, RFI was genetically different over lactation, especially between early and later lactation stages. Genetic correlation estimates for RFI between early and later lactation tended to be higher when using model 2] compared with model 1]. In conclusion, partial regression coefficients of DMI on energy sinks differed across lactation when modeling RFI. Neglect of lactation stage when defining RFI could affect the assessment of RFI and the estimation of genetic parameters for RFI across lactation.