The dynamic behavior of feed efficiency in primiparous dairy cattle

Abstract

A variety of measures are currently used to evaluate feed efficiency in livestock, with some of the most popular being the linear regression of nutrient intake on the various energy sinks of the cohort being evaluated. The adoption of novel on-farm technologies has greatly increased the breadth and depth of data being collected on a daily basis, which creates the opportunity for the implementation of more advanced feed efficiency models. The objectives of the current study were to leverage data collected using high-throughput biometric technologies to evaluate changes of early-lactation feed efficiency on a daily basis and to develop a novel measure of feed efficiency based on the NRC net energy model. Daily records of nutrient intake, fat-and protein-corrected milk yield, body weight, and body condition score were used to model 7 different indices of feed efficiency (gross feed efficiency, return over feed costs, residual feed intake, residual net energy intake, and net energy efficiencies of lactation, maintenance, and body reserve flux) in primiparous Holstein heifers (n = 40) from 0 to 150 d in milk. We observed that feed efficiency was dynamic and fluctuated over the course of the experimental period regardless of the efficiency measure used, but most measures followed similar trends in changes of efficiency on a day-to-day basis. Of the measures evaluated, return over feed costs would be most suited for management purposes due to practicality and simplicity, whereas other measures, such as the efficiency of net energy flux to and from body reserves, present potential targets for inclusion in breeding goals. Net energy efficiency of lactation was estimated to have higher repeatability compared with residual feed or energy intake, which may reduce the time required to estimate whole-lactation efficiency. Because decreased net energy balance was strongly correlated with increased efficiency for all indices evalu-ated, future work investigating the associations of feed efficiency with the magnitude and duration of negative energy balance is warranted.

Genetic mechanisms underlying feed utilization and implementation of genomic selection for improved feed efficiency in dairy cattle

“…As a result, this trait can be improved by increasing milk yield, decreasing feed intake, or a combination of both strategies. More complex measures of feed efficiency, such as RFI (Koch et al 1963), REI (Fischer et al 2018), or net energy efficiency (Seymour et al 2020), share some commonalities. This includes the concept of categorizing energy expenditures into maintenance, growth, or production activities, and will be the focus of this section.…”

“…In general, animals which partition a greater proportion of energy towards productive purposes are considered to be more feed efficient. The biological processes governing anabolic and catabolic processes are generally considered to be highly regulated and subject to strict thermodynamic constraints (Baldwin et al 1980;Seymour et al 2020), making genetic selection for improved efficiency of these pathways somewhat challenging. However, Bottje (2019) has recently provided support for the theory that defective proteins in the electron transport chain may lead to suboptimal mitochondrial function and reduce the overall energetic efficiency of the animal.…”

Grouping crossbred Holstein x Gyr heifers according to different feed efficiency indexes and its effects on energy and nitrogen partitioning, blood metabolic variables and gas exchanges

“…1 Selection of the divergent animals for RFI, RG, FCE, was based on data of the feed efficiency test of an earlier study. 2 Residual feed intake 3 Residual weight gain 4 Feed conversion efficiency 5 High efficiency 6 Low efficiency 7 Stander error of the means 8 Statistical difference between HE and LE 9 Dry matter intake…”

“…1 Dry matter intake data are restricted to the 5 d measurement period of the digestibility trial. 2 Residual feed intake 3 Residual weight gain 4 Feed conversion efficiency 5 High efficiency 6…”

“…According to Arthur and Herd [4], there is individual variation in nutrient utilization efficiency among animals with similar characteristics. Differences in efficiency between animals can be dependent on body weight, stage of production, growth composition, environmental conditions and their interactions with other factors such as rumen kinetics, digestion, absorption and efficiency of energy and protein utilization [5,6]. However, the relationships between groups of high and low FE and the effects on energy and nitrogen partitioning, blood metabolic variables and gas exchanges are not well understood.…”