2015
DOI: 10.3168/jds.2014.8510
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Heterogeneity in genetic and nongenetic variation and energy sink relationships for residual feed intake across research stations and countries

Abstract: Our long-term objective is to develop breeding strategies for improving feed efficiency in dairy cattle. In this study, phenotypic data were pooled across multiple research stations to facilitate investigation of the genetic and nongenetic components of feed efficiency in Holstein cattle. Specifically, the heritability of residual feed intake (RFI) was estimated and heterogeneous relationships between RFI and traits relating to energy utilization were characterized across research stations. Milk, fat, protein,… Show more

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Cited by 111 publications
(223 citation statements)
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“…As RFI is corrected for BW, this is an important distinction and the reason why feed saved (integrating RFI and maintenance costs associated with higher BW) is a more desirable trait for implementation compared with RFI. Tempelman et al (2015) combined data from research stations in the United States, United Kingdom, and the Netherlands and observed heterogeneous variation in RFI arising from multiple environments from which data were sourced. Therefore, multivariate analyses are preferable when the trait is measured in different environments or life stages (De Haas et al, 2012) as they can treat differences both in trait definitions and genotype by environment interactions appropriately.…”
Section: Discussionmentioning
confidence: 99%
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“…As RFI is corrected for BW, this is an important distinction and the reason why feed saved (integrating RFI and maintenance costs associated with higher BW) is a more desirable trait for implementation compared with RFI. Tempelman et al (2015) combined data from research stations in the United States, United Kingdom, and the Netherlands and observed heterogeneous variation in RFI arising from multiple environments from which data were sourced. Therefore, multivariate analyses are preferable when the trait is measured in different environments or life stages (De Haas et al, 2012) as they can treat differences both in trait definitions and genotype by environment interactions appropriately.…”
Section: Discussionmentioning
confidence: 99%
“…The heritability of RFI in Australian cows was 0.20 and heritabilities for growing calves and a combined data set of Dutch and UK cows were both 0.35 (Table 2), both of which are in the range of previous stud-ies Tempelman et al, 2015). The genetic correlation between RFI in growing calves and lactating cows was 0.67 (±0.45).…”
Section: Genetic Parametersmentioning
confidence: 96%
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“…A full description of the data editing strategies can be found in Tempelman et al (2015). Milk energy output is expressed in megacalories and was calculated from weekly MY plus the fat % (FP), protein % (PP), and lactose % (LP), using the following formula according to National Research Dairy Council (2001) Kleiber (1932) determined MBW to be proportional to the basal metabolic rate of animals and to be representative of maintenance nutrient requirements for animals as a function of their BW.…”
Section: Data Collection and Editing: Feed Intake Traitsmentioning
confidence: 99%
“…Because RFI is independent of production level, recent attention has been given to using RFI as a tool to assess feed efficiency in dairy cattle for purposes of genetic selection (Connor et al, 2013;Green et al, 2013;Macdonald et al, 2014). The heritability of RFI is 0.15 to 0.19 in lactating dairy cattle (van Arendonk et al, 1991;Tempelman et al, 2015) and 0.22 to 0.38 in growing dairy heifers (Williams et al, 2011;Pryce et al, 2012). If RFI is to be used in selection strategies, it is important to know if it is repeatable across the range of diets commonly used on commercial dairy farms.…”
Section: Introductionmentioning
confidence: 99%