Short communication: Validation of genomic breeding value predictions for feed intake and feed efficiency traits

Pryce, J.E.; González-Recio, Óscar; Thornhill, J. B.; Marett, L. C.; Wales, W. J.; Coffey, M.P.; Haas, Y. de; Veerkamp, R.F.; Hayes, Ben J.

doi:10.3168/jds.2013-7376

Cited by 22 publications

(27 citation statements)

References 9 publications

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“…This term was, however, not included in other REI definitions (e.g., Coleman et al, 2010;Pryce et al, 2014). Body condition score is independent of skeletal size and is a measure of depth of muscle and subcutaneous fat.…”

Section: Residual Traitsmentioning

confidence: 99%

“…Residual feed intake, used predominately in growing animals as a measure of feed efficiency (Berry and Crowley, 2013), is now also being used in lactating dairy cow populations (Coleman et al, 2010;McParland et al, 2014;Pryce 469 et al, 2014). The definition of residual energy intake (REI) in lactating cows does, however, differ among studies (Coleman et al, 2010;McParland et al, 2014;Pryce et al, 2014). Consequently, the applications and benefits of these definitions are different.…”

Section: Introductionmentioning

confidence: 99%

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Inter-relationships among alternative definitions of feed efficiency in grazing lactating dairy cows

Hurley

López‐Villalobos

McParland

et al. 2016

Journal of Dairy Science

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International interest in feed efficiency, and in particular energy intake and residual energy intake (REI), is intensifying due to a greater global demand for animalderived protein and energy sources. Feed efficiency is a trait of economic importance, and yet is overlooked in national dairy cow breeding goals. This is due primarily to a lack of accurate data on commercial animals, but also a lack of clarity on the most appropriate definition of the feed intake and utilization complex. The objective of the present study was to derive alternative definitions of energetic efficiency in grazing lactating dairy cows and to quantify the inter-relationships among these alternative definitions. Net energy intake (NEI) from pasture and concentrate intake was estimated up to 8 times per lactation for 2,693 lactations from 1,412 Holstein-Friesian cows. Energy values of feed were based on the French Net Energy system where 1 UFL is the net energy requirements for lactation equivalent of 1 kg of air-dry barley. A total of 8,183 individual feed intake measurements were available. Energy balance was defined as the difference between NEI and energy expenditure. Efficiency traits were either ratio-based or residual-based; the latter were derived from least squares regression models. Residual energy intake was defined as NEI minus predicted energy to fulfill the requirements for the various energy sinks. The energy sinks (e.g., NE L , metabolic live weight) and additional contributors to energy kinetics (e.g., live weight loss) combined, explained 59% of the variation in NEI, implying that REI represented 41% of the variance in total NEI. The most efficient 10% of test-day records, as defined by REI (n = 709), on average were associated with a 7.59 UFL/d less NEI (average NEI of the entire population was 16.23 UFL/d) than the least efficient 10% of test-day records based on REI (n = 709).Additionally, the most efficient 10% of test-day records, as defined by REI, were associated with superior energy conversion efficiency (ECE, i.e., NE L divided by NEI; ECE = 0.55) compared with the least efficient 10% of test-day records (ECE = 0.33). Moreover, REI was positively correlated with energy balance, implying that more negative REI animals (i.e., deemed more efficient) are expected to be, on average, in greater negative energy balance. Many of the correlations among the 14 defined efficiency traits differed from unity, implying that each trait is measuring a different aspect of efficiency.

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Section: Residual Traitsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Inter-relationships among alternative definitions of feed efficiency in grazing lactating dairy cows

Hurley

López‐Villalobos

McParland

et al. 2016

Journal of Dairy Science

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“…In a similar study, Pryce et al (2014a) used low-density (SNP50) genotypes of 78 Australian multiparous Holstein cows to impute 609 321 SNP that were previously used to genotype a reference population of growing heifers (Pryce et al, 2012). The imputed SNP of the lactating cows were used to estimate their GEBV for RFI growth .…”

Section: Selection For Correlated Traitsmentioning

confidence: 99%

Invited review: Improving feed efficiency in dairy production: challenges and possibilities

Connor

2015

Animal

134

112

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Despite substantial advances in milk production efficiency of dairy cattle over the last 50 years, rising feed costs remain a significant threat to producer profitability. There also is a greater emphasis being placed on reducing the negative impacts of dairy production on the environment; thus means to lower greenhouse gas (GHG) emissions and nutrient losses to the environment associated with cattle production are being sought. Improving feed efficiency among dairy cattle herds offers an opportunity to address both of these issues for the dairy industry. However, the best means to assess feed efficiency and make genetic progress in efficiency-related traits among lactating cows without negatively impacting other economically important traits is not entirely obvious. In this review, multiple measurements of feed efficiency for lactating cows are described, as well as the heritability of the traits and their genetic and phenotypic correlations with other production traits. The measure of feed efficiency, residual feed intake is discussed in detail in terms of the benefits for its selection, how it could be assessed in large commercial populations, as well as biological mechanisms contributing to its variation among cows, as it has become a commonly used method to estimate efficiency in the recent scientific literature.

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“…Residual feed intake (RFI) is commonly used in growing beef animals as a measure of feed efficiency (Berry and Crowley, 2013) and is increasing in popularity in lactating dairy cow populations (Coleman et al, 2010;Pryce et al, 2014). Residual feed intake in growing animals may be defined as the difference between actual energy intake and the energy intake predicted from the performance of the animal (Berry and Crowley, 2013).…”

Section: Introductionmentioning

confidence: 99%

Mid-infrared spectrometry of milk as a predictor of energy intake and efficiency in lactating dairy cows

McParland

Lewis

Kennedy

et al. 2014

Journal of Dairy Science

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Interest is increasing in the feed intake complex of individual dairy cows, both for management and animal breeding. However, energy intake data on an individual-cow basis are not routinely available. The objective of the present study was to quantify the ability of routinely undertaken mid-infrared (MIR) spectroscopy analysis of individual cow milk samples to predict individual cow energy intake and efficiency. Feed efficiency in the present study was described by residual feed intake (RFI), which is the difference between actual energy intake and energy used (e.g., milk production, maintenance, and body tissue anabolism) or supplied from body tissue mobilization. A total of 1,535 records for energy intake, RFI, and milk MIR spectral data were available from an Irish research herd across 36 different test days from 535 lactations on 378 cows. Partial least squares regression analyses were used to relate the milk MIR spectral data to either energy intake or efficiency. The coefficient of correlation (R EX ) of models to predict RFI across lactation ranged from 0.48 to 0.60 in an external validation data set; the predictive ability was, however, strongest (R EX = 0.65) in early lactation (<60 d in milk). The inclusion of milk yield as a predictor variable improved the accuracy of predicting energy intake across lactation (R EX = 0.70). The correlation between measured RFI and measured energy balance across lactation was 0.85, whereas the correlation between RFI and energy balance, both predicted from the MIR spectrum, was 0.65. Milk MIR spectral data are routinely generated for individual cows throughout lactation and, therefore, the prediction equations developed in the present study can be immediately (and retrospectively where MIR spectral data have been stored) applied to predict energy intake and efficiency to aid in management and breeding decisions.

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Short communication: Validation of genomic breeding value predictions for feed intake and feed efficiency traits

Cited by 22 publications

References 9 publications

Inter-relationships among alternative definitions of feed efficiency in grazing lactating dairy cows

Inter-relationships among alternative definitions of feed efficiency in grazing lactating dairy cows

Invited review: Improving feed efficiency in dairy production: challenges and possibilities

Mid-infrared spectrometry of milk as a predictor of energy intake and efficiency in lactating dairy cows

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