Optimizing feed intake recording and feed efficiency estimation to increase the rate of genetic gain for feed efficiency in beef cattle

Manafiazar, Ghader; Basarab, J. A.; McKeown, Lisa; Stewart-Smith, J.; Baron, V. S.; MacNeil, M. D.; Plastow, Graham

doi:10.1139/cjas-2016-0118

Cited by 11 publications

(10 citation statements)

References 12 publications

(39 reference statements)

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“…Notwithstanding this, recent studies have attempted to reduce the test duration further (Culbertson et al, 2015;Cassady et al, 2016). Indeed, where BW was recorded for 63 (Wang et al, 2006) and 84 (Manafiazar et al, 2017) days, apparently adequate feed intake test durations as short as 35 to 42 days, respectively have been reported. Although shortening the duration of the feed intake test period resulted in a loss in accuracy (reduction in Spearman's correlation coefficient) of 5% to 7%, such an approach would reduce the cost of feed intake recording and increase annual animal throughput (Manafiazar et al, 2017).…”

Section: Measuring and Calculation Of Residual Feed Intakementioning

confidence: 95%

“…Indeed, where BW was recorded for 63 (Wang et al, 2006) and 84 (Manafiazar et al, 2017) days, apparently adequate feed intake test durations as short as 35 to 42 days, respectively have been reported. Although shortening the duration of the feed intake test period resulted in a loss in accuracy (reduction in Spearman's correlation coefficient) of 5% to 7%, such an approach would reduce the cost of feed intake recording and increase annual animal throughput (Manafiazar et al, 2017). The accuracy of shorter test durations, however, is likely to be dependent on prevailing diet composition and animal growth rate (Goonewardene et al, 2004).…”

Section: Measuring and Calculation Of Residual Feed Intakementioning

confidence: 95%

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Invited review: Improving feed efficiency of beef cattle – the current state of the art and future challenges

Kenny

Fitzsimons

Waters

et al. 2018

Animal

160

135

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Improvements in feed efficiency of beef cattle have the potential to increase producer profitability and simultaneously lower the environmental footprint of beef production. Although there are many different approaches to measuring feed efficiency, residual feed intake (RFI) has increasingly become the measure of choice. Defined as the difference between an animal's actual and predicted feed intake (based on weight and growth), RFI is conceptually independent of growth and body size. In addition, other measurable traits related to energy expenditure such as estimates of body composition can be included in the calculation of RFI to also force independence from these traits. Feed efficiency is a multifactorial and complex trait in beef cattle and inter-animal variation stems from the interaction of many biological processes influenced, in turn, by physiological status and management regimen. Thus, the purpose of this review was to summarise and interpret current published knowledge and provide insight into research areas worthy of further investigation. Indeed, where sufficient suitable reports exist, meta-analyses were conducted in order to mitigate ambiguity between studies in particular. We have identified a paucity of information on the contribution of key biological processes, including appetite regulation, post-ruminal nutrient absorption, and cellular energetics and metabolism to the efficiency of feed utilisation in cattle. In addition, insufficient information exists on the relationship between RFI status and productivity-related traits at pasture, a concept critical to the overall lifecycle of beef production systems. Overall, published data on the effect of RFI status on both terminal and maternal traits, coupled with the moderate repeatability and heritability of the trait, suggest that breeding for improved RFI, as part of a multi-trait selection index, is both possible and cumulative, with benefits evident throughout the production cycle. Although the advent of genomic selection, with associated improved prediction accuracy, will expedite the introgression of elite genetics for feed efficiency within beef cattle populations, there are challenges associated with this approach which may, in the long-term, be overcome by increased international collaborative effort but, in the short term, will not obviate the on-going requirement for accurate measurement of the primary phenotype.

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Section: Measuring and Calculation Of Residual Feed Intakementioning

confidence: 95%

Section: Measuring and Calculation Of Residual Feed Intakementioning

confidence: 95%

Invited review: Improving feed efficiency of beef cattle – the current state of the art and future challenges

Kenny

Fitzsimons

Waters

et al. 2018

Animal

160

135

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“…1 F1: single trait model for analysis of average daily feed intake (DFI) with contemporary group effects fixed; R1: single trait model for analysis of DFI with contemporary group effects random; F2: bivariate analysis model of average daily gain (ADGC) and DFI by bulls tested in phase C with contemporary group effects fixed; R2: model similar to F2, but with contemporary group effects random; F3: three-trait model of ADGC and DFI and average daily gain (ADGD) by bulls tested in phase D with contemporary groups fixed; and R3: three-trait model of average daily gain and average daily feed intake by bulls tested in phase C and average daily gain by bulls tested in phase D with contemporary groups random Genetic evaluations for efficiency traits can be based on indexes of EBV from multiple trait analyses (Kennedy et al, 1993;Thallman et al, 2018). Decoupling recording of average daily gain and feed intake would facilitate reduced cost of data collection by shortening the feed intake test period (Nielsen et al, 2013;Manafiazar et al, 2017;Thallman et al, 2018) with the potential downstream effect of more animals being phenotyped for feed intake at a reduced cost per animal (Culbertson et al, 2015). However, the relatively small genetic correlations between ADG C and ADG D observed with models F3 and R3 are troubling.…”

Section: Resultsmentioning

confidence: 99%

Alternative models for genetic evaluation of feed intake by Afrikaner cattle

MacNeil¹,

Scholtz²,

Jordaan³

et al. 2019

SA J. An. Sci.

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The objectives of this study were to evaluate statistical models of potential utility for genetic evaluation of feed intake and to estimate the (co)variance components and genetic parameters that would be necessary for their use in a national cattle evaluation scheme. Data were from Afrikaner bulls that were tested between 1974 and 2016 in Phases C (n = 1 250) and D (n = 11 083) of the National Beef Recording and Improvement Scheme. Statistical analyses in which the number of traits varied and contemporary group effects were considered either random or fixed were conducted using multiple-trait derivative-free restricted maximum likelihood. Contemporary group effects were important. When they were considered random, the estimated phenotypic variance of feed intake increased and its heritability reduced from approximately 0.43 ± 0.09 to approximately 0.30 ± 0.06. Use of average daily gain, recorded either concurrently with the feed intake measure (ADG C) or from related bulls reared on-farm (ADG D), had relatively little effect on estimated heritability of feed intake. Thus, considering contemporary group effects random consistently increased the accuracy of the estimated breeding values. Relatively small genetic correlations between ADG C and ADG D complicated the ultimate application of data recorded in Phase C and the use of data recorded in Phase D in decoupling the phenotypes for feed intake and growth in an evaluation of feed efficiency. Some modification of testing procedures may be necessary to facilitate this application of the results.

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“…A major disadvantage of RFI is that it requires accurate measures of individual animal feed intake. To meet the criteria for evaluation, individual animals are acclimatized to a feed intake measurement system for a 21 d period, followed by a 45-50 d measurement period that requires body weight to be recorded on two consecutive days at the beginning, end, and at regular intervals throughout the feeding period (Manafiazar et al 2017;Kenny et al 2018). A limitation of RFI is its dependence on production system and feeding management as well as its reliance on a predicted dry matter intake (DMI) based on maintenance and growth requirements (Table 1).…”

Section: Measures Of Efficiencymentioning

confidence: 99%

Strategies to improve the efficiency of beef cattle production

et al. 2021

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Globally, there are approximately 1 billion beef cattle and compared to poultry and swine, beef cattle have the poorest conversion efficiency of feed to meat. However, these metrics fail to consider that beef cattle produce high quality protein from feeds that are unsuitable for other livestock species. Strategies to improve the efficiency of beef cattle are focusing on operational and breeding management, host genetics, functional efficiency of rumen and respiratory microbiomes, and the structure and composition of feed. These strategies must also consider the health and immunity of the herd as well as the need for beef cattle to thrive in a changing environment. Genotyping can identify hybrid vigor with positive consequences for animal health, productivity and environmental adaptability. The role of microbiome-host interactions play a key role in the efficient nutrient digestion and host health. Microbial markers and gene expression patterns within the rumen microbiome are being used to identify hosts that are efficient at fibre digestion. Plant breeding and processing are optimizing the feed value of both forages and concentrates. Strategies to improve the efficiency of cattle production are a prerequisite for the sustainable intensification needed to satisfy the future demand for beef.

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Optimizing feed intake recording and feed efficiency estimation to increase the rate of genetic gain for feed efficiency in beef cattle

Cited by 11 publications

References 12 publications

Invited review: Improving feed efficiency of beef cattle – the current state of the art and future challenges

Invited review: Improving feed efficiency of beef cattle – the current state of the art and future challenges

Alternative models for genetic evaluation of feed intake by Afrikaner cattle

Strategies to improve the efficiency of beef cattle production

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