Estimating Feed Efficiency of Lactating Dairy Cattle Using Residual Feed Intake

Connor, Erin E.; Hutchison, J.L.; Norman, H.D.

doi:10.1002/9781118392331.ch11

Cited by 7 publications

(11 citation statements)

References 45 publications

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“…Reported heritability estimates generally are low to moderate, with estimates ranging from 0.01 to 0.40 among lactating cows (de Haas et al, 2011;Connor et al, 2012a and and 0.22 to 0.40 among growing heifers (Pryce et al, 2012;Lin et al, 2013). In addition, genetic variation in RFI within dairy herds has been demonstrated (Williams et al, 2011;Berry and Crowley, 2013;Vallimont et al, 2013).…”

Section: Estimates Of Feed Efficiency In Dairy Cattlementioning

confidence: 99%

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

Connor

2015

Animal

132

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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Section: Estimates Of Feed Efficiency In Dairy Cattlementioning

confidence: 99%

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

Connor

2015

Animal

132

112

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“…There is growing evidence that feed efficiency is different even in high-efficiency herds that feed the same diet [3]. The low RFI (efficient) cows are those that consume less feed than the expected for maintenance and production, compared with the high RFI cows, and RFI is a heritable trait for dairy cows [4–6]. Several mechanisms have been suggested to explain the causes of variation in RFI between dairy cows, including rumen microbial populations [7], feeding behavior [8, 9] and nutrients digestibility [10, 11].…”

Section: Introductionmentioning

confidence: 99%

Nitrogen partitioning and microbial protein synthesis in lactating dairy cows with different phenotypic residual feed intake

Xie

Wang

et al. 2019

J Animal Sci Biotechnol

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Background Residual feed intake (RFI) is an inheritable measure of feed efficiency that is independent on level of production. However, physiological and metabolic mechanisms underlying divergent RFI are not fully elucidated. This study was conducted to investigate dietary nitrogen (N) partitioning and microbial protein synthesis in lactating dairy cows divergent in phenotypic RFI. Results Thirty Holstein dairy cows (milk yield = 35.3 ± 4.71 kg/d; milk protein yield = 1.18 ± 0.13 kg/d; mean ± standard deviation) were selected for the experiment to derive RFI. After the RFI measurement period of 50 d, the 10 lowest RFI cows and 8 highest RFI cows were selected. The low RFI cows had lower dry matter intake (DMI, P < 0.05) than the high RFI cows, but they produced similar energy-corrected milk. The ratios of milk to DMI (1.41 vs. 1.24, P < 0.01) and energy-corrected milk to DMI (1.48 vs. 1.36, P < 0.01) were greater in low RFI cows than those in the high RFI cows. The low RFI cows had lower milk urea nitrogen than that in the high RFI cows ( P = 0.05). Apparent digestibility of nutrients did not differ between two groups ( P > 0.10). Compared with high RFI animals, the low RFI cows had a lower retention of N (5.72 vs. 51.4 g/d, P < 0.05) and a higher partition of feed N to milk N (29.7% vs. 26.5%, P < 0.05). Conclusions The results suggest that differences in N partition, synthesis of microbial protein, and utilization of metabolizable protein could be part of the mechanisms associated with variance in the RFI. Electronic supplementary material The online version of this article (10.1186/s40104-019-0356-3) contains supplementary material, which is available to authorized users.

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“…Many approaches have been developed and adopted to select the most feed-efficient cows. Currently, residual feed intake (RFI) has been used to measure FE in dairy cows [3, 4]. Residual feed intake is the difference between the predicted and actual feed intake [5].…”

Section: Introductionmentioning

confidence: 99%

Gene co-expression networks from RNA sequencing of dairy cattle identifies genes and pathways affecting feed efficiency

et al. 2018

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BackgroundSelection for feed efficiency is crucial for overall profitability and sustainability in dairy cattle production. Key regulator genes and genetic markers derived from co-expression networks underlying feed efficiency could be included in the genomic selection of the best cows. The present study identified co-expression networks associated with high and low feed efficiency and their regulator genes in Danish Holstein and Jersey cows.RNA-sequencing data from Holstein and Jersey cows with high and low residual feed intake (RFI) and treated with two diets (low and high concentrate) were used. Approximately 26 million and 25 million pair reads were mapped to bovine reference genome for Jersey and Holstein breed, respectively. Subsequently, the gene count expressions data were analysed using a Weighted Gene Co-expression Network Analysis (WGCNA) approach. Functional enrichment analysis from Ingenuity® Pathway Analysis (IPA®), ClueGO application and STRING of these modules was performed to identify relevant biological pathways and regulatory genes.ResultsWGCNA identified two groups of co-expressed genes (modules) significantly associated with RFI and one module significantly associated with diet. In Holstein cows, the salmon module with module trait relationship (MTR) = 0.7 and the top upstream regulators ATP7B were involved in cholesterol biosynthesis, steroid biosynthesis, lipid biosynthesis and fatty acid metabolism. The magenta module has been significantly associated (MTR = 0.51) with the treatment diet involved in the triglyceride homeostasis. In Jersey cows, the lightsteelblue1 (MTR = − 0.57) module controlled by IFNG and IL10RA was involved in the positive regulation of interferon-gamma production, lymphocyte differentiation, natural killer cell-mediated cytotoxicity and primary immunodeficiency.ConclusionThe present study provides new information on the biological functions in liver that are potentially involved in controlling feed efficiency. The hub genes and upstream regulators (ATP7b, IFNG and IL10RA) involved in these functions are potential candidate genes for the development of new biomarkers. However, the hub genes, upstream regulators and pathways involved in the co-expressed networks were different in both breeds. Hence, additional studies are required to investigate and confirm these findings prior to their use as candidate genes.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2553-z) contains supplementary material, which is available to authorized users.

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Estimating Feed Efficiency of Lactating Dairy Cattle Using Residual Feed Intake

Cited by 7 publications

References 45 publications

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

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

Nitrogen partitioning and microbial protein synthesis in lactating dairy cows with different phenotypic residual feed intake

Gene co-expression networks from RNA sequencing of dairy cattle identifies genes and pathways affecting feed efficiency

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