Section: Animal Science
Topic: Agricultural sciences, Applied biological sciences

Identifying cattle with superior growth feed efficiency through their natural 15N abundance and plasma urea concentration: A meta-analysis

10.24072/pcjournal.130 - Peer Community Journal, Volume 2 (2022), article no. e31.

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The objective of this study was to test two candidate biomarkers of feed efficiency in growing cattle. A database was built using performance data from 13 trials conducted with growing heifers, steers and young bulls and testing 34 dietary treatments. Different breeds were used with Charolais (37%), Simmental (15%), and cross-bred (40%) cattle being the most numerous. The database included 759 individual records for animal performance and laboratory data for N isotopic discrimination measured in plasma or muscle (Δ15Nanimal-diet; n = 749) and plasma urea concentration (n = 659). Feed conversion efficiency (FCE) and residual feed intake (RFI) criteria were calculated for a duration ranging between 56 and 259 d, depending on the trial. For FCE prediction, mixed models included the random effects of study, treatment within-study and pen within-study (i.e. contemporary group; CG) allowing these effects to be progressively excluded from the relationship. For RFI prediction, simple linear regressions were tested with the CG effect removed from biomarker values before analysis. Better models were obtained with Δ15Nanimal-diet compared to plasma urea concentration, irrespective of using mean or individual values and regardless of the feed efficiency criterion. Prediction error (0.027 kg/kg) from mixed-effect models using mean FCE and Δ15Nanimal-diet values would allow discrimination of 2 dietary treatments or production conditions in terms of FCE if they differ by more than 0.10 kg/kg. The Δ15Nanimal-diet values showed a negative and significant (P<0.001) relationship with FCE at the individual level and results highlighted that it is possible to significantly discriminate two animals randomly selected from the same CG if they differ by at least 0.06 kg/kg FCE. In addition, the top 20% highest and lowest animals within-CG in terms of RFI and FCE (extreme animals) showed significant (P<0.001) differences in Δ15Nanimal-diet values, while only extreme FCE animals could be discriminated when using plasma urea concentrations (P=0.002). No gain in feed efficiency prediction was observed when combining candidate biomarkers. However, when average daily gain data was combined with Δ15Nanimal-diet, the prediction of FCE at the individual level was strengthened compared to using only one of them, in which case average daily gain was the best single predictor. Our findings confirm that Δ15Nanimal-diet may be useful to form groups of animals for precision feeding when feed intake and body weight gain are not available. Further studies are warranted, however, to evaluate the usefulness of this promising biomarker for genetic selection.

Published online:
DOI: 10.24072/pcjournal.130
Type: Research article
Cantalapiedra-Hijar, Gonzalo 1; Morel, Isabelle 2; Sepchat, Bernard 3; Chantelauze, Céline 1, 4; Miller, Gemma A. 5; Duthie, Carol-Anne 5; Ortigues-Marty, Isabelle 1; Dewhurst, Richard J. 5

1 INRAE, Université Clermont Auvergne, Vetagro Sup, UMRH, 63122 Saint-Genes-Champanelle, France
2 Agroscope, Route de la Tioleyre 4, 1725 Posieux, Switzerland
3 INRAE, UE Herbipôle, 63122 St Genès Champanelle, France
4 Université Clermont Auvergne, INRAE, UNH, Plateforme d’Exploration du Métabolisme, MetaboHUB, Clermont, F-63000 Clermont-Ferrand, France
5 SRUC, West Mains Road, Edinburgh EH9 3JG, United Kingdom
License: CC-BY 4.0
Copyrights: The authors retain unrestricted copyrights and publishing rights
     author = {Cantalapiedra-Hijar, Gonzalo and Morel, Isabelle and Sepchat, Bernard and Chantelauze, C\'eline and Miller, Gemma A. and Duthie, Carol-Anne and Ortigues-Marty, Isabelle and Dewhurst, Richard J.},
     title = {Identifying cattle with superior growth feed efficiency through their natural {\protect\textsuperscript{15}N} abundance and plasma urea concentration: {A} meta-analysis},
     journal = {Peer Community Journal},
     eid = {e31},
     publisher = {Peer Community In},
     volume = {2},
     year = {2022},
     doi = {10.24072/pcjournal.130},
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AU  - Duthie, Carol-Anne
AU  - Ortigues-Marty, Isabelle
AU  - Dewhurst, Richard J.
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JO  - Peer Community Journal
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%A Cantalapiedra-Hijar, Gonzalo
%A Morel, Isabelle
%A Sepchat, Bernard
%A Chantelauze, Céline
%A Miller, Gemma A.
%A Duthie, Carol-Anne
%A Ortigues-Marty, Isabelle
%A Dewhurst, Richard J.
%T Identifying cattle with superior growth feed efficiency through their natural 15N abundance and plasma urea concentration: A meta-analysis
%J Peer Community Journal
%D 2022
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%R 10.24072/pcjournal.130
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Cantalapiedra-Hijar, Gonzalo; Morel, Isabelle; Sepchat, Bernard; Chantelauze, Céline; Miller, Gemma A.; Duthie, Carol-Anne; Ortigues-Marty, Isabelle; Dewhurst, Richard J. Identifying cattle with superior growth feed efficiency through their natural 15N abundance and plasma urea concentration: A meta-analysis. Peer Community Journal, Volume 2 (2022), article  no. e31. doi : 10.24072/pcjournal.130.

Peer reviewed and recommended by PCI : 10.24072/pci.animsci.100012

Conflict of interest of the recommender and peer reviewers:
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article.

[1] Ancin‐Murguzur, F. J.; Tarroux, A.; Bråthen, K. A.; Bustamante, P.; Descamps, S. Using near‐infrared reflectance spectroscopy (NIRS) to estimate carbon and nitrogen stable isotope composition in animal tissues, Ecology and Evolution, Volume 11 (2021) no. 15, pp. 10483-10488 | DOI

[2] Archer, J. A.; Arthur, P. F.; Herd, R. M.; Parnell, P. F.; Pitchford, W. S. Optimum postweaning test for measurement of growth rate, feed intake, and feed efficiency in British breed cattle., Journal of Animal Science, Volume 75 (1997) no. 8 | DOI

[3] Arthur, P.; Herd, R. Genetic improvement of feed efficiency In: R. A. Hill, editor, Feed efficiency in the beef industry, Wiley-Blackwell, Ames, IA, USA (2012), pp. 93-103

[4] Basarab, J.; Beauchemin, K.; Baron, V.; Ominski, K.; Guan, L.; Miller, S.; Crowley, J. Reducing GHG emissions through genetic improvement for feed efficiency: effects on economically important traits and enteric methane production, Animal, Volume 7 (2013), pp. 303-315 | DOI

[5] Berry, D. P.; Crowley, J. J. Cell Biology Symposium: Genetics of feed efficiency in dairy and beef cattle, Journal of Animal Science, Volume 91 (2013) no. 4, pp. 1594-1613 | DOI

[6] Cantalapiedra-Hijar, G.; Ortigues-Marty, I.; Sepchat, B.; Agabriel, J.; Huneau, J. F.; Fouillet, H. Diet–animal fractionation of nitrogen stable isotopes reflects the efficiency of nitrogen assimilation in ruminants, British Journal of Nutrition, Volume 113 (2015) no. 7, pp. 1158-1169 | DOI

[7] Cantalapiedra-Hijar, G.; Fouillet, H.; Huneau, J.; Fanchone, A.; Doreau, M.; Nozière, P.; Ortigues-Marty, I. Relationship between efficiency of nitrogen utilization and isotopic nitrogen fractionation in dairy cows: contribution of digestion v. metabolism?, Animal, Volume 10 (2016) no. 2, pp. 221-229 | DOI

[8] Cantalapiedra-Hijar, G.; Dewhurst, R.; Cheng, L.; Cabrita, A.; Fonseca, A.; Nozière, P.; Makowski, D.; Fouillet, H.; Ortigues-Marty, I. Nitrogen isotopic fractionation as a biomarker for nitrogen use efficiency in ruminants: a meta-analysis, Animal, Volume 12 (2018) no. 9, pp. 1827-1837 | DOI

[9] Cantalapiedra-Hijar, G.; Abo-Ismail, M.; Carstens, G.; Guan, L.; Hegarty, R.; Kenny, D.; McGee, M.; Plastow, G.; Relling, A.; Ortigues-Marty, I. Biological determinants of between-animal variation in feed efficiency of growing beef cattle, Animal, Volume 12 (2018) | DOI

[10] Cantalapiedra-Hijar, G.; Ortigues-Marty, I.; Sepchat, B.; Titgemeyer, E.; Bahloul, L. Methionine-balanced diets improve cattle performance in fattening young bulls fed high-forage diets through changes in nitrogen metabolism, British Journal of Nutrition, Volume 124 (2020) no. 3, pp. 273-285 | DOI

[11] Cantalapiedra-Hijar, G.; Guarnido, P.; Schiphorst, A.-M.; Robins, R. J.; Renand, G.; Ortigues-Marty, I. Natural 15N abundance in specific amino acids indicates associations between transamination rates and residual feed intake in beef cattle, Journal of Animal Science, Volume 98 (2020) no. 6 | DOI

[12] Carmelo, V. A. O.; Banerjee, P.; da Silva Diniz, W. J.; Kadarmideen, H. N. Metabolomic networks and pathways associated with feed efficiency and related-traits in Duroc and Landrace pigs, Scientific Reports, Volume 10 (2020) no. 1 | DOI

[13] Cortese; Segato; Andrighetto; Ughelini; Chinello; Schiavon; Marchesini The Effects of Decreasing Dietary Crude Protein on the Growth Performance, Feed Efficiency and Meat Quality of Finishing Charolais Bulls, Animals, Volume 9 (2019) no. 11 | DOI

[14] Cruz, G. D.; Rodríguez-Sánchez, J. A.; Oltjen, J. W.; Sainz, R. D. Performance, residual feed intake, digestibility, carcass traits, and profitability of Angus-Hereford steers housed in individual or group pens1, Journal of Animal Science, Volume 88 (2010) no. 1, pp. 324-329 | DOI

[15] da Silva, L.; Pereira, O.; da Silva, T.; Valadares Filho, S.; Ribeiro, K. Effects of silage crop and dietary crude protein levels on digestibility, ruminal fermentation, nitrogen use efficiency, and performance of finishing beef cattle, Animal Feed Science and Technology, Volume 220 (2016), pp. 22-33 | DOI

[16] Dykier, K.; Oltjen, J.; Robinson, P.; Sainz, R. Effects of finishing diet sorting and digestibility on performance and feed efficiency in beef steers, Animal, Volume 14 (2020) no. 1, pp. 59-65 | DOI

[17] Fischer, A.; Edouard, N.; Faverdin, P. Precision feed restriction improves feed and milk efficiencies and reduces methane emissions of less efficient lactating Holstein cows without impairing their performance, Journal of Dairy Science, Volume 103 (2020) no. 5, pp. 4408-4422 | DOI

[18] Foroutan, A.; Fitzsimmons, C.; Mandal, R.; Berjanskii, M. V.; Wishart, D. S. Serum Metabolite Biomarkers for Predicting Residual Feed Intake (RFI) of Young Angus Bulls, Metabolites, Volume 10 (2020) no. 12 | DOI

[19] Fuller, B. T.; Fuller, J. L.; Sage, N. E.; Harris, D. A.; O'Connell, T. C.; Hedges, R. E. M. Nitrogen balance and δ15N: why you're not what you eat during pregnancy, Rapid Communications in Mass Spectrometry, Volume 18 (2004) no. 23, pp. 2889-2896 | DOI

[20] Gabler, M.; Heinrichs, A. Dietary Protein to Metabolizable Energy Ratios on Feed Efficiency and Structural Growth of Prepubertal Holstein Heifers, Journal of Dairy Science, Volume 86 (2003) no. 1, pp. 268-274 | DOI

[21] Gaye-Siessegger, J.; Focken, U.; Muetzel, S.; Abel, H.; Becker, K. Feeding level and individual metabolic rate affect ?13C and ?15N values in carp: implications for food web studies, Oecologia, Volume 138 (2004) no. 2, pp. 175-183 | DOI

[22] Geay, Y. Energy and Protein Utilization in Growing Cattle, Journal of Animal Science, Volume 58 (1984) no. 3, pp. 766-778 | DOI

[23] Goldansaz, S. A.; Markus, S.; Berjanskii, M.; Rout, M.; Guo, A. C.; Wang, Z.; Plastow, G.; Wishart, D. S. Candidate serum metabolite biomarkers of residual feed intake and carcass merit in sheep, Journal of Animal Science, Volume 98 (2020) no. 10 | DOI

[24] Guarnido-Lopez, P.; Ortigues-Marty, I.; Taussat, S.; Fossaert, C.; Renand, G.; Cantalapiedra-Hijar, G. Plasma proteins δ15N vs plasma urea as candidate biomarkers of between-animal variations of feed efficiency in beef cattle: Phenotypic and genetic evaluation, Animal, Volume 15 (2021) no. 8 | DOI

[25] INRA INRA feeding system for ruminants, Wageningen Academic Publishers, Wageningen, the Netherlands, 2018, 640 pages

[26] Jorge-Smeding, E.; Bonnet, M.; Renand, G.; Taussat, S.; Graulet, B.; Ortigues-Marty, I.; Cantalapiedra-Hijar, G. Common and diet-specific metabolic pathways underlying residual feed intake in fattening Charolais yearling bulls, Scientific Reports, Volume 11 (2021) no. 1 | DOI

[27] Karisa, B.; Thomson, J.; Wang, Z.; Li, C.; Montanholi, Y.; Miller, S.; Moore, S.; Plastow, G. Plasma metabolites associated with residual feed intake and other productivity performance traits in beef cattle, Livestock Science, Volume 165 (2014), pp. 200-211 | DOI

[28] Kelly, A. K.; McGee, M.; Crews, D. H.; Sweeney, T.; Boland, T. M.; Kenny, D. A. Repeatability of feed efficiency, carcass ultrasound, feeding behavior, and blood metabolic variables in finishing heifers divergently selected for residual feed intake1, Journal of Animal Science, Volume 88 (2010) no. 10, pp. 3214-3225 | DOI

[29] Kohn, R. A.; Dinneen, M. M.; Russek-Cohen, E. Using blood urea nitrogen to predict nitrogen excretion and efficiency of nitrogen utilization in cattle, sheep, goats, horses, pigs, and rats1, Journal of Animal Science, Volume 83 (2005) no. 4, pp. 879-889 | DOI

[30] Liu, E.; VandeHaar, M. Relationship of residual feed intake and protein efficiency in lactating cows fed high- or low-protein diets, Journal of Dairy Science, Volume 103 (2020) no. 4, pp. 3177-3190 | DOI

[31] Meale, S. J.; Auffret, M. D.; Watson, M.; Morgavi, D. P.; Cantalapiedra-Hijar, G.; Duthie, C.-A.; Roehe, R.; Dewhurst, R. J. Fat accretion measurements strengthen the relationship between feed conversion efficiency and Nitrogen isotopic discrimination while rumen microbial genes contribute little, Scientific Reports, Volume 8 (2018) no. 1 | DOI

[32] Menezes, A.; Valadares Filho, S.; Costa e Silva, L.; Pacheco, M.; Pereira, J.; Rotta, P.; Zanetti, D.; Detmann, E.; Silva, F.; Godoi, L.; Rennó, L. Does a reduction in dietary crude protein content affect performance, nutrient requirements, nitrogen losses, and methane emissions in finishing Nellore bulls?, Agriculture, Ecosystems & Environment, Volume 223 (2016), pp. 239-249 | DOI

[33] Ben Meir, Y.; Nikbachat, M.; Portnik, Y.; Jacoby, S.; Levit, H.; Bikel, D.; Adin, G.; Moallem, U.; Miron, J.; Mabjeesh, S.; Halachmi, I. Dietary restriction improved feed efficiency of inefficient lactating cows, Journal of Dairy Science, Volume 102 (2019) no. 10, pp. 8898-8906 | DOI

[34] Ben Meir, Y.; Nikbachat, M.; Portnik, Y.; Jacoby, S.; Adin, G.; Moallem, U.; Halachmi, I.; Miron, J.; Mabjeesh, S. Effect of forage-to-concentrate ratio on production efficiency of low-efficient high-yielding lactating cows, Animal, Volume 15 (2021) no. 1 | DOI

[35] D. N. Moriasi; J. G. Arnold; M. W. Van Liew; R. L. Bingner; R. D. Harmel; T. L. Veith Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations, Transactions of the ASABE, Volume 50 (2007) no. 3, pp. 885-900 | DOI

[36] Nasrollahi, S. M.; Meale, S. J.; Morgavi, D. P.; Schiphorst, A. M.; Robins, R. J.; Ortigues-Marty, I.; Cantalapiedra-Hijar, G. The origin of N isotopic discrimination and its relationship with feed efficiency in fattening yearling bulls is diet-dependent, PLOS ONE, Volume 15 (2020) no. 6 | DOI

[37] Negussie, E.; de Haas, Y.; Dehareng, F.; Dewhurst, R.; Dijkstra, J.; Gengler, N.; Morgavi, D.; Soyeurt, H.; van Gastelen, S.; Yan, T.; Biscarini, F. Invited review: Large-scale indirect measurements for enteric methane emissions in dairy cattle: A review of proxies and their potential for use in management and breeding decisions, Journal of Dairy Science, Volume 100 (2017) no. 4, pp. 2433-2453 | DOI

[38] O’brien, R. M. A Caution Regarding Rules of Thumb for Variance Inflation Factors, Quality &amp; Quantity, Volume 41 (2007) no. 5, pp. 673-690 | DOI

[39] Pinheiro JC; Bates DM Linear mixed-effects models: basic concepts and examples. Mixed-effects models in S and S-Plus, Springer, New York, 2000

[40] R Core Team, Vienna, Austria: R Foundation for Statistical Computing. Retrieved from, 2019

[41] Remien, C. H. Modeling the dynamics of stable isotope tissue-diet enrichment, Journal of Theoretical Biology, Volume 367 (2015), pp. 14-20 | DOI

[42] Richardson, E. C.; Herd, R. M.; Archer, J. A.; Arthur, P. F. Metabolic differences in Angus steers divergently selected for residual feed intake, Australian Journal of Experimental Agriculture, Volume 44 (2004) no. 5 | DOI

[43] Sears, J.; Hatch, S. A.; O’Brien, D. M. Disentangling effects of growth and nutritional status on seabird stable isotope ratios, Oecologia, Volume 159 (2008) no. 1, pp. 41-48 | DOI

[44] Soleimani, T.; Gilbert, H. An approach to achieve overall farm feed efficiency in pig production: environmental evaluation through individual life cycle assessment, The International Journal of Life Cycle Assessment, Volume 26 (2021) no. 3, pp. 455-469 | DOI

[45] Taussat, S.; Saintilan, R.; Krauss, D.; Maupetit, D.; Fouilloux, M.-N.; Renand, G. Relationship between feed efficiency and slaughter traits of French Charolais bulls, Journal of Animal Science, Volume 97 (2019) no. 6, pp. 2308-2319 | DOI

[46] Wattiaux, M. A.; Reed, J. D. Fractionation of nitrogen isotopes by mixed ruminal bacteria., Journal of Animal Science, Volume 73 (1995) no. 1, pp. 257-266 | DOI

[47] Wheadon, N. M.; McGee, M.; Edwards, G. R.; Dewhurst, R. J. Plasma nitrogen isotopic fractionation and feed efficiency in growing beef heifers, British Journal of Nutrition, Volume 111 (2014) no. 9, pp. 1705-1711 | DOI

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