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Review: Towards the agroecological management of ruminants, pigs and poultry through the development of sustainable breeding programmes: I-selection goals and criteria

Published online by Cambridge University Press:  12 May 2016

F. Phocas ,
C. Belloc ,
J. Bidanel ,
L. Delaby ,
J. Y. Dourmad ,
B. Dumont ,
P. Ezanno ,
L. Fortun-Lamothe ,
G. Foucras  and
B. Frappat
...Show all authors
F. Phocas*
Affiliation:
GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350 Jouy-en-Josas, France
C. Belloc
Affiliation:
INRA, Oniris, LUNAM Université, UMR1300 BioEpAR, CS40706, 44307 Nantes, France
J. Bidanel
Affiliation:
IFIP-Institut du Porc, La Motte au Vicomte, 35650 Le Rheu, France
L. Delaby
Affiliation:
PEGASE, INRA, AgroCampus, 35590 Saint Gilles, France
J. Y. Dourmad
Affiliation:
PEGASE, INRA, AgroCampus, 35590 Saint Gilles, France
B. Dumont
Affiliation:
INRA, UMR1213 Herbivores, Theix, 63122 Saint Genès-Champanelle, France
P. Ezanno
Affiliation:
INRA, Oniris, LUNAM Université, UMR1300 BioEpAR, CS40706, 44307 Nantes, France
L. Fortun-Lamothe
Affiliation:
GenPhySE, INRA, INPT, Université de Toulouse, INP-ENSAT, INP-ENVT, 31326 Castanet-Tolosan, France
G. Foucras
Affiliation:
IHAP, INRA, INPT, Université de Toulouse, INP- ENVT, 31076 Toulouse, France
B. Frappat
Affiliation:
Institut de l’Elevage, 149 rue de Bercy, 75595 Paris, France
E. González-García
Affiliation:
INRA, UMR868, Systèmes d’Elevage Méditerranées et Tropicaux (SELMET), Montpellier 34060, France
D. Hazard
Affiliation:
GenPhySE, INRA, INPT, Université de Toulouse, INP-ENSAT, INP-ENVT, 31326 Castanet-Tolosan, France
C. Larzul
Affiliation:
GenPhySE, INRA, INPT, Université de Toulouse, INP-ENSAT, INP-ENVT, 31326 Castanet-Tolosan, France
S. Lubac
Affiliation:
Institut Technique de l’Aviculture, 23 rue Baldassini, 69 364 Lyon cedex 07, France
S. Mignon-Grasteau
Affiliation:
URA, INRA, 37380 Nouzilly, France
C. R. Moreno
Affiliation:
GenPhySE, INRA, INPT, Université de Toulouse, INP-ENSAT, INP-ENVT, 31326 Castanet-Tolosan, France
M. Tixier-Boichard
Affiliation:
GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350 Jouy-en-Josas, France
M. Brochard
Affiliation:
Institut de l’Elevage, 149 rue de Bercy, 75595 Paris, France
*
† E-mail: Florence.phocas@jouy.inra.fr
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Abstract

Agroecology uses natural processes and local resources rather than chemical inputs to ensure production while limiting the environmental footprint of livestock and crop production systems. Selecting to achieve a maximization of target production criteria has long proved detrimental to fitness traits. However, since the 1990s, developments in animal breeding have also focussed on animal robustness by balancing production and functional traits within overall breeding goals. We discuss here how an agroecological perspective should further shift breeding goals towards functional traits rather than production traits. Breeding for robustness aims to promote individual adaptive capacities by considering diverse selection criteria which include reproduction, animal health and welfare, and adaptation to rough feed resources, a warm climate or fluctuating environmental conditions. It requires the consideration of genotype×environment interactions in the prediction of breeding values. Animal performance must be evaluated in low-input systems in order to select those animals that are adapted to limiting conditions, including feed and water availability, climate variations and diseases. Finally, we argue that there is no single agroecological animal type, but animals with a variety of profiles that can meet the expectations of agroecology. The standardization of both animals and breeding conditions indeed appears contradictory to the agroecological paradigm that calls for an adaptation of animals to local opportunities and constraints in weakly artificialized systems tied to their physical environment.

Keywords

livestockgenotype by environment interactionagroecologyorganic farminglow-input system
Type
Review Article
Information
animal , Volume 10 , Issue 11 , November 2016 , pp. 1749 - 1759
Copyright
© The Animal Consortium 2016 

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References

Ahlman, T, Berglund, B, Rydhmer, L and Strandberg, E 2011. Culling reasons in organic and conventional dairy herds and genotype by environment interaction for longevity. Journal of Dairy Science 94, 1568–1575.Google Scholar
Ahlman, T, Ljung, M, Rydhmer, L, Röcklinsberg, H, Strandberg, E and Wallenbeck, A 2014. Differences in preferences for breeding traits between organic and conventional dairy producers in Sweden. Livestock Science 162, 5–14.Google Scholar
Alhidary, IA, Shini, S, Al Jassim, RAM and Gaughan, JB 2012. Physiological responses of Australian Merino wethers exposed to high heat load. Journal of Animal Science 90, 212–220.Google Scholar
Azoulay, Y, Druyan, S, Yadgary, L, Hadad, Y and Cahaner, A 2011. The viability and performance under hot conditions of featherless broilers versus fully feathered broilers. Poultry Science 90, 19–29.Google Scholar
Becker, EW 2007. Micro-algae as a source of protein. Biotechnology Advances 25, 207–210.Google Scholar
Bell, MJ, Potterton, SL, Graignon, J, Saunders, N, Wilcox, RH, Hunter, M, Goodman, JR and Garnsworthy, PC 2014. Variation in enteric methane emissions among cows on commercial dairy farms. Animal 8, 1540–1546.Google Scholar
Bell, MJ, Wall, E, Russell, G, Simm, G and Scott, AW 2011. The effect of improving cow productivity, fertility and longevity on the global warming potential of dairy systems. Journal of Dairy Science 94, 3662–3678.Google Scholar
Berman, A 2011. Invited review: are adaptations present to support dairy cattle productivity in warm climates? Journal of Dairy Science 94, 2147–2158.CrossRefGoogle ScholarPubMed
Bloemhof, S, Kause, A, Knol, EF, Van Arendonk, JAM and Misztal, I 2012. Heat stress effects on farrowing rate in sows: genetic parameter estimation using within-line and crossbred models. Journal Animal Science 90, 2109–2119.Google Scholar
Boettcher, PJ, Fatehi, J and Schutz, MM 2003. Genotype×environment interactions in conventional versus pasture-based dairies in Canada. Journal of Dairy Science 86, 383–389.Google Scholar
Brandt, H, Werner, DN, Baulain, U, Brade, W and Weissmann, F 2010. Genotype–environment interactions for growth and carcass traits in different pig breeds kept under conventional and organic production systems. Animal 4, 535–544.Google Scholar
Carabano, MJ, Bachagha, K, Ramon, M and Diaz, C 2014. Modeling heat stress effect on Holstein cows under hot and dry conditions: selection tools. Journal of Dairy Science 97, 7889–7904.Google Scholar
de Haas, Y, Windig, JJ, Calus, MPL, Dijkstra, J, de Haan, M, Bannink, A and Veerkamp, RF 2011. Genetic parameters for predicted methane production and potential for reducing enteric emissions through genomic selection. Journal of Dairy Science 94, 6122–6134.Google Scholar
Delaby, L, Faverdin, P, Michel, G, Disenhaus, C and Peyraud, JL 2009. Effect of different feeding strategies on lactation performance of Holstein and Normande dairy cows. Animal 3, 891–905.CrossRefGoogle ScholarPubMed
Delaby, L and Fiorelli, JL 2014. Elevages laitiers à bas intrants: entre traditions et innovations. INRA. Productions Animales 27, 123–134.Google Scholar
De Verdal, H, Mignon-Grasteau, S, Bastianelli, D, Même, N, Le Bihan-Duval, E and Narcy, A 2013a. Reducing the environmental impact of poultry breeding by genetic selection. Journal of Animal Science 91, 613–622.Google Scholar
De Verdal, H, Narcy, A, Bastianelli, D, Chapuis, H, Meme, N, Urvoix, S, Le Bihan-Duval, E and Mignon-Grasteau, S 2011. Improving the efficiency of feed utilization in poultry by selection. 2. Genetic parameters of excretion traits and correlations with anatomy of the gastro-intestinal tract and digestive efficiency. BMC Genetics 12, 10.Google Scholar
De Verdal, H, Narcy, A, Bastianelli, D, Meme, N, Urvoix, S, Collin, A, Le Bihan-Duval, E and Mignon-Grasteau, S 2013b. Genetic variability of metabolic characteristics in chickens selected for their ability to digest wheat. Journal of Animal Science 91, 2605–2615.Google Scholar
Dumont, B, Fortun-Lamothe, L, Jouven, M, Thomas, M and Tichit, M 2013. Prospects from agroecology and industrial ecology for animal production in the 21st century. Animal 7, 1028–1043.CrossRefGoogle Scholar
Dumont, B, González-García, E, Thomas, M, Fortun-Lamothe, L, Ducrot, C, Dourmad, JY and Tichit, M 2014. Forty research issues for the redesign of animal production systems in the 21st century. Animal 8, 1382–1393.Google Scholar
Ellis, S 2004. Review: the cattle major histocompatibility complex: is it unique? Veterinary Immunology and Immunopathology 102, 1–8.CrossRefGoogle ScholarPubMed
FAO 2006. Livestock’s long shadow: environmental issues and options. LEAD, FAO, Rome, Italy.Google Scholar
Flori, L, Gao, Y, Laloë, D, Lemonnier, G, Leplat, JJ, Teillaud, A, Cossalter, AM, Laffitte, J, Pinton, P, de Vaureix, C, Bouffaud, M, Mercat, MJ, Lefevre, F, Oswald, IP, Bidanel, JP and Rogel-Gaillard, C 2011. Immunity traits in pigs: substantial genetic variation and limited covariation. PLoS One 6, e22717.Google Scholar
Friggens, NC, Ingvartsen, KL and Emmans, GC 2004. Prediction of body lipid change in pregnancy and lactation. Journal of Dairy Science 87, 988–1000.Google Scholar
Fulkerson, WJ, Davison, TM, Garcia, SC, Hough, G, Goddard, ME, Dobos, R and Blockey, M 2008. Holstein-Friesian dairy cows under a predominantly grazing system: interaction between genotype and environment. Journal of Dairy Science 91, 826–839.CrossRefGoogle Scholar
Gavojdian, D, Kusza, S and Javor, A 2014. Implications of genotype by environment interactions in dairy sheep welfare. Animal Science and Biotechnologies 47, 289–295.Google Scholar
González-García, E, Gozzo de Figuereido, V, Foulquie, D, Jousserand, E, Autran, P, Camous, S, Tesniere, A, Bocquier, F and Jouven, M 2014. Circannual body reserves dynamics and metabolic profile in Romane ewes reared in a pastoral system. Domestic Animal Endocrinology 46, 37–48.CrossRefGoogle Scholar
Haile-Mariam, M, Carrick, MJ and Goddard, ME 2008. Genotype by environment interaction for fertility, survival, and milk production traits in Australian dairy cattle. Journal of Dairy Science 91, 4840–4853.Google Scholar
Hammami, H, Bormann, J, M’hamdi, N, Montaldo, HH and Gengler, N 2013. Evaluation of heat stress effects on production traits and somatic cell score of Holsteins in a temperate environment. Journal of Dairy Science 96, 1844–1855.Google Scholar
Harinder, P, Makkar, S, Tran, G, Heuzé, V and Ankers, P 2014. Review: state-of-the-art on use of insects as animal Feed. Animal Feed Science adn Techology 197, 1–33.Google Scholar
Herrero, M, Havlik, P, Valin, H, Notenbaert, A, Rufino, MC, Thornton, PK, Blümmel, M, Weiss, F, Grace, D and Obersteiner, M 2013. Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems. Proceedings of the National Academy of Sciences of the USA 110, 20888–20893.CrossRefGoogle ScholarPubMed
Huisman, AE, Brown, DJ and Fogarty, NM 2016. Ability of sire breeding values to predict progeny bodyweight, fat and muscle using various transformations across environments in terminal sire sheep breeds. Animal Production Science 56, 95–101.Google Scholar
Huquet, B, Leclerc, H and Ducrocq, V 2012. Modelling and estimation of genotype by environment interactions for production traits in French dairy cattle. Genetics Selection Evolution 44, 1–14.Google Scholar
IFOAM 2014. Organic Animal Husbandry across the world: Towards an Action Plan for development and strengthening of Organic Animal Husbandry. In Proceedings of the IAHA-Preconference and Workshop, IFOAM 18th Organic World Congress, 12 to 15 October, Istanbul, Turkey.Google Scholar
Kadowaki, H, Suzuki, E, Kojima-Shibata, C, Suzuki, K, Okamura, T, Onodera, W, Kojima-Shibata, C and Kano, H 2012. Selection for resistance to swine mycoplasmal pneumonia over 5 generations in Landrace pigs. Livesock Science 147, 20–26.Google Scholar
Kearney, JF, Schutz, MM, Boettcher, PJ and Weigel, KA 2004. Genotype×environment interaction for grazing vs. confinement. II. Health and reproduction traits. Journal of Dairy Science 87, 510–516.Google Scholar
Lamont, SJ, Pinard-van der Laan, MH, Cahaner, A, Van Der Poel, JJ and Parmentier, HK 2003. Selection for disease resistance: direct selection on the immune response. In Poultry genetics, breeding and biotechnology (ed. WM Muir and SE Aggrey), pp. 399–418. CABI, Wallingord.Google Scholar
Lawrence, AB. and Wall, E 2014. Selection for environmental fit from existing domesticated species. Revue Scientifique et Technique-Office International des Epizooties 33, 171–179.Google Scholar
Leenhouwers, JI, Ten Napel, J, Hanenberg, EHAT and Merks, JWM 2011. Breeding replacement gilts for organic pig herds. Animal 5, 615–621.Google Scholar
Littlejohn, MD, Henty, KM, Tiplady, K, Johnson, T, Harland, C, Lopdell, T, Sherlock, RG, Li, W, Lukefahr, SD, Shanks, BC, Garrick, DJ, Snell, RG, Spelman, RJ and Davis, SR 2014. Functionally reciprocal mutations of the prolactin signaling pathway define hairy and slick cattle. Nature Communications 5, 5861.Google Scholar
Mark, T 2004. Applied genetic evaluations for production and functional traits in dairy cattle. Journal of Dairy Science 87, 2641–2652.Google Scholar
Martin, C, Morgavi, DP and Doreau, M 2010. Methane mitigation in ruminants: from microbe to the farm scale. Animal 4, 351–365.CrossRefGoogle Scholar
McLaren, A, Brotherstone, S, Lambe, NR, Conington, J, Mrode, R and Bunger, L 2015. The effects of different farm environments on the performance of Texel sheep. Animal 9, 1624–1634.Google Scholar
Morris, CA 2007. A review of genetic resistance to disease in Bos taurus cattle. Veterinary Journal 174, 481–491.Google Scholar
Morris, CA, Baker, RL, Hickey, SM, Johnson, DL, Cullen, NG and Wilson, JA 1993. Evidence of genotype by environment interaction for reproductive and maternal traits in beef cattle. Animal Production 56, 69–83.Google Scholar
Mulder, HA, Veerkamp, RF, Ducro, BJ, van Arendonk, JAM and Bijma, P 2006. Optimization of dairy cattle breeding programs for different environments with genotype by environment interaction. Journal Dairy Science 89, 1740–1752.Google Scholar
Nauta, WJ, Baars, T, Groen, AF, Veerkamp, RF and Roep, D 2001. Animal breeding in organic farming. Discussion paper. Retrieved on 21 September 2015 from http://orgprints.org/4824/1/4824.pdf Google Scholar
N’Dri, AL, Mignon-Grasteau, S, Sellier, N, Tixier-Boichard, M and Beaumont, C 2007a. Interactions between the naked neck gene, sex, and fluctuating ambient temperature on heat tolerance, growth, body composition, meat quality, and sensory analysis of slow growing meat-type broilers. Livestock Science 110, 33–45.Google Scholar
N’Dri, AL, Sellier, N, Tixier-Boichard, M, Beaumont, C and Mignon-Grasteau, S 2007b. Genotype by environment interactions in relation to growth traits in slow growing chickens. Genetics. Selection and Evolution 39, 513–528.Google Scholar
Pabiou, T, Nilforooshan, M, Laloë, D, Hjerpe, E and Venot, E 2014. Across Country Genetic Parameters in Beef Cattle for Interbeef Weaning Weight Genetic Evaluation. In Proceedings 10thWorld Congress of Genetics Applied to Livestock Production, 17 to 22 August, Vancouver, BC, Canada.Google Scholar
Phocas, F, Agabriel, J, Dupont-Nivet, M, Geurden, I, Médale, F, Mignon-Grasteau, S, Gilbert, H and Dourmad, JY 2014. Le phénotypage de l’efficacité alimentaire et de ses composantes, une nécessité pour accroître l’efficience des productions animales. INRA Productions Animales 27, 235–248.Google Scholar
Phocas, F, Belloc, C, Delaby, L, Dourmad, JY, Ducrot, C, Dumont, B, Ezanno, P, Foucras, G, Gonzales-Garcia, E, Hazard, D, Lamothe, L, Larzul, C, Mignon-Grasteau, S, Moreno, CR, Tixier-Boichard, M, Brochard, M, Bidanel, J, Frappat, B and Lubac, S 2015. Outils et leviers pour favoriser le développement d’une génétique animale adaptée aux enjeux de l’agroécologie. Rapport de l’étude no. SSP-2014-061 commanditée par le Ministère de l’Agriculture, l’Alimentation et la Forêt, septembre 2015. 120 p. Available at http://agriculture.gouv.fr/outils-et-leviers-pour-favoriser-le-developpement-dune-genetique-animale-adaptee-aux-enjeux-de-lagro.Google Scholar
Pinard-van der Laan, MH, Lillehoj, HS and Zhu, JJ 2003. Genetic resistance and transmission of avian parasites. In Poultry genetics, breeding and biotechnology (ed. WM Muir and SE Aggrey), pp. 313–326. CABI, Wallingford.Google Scholar
Pinares-Patiño, CS, Hickey, SM, Young, EA, Dodds, KG, MacLean, S, Molano, G, Sandoval, E, Kjestrup, H, Harland, R, Hunt, C, Pickering, NK and McEwan, JC 2013. Heritability estimates of methane emissions from sheep. Animal 7, 316–321.Google Scholar
Rauw, WM, Kanis, E, Noordhuizen-Stassen, EN and Grommers, FJ. 1998. Undesirable side effects of selection for high production efficiency in farm animals: a review. Livestock Production Science 56, 15–33.Google Scholar
Renaudeau, D, Huc, E and Noblet, J 2007. Acclimation to high ambient temperature in Large White and Caribbean Creole growing pigs. Journal of Animal Science 85, 779–790.Google Scholar
Robertson, A 1959. The sampling variance of the genetic correlation coefficient. Biometrics 15, 469–485.CrossRefGoogle Scholar
Rupp, R, Bergonier, D, Dion, S, Hygoneng, MC, Aurel, MR, Robert-Granié, C and Foucras, G 2009. Response to somatic cell count-based selection for mastitis resistance in a divergent selection experiment in sheep. Journal of Dairy Science 92, 1203–1219.Google Scholar
Strandberg, E, Brotherstone, S, Wall, E and Coffey, MP 2009. Genotype by environment interaction for first-lactation female fertility traits in UK dairy cattle. Journal of Dairy Science 92, 3437–3446.Google Scholar
Thompson-Crispi, KA, Hine, B, Quinton, M, Miglior, F and Mallard, BA 2012b. Short communication: association of disease incidence and adaptive immune response in Holstein dairy cows. Journal of Dairy Science 95, 3888–3893.Google Scholar
Thompson-Crispi, KA, Sewalem, A, Miglior, F and Mallard, BA 2012a. Genetic parameters of adaptive immune response traits in Canadian Holsteins. Journal of Dairy Science 95, 401–409.Google Scholar
Thornton, PK 2010. Livestock production: recent trends, future prospects. Philosophical Transactions of the Royal Society B 365, 2853–2867.Google Scholar
Wallenbeck, A, Gustafson, G and Rydhmer, L 2009a. Sow performance and maternal behaviour in organic and conventional herds. Acta Agriculturae Scandinavica 59, 181–191.Google Scholar
Wallenbeck, A, Rydhmer, L and Lundeheim, N 2009b. G×E interactions for growth and carcass leanness: re-ranking of boars in organic and conventional pig production. Livestock Science 123, 154–160.Google Scholar
Wallenbeck, A, Rydhmer, L, Röcklinsberg, H, Ljung, M, Strandberg, E and Ahlman, T 2015. Preferences for pig breeding goals among organic and conventional farmers in Sweden. Organic Agriculture 5, 1–12.Google Scholar
Warner, CM, Meeker, DL and Rothschild, MF 1986. Genetic control of immune responsiveness: a review of Its use as a tool for selection for disease resistance. Journal of Animal Science 64, 394–406.Google Scholar
Wilkie, B and Mallard, B 1999. Selection for high immune response: an alternative approach to animal health maintenance? Veterinary Immunology and Immunopathology 72, 231–235.Google Scholar
Yin, T, Bapst, B, Borstel, UUV, Simianer, H and König, S 2012. Genetic parameters for Gaussian and categorical traits in organic and low input dairy cattle herds based on random regression methodology. Livestock Science 147, 159–169.Google Scholar
Zerjal, T, Gourichon, D, Rivet, B and Bordas, A 2013. Performance comparison of laying hens segregating for the frizzle gene under thermoneutral and high ambient temperatures. Poultry Science 92, 1474–1485.Google Scholar