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

Florence Phocas, Catherine Belloc, Joël Bidanel, Luc Delaby, Jean-Yves Dourmad, Bertrand Dumont, Pauline Ezanno, Laurence Lamothe, Gilles Foucras, Brigitte Frappat, et al.

► To cite this version:

Florence Phocas, Catherine Belloc, Joël Bidanel, Luc Delaby, Jean-Yves Dourmad, et al. Review: Towards the agroecological management of ruminants, pigs and poultry through the development of sustainable breeding programmes: I-selection goals and criteria. Animal, 2016, 10 (11), pp.1749-1759. 10.1017/S1751731116000926. hal-01533895

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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

Florence Phocas, Catherine Belloc, Joël Bidanel, Luc Delaby, Jean-Yves Dourmad, Bertrand Dumont, Pauline Ezanno, Laurence Lamothe, Gilles Foucras, Brigitte Frappat, et al.

► To cite this version:

Florence Phocas, Catherine Belloc, Joël Bidanel, Luc Delaby, Jean-Yves Dourmad, et al. Review: Towards the agroecological management of ruminants, pigs and poultry through the development of sustainable breeding programmes: I-selection goals and criteria. Animal, 2016, 10 (11), pp.1749-1759. 10.1017/S1751731116000926. hal-01533895

HAL Id: hal-01533895

https://hal.science/hal-01533895v1

Submitted on 10 Jan 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
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<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
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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

F. Phocas<fnref n="1" />†, C. Belloc², J. Bidanel³, L. Delaby⁴, J. Y. Dourmad⁴, B. Dumont⁵, P. Ezanno², L. Fortun-Lamothe⁶, G. Foucras⁷, B. Frappat⁸, E. González-García⁹, D. Hazard⁶, C. Larzul⁶, S. Lubac¹⁰, S. Mignon-Grasteau¹¹, C. R. Moreno⁶, M. Tixier-Boichard<fnref n="1" /> and M. Brochard⁸

(Received 2 November 2015; Accepted 15 April 2016; First published online 12 May 2016)

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:** livestock, genotype by environment interaction, agroecology, organic farming, low-input system

## Implications

This paper explains which of the current selection criteria are relevant to agroecology, namely fertility, animal health and welfare, and adaptation to roughage, a warm climate or fluctuating environmental conditions. It offers clues for breeders who wish to combine these criteria in order to improve animal robustness under agroecological systems, and explains how new criteria can be determined in order to target improved animal health and adaptation to harsh environments. Whereas similar selection criteria are important to all livestock sectors, this paper describes the variable impacts of genotype by environment interactions in

ruminants, pigs and poultry, and recommends that these interactions should be taken into account in the prediction of breeding values.

## Introduction

Industrial livestock farming systems are criticized as being unsustainable because of their contributions to greenhouse gas emissions, environment pollution and biodiversity losses, and because feeding livestock using crop resources directly competes with human food production (FAO, 2006; Herrero et al., 2013). Livestock production systems will thus increasingly be constrained by the need to operate in a carbon-constrained economy and to cope with changing

<footnote n="1">¹GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350 Jouy-en-Josas, France; ²INRA, Oniris, LUNAM Université, UMR1300 BioEpAR, CS40706, 44307 Nantes, France; ³IFIP-Institut du Porc, La Motte au Vicomte, 35650 Le Rheu, France; ⁴PEGASE, INRA, AgroCampus, 35590 Saint Gilles, France; ⁵INRA, UMR1213 Herbivores, Theix, 63122 Saint Genès-Champanelle, France; ⁶GenPhySE, INRA, INPT, Université de Toulouse, INP-ENSAT, INP-ENVT, 31326 Castanet-Tolosan, France; ⁷IHAP, INRA, INPT, Université de Toulouse, INP-ENVT, 31076 Toulouse, France; ⁸Institut de l'Elevage, 149 rue de Bercy, 75595 Paris, France; ⁹INRA, UMR868, Systèmes d'Elevage Méditerranées et Tropicaux (SELMET), Montpellier 34060, France; ¹⁰Institut Technique de l'Aviculture, 23 rue Baldassini, 69 364 Lyon cedex 07, France; ¹¹URA, INRA, 37380 Nouzilly, France</footnote>

<footnote>† E-mail: Florence.phocas@jouy.inra.fr</footnote>
# Review: Towards the agroecological management of ruminants, pigs and poultry through the development of sustainable breeding programmes: I-selection goals and criteria

F. Phocas<fnref n="1" />†, C. Belloc², J. Bidanel³, L. Delaby⁴, J. Y. Dourmad⁴, B. Dumont⁵, P. Ezanno², L. Fortun-Lamothe⁶, G. Foucras⁷, B. Frappat⁸, E. González-García⁹, D. Hazard⁶, C. Larzul⁶, S. Lubac¹⁰, S. Mignon-Grasteau¹¹, C. R. Moreno⁶, M. Tixier-Boichard<fnref n="1" /> and M. Brochard⁸

(Received 2 November 2015; Accepted 15 April 2016; First published online 12 May 2016)

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:** livestock, genotype by environment interaction, agroecology, organic farming, low-input system

## Implications

This paper explains which of the current selection criteria are relevant to agroecology, namely fertility, animal health and welfare, and adaptation to roughage, a warm climate or fluctuating environmental conditions. It offers clues for breeders who wish to combine these criteria in order to improve animal robustness under agroecological systems, and explains how new criteria can be determined in order to target improved animal health and adaptation to harsh environments. Whereas similar selection criteria are important to all livestock sectors, this paper describes the variable impacts of genotype by environment interactions in

ruminants, pigs and poultry, and recommends that these interactions should be taken into account in the prediction of breeding values.

## Introduction

Industrial livestock farming systems are criticized as being unsustainable because of their contributions to greenhouse gas emissions, environment pollution and biodiversity losses, and because feeding livestock using crop resources directly competes with human food production (FAO, 2006; Herrero et al., 2013). Livestock production systems will thus increasingly be constrained by the need to operate in a carbon-constrained economy and to cope with changing

<footnote n="1">¹GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350 Jouy-en-Josas, France; ²INRA, Oniris, LUNAM Université, UMR1300 BioEpAR, CS40706, 44307 Nantes, France; ³IFIP-Institut du Porc, La Motte au Vicomte, 35650 Le Rheu, France; ⁴PEGASE, INRA, AgroCampus, 35590 Saint Gilles, France; ⁵INRA, UMR1213 Herbivores, Theix, 63122 Saint Genès-Champanelle, France; ⁶GenPhySE, INRA, INPT, Université de Toulouse, INP-ENSAT, INP-ENVT, 31326 Castanet-Tolosan, France; ⁷IHAP, INRA, INPT, Université de Toulouse, INP-ENVT, 31076 Toulouse, France; ⁸Institut de l'Elevage, 149 rue de Bercy, 75595 Paris, France; ⁹INRA, UMR868, Systèmes d'Elevage Méditerranées et Tropicaux (SELMET), Montpellier 34060, France; ¹⁰Institut Technique de l'Aviculture, 23 rue Baldassini, 69 364 Lyon cedex 07, France; ¹¹URA, INRA, 37380 Nouzilly, France</footnote>

<footnote>† E-mail: Florence.phocas@jouy.inra.fr</footnote>
environmental and socio-cultural values. Nevertheless, agroecology cannot be developed if both market and societal expectations are not taken into account at the same time as the economic viability of farms. In developed countries, the consumption of meat and milk products is stagnating (Thornton, 2010) and many production systems are trying to increase their efficiency while simultaneously limiting their environmental footprint (Herrero et al., 2013). Agroecology offers a scientific and operational framework to move animal production systems towards greater sustainability. In its scientific definition, agroecology applies the concepts and principles of ecology to the design and management of sustainable agro-ecosystems. It can be broken down into a set of practices that aim to stimulate natural processes in order to design production systems that are weakly artificialized, environmentally friendly and less dependent on inputs, particularly those of a chemical nature. Dumont et al. (2013) considered the prospects for agroecology across a broad diversity of livestock systems and proposed five principles to be optimized in livestock production systems: (i) achieve integrated animal health management, (ii) decrease the external inputs needed for production, (iii) decrease pollution by optimizing the metabolic functioning of farming systems, (iv) enhance diversity within livestock production systems to strengthen their resilience and efficiency and (v) preserve biological diversity by adapting management at the farm and landscape scales. Each of these principles is based on ecological processes, so that animal husbandry is perceived through a paradigm which is derived from ecology. These principles could then be used as guidelines when introducing combinations of agroecological practices into the design of farming systems adapted to local conditions.

Agroecology thus pays particular attention to diversity. Animal genetic resources and local breeds offer opportunities to adapt livestock to constrained feeding environments, so that their preservation is highly relevant when developing agroecological systems (Dumont et al., 2013). There is currently much debate about the type of animals that would best fit these systems. It is uncertain whether animals which have been bred for conventional systems are able to survive, reproduce and maintain production in less controlled environments. Quantitative genetics, genomics and reproduction technologies have transformed animal breeding from a small-scale farm-based or regional activity into a global system based on standardized practices, particularly in the pig and poultry sectors but also in cattle. Farmers use reproducers from a single selection programme, or in other words animals bred for high added value in a conventional production environment (Nauta et al., 2001). By contrast, agroecology calls for animals with different performance characteristics and the need to breed for robustness across environments. The main challenges are to identify sets of selection criteria that are highly correlated with animal robustness, and to consider genotype × environment interactions in the prediction of breeding values (Dumont et al., 2014). However, the literature on breeding goals and selection criteria that can match the requirements of farmers

engaged in low-input production systems is very scarce; only four studies have addressed these issues to date. Three of them dealt with organic farming, either using a general approach across livestock sectors and countries (IFOAM, 2014), or an approach focussed on particular livestock systems in Sweden, that is milk production (Ahlman et al., 2014) and pig production (Wallenbeck et al., 2015). The fourth survey was recently carried out in France on the ruminant, pig, and poultry sectors, at the request of the Ministry of Agriculture. Representatives of breeding schemes and breeders already involved in agroecological transition were interviewed about their breeding goals and strategies (Phocas et al., 2015); the survey outputs are summarized in this paper. The aim of the present review is therefore to offer insights into breeding goals and selection criteria that may help to provide farmers with animals which are better suited to agroecological systems. While adapting animals to less controlled environments is a key common objective, analyzing breeding goals in ruminants, pigs and poultry at the same time will clarify the differences between generic and specific objectives and criteria across sectors. It should be noted that the methods used to determine breeding objectives in developing countries differ somewhat from those applied in developed countries, where they are more clearly determined by strong market signals. Breeding objectives for smallholder production systems in developing countries need to take account of the usually harsher environmental conditions, while considering the broad range of socio-economic and cultural values attached to livestock in different societies, including the keeping of livestock for finance and insurance or religious purposes, etc. We have therefore limited the scope of this review to developed (mostly temperate) countries.

## Are the traits selected in conventional breeding still relevant to livestock production systems based on agroecological principles?

Between the early 1960s and the mid-2000s, carcass weights rose by about 30% in chickens and beef cattle, and by 20% in pigs. Increases in milk production per animal reached around 30% for cows' milk, about the same as the rise in egg production per chicken over the same period (Thornton, 2010). Since the 1990s, genetic improvement programmes have gradually been reoriented towards reducing production costs and accounting for societal and environmental expectations with respect to product quality and image, the limitation of pollution, biodiversity conservation and animal welfare. This reorientation has involved an increasing number of traits being included in the breeding goals of a population, as illustrated in Figure 1 relative to the meat production sector in France. The inclusion of a new trait is performed cumulatively in a breeding programme: the new trait complements those already selected, and the weight given to each trait in the breeding goal varies over time in line with evolutions in the socio-economic context and the
environmental and socio-cultural values. Nevertheless, agroecology cannot be developed if both market and societal expectations are not taken into account at the same time as the economic viability of farms. In developed countries, the consumption of meat and milk products is stagnating (Thornton, 2010) and many production systems are trying to increase their efficiency while simultaneously limiting their environmental footprint (Herrero et al., 2013). Agroecology offers a scientific and operational framework to move animal production systems towards greater sustainability. In its scientific definition, agroecology applies the concepts and principles of ecology to the design and management of sustainable agro-ecosystems. It can be broken down into a set of practices that aim to stimulate natural processes in order to design production systems that are weakly artificialized, environmentally friendly and less dependent on inputs, particularly those of a chemical nature. Dumont et al. (2013) considered the prospects for agroecology across a broad diversity of livestock systems and proposed five principles to be optimized in livestock production systems: (i) achieve integrated animal health management, (ii) decrease the external inputs needed for production, (iii) decrease pollution by optimizing the metabolic functioning of farming systems, (iv) enhance diversity within livestock production systems to strengthen their resilience and efficiency and (v) preserve biological diversity by adapting management at the farm and landscape scales. Each of these principles is based on ecological processes, so that animal husbandry is perceived through a paradigm which is derived from ecology. These principles could then be used as guidelines when introducing combinations of agroecological practices into the design of farming systems adapted to local conditions.

Agroecology thus pays particular attention to diversity. Animal genetic resources and local breeds offer opportunities to adapt livestock to constrained feeding environments, so that their preservation is highly relevant when developing agroecological systems (Dumont et al., 2013). There is currently much debate about the type of animals that would best fit these systems. It is uncertain whether animals which have been bred for conventional systems are able to survive, reproduce and maintain production in less controlled environments. Quantitative genetics, genomics and reproduction technologies have transformed animal breeding from a small-scale farm-based or regional activity into a global system based on standardized practices, particularly in the pig and poultry sectors but also in cattle. Farmers use reproducers from a single selection programme, or in other words animals bred for high added value in a conventional production environment (Nauta et al., 2001). By contrast, agroecology calls for animals with different performance characteristics and the need to breed for robustness across environments. The main challenges are to identify sets of selection criteria that are highly correlated with animal robustness, and to consider genotype × environment interactions in the prediction of breeding values (Dumont et al., 2014). However, the literature on breeding goals and selection criteria that can match the requirements of farmers

engaged in low-input production systems is very scarce; only four studies have addressed these issues to date. Three of them dealt with organic farming, either using a general approach across livestock sectors and countries (IFOAM, 2014), or an approach focussed on particular livestock systems in Sweden, that is milk production (Ahlman et al., 2014) and pig production (Wallenbeck et al., 2015). The fourth survey was recently carried out in France on the ruminant, pig, and poultry sectors, at the request of the Ministry of Agriculture. Representatives of breeding schemes and breeders already involved in agroecological transition were interviewed about their breeding goals and strategies (Phocas et al., 2015); the survey outputs are summarized in this paper. The aim of the present review is therefore to offer insights into breeding goals and selection criteria that may help to provide farmers with animals which are better suited to agroecological systems. While adapting animals to less controlled environments is a key common objective, analyzing breeding goals in ruminants, pigs and poultry at the same time will clarify the differences between generic and specific objectives and criteria across sectors. It should be noted that the methods used to determine breeding objectives in developing countries differ somewhat from those applied in developed countries, where they are more clearly determined by strong market signals. Breeding objectives for smallholder production systems in developing countries need to take account of the usually harsher environmental conditions, while considering the broad range of socio-economic and cultural values attached to livestock in different societies, including the keeping of livestock for finance and insurance or religious purposes, etc. We have therefore limited the scope of this review to developed (mostly temperate) countries.

## Are the traits selected in conventional breeding still relevant to livestock production systems based on agroecological principles?

Between the early 1960s and the mid-2000s, carcass weights rose by about 30% in chickens and beef cattle, and by 20% in pigs. Increases in milk production per animal reached around 30% for cows' milk, about the same as the rise in egg production per chicken over the same period (Thornton, 2010). Since the 1990s, genetic improvement programmes have gradually been reoriented towards reducing production costs and accounting for societal and environmental expectations with respect to product quality and image, the limitation of pollution, biodiversity conservation and animal welfare. This reorientation has involved an increasing number of traits being included in the breeding goals of a population, as illustrated in Figure 1 relative to the meat production sector in France. The inclusion of a new trait is performed cumulatively in a breeding programme: the new trait complements those already selected, and the weight given to each trait in the breeding goal varies over time in line with evolutions in the socio-economic context and the
<figure><img src="image_3.png" /><figcaption>**Figure 1** Historical evolution of breeding goals in livestock selection programmes for meat production.</figcaption></figure>

introduction of new selection criteria. Such a reorientation becomes even more crucial as adverse effects on functional traits such as health and reproduction have been observed due to intensive selection on production traits (Rauw *et al.*, 1998). Therefore, during the past decade, there has been growing interest in selecting for robustness in farm animals (Lawrence and Wall, 2014). To improve the robustness of animals involved in a production process, breeding goals now are constituted by a combination of traits related to the biological functions of production, reproduction, survival, health and welfare.

To determine whether current breeding goals are aligned or not with the expectations of farmers who are already applying agroecological principles, 62 semi-structured interviews concerning selection priorities for developing agroecological livestock production systems were conducted with French breeders (47) and representatives of breeding programmes (15) in the ruminant, pig and poultry sectors (Phocas et al., 2015). The 47 farmers were sampled because they were already applying agroecology principles to management of their systems. They were asked to rank (from 1: lowest priority to 8: highest priority) the following eight groups of breeding goals: 'Health', 'Reproduction', 'Robustness', 'Efficiency and Production', 'Wastes in the environment', 'Genetic originality', 'Product Quality' and 'Behaviour and Welfare'. All the interviewees shared general priorities across the species (Figure 2); namely the need to produce animals resilient to sanitary risks that are also efficient in feed use, reproduce well and are easy to raise (animal behaviour).

## Breeding goals for ruminants

In ruminant sectors, farmers play an important role in animal selection at either an individual level when replacing females in their herd or at a collective level in terms of breeding

Agroecological breeding goals for livestock

<figure><img src="image_4.png" /><figcaption>**Figure 2** Agroecological priorities (8 ranking highest) among the different animal characteristics in breeding goals, according to French breeders and representatives from livestock breeding programmes.</figcaption></figure>

programmes for AI males when breeding companies are cooperatives owned by farmers (which is frequently the case, at least in European countries). Their expectations are therefore naturally taken into account. The first expectation for farmers is efficient production. Furthermore, the need for simplified farming practices becomes a priority as herd and farm sizes increase. The aim is to produce more autonomous animals that are easy to breed (unassisted calving or lambing, docile animals, etc.), with good reproduction performance (fertility, maternal qualities), good disease resistance and good feed efficiency in order to limit inputs while achieving targeted growth rates or milk yields. In meat sectors, the traits of principal interest are carcass weight and conformation, a lack of fat cover and meat organoleptic qualities (tenderness, flavour). In dairy production, the most important traits are milk production (milk yield, protein and fat content), functional abilities (udder health, fertility, longevity, etc.), and conformation traits. In general, the expectations expressed by farmers who apply agroecological practices in France (Phocas et al., 2015) cover a range of traits for which genetic evaluations are available in French ruminant sectors (dairy and suckling cows, dairy and meat ewes and dairy goats), with the important exception of feed efficiency for roughage. Farmers do not like to establish priorities (as shown in Figure 2) among the various animal performance characteristics, but prefer to speak of balanced characteristics and an overall capacity for productive efficiency. Such a combination of performance characteristics is very often referred to as robustness or 'hardiness' by farmers. One notable exception concerns the limitation of wastes in the environment, which is not considered to be a direct selection objective, but only a favourable consequence of selection for animal feed efficiency.
<figure><img src="image_2.png" /><figcaption>**Figure 1** Historical evolution of breeding goals in livestock selection programmes for meat production.</figcaption></figure>

introduction of new selection criteria. Such a reorientation becomes even more crucial as adverse effects on functional traits such as health and reproduction have been observed due to intensive selection on production traits (Rauw *et al.*, 1998). Therefore, during the past decade, there has been growing interest in selecting for robustness in farm animals (Lawrence and Wall, 2014). To improve the robustness of animals involved in a production process, breeding goals now are constituted by a combination of traits related to the biological functions of production, reproduction, survival, health and welfare.

To determine whether current breeding goals are aligned or not with the expectations of farmers who are already applying agroecological principles, 62 semi-structured interviews concerning selection priorities for developing agroecological livestock production systems were conducted with French breeders (47) and representatives of breeding programmes (15) in the ruminant, pig and poultry sectors (Phocas *et al.*, 2015). The 47 farmers were sampled because they were already applying agroecology principles to management of their systems. They were asked to rank (from 1: lowest priority to 8: highest priority) the following eight groups of breeding goals: 'Health', 'Reproduction', 'Robustness', 'Efficiency and Production', 'Wastes in the environment', 'Genetic originality', 'Product Quality' and 'Behaviour and Welfare'. All the interviewees shared general priorities across the species (Figure 2); namely the need to produce animals resilient to sanitary risks that are also efficient in feed use, reproduce well and are easy to raise (animal behaviour).

## Breeding goals for ruminants

In ruminant sectors, farmers play an important role in animal selection at either an individual level when replacing females in their herd or at a collective level in terms of breeding

<figure><img src="image_3.png" /><figcaption>**Figure 2** Agroecological priorities (8 ranking highest) among the different animal characteristics in breeding goals, according to French breeders and representatives from livestock breeding programmes.</figcaption></figure>

programmes for AI males when breeding companies are cooperatives owned by farmers (which is frequently the case, at least in European countries). Their expectations are therefore naturally taken into account. The first expectation for farmers is efficient production. Furthermore, the need for simplified farming practices becomes a priority as herd and farm sizes increase. The aim is to produce more autonomous animals that are easy to breed (unassisted calving or lambing, docile animals, etc.), with good reproduction performance (fertility, maternal qualities), good disease resistance and good feed efficiency in order to limit inputs while achieving targeted growth rates or milk yields. In meat sectors, the traits of principal interest are carcass weight and conformation, a lack of fat cover and meat organoleptic qualities (tenderness, flavour). In dairy production, the most important traits are milk production (milk yield, protein and fat content), functional abilities (udder health, fertility, longevity, etc.), and conformation traits. In general, the expectations expressed by farmers who apply agroecological practices in France (Phocas et al., 2015) cover a range of traits for which genetic evaluations are available in French ruminant sectors (dairy and suckling cows, dairy and meat ewes and dairy goats), with the important exception of feed efficiency for roughage. Farmers do not like to establish priorities (as shown in Figure 2) among the various animal performance characteristics, but prefer to speak of balanced characteristics and an overall capacity for productive efficiency. Such a combination of performance characteristics is very often referred to as robustness or 'hardiness' by farmers. One notable exception concerns the limitation of wastes in the environment, which is not considered to be a direct selection objective, but only a favourable consequence of selection for animal feed efficiency.
A critical examination of the current selection index based on conventional dairy production and expectations of Swedish dairy producers in terms of organic production (Ahlman et al., 2014) also showed that the same traits are important to all breeders, irrespective of their production systems, although organic farmers give slightly more importance to health traits (especially resistance to mastitis and parasites) and place less emphasis on milk production. By comparing the main reasons for culling between conventional and organic dairy farms in Sweden, Ahlman et al. (2011) showed that the principal causes were the same in both systems, although their ranking differed slightly. Under conventional breeding, the leading reason for cow culling during first or second lactations was fertility (25% of culling), followed by udder health (22%). In an organic setting, this order was reversed, with 31% for udder health and 22% for fertility. This could be explained in part by the limits on the use of drugs in organic systems, and in part by the lower production targets of organic systems, which have a greater reliance on grass and harvested forage in the diet of animals. Insufficient production was the third reason for culling (6% in the Holstein breed), with comparable levels between systems but with different rates between breeds, being higher for insufficient production in the least productive breeds (10% to 11% for Swedish Red).

### Breeding goals in pig and poultry species

In pigs and poultry, pure-bred lines are used to produce cross-breds for the market. In terms of the future expectations of conventional farmers regarding improvements to livestock productivity by reducing feed inputs, veterinary costs and labour in the monogastric sectors, selection still needs to focus on enhancing production and reproduction traits. In sire lines, this includes improving feed efficiency and increasing growth rate and the lean content of carcasses, while maintaining technological quality of the product (ham in pigs, meat in broiler poultry and eggs in laying hens), while in maternal lines the goal is to increase the profligacy of sows and laying poultry. In addition, selection is taking account of the feed efficiency of growing animals, the maternal abilities of sows, and more generally the health of animals. Interviews conducted with actors in the French pig sector (Phocas et al., 2015) revealed that the animal performance characteristics sought by pig farmers primarily concerned health, regardless of the production system (outdoor, organic, conventional agriculture), the aim being to sustain good stability of the herd microbism. A desire to reduce or suppress the use of veterinary health products was consistently cited. Animal robustness was the second priority of pig breeders, with farmers wanting animals to cope with their environment and perform well. Animal behaviour was identified as the third leading priority for farmers, who mentioned sow autonomy and an absence of aggressive animals from the herd (Figure 2).

In the poultry sector, the same interests were expressed as by pig breeders, with priority being given to improving health traits, followed by robustness and animal behaviour traits,

while at the same time enabling a continuous improvement in production efficiency (Figure 2). However, priorities are different according to the stage considered in the sector. The selection stage concerns a small number of breeding companies which ensure the selection of pure lines and choose the crosses to be made in response to downstream demand and to balance their often conflicting priorities to achieve the best product compromise. The hatching stage opts for selection criteria targeting reproduction to obtain the optimum number and quality of day-old chicks. Producer groups choose cross-breds to supply their farmers from the lists proposed by hatcheries. Their aim is to further improve feed efficiency in order to reduce production costs. For egg production, they also wish to reduce behavioural problems that lead to high mortality rates. The role of farmers is minimal when it comes to choosing the genotypes because they are affiliated to a producer group that supplies the chicks. Through technical monitoring, the producer group gains a global vision of production and animal requirements, and presents its observations and demands to the hatchery and breeding company. In this context, independent farmers do not have sufficient power to influence the genetic policies adopted by breeding companies.

Generally speaking, whatever the sector and production system, all studies have emphasized the fact that the traits of central interest to breeders are those that affect the robustness of animals, especially their health and ability to reproduce well in more fluctuating environments, and their feed efficiency. For these reasons, the answer to the initial question is: yes, the traits selected during conventional breeding are still relevant to livestock production systems based on agroecological principles. However the weightings in overall breeding goals may differ as a function of production systems. These weightings can either be obtained through surveys (Ahlman et al., 2014; Wallenbeck et al., 2015) or derived from bio-economic models that consider different production systems (Leenhouwers et al., 2011).

### Selection for environmental fit

Because agroecological farming conditions are less controlled and fluctuate more than industrial conditions, the objective is to obtain animals whose performance is less sensitive to environmental changes (Dumont et al., 2014). The concept of robustness therefore relates to the assessment of genotype by environment (G × E) interactions, which can provide indicators of animal adaptability across a broad range of environments, that is environmental sensitivity. The primary breeding goals, and the development of corresponding selection criteria for low-input systems, are therefore strongly dependent on G × E interactions. The greater the differences between high-input and low-input systems, the less likely it is that the same performance characteristics will be targeted. In addition, the conditions to measure selection criteria should be those that are targeted for breeding in the event of significant G × E interactions.
A critical examination of the current selection index based on conventional dairy production and expectations of Swedish dairy producers in terms of organic production (Ahlman et al., 2014) also showed that the same traits are important to all breeders, irrespective of their production systems, although organic farmers give slightly more importance to health traits (especially resistance to mastitis and parasites) and place less emphasis on milk production. By comparing the main reasons for culling between conventional and organic dairy farms in Sweden, Ahlman et al. (2011) showed that the principal causes were the same in both systems, although their ranking differed slightly. Under conventional breeding, the leading reason for cow culling during first or second lactations was fertility (25% of culling), followed by udder health (22%). In an organic setting, this order was reversed, with 31% for udder health and 22% for fertility. This could be explained in part by the limits on the use of drugs in organic systems, and in part by the lower production targets of organic systems, which have a greater reliance on grass and harvested forage in the diet of animals. Insufficient production was the third reason for culling (6% in the Holstein breed), with comparable levels between systems but with different rates between breeds, being higher for insufficient production in the least productive breeds (10% to 11% for Swedish Red).

### Breeding goals in pig and poultry species

In pigs and poultry, pure-bred lines are used to produce cross-breds for the market. In terms of the future expectations of conventional farmers regarding improvements to livestock productivity by reducing feed inputs, veterinary costs and labour in the monogastric sectors, selection still needs to focus on enhancing production and reproduction traits. In sire lines, this includes improving feed efficiency and increasing growth rate and the lean content of carcasses, while maintaining technological quality of the product (ham in pigs, meat in broiler poultry and eggs in laying hens), while in maternal lines the goal is to increase the profligacy of sows and laying poultry. In addition, selection is taking account of the feed efficiency of growing animals, the maternal abilities of sows, and more generally the health of animals. Interviews conducted with actors in the French pig sector (Phocas et al., 2015) revealed that the animal performance characteristics sought by pig farmers primarily concerned health, regardless of the production system (outdoor, organic, conventional agriculture), the aim being to sustain good stability of the herd microbism. A desire to reduce or suppress the use of veterinary health products was consistently cited. Animal robustness was the second priority of pig breeders, with farmers wanting animals to cope with their environment and perform well. Animal behaviour was identified as the third leading priority for farmers, who mentioned sow autonomy and an absence of aggressive animals from the herd (Figure 2).

In the poultry sector, the same interests were expressed as by pig breeders, with priority being given to improving health traits, followed by robustness and animal behaviour traits,

while at the same time enabling a continuous improvement in production efficiency (Figure 2). However, priorities are different according to the stage considered in the sector. The selection stage concerns a small number of breeding companies which ensure the selection of pure lines and choose the crosses to be made in response to downstream demand and to balance their often conflicting priorities to achieve the best product compromise. The hatching stage opts for selection criteria targeting reproduction to obtain the optimum number and quality of day-old chicks. Producer groups choose cross-breds to supply their farmers from the lists proposed by hatcheries. Their aim is to further improve feed efficiency in order to reduce production costs. For egg production, they also wish to reduce behavioural problems that lead to high mortality rates. The role of farmers is minimal when it comes to choosing the genotypes because they are affiliated to a producer group that supplies the chicks. Through technical monitoring, the producer group gains a global vision of production and animal requirements, and presents its observations and demands to the hatchery and breeding company. In this context, independent farmers do not have sufficient power to influence the genetic policies adopted by breeding companies.

Generally speaking, whatever the sector and production system, all studies have emphasized the fact that the traits of central interest to breeders are those that affect the robustness of animals, especially their health and ability to reproduce well in more fluctuating environments, and their feed efficiency. For these reasons, the answer to the initial question is: yes, the traits selected during conventional breeding are still relevant to livestock production systems based on agroecological principles. However the weightings in overall breeding goals may differ as a function of production systems. These weightings can either be obtained through surveys (Ahlman et al., 2014; Wallenbeck et al., 2015) or derived from bio-economic models that consider different production systems (Leenhouwers et al., 2011).

### Selection for environmental fit

Because agroecological farming conditions are less controlled and fluctuate more than industrial conditions, the objective is to obtain animals whose performance is less sensitive to environmental changes (Dumont et al., 2014). The concept of robustness therefore relates to the assessment of genotype by environment (G × E) interactions, which can provide indicators of animal adaptability across a broad range of environments, that is environmental sensitivity. The primary breeding goals, and the development of corresponding selection criteria for low-input systems, are therefore strongly dependent on G × E interactions. The greater the differences between high-input and low-input systems, the less likely it is that the same performance characteristics will be targeted. In addition, the conditions to measure selection criteria should be those that are targeted for breeding in the event of significant G × E interactions.
Assessment of the importance of these is therefore an pre-
requisite to answering the question as to whether animals
bred for conventional farming are suitable for agroecological
farming systems. Before 2001, no scientific attempts were
made to compare the possible G×E interactions affecting
functional and production traits between conventional and
low-input production systems in temperate countries (Nauta
et al., 2001).

Genotype by environment interactions in ruminant species

Research projects based on long-term experiments are often
designed to assess different types (breeds, genetic values)
of animals in controlled environments that are generally
differentiated by their nutrient inputs (energy and protein
contents using the same feed ingredients, or not). The
interactions studied mainly concern production traits (lacta-
tion, growth), and sometimes reproduction and health.
Performance-related studies conducted in commercial cattle
farms analyze these interactions under uncontrolled condi-
tions identified using environmental descriptors such as
geography (country, intra-country region), climate (tem-
perature, humidity), production level and reproduction
management.

There is general agreement that very weak G × E interac-
tions exist for production traits in ruminant species. This has
been based on estimates of genetic correlations (Rg) across
environments that are usually higher than the threshold
value of 0.80 proposed by Robertson (1959) in order to

quantify non-significant differences from a correlation of 1
where no re-ranking occurs across the environments
(Figure 3). The literature mostly indicates that G×E inter-
actions in dairy cattle are very weak for milk traits. This has
been evidenced on farms subject to markedly differing
environmental conditions within a country (Haile-Mariam
et al., 2008), such as intensive v. grazing systems (Boettcher
et al., 2003; Kearney et al., 2004), or different production
levels (Huquet et al., 2012). For international breeds such as
the Holstein (Mark, 2004) this difference has also been
demonstrated between countries, with some of the weakest
correlations (0.72 to 0.76) being seen between New Zealand
and countries from Europe or North America. In beef cattle,
there have been far fewer studies on G×E interactions
based on commercial farm conditions. Pabiou et al. (2014)
showed that genetic Rg for weaning weight in Limousin and
Charolais cattle across different European countries were on
average about 0.75 (ranging from 0.6 to 0.9 for two by two
country estimates), which is lower than across country Rg for
milk production traits (on average 0.88; Mark, 2004), but still
sufficiently high (>0.6) not to recommend splitting limited
cattle populations for the purposes of efficient breeding
programmes (Mulder et al., 2006).

As for small ruminants, G × E interactions need to be taken
into account as a long-term and high-priority research topic
as very few studies have been performed to assess G × E
interactions on overall productivity, health and welfare, even
in vulnerable groups such as lactating ewes and newborn

<figure><img src="image_5.png" /></figure>

Case 1 : no G x E effect on performance

> Genetic variance is similar for E1 and E2
environment

> Genotypes rank similarly for E1 and E2
Heritability is similar across E1 and E2.

Genetic correlation between E1 and E2 is 1.

<figure><img src="image_6.png" /></figure>

Case 2 : G x E scaling effect on performance

> Genetic variance is smaller for E2

> Genotypes rank similarly for E1 and E2

Heritability may be different across E1 and E2.

Genetic correlation between E1 and E2 is 1.

<figure><img src="image_7.png" /></figure>

Case 3 : G x E reranking effect on performance

> Genetic variance may be different for E1 and E2

> Genotypes rank differently for E1 and E2

Heritability may be different across E1 and E2.

Genetic correlation between E1 and E2 is below 1.
Very different environmental sensitivities are
observed between genotypes.

In the example, genotype C is very robust while
genotype A is very sensitive to the environment.

<caption>**Figure 3** Impact of Genotype by Environment (G × E) interactions on genetic parameters and ranking of genotypes according to environmental conditions.</caption>
Assessment of the importance of these is therefore an pre-
requisite to answering the question as to whether animals
bred for conventional farming are suitable for agroecological
farming systems. Before 2001, no scientific attempts were
made to compare the possible G×E interactions affecting
functional and production traits between conventional and
low-input production systems in temperate countries (Nauta
et al., 2001).

Genotype by environment interactions in ruminant species

Research projects based on long-term experiments are often
designed to assess different types (breeds, genetic values)
of animals in controlled environments that are generally
differentiated by their nutrient inputs (energy and protein
contents using the same feed ingredients, or not). The
interactions studied mainly concern production traits (lacta-
tion, growth), and sometimes reproduction and health.
Performance-related studies conducted in commercial cattle
farms analyze these interactions under uncontrolled condi-
tions identified using environmental descriptors such as
geography (country, intra-country region), climate (tem-
perature, humidity), production level and reproduction
management.

There is general agreement that very weak G × E interac-
tions exist for production traits in ruminant species. This has
been based on estimates of genetic correlations (Rg) across
environments that are usually higher than the threshold
value of 0.80 proposed by Robertson (1959) in order to

quantify non-significant differences from a correlation of 1
where no re-ranking occurs across the environments
(Figure 3). The literature mostly indicates that G×E inter-
actions in dairy cattle are very weak for milk traits. This has
been evidenced on farms subject to markedly differing
environmental conditions within a country (Haile-Mariam
et al., 2008), such as intensive v. grazing systems (Boettcher
et al., 2003; Kearney et al., 2004), or different production
levels (Huquet et al., 2012). For international breeds such as
the Holstein (Mark, 2004) this difference has also been
demonstrated between countries, with some of the weakest
correlations (0.72 to 0.76) being seen between New Zealand
and countries from Europe or North America. In beef cattle,
there have been far fewer studies on G×E interactions
based on commercial farm conditions. Pabiou et al. (2014)
showed that genetic Rg for weaning weight in Limousin and
Charolais cattle across different European countries were on
average about 0.75 (ranging from 0.6 to 0.9 for two by two
country estimates), which is lower than across country Rg for
milk production traits (on average 0.88; Mark, 2004), but still
sufficiently high (>0.6) not to recommend splitting limited
cattle populations for the purposes of efficient breeding
programmes (Mulder et al., 2006).

As for small ruminants, G × E interactions need to be taken
into account as a long-term and high-priority research topic
as very few studies have been performed to assess G × E
interactions on overall productivity, health and welfare, even
in vulnerable groups such as lactating ewes and newborn

<figure><img src="image_4.png" /></figure>

Case 1 : no G x E effect on performance

> Genetic variance is similar for E1 and E2 environment

> Genotypes rank similarly for E1 and E2
Heritability is similar across E1 and E2.

Genetic correlation between E1 and E2 is 1.

<figure><img src="image_5.png" /></figure>

Case 2 : G x E scaling effect on performance

> Genetic variance is smaller for E2

> Genotypes rank similarly for E1 and E2

Heritability may be different across E1 and E2.

Genetic correlation between E1 and E2 is 1.

<figure><img src="image_6.png" /></figure>

Case 3 : G x E reranking effect on performance

> Genetic variance may be different for E1 and E2

> Genotypes rank differently for E1 and E2

Heritability may be different across E1 and E2.

Genetic correlation between E1 and E2 is below 1.
Very different environmental sensitivities are
observed between genotypes.

In the example, genotype C is very robust while
genotype A is very sensitive to the environment.

<caption>**Figure 3** Impact of Genotype by Environment (G × E) interactions on genetic parameters and ranking of genotypes according to environmental conditions.</caption>
lambs (Gavojdian et al., 2014). Sheep production systems vary considerably between countries and regions. Sheep are generally regarded as being quite robust to variations in environmental factors, and some breeds (such as Lacaune or Eastern Friesian) are being reared in different countries under an extremely broad range of conditions. A recent investigation of sire sensitivity across diverse farm environments proved that some genotypes were sensitive whereas others were robust with respect to meat sheep production (McLaren et al., 2015). In future genetic evaluations, accounting for environmental sensitivity could enable the identification and selection of sires predicted to be best suited to specific environments (McLaren et al., 2015; Huisman et al., 2016).

Unlike production traits, there is a trend towards seeing stronger G×E interactions with respect to fertility, health and survival traits, although the literature is limited on this topic. In beef cattle, continental breeds with high genetic potential for muscle growth have been shown to have lower fertility levels than British breeds, but only when they are reared in the least favourable environments (Morris et al., 1993).

In dairy cattle, the few estimates available regarding heritability for female reproduction traits in low-input and organic dairy cattle herds differ from those estimated for high-input production systems (Yin et al., 2012). These authors argued that these differences underline the need to implement an organic breeding programme based on data obtained only from cows in organic or low input herds. In our opinion, this statement requires further validation, because it was not based on estimates of genetic correlations between conventional and alternative production systems. Nevertheless, in Holstein cattle, there is some evidence that certain fertility traits, and particularly calving-to-first service, have displayed G×E interactions when considering the herd-average production as the environmental descriptor. These interactions have differed markedly depending on the study, being relatively substantial (Rg of around 0.6) between extreme conditions such as those observed in Australia (Haile-Mariam et al., 2008) and Canada (Boettcher et al., 2003), but quite moderate (Rg of around 0.8) in UK dairy systems (Strandberg et al., 2009), or even non-existent between grazing v. confinement in US herds (Kearney et al., 2004).

Under a temperate climate in Europe, seasonality in terms of the quantity and quality of forage production encourages the phasing of herd feed demand with resource availability. Pasture-based systems for beef and dairy production can therefore optimize this synchronism by grouping calving in late winter/early spring. Indeed, the peak needs of breeding females appear a few weeks after calving, which corresponds to the period of full pasture production and grass with a nutritional value which matches the energy and protein needs of animals. The ability of an animal to calve at a selected time, and to breed each year within a limited period (between 8 and 13 weeks), is a crucial factor that is often evaluated during G×E experiments (Fulkerson et al., 2008). When comparing Holstein and Normande cows in two environments that differ by opposing high and low feed

inputs, Delaby and Fiorelli (2014) were able to show that in terms of their ability to calve after a breeding period limited to 90 days, Normande cows were relatively insensitive to the level of nutrient inputs (respectively 70% and 68% of calvings under both systems), while Holstein cows were less able to reproduce when reared under low input conditions (47% v. 57% of calvings). However, Fulkerson et al. (2008) in Australia, or Delaby et al. (2009) in France, were not able to reveal any clear interactions between different genotypes and nutrient input levels in the case of grouped spring calving systems. The response will actually depend on the degree of under-feeding relative to the cow's genetic merit for production. An excessive mobilization of body reserves to compensate for the gap between nutrient intake and mammary gland demand in an animal with high dairy potential will result in a failure to ensure gestation within a limited period.

*Genotype by environment interactions in pigs and poultry*
Because of the multi-stage structure of these sectors, animals from selection nuclei are reared under highly controlled and optimized conditions, while their cross-bred offspring have to produce under highly diverse conditions. The three potential sources of interactions are the farming system (extensive v. intensive), the climate and feed (optimized diet or not), and the level of sanitary pressure. The stronger the G×E interactions, the less efficient will selection be for commercial herds, and the choice of genotypes as a function of rearing environments will be crucial.

In poultry, this is especially true for Label Rouge chickens, for which the production environment (with access to outdoor runs) differs markedly from the confined selection conditions. N'Dri et al. (2007b) showed that animals selected on their food conversion ratio in individual cages or on the floor were very different. De Verdal et al. (2013b) showed that although genetic correlations between wheat and corn diets could be high for protein and lipid digestibility (0.84 to 0.88), they were lower for energy and starch digestibility (0.63 to 0.73) in broilers. In pigs, the genetic correlation between growth performance or body composition as measured in selection, and the same traits measured at the production stage, could be low to moderate, and even negative in some cases. Under Swedish production conditions, Wallenbeck et al. (2009a and 2009b) studied G×E interactions by comparing conventional and organic farming systems. They showed that the nesting behaviours of sows were more pronounced, post-natal piglet mortality was higher and sows had more lactation oestrus in organic farming systems (Wallenbeck et al., 2009a). As for growth rate and backfat thickness, a significant G×E interaction was observed. The rank correlation of boars evaluated under conventional and organic systems reached only 0.48 for growth and 0.42 for adiposity, leading the authors to propose a specific genetic evaluation index for organic farming systems (Wallenbeck et al., 2009b). Such findings have sometimes led to implementing measures closest to the production conditions, as well as those applied during
lambs (Gavojdian et al., 2014). Sheep production systems vary considerably between countries and regions. Sheep are generally regarded as being quite robust to variations in environmental factors, and some breeds (such as Lacaune or Eastern Friesian) are being reared in different countries under an extremely broad range of conditions. A recent investigation of sire sensitivity across diverse farm environments proved that some genotypes were sensitive whereas others were robust with respect to meat sheep production (McLaren et al., 2015). In future genetic evaluations, accounting for environmental sensitivity could enable the identification and selection of sires predicted to be best suited to specific environments (McLaren et al., 2015; Huisman et al., 2016).

Unlike production traits, there is a trend towards seeing stronger G×E interactions with respect to fertility, health and survival traits, although the literature is limited on this topic. In beef cattle, continental breeds with high genetic potential for muscle growth have been shown to have lower fertility levels than British breeds, but only when they are reared in the least favourable environments (Morris et al., 1993).

In dairy cattle, the few estimates available regarding heritability for female reproduction traits in low-input and organic dairy cattle herds differ from those estimated for high-input production systems (Yin et al., 2012). These authors argued that these differences underline the need to implement an organic breeding programme based on data obtained only from cows in organic or low input herds. In our opinion, this statement requires further validation, because it was not based on estimates of genetic correlations between conventional and alternative production systems. Nevertheless, in Holstein cattle, there is some evidence that certain fertility traits, and particularly calving-to-first service, have displayed G×E interactions when considering the herd-average production as the environmental descriptor. These interactions have differed markedly depending on the study, being relatively substantial (Rg of around 0.6) between extreme conditions such as those observed in Australia (Haile-Mariam et al., 2008) and Canada (Boettcher et al., 2003), but quite moderate (Rg of around 0.8) in UK dairy systems (Strandberg et al., 2009), or even non-existent between grazing v. confinement in US herds (Kearney et al., 2004).

Under a temperate climate in Europe, seasonality in terms of the quantity and quality of forage production encourages the phasing of herd feed demand with resource availability. Pasture-based systems for beef and dairy production can therefore optimize this synchronism by grouping calving in late winter/early spring. Indeed, the peak needs of breeding females appear a few weeks after calving, which corresponds to the period of full pasture production and grass with a nutritional value which matches the energy and protein needs of animals. The ability of an animal to calve at a selected time, and to breed each year within a limited period (between 8 and 13 weeks), is a crucial factor that is often evaluated during G×E experiments (Fulkerson et al., 2008). When comparing Holstein and Normande cows in two environments that differ by opposing high and low feed

inputs, Delaby and Fiorelli (2014) were able to show that in terms of their ability to calve after a breeding period limited to 90 days, Normande cows were relatively insensitive to the level of nutrient inputs (respectively 70% and 68% of calvings under both systems), while Holstein cows were less able to reproduce when reared under low input conditions (47% v. 57% of calvings). However, Fulkerson et al. (2008) in Australia, or Delaby et al. (2009) in France, were not able to reveal any clear interactions between different genotypes and nutrient input levels in the case of grouped spring calving systems. The response will actually depend on the degree of under-feeding relative to the cow's genetic merit for production. An excessive mobilization of body reserves to compensate for the gap between nutrient intake and mammary gland demand in an animal with high dairy potential will result in a failure to ensure gestation within a limited period.

*Genotype by environment interactions in pigs and poultry*
Because of the multi-stage structure of these sectors, animals from selection nuclei are reared under highly controlled and optimized conditions, while their cross-bred offspring have to produce under highly diverse conditions. The three potential sources of interactions are the farming system (extensive v. intensive), the climate and feed (optimized diet or not), and the level of sanitary pressure. The stronger the G×E interactions, the less efficient will selection be for commercial herds, and the choice of genotypes as a function of rearing environments will be crucial.

In poultry, this is especially true for Label Rouge chickens, for which the production environment (with access to outdoor runs) differs markedly from the confined selection conditions. N'Dri et al. (2007b) showed that animals selected on their food conversion ratio in individual cages or on the floor were very different. De Verdal et al. (2013b) showed that although genetic correlations between wheat and corn diets could be high for protein and lipid digestibility (0.84 to 0.88), they were lower for energy and starch digestibility (0.63 to 0.73) in broilers. In pigs, the genetic correlation between growth performance or body composition as measured in selection, and the same traits measured at the production stage, could be low to moderate, and even negative in some cases. Under Swedish production conditions, Wallenbeck et al. (2009a and 2009b) studied G×E interactions by comparing conventional and organic farming systems. They showed that the nesting behaviours of sows were more pronounced, post-natal piglet mortality was higher and sows had more lactation oestrus in organic farming systems (Wallenbeck et al., 2009a). As for growth rate and backfat thickness, a significant G×E interaction was observed. The rank correlation of boars evaluated under conventional and organic systems reached only 0.48 for growth and 0.42 for adiposity, leading the authors to propose a specific genetic evaluation index for organic farming systems (Wallenbeck et al., 2009b). Such findings have sometimes led to implementing measures closest to the production conditions, as well as those applied during
selection. However, even if G×E interactions have been
highlighted, their magnitude does not necessarily justify
specific treatment. Brandt *et al.* (2010) showed that the dif-
ferences between standard and local pig breed genotypes
were reduced under organic compared to conventional
farming systems, while standard genotypes still maintained
superior performance irrespective of the farming system.
From an economic point of view, they concluded that modern
breeds should also be used in organic production systems.

As a general rule, it may be necessary to take account of some G×E interactions in genetic evaluations, especially in monogastric species for which conventional and agroecological farming systems are highly differentiated. However, scaling interactions (differences in heritability across environments) appear to occur more frequently than important re-ranking interactions (Rg <0.80), meaning that the same reproducers will be selected whatever the environmental conditions under which the selection criteria are measured.

New selection criteria to better adapt animals to less controlled environments

New selection criteria could be envisaged in order to con-
tribute to the agroecological principles detailed in the intro-
duction to this paper.

Sparing natural resources

To improve the efficiency of transforming feed into animal product, breeders have long been selecting animals on feed efficiency (ratio between the amount of feed consumed and the amount of milk, meat or eggs produced) or on residual feed intake (difference between actual consumption and the theoretical intake based on energy needs for maintenance and production), since individual feed intake can be measured reliably, at least in selection nucleus herds under high-energy diets. In addition to being accurate, satisfactory measures of feed intake need to be recorded with the minimal disruption of animal behaviour regarding feed access, particularly in groups of thousands of animals, such as birds reared on the floor. Another issue concerns estimates of the quantities of grass ingested by ruminants in order to investigate feed efficiency relative to forages and other sources of fibre. The difficult and expensive implementation of classical techniques based on indigestible markers limits the possibilities of a large-scale phenotyping of grass intake. The dynamics (mobilization/accretion) of body reserves is also an important adaptive trait required to cope with fluctuations in natural resources (Friggens et al., 2004; González-García et al., 2014) that need to be measured indirectly (such as body condition score or imaging technologies) in order to easily quantify stored fat levels. Numerous research programmes are under way throughout the world on these subjects, focussed on different livestock sectors, but no generic and validated solutions have yet been found. Approaches based on high-frequency automated measurements on living animals, such as imaging for body condition

score, accelerometers or videos for feeding behaviour and
ingestion, and thermography, are promising but yet to be
developed for routine use (Phocas et al., 2014). Further work
is also ongoing to facilitate the measurement of digestive
efficiency using infrared spectroscopy in both ruminants and
monogastric animals.

Regarding feed efficiency from an agroecological perspective, the question is not really which criteria should be used but rather the need to determine the environmental conditions under which they should be measured, and in particular with which diet. Therefore, we must seek after more efficient animals, reducing their waste outputs, while feeding more grass for ruminants and providing feedstuffs with a lower energy content and protein quality for monogastrics. Using local feed resources is a basic principle in agroecology, but these may vary considerably depending on the regions, seasons and years of production. New, high-protein feedstuffs containing insects or algae may also offer interesting solutions as protein sources (Becker, 2007; Harinder et al., 2014) without having a negative impact on livestock efficiency. The aim is to improve the efficiency of transforming such alternative diets into animal products. It is also necessary to further quantify the targeted level of production that might be consistent with these alternative diets, characterized by lower energy and protein densities than so-called 'optimal' diets.

Another key issue for all species in the future relates to the
use efficiency of proteins and minerals. Most work on feed
efficiency to date has assumed that intakes of amino acids
and minerals will satisfy all nutritional requirements for
animal maintenance and production. However, in order to
increase farm autonomy in the supply of vegetable proteins,
as well as to limit nitrogen release into the environment, it
may be necessary to explore opportunities to improve protein
efficiency. Very few results have been obtained to date on
this subject, although some suggest an individual variability
in terms of both digestive and metabolic efficiencies
(de Verdal et al., 2013b). But it remains unclear in all species
precisely why an animal is more efficient than another in
depositing protein.

Limiting the environmental impact of livestock production

One important point to highlight from an agroecological perspective is that animals with the highest feed efficiency are also those which produce less effluent per unit of product. For instance, de Verdal et al., 2013a) showed that selection on digestive efficiency could reduce by 14% to 17% the surface areas required for the spreading of poultry manure in line with European regulations.

Although the first factor to be controlled in order to limit
wastes is obviously the match between inputs and nutritional
requirements, the variable conversion efficiency of dietary
proteins induces environmental nitrogen emissions that vary
between animals. Few attempts have been made to deter-
mine direct selection criteria on excreta characteristics that
might influence this environmental impact. For instance, the
ratio of nitrogen to phosphorus is an important parameter
selection. However, even if G×E interactions have been highlighted, their magnitude does not necessarily justify specific treatment. Brandt *et al.* (2010) showed that the differences between standard and local pig breed genotypes were reduced under organic compared to conventional farming systems, while standard genotypes still maintained superior performance irrespective of the farming system. From an economic point of view, they concluded that modern breeds should also be used in organic production systems.

As a general rule, it may be necessary to take account of some G×E interactions in genetic evaluations, especially in monogastric species for which conventional and agroecological farming systems are highly differentiated. However, scaling interactions (differences in heritability across environments) appear to occur more frequently than important re-ranking interactions (Rg <0.80), meaning that the same reproducers will be selected whatever the environmental conditions under which the selection criteria are measured.

## New selection criteria to better adapt animals to less controlled environments

New selection criteria could be envisaged in order to contribute to the agroecological principles detailed in the introduction to this paper.

### Sparing natural resources

To improve the efficiency of transforming feed into animal product, breeders have long been selecting animals on feed efficiency (ratio between the amount of feed consumed and the amount of milk, meat or eggs produced) or on residual feed intake (difference between actual consumption and the theoretical intake based on energy needs for maintenance and production), since individual feed intake can be measured reliably, at least in selection nucleus herds under high-energy diets. In addition to being accurate, satisfactory measures of feed intake need to be recorded with the minimal disruption of animal behaviour regarding feed access, particularly in groups of thousands of animals, such as birds reared on the floor. Another issue concerns estimates of the quantities of grass ingested by ruminants in order to investigate feed efficiency relative to forages and other sources of fibre. The difficult and expensive implementation of classical techniques based on indigestible markers limits the possibilities of a large-scale phenotyping of grass intake. The dynamics (mobilization/accretion) of body reserves is also an important adaptive trait required to cope with fluctuations in natural resources (Friggens *et al.*, 2004; González-García *et al.*, 2014) that need to be measured indirectly (such as body condition score or imaging technologies) in order to easily quantify stored fat levels. Numerous research programmes are under way throughout the world on these subjects, focussed on different livestock sectors, but no generic and validated solutions have yet been found. Approaches based on high-frequency automated measurements on living animals, such as imaging for body condition

score, accelerometers or videos for feeding behaviour and ingestion, and thermography, are promising but yet to be developed for routine use (Phocas *et al.*, 2014). Further work is also ongoing to facilitate the measurement of digestive efficiency using infrared spectroscopy in both ruminants and monogastric animals.

Regarding feed efficiency from an agroecological perspective, the question is not really which criteria should be used but rather the need to determine the environmental conditions under which they should be measured, and in particular with which diet. Therefore, we must seek after more efficient animals, reducing their waste outputs, while feeding more grass for ruminants and providing feedstuffs with a lower energy content and protein quality for monogastrics. Using local feed resources is a basic principle in agroecology, but these may vary considerably depending on the regions, seasons and years of production. New, high-protein feedstuffs containing insects or algae may also offer interesting solutions as protein sources (Becker, 2007; Harinder *et al.*, 2014) without having a negative impact on livestock efficiency. The aim is to improve the efficiency of transforming such alternative diets into animal products. It is also necessary to further quantify the targeted level of production that might be consistent with these alternative diets, characterized by lower energy and protein densities than so-called 'optimal' diets.

Another key issue for all species in the future relates to the use efficiency of proteins and minerals. Most work on feed efficiency to date has assumed that intakes of amino acids and minerals will satisfy all nutritional requirements for animal maintenance and production. However, in order to increase farm autonomy in the supply of vegetable proteins, as well as to limit nitrogen release into the environment, it may be necessary to explore opportunities to improve protein efficiency. Very few results have been obtained to date on this subject, although some suggest an individual variability in terms of both digestive and metabolic efficiencies (de Verdal *et al.*, 2013b). But it remains unclear in all species precisely why an animal is more efficient than another in depositing protein.

### Limiting the environmental impact of livestock production

One important point to highlight from an agroecological perspective is that animals with the highest feed efficiency are also those which produce less effluent per unit of product. For instance, de Verdal *et al.*, 2013a) showed that selection on digestive efficiency could reduce by 14% to 17% the surface areas required for the spreading of poultry manure in line with European regulations.

Although the first factor to be controlled in order to limit wastes is obviously the match between inputs and nutritional requirements, the variable conversion efficiency of dietary proteins induces environmental nitrogen emissions that vary between animals. Few attempts have been made to determine direct selection criteria on excreta characteristics that might influence this environmental impact. For instance, the ratio of nitrogen to phosphorus is an important parameter
because European regulations limit the quantities of these
elements that can be spread on fields to prevent leaching. De
Verdal *et al.* (2011) showed that the ratios between excretion
and phosphorus and nitrogen intake are heritable in poultry.
However, these criteria are quite complex to measure as this
requires dry droppings collected in individual cages.

Last but not the least in terms of environmental footprint, greenhouse gas emissions (mainly methane and nitrous oxide) are today a major concern for all livestock sectors. With respect to enteric methane production by ruminants, agroecology has to address the dilemma of enhancing pasture-based production systems while reducing methane emissions. Indeed, ruminants produce more methane when they are fed forage-based diet than with a high-concentrate diet (Martin *et al.*, 2010). In this context, one challenge is to propose both feeding and breeding practices that can reduce methane emissions while competing less with human food (Dumont *et al.*, 2014). Part of the solution lies in the genetic variability of methane emissions that has been evidenced in cattle (Bell *et al.*, 2014) and sheep (Pinares-Patiño *et al.*, 2013). Lower methane emissions could be achieved through indirect selection on correlated traits such as residual feed intake; reductions in methane emissions per cow of around 11% to 26% within 10 years are thus theoretically possible by selecting more efficient cows de Haas *et al.*, 2011). A modelling study (Bell *et al.*, 2011), based on data from a long-term experiment in Holstein cattle in Scotland, compared the environmental impact (CO₂-eq production) of dairy systems differing in terms of the intake of concentrate (moderate (25%) with high summer pasture v. high (50%) without grazing) depending on the genetic level (medium or high) of cows for milk fat and protein contents. The system without grazing and with highly selected cows produced the least CO₂-eq and used less surface area per kg of milk produced (at constant energy), but was also that which emitted the most CO₂-eq per hectare. These results further emphasize the difficulty in finding a single answer in terms of environmental footprint, depending on the unit of expression of the emissions (per kg of product, per hectare). However, regardless of the production system considered, the only trait capable of significantly reducing CO₂-eq emissions was to reduce intake at constant production, which equates to a lower residual feed intake.

*Improving animal adaptation to warm climatic conditions*

The best estimates obtained by climate models regarding rises in global average temperatures over this century range from 1.0°C to 3.7°C higher than those seen between 1971 and 2000, under the lowest and highest representative concentration pathway (RCP) scenarios. The United Nations target of limiting the rise in global average temperatures to <2°C above pre-industrial levels is projected to be exceeded between 2042 and 2050 by the three highest of the four RCP scenarios. Even in temperate European countries, global warming will increase the number and length of heat waves (temperature above 25°C) with which animals will have to cope. The average annual land temperature over Europe is

projected to increase by more than the global average
temperature for the rest of this century, by around 2.4°C
under the intermediate RCP scenario and by 4.1°C under
the highest RCP scenario (http://www.eea.europa.eu/data-
and-maps/indicators/global-and-european-temperature-1/
assessment).

In this context of climate change, ensuring sustainable
livestock production systems with low energy and pharma-
ceutical inputs will mean that breeders will require animals
that are resistant to both abiotic stresses (heat, humidity) and
biotic stresses (pathogens, particularly parasites) because of
the sanitary risks induced in herds of grazing ruminants and
animals bred on the floor (monogastric species).

Regarding robustness in less controlled environments, the
most active field of study in monogastric species undoubt-
edly concerns the resistance of animals to heat stress. In
addition to the scientific aspect of adaptation to climate
change, this research is mainly linked to the economic
interests of international companies that are seeking to
disseminate the same genotypes in tropical countries as
in temperate countries. It is then necessary to resolve the
conflict between production and adaptation to hot climates:
a high level of feed intake is necessary for an animal to
produce, which in turn induces intense feed thermogenesis,
making it poorly suited to hot conditions. This problem could
be solved by either reducing its feed intake or improving its
ability to dissipate heat.

Because rapid growth is associated with increased feed intake, birds selected on growth rate are more sensitive to heat conditions. Using slow growing birds is therefore a way to reduce their heat sensitivity. By comparing slow growing Label Rouge and rapid growing broiler chickens at 32°C, N'Dri *et al.* (2007a) obtained comparable quantities of meat per day because of the marked reduction in growth and the high mortality among broilers, whereas Label Rouge chickens were not affected by the temperature. In chickens, heat dissipation is limited by their plumage. One way to improve the heat dissipation capacity of birds is therefore to use less feathered birds, such as those carrying the naked neck, frizzle or scaleless genes, which have all been shown to be able to grow better than fully feathered birds under heat stress (Azoulay *et al.*, 2011; Zerjal *et al.*, 2013).

Pigs are generally considered to be little heat resistant. The reproductive performance of sows can be affected by outside temperatures higher than 20°C. At high temperatures, both reproductive performance and growth are affected. Several comparisons of local and standard genotypes have been performed in the context of pig production in the tropics, and they gave an advantage (or at least no disadvantage) to local genotypes (e.g. Renaudeau *et al.*, 2007). To date, there have been no real selection criterion on heat resistance in pigs, except regarding the measurement of production and reproduction performances under thermal stress conditions (Bloemhof *et al.*, 2012).

In ruminant species, numerous studies have also been
based on the production performance of different breeds
raised under tropical conditions. Berman's review (2011) did
because European regulations limit the quantities of these
elements that can be spread on fields to prevent leaching. De
Verdal *et al.* (2011) showed that the ratios between excretion
and phosphorus and nitrogen intake are heritable in poultry.
However, these criteria are quite complex to measure as this
requires dry droppings collected in individual cages.

Last but not the least in terms of environmental footprint,
greenhouse gas emissions (mainly methane and nitrous
oxide) are today a major concern for all livestock sectors.
With respect to enteric methane production by ruminants,
agroecology has to address the dilemma of enhancing
pasture-based production systems while reducing methane
emissions. Indeed, ruminants produce more methane when
they are fed forage-based diet than with a high-concentrate
diet (Martin *et al.*, 2010). In this context, one challenge is to
propose both feeding and breeding practices that can reduce
methane emissions while competing less with human food
(Dumont *et al.*, 2014). Part of the solution lies in the genetic
variability of methane emissions that has been evidenced in
cattle (Bell *et al.*, 2014) and sheep (Pinares-Patiño *et al.*,
2013). Lower methane emissions could be achieved through
indirect selection on correlated traits such as residual feed
intake; reductions in methane emissions per cow of around
11% to 26% within 10 years are thus theoretically possible
by selecting more efficient cows de Haas *et al.*, 2011).
A modelling study (Bell *et al.*, 2011), based on data from a
long-term experiment in Holstein cattle in Scotland, com-
pared the environmental impact (CO₂-eq production) of dairy
systems differing in terms of the intake of concentrate
(moderate (25%) with high summer pasture v. high (50%)
without grazing) depending on the genetic level (medium or
high) of cows for milk fat and protein contents. The system
without grazing and with highly selected cows produced the
least CO₂-eq and used less surface area per kg of milk pro-
duced (at constant energy), but was also that which emitted
the most CO₂-eq per hectare. These results further emphasize
the difficulty in finding a single answer in terms of environ-
mental footprint, depending on the unit of expression of the
emissions (per kg of product, per hectare). However,
regardless of the production system considered, the only trait
capable of significantly reducing CO₂-eq emissions was to
reduce intake at constant production, which equates to a
lower residual feed intake.

*Improving animal adaptation to warm climatic conditions*

The best estimates obtained by climate models regarding
rises in global average temperatures over this century range
from 1.0°C to 3.7°C higher than those seen between 1971
and 2000, under the lowest and highest representative
concentration pathway (RCP) scenarios. The United Nations
target of limiting the rise in global average temperatures to
<2°C above pre-industrial levels is projected to be exceeded
between 2042 and 2050 by the three highest of the four RCP
scenarios. Even in temperate European countries, global
warming will increase the number and length of heat waves
(temperature above 25°C) with which animals will have to
cope. The average annual land temperature over Europe is

projected to increase by more than the global average
temperature for the rest of this century, by around 2.4°C
under the intermediate RCP scenario and by 4.1°C under
the highest RCP scenario (http://www.eea.europa.eu/data-
and-maps/indicators/global-and-european-temperature-1/
assessment).

In this context of climate change, ensuring sustainable
livestock production systems with low energy and pharma-
ceutical inputs will mean that breeders will require animals
that are resistant to both abiotic stresses (heat, humidity) and
biotic stresses (pathogens, particularly parasites) because of
the sanitary risks induced in herds of grazing ruminants and
animals bred on the floor (monogastric species).

Regarding robustness in less controlled environments, the
most active field of study in monogastric species undoubt-
edly concerns the resistance of animals to heat stress. In
addition to the scientific aspect of adaptation to climate
change, this research is mainly linked to the economic
interests of international companies that are seeking to
disseminate the same genotypes in tropical countries as
in temperate countries. It is then necessary to resolve the
conflict between production and adaptation to hot climates:
a high level of feed intake is necessary for an animal to
produce, which in turn induces intense feed thermogenesis,
making it poorly suited to hot conditions. This problem could
be solved by either reducing its feed intake or improving its
ability to dissipate heat.

Because rapid growth is associated with increased feed
intake, birds selected on growth rate are more sensitive to
heat conditions. Using slow growing birds is therefore a way
to reduce their heat sensitivity. By comparing slow growing
Label Rouge and rapid growing broiler chickens at 32°C,
N'Dri *et al.* (2007a) obtained comparable quantities of meat
per day because of the marked reduction in growth and
the high mortality among broilers, whereas Label Rouge
chickens were not affected by the temperature. In chickens,
heat dissipation is limited by their plumage. One way to
improve the heat dissipation capacity of birds is therefore to
use less feathered birds, such as those carrying the naked
neck, frizzle or scaleless genes, which have all been shown to
be able to grow better than fully feathered birds under heat
stress (Azoulay *et al.*, 2011; Zerjal *et al.*, 2013).

Pigs are generally considered to be little heat resistant. The
reproductive performance of sows can be affected by outside
temperatures higher than 20°C. At high temperatures, both
reproductive performance and growth are affected. Several
comparisons of local and standard genotypes have been
performed in the context of pig production in the tropics, and
they gave an advantage (or at least no disadvantage) to local
genotypes (e.g. Renaudeau *et al.*, 2007). To date, there have
been no real selection criterion on heat resistance in pigs,
except regarding the measurement of production and
reproduction performances under thermal stress conditions
(Bloemhof *et al.*, 2012).

In ruminant species, numerous studies have also been
based on the production performance of different breeds
raised under tropical conditions. Berman's review (2011) did
not lend support to the notion that 'breeds which evolved in warm climates (e.g. the *Bos indicus* and *Bos Taurus Sanga* types) share attributes that endow them with higher capacity for heat dissipation'. With the exception of the slick hair gene and the hairy mutation (Littlejohn *et al.*, 2014), hair coat attributes in warm climates largely reflect the effects of nutrition, management and climate during the animal's lifetime, rather than differences in genetic constitution. However, within a breed, sufficient genetic variation exists to enable successful selection for heat tolerance. The question therefore arises as to whether it might be useful from an agroecological perspective to develop specific breeding programmes for international breeds to be used in production regions experiencing long periods of hot days. This would obviously be worthwhile in the tropics, but also in Europe due to climate change. Indeed, Hammami *et al.* (2013) showed that the heat stress thresholds under a continental temperate climate (Luxembourg) for production traits and somatic cell counts in Holstein cows were really lower (18°C *v.* values between 23°C and 30°C) than other estimates under tropical or Mediterranean climate conditions. Carabano *et al.* (2014) showed for Holstein cows bred in Southern Spain in hot but dry conditions that their comfort thresholds could differ markedly depending on the production trait: about 29°C for milk yield, 18°C for protein yield and only 15°C for fat yield and somatic cell count. Selection criteria other than those which target production levels are now being sought in order to better evaluate the heat resistance of ruminants. For example, changes in body temperature, heat generation and respiratory rate have been used to search for genomic associations in sheep (Alhiday *et al.*, 2012). It may also be necessary to determine whether the genomic introgression of some gene variants with major effects on heat tolerance needs to be performed.

*Improving animal health in less controlled environments*

The emergence of disease at the herd scale is multifactorial: the source and virulence of pathogens, climatic conditions, herd management factors such as animal density and the timing of animal grazing, feed availability, the use of preventive or curative measures and intrinsic animal resistance/ tolerance to diseases. In low-input systems, disease-resistant animals are necessary because treatments have to be limited and outdoor access increases the risks of exposure to various pathogens, such as gastrointestinal parasites. Although it is a matter of great importance in all livestock sectors, our current knowledge of the genetics of animal health is scant. In particular, there remain many questions regarding the traits that could be measured to obtain an efficient response to selection for overall disease resistance. Three different methods have been studied in order to improve resistance against infectious diseases.

The first approach is based on selective breeding that directly targets increasing animal resistance to specific infectious diseases. This has mainly focussed on diseases with a high incidence and major economic impact, such as mastitis in dairy ruminants, infection by helminths during grazing in small

ruminants and in outdoor poultry systems. Selection against infection by a given pathogen or group of pathogens has been successful during several experiments, despite low to moderate heritability values in poultry (Pinard-van der Laan *et al.*, 2003), pigs (Kadowaki *et al.*, 2012), and ruminants (Morris, 2007; Rupp *et al.*, 2009). However, this type of selection may impair the ability of animals to resist pathogens other than those targeted by the selection process. The results of selection may even be dependent on the pathogenic strain used for selection, such as during a selection experiment for resistance to Marek's disease (Lamont *et al.*, 2003). Moreover, even if it is possible to select on resistance to a specific pathogen, it is very difficult to choose it, as this may be dependent on production conditions and there is rarely one pathogen that predominates. Under less controlled environments, it is therefore essential to develop a more holistic strategy to improve the overall capacity of animals to be healthy.

One alternative is to select simultaneously on resistance to several major pathogens by identifying patterns of resistance common to several pathogens and considering genes such as those in the major histocompatibility complex (MHC) system which have been shown to be involved in resistance to various pathogens that affect poultry (Lamont *et al.*, 2003), pigs (Warner *et al.*, 1986) or cattle (Ellis, 2004). However, it is important to maintain high MHC diversity in order to retain the population's ability to respond as a whole against highly variable and rapidly evolving pathogens. Indeed, the selection of particular MHC haplotypes may become inefficient in the long term.

Finally, a more general approach is to try to improve the immunocompetence of animals by selecting a set of immune function traits that are heritable and crucial for resistance to infections, such as antibody production, cellular response and phagocytic activity. Indeed, the immune system protects the organism against pathogenic challenges through its innate and adaptive defences. Significant genetic variations in immune response traits have been observed in pigs (Flori *et al.*, 2011), poultry (Lamont *et al.*, 2003) and cattle (Thompson-Crispi *et al.*, 2012a). In dairy cattle, selection for high immune responders has been linked to reductions in the incidence of mastitis, ketosis, metritis and retained placenta in cows with both high antibody and cell-mediated immune responses when compared to average or low responders for these traits (Thompson-Crispi *et al.*, 2012b). However, the efficiency of selection on these criteria in terms of improving the overall health of farm animals is far from being established; insufficient results have been obtained in this area whatever the livestock sectors, and selection experiments have produced contrasted results in poultry (Lamont *et al.*, 2003) or pigs (Wilkie and Mallard, 1999).

*Consequences*

The development of innovations in genomics and high-throughput phenotyping should eventually enable us to rethink and diversify selection criteria while shortening the
not lend support to the notion that 'breeds which evolved in warm climates (e.g. the *Bos indicus* and *Bos Taurus Sanga* types) share attributes that endow them with higher capacity for heat dissipation'. With the exception of the slick hair gene and the hairy mutation (Littlejohn *et al.*, 2014), hair coat attributes in warm climates largely reflect the effects of nutrition, management and climate during the animal's lifetime, rather than differences in genetic constitution. However, within a breed, sufficient genetic variation exists to enable successful selection for heat tolerance. The question therefore arises as to whether it might be useful from an agroecological perspective to develop specific breeding programmes for international breeds to be used in production regions experiencing long periods of hot days. This would obviously be worthwhile in the tropics, but also in Europe due to climate change. Indeed, Hammami *et al.* (2013) showed that the heat stress thresholds under a continental temperate climate (Luxembourg) for production traits and somatic cell counts in Holstein cows were really lower (18°C *v.* values between 23°C and 30°C) than other estimates under tropical or Mediterranean climate conditions. Carabano *et al.* (2014) showed for Holstein cows bred in Southern Spain in hot but dry conditions that their comfort thresholds could differ markedly depending on the production trait: about 29°C for milk yield, 18°C for protein yield and only 15°C for fat yield and somatic cell count. Selection criteria other than those which target production levels are now being sought in order to better evaluate the heat resistance of ruminants. For example, changes in body temperature, heat generation and respiratory rate have been used to search for genomic associations in sheep (Alhiday *et al.*, 2012). It may also be necessary to determine whether the genomic introgression of some gene variants with major effects on heat tolerance needs to be performed.

*Improving animal health in less controlled environments*

The emergence of disease at the herd scale is multifactorial: the source and virulence of pathogens, climatic conditions, herd management factors such as animal density and the timing of animal grazing, feed availability, the use of preventive or curative measures and intrinsic animal resistance/ tolerance to diseases. In low-input systems, disease-resistant animals are necessary because treatments have to be limited and outdoor access increases the risks of exposure to various pathogens, such as gastrointestinal parasites. Although it is a matter of great importance in all livestock sectors, our current knowledge of the genetics of animal health is scant. In particular, there remain many questions regarding the traits that could be measured to obtain an efficient response to selection for overall disease resistance. Three different methods have been studied in order to improve resistance against infectious diseases.

The first approach is based on selective breeding that directly targets increasing animal resistance to specific infectious diseases. This has mainly focussed on diseases with a high incidence and major economic impact, such as mastitis in dairy ruminants, infection by helminths during grazing in small

ruminants and in outdoor poultry systems. Selection against infection by a given pathogen or group of pathogens has been successful during several experiments, despite low to moderate heritability values in poultry (Pinard-van der Laan *et al.*, 2003), pigs (Kadowaki *et al.*, 2012), and ruminants (Morris, 2007; Rupp *et al.*, 2009). However, this type of selection may impair the ability of animals to resist pathogens other than those targeted by the selection process. The results of selection may even be dependent on the pathogenic strain used for selection, such as during a selection experiment for resistance to Marek's disease (Lamont *et al.*, 2003). Moreover, even if it is possible to select on resistance to a specific pathogen, it is very difficult to choose it, as this may be dependent on production conditions and there is rarely one pathogen that predominates. Under less controlled environments, it is therefore essential to develop a more holistic strategy to improve the overall capacity of animals to be healthy.

One alternative is to select simultaneously on resistance to several major pathogens by identifying patterns of resistance common to several pathogens and considering genes such as those in the major histocompatibility complex (MHC) system which have been shown to be involved in resistance to various pathogens that affect poultry (Lamont *et al.*, 2003), pigs (Warner *et al.*, 1986) or cattle (Ellis, 2004). However, it is important to maintain high MHC diversity in order to retain the population's ability to respond as a whole against highly variable and rapidly evolving pathogens. Indeed, the selection of particular MHC haplotypes may become inefficient in the long term.

Finally, a more general approach is to try to improve the immunocompetence of animals by selecting a set of immune function traits that are heritable and crucial for resistance to infections, such as antibody production, cellular response and phagocytic activity. Indeed, the immune system protects the organism against pathogenic challenges through its innate and adaptive defences. Significant genetic variations in immune response traits have been observed in pigs (Flori *et al.*, 2011), poultry (Lamont *et al.*, 2003) and cattle (Thompson-Crispi *et al.*, 2012a). In dairy cattle, selection for high immune responders has been linked to reductions in the incidence of mastitis, ketosis, metritis and retained placenta in cows with both high antibody and cell-mediated immune responses when compared to average or low responders for these traits (Thompson-Crispi *et al.*, 2012b). However, the efficiency of selection on these criteria in terms of improving the overall health of farm animals is far from being established; insufficient results have been obtained in this area whatever the livestock sectors, and selection experiments have produced contrasted results in poultry (Lamont *et al.*, 2003) or pigs (Wilkie and Mallard, 1999).

*Consequences*

The development of innovations in genomics and high-throughput phenotyping should eventually enable us to rethink and diversify selection criteria while shortening the
interval between breeding goals being set and actual improvements in livestock. However, faced with spectacular developments in the knowledge of the genome, there is a major lack of knowledge on relevant phenotypes that could enable us to better exploit the genetic variability of animal performance in order to improve the efficiency and robustness of animals under diverse and fluctuating environmental conditions. The standardization of both animals and breeding conditions seems antithetical to the very principles of agroecology, which tries to enhance diversity within livestock farming systems so as to improve their resilience, and to benefit from complementarities and interactions between the resources available. Therefore, if we are to meet the needs of agroecology, breeding programmes in all livestock sectors need to evolve towards increasingly diverse genotypes, rather than targeting the myth of an 'ideal animal' that will fit an 'ideal agroecological system'. In a second paper, we will be further discussing the breeding strategies that may help to diversify genetic resources in different livestock sectors.

## Acknowledgements

The authors would like to acknowledge support from the French Ministry of Agriculture in funding our review of the literature and carrying out interviews (study SSP-2014-061). They also thank all the breeders and representatives of breeding programmes in the ruminant, pig, and poultry sectors for the time they gave for our interviews. Thanks also go to staff from Institut de l'Elevage, Institut de la Filière Porcine, and Institut de l'Aviculture, who helped with the interviewing.

## 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.

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.

Alhiday 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.

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.

Becker EW 2007. Micro-algae as a source of protein. Biotechnology Advances 25, 207-210.

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.

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.

Berman A 2011. Invited review: are adaptations present to support dairy cattle productivity in warm climates? Journal of Dairy Science 94, 2147-2158.

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.

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.

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.

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.

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.

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.

Delaby L and Fiorelli JL 2014. Elevages laitiers à bas intrants: entre traditions et innovations. INRA. Productions Animales 27, 123-134.

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.

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.

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.

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.

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.

Ellis S 2004. Review: the cattle major histocompatibility complex: is it unique? Veterinary Immunology and Immunopathology 102, 1-8.

FAO 2006. Livestock's long shadow: environmental issues and options. LEAD, FAO, Rome, Italy.

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, Lefèvre F, Oswald JP, Bidanel JP and Rogel-Gaillard C 2011. Immunity traits in pigs: substantial genetic variation and limited covariation. PLoS One 6, e22717.

Friggens NC, Ingvartsen KL and Emmans GC 2004. Prediction of body lipid change in pregnancy and lactation. Journal of Dairy Science 87, 988-1000.

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.

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.

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.

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.

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.

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.

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.
interval between breeding goals being set and actual improvements in livestock. However, faced with spectacular developments in the knowledge of the genome, there is a major lack of knowledge on relevant phenotypes that could enable us to better exploit the genetic variability of animal performance in order to improve the efficiency and robustness of animals under diverse and fluctuating environmental conditions. The standardization of both animals and breeding conditions seems antithetical to the very principles of agroecology, which tries to enhance diversity within livestock farming systems so as to improve their resilience, and to benefit from complementarities and interactions between the resources available. Therefore, if we are to meet the needs of agroecology, breeding programmes in all livestock sectors need to evolve towards increasingly diverse genotypes, rather than targeting the myth of an 'ideal animal' that will fit an 'ideal agroecological system'. In a second paper, we will be further discussing the breeding strategies that may help to diversify genetic resources in different livestock sectors.

## Acknowledgements

The authors would like to acknowledge support from the French Ministry of Agriculture in funding our review of the literature and carrying out interviews (study SSP-2014-061). They also thank all the breeders and representatives of breeding programmes in the ruminant, pig, and poultry sectors for the time they gave for our interviews. Thanks also go to staff from Institut de l'Elevage, Institut de la Filière Porcine, and Institut de l'Aviculture, who helped with the interviewing.

## 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.

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.

Alhiday 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.

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.

Becker EW 2007. Micro-algae as a source of protein. Biotechnology Advances 25, 207-210.

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.

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.

Berman A 2011. Invited review: are adaptations present to support dairy cattle productivity in warm climates? Journal of Dairy Science 94, 2147-2158.

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.

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.

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.

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.

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.

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.

Delaby L and Fiorelli JL 2014. Elevages laitiers à bas intrants: entre traditions et innovations. INRA. Productions Animales 27, 123-134.

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.

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.

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.

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.

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.

Ellis S 2004. Review: the cattle major histocompatibility complex: is it unique? Veterinary Immunology and Immunopathology 102, 1-8.

FAO 2006. Livestock's long shadow: environmental issues and options. LEAD, FAO, Rome, Italy.

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, Lefèvre F, Oswald JP, Bidanel JP and Rogel-Gaillard C 2011. Immunity traits in pigs: substantial genetic variation and limited covariation. PLoS One 6, e22717.

Friggens NC, Ingvartsen KL and Emmans GC 2004. Prediction of body lipid change in pregnancy and lactation. Journal of Dairy Science 87, 988-1000.

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.

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.

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.

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.

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.

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.

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.
Agroecological breeding goals for livestock

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.

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.

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.

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.

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.

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, Wallingford.

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.

Leenhouwers Jl, Ten Napel J, Hanenberg EHAT and Merks JWM 2011. Breeding replacement gilts for organic pig herds. Animal 5, 615–621.

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.

Mark T 2004. Applied genetic evaluations for production and functional traits in dairy cattle. Journal of Dairy Science 87, 2641–2652.

Martin C, Morgavi DP and Doreau M 2010. Methane mitigation in ruminants: from microbe to the farm scale. Animal 4, 351–365.

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.

Morris CA 2007. A review of genetic resistance to disease in *Bos taurus* cattle. Veterinary Journal 174, 481–491.

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.

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.

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

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.

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.

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 10th World Congress of Genetics Applied to Livestock Production, 17 to 22 August, Vancouver, BC, Canada.

Phocas F, Agabriel J, Dupont-Nivet M, Geurden I, Médale F, Mignon-Grasteau S, Gilbert H and Dourmad JY 2014. Le phénomotype de l'efficacité alimentaire et de ses composantes, une nécessité pour accroître l'efficience des productions animales. INRA Productions Animales 27, 235–248.

Phocas F, Belloc C, Delaby L, Dourmad JY, Ducrot C, Dumont B, Ezanno P, Foucas 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.

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.

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.

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.

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.

Robertson A 1959. The sampling variance of the genetic correlation coefficient. Biometrics 15, 469–485.

Rupp R, Bergonier D, Dion S, Hygoneng MC, Aurel MR, Robert-Granié C and Foucas 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.

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.

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.

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.

Thornton PK 2010. Livestock production: recent trends, future prospects. Philosophical Transactions of the Royal Society B 365, 2853–2867.

Wallenbeck A, Gustafson G and Rydhmer L 2009a. Sow performance and maternal behaviour in organic and conventional herds. Acta Agriculturae Scandinavica 59, 181–191.

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.

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.

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.

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.

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.

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.
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.

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.

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.

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.

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.

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, Wallingford.

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.

Leenhouwers Jl, Ten Napel J, Hanenberg EHAT and Merks JWM 2011. Breeding replacement gilts for organic pig herds. Animal 5, 615–621.

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.

Mark T 2004. Applied genetic evaluations for production and functional traits in dairy cattle. Journal of Dairy Science 87, 2641–2652.

Martin C, Morgavi DP and Doreau M 2010. Methane mitigation in ruminants: from microbe to the farm scale. Animal 4, 351–365.

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.

Morris CA 2007. A review of genetic resistance to disease in *Bos taurus* cattle. Veterinary Journal 174, 481–491.

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.

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.

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

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.

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.

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.

Phocas F, Agabriel J, Dupont-Nivet M, Geurden I, Médale F, Mignon-Grasteau S, Gilbert H and Dourmad JY 2014. Le phénomotype de l'efficacité alimentaire et de ses composantes, une nécessité pour accroître l'efficience des productions animales. INRA Productions Animales 27, 235–248.

Phocas F, Belloc C, Delaby L, Dourmad JY, Ducrot C, Dumont B, Ezanno P, Foucas G, Gonzales-García 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.

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.

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.

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.

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.

Robertson A 1959. The sampling variance of the genetic correlation coefficient. Biometrics 15, 469–485.

Rupp R, Bergonier D, Dion S, Hygoneng MC, Aurel MR, Robert-Granié C and Foucas 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.

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.

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.

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.

Thornton PK 2010. Livestock production: recent trends, future prospects. Philosophical Transactions of the Royal Society B 365, 2853–2867.

Wallenbeck A, Gustafson G and Rydhmer L 2009a. Sow performance and maternal behaviour in organic and conventional herds. Acta Agriculturae Scandinavica 59, 181–191.

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.

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.

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.

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.

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.

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.