56. Towards the characterisation of animal robustness by dynamic energy allocation indicators in fattening pigs

Lenoir, Guillaume; Tamayo, Rafael Munoz; Flatres-Grall, Loïc; David, Ingrid; Friggens, Nicolas N.C.

doi:10.3920/978-90-8686-940-4_56

Cited by 4 publications

(1 citation statement)

References 6 publications

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“…The trait α t , which describes the allocation of net energy to growth during the fattening period, had moderate heritabilities, in the same range as those estimated for FCR or RFI. In a previous study [48], we considered the average estimate of α t during the evaluated period and not the daily estimates, and obtained a lower heritability (0.16 ± 0.05) but this was based on a different dataset. For RFI, David et al [49] reported heritabilities ranging from 0.19 ± 0.06 to 0.28 ± 0.06, using an RR model for weekly estimates of RFI over 10 weeks in pigs.…”

Section: Estimation Of the Genetic Variance Of The Allocation Coeffic...mentioning

confidence: 95%

Disentangling the dynamics of energy allocation to develop a proxy for robustness of fattening pigs

Lenoir,

Flatres-Grall,

Muñoz-Tamayo

et al. 2023

Genet Sel Evol

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Background There is a growing need to improve robustness of fattening pigs, but this trait is difficult to phenotype. Our first objective was to develop a proxy for robustness of fattening pigs by modelling the longitudinal energy allocation coefficient to growth, with the resulting environmental variance of this allocation coefficient considered as a proxy for robustness. The second objective was to estimate its genetic parameters and correlations with traits under selection and with phenotypes that are routinely collected. In total, 5848 pigs from a Pietrain NN paternal line were tested at the AXIOM boar testing station (Azay-sur-Indre, France) from 2015 to 2022. This farm is equipped with an automatic feeding system that records individual weight and feed intake at each visit. We used a dynamic linear regression model to characterize the evolution of the allocation coefficient between the available cumulative net energy, which was estimated from feed intake, and cumulative weight gain during the fattening period. Longitudinal energy allocation coefficients were analysed using a two-step approach to estimate both the genetic variance of the coefficients and the genetic variance in their residual variance, which will be referred to as the log-transformed squared residual (LSR). Results The LSR trait, which could be interpreted as an indicator of the response of the animal to perturbations/stress, showed a low heritability (0.05 ± 0.01), a high favourable genetic correlation with average daily growth (− 0.71 ± 0.06), and unfavourable genetic correlations with feed conversion ratio (− 0.76 ± 0.06) and residual feed intake (− 0.83 ± 0.06). Segmentation of the population in four classes using estimated breeding values for LSR showed that animals with the lowest estimated breeding values were those with the worst values for phenotypic proxies of robustness, which were assessed using records routinely collected on farm. Conclusions Results of this study show that selection for robustness, based on estimated breeding values for environmental variance of the allocation coefficients to growth, can be considered in breeding programs for fattening pigs.

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Section: Estimation Of the Genetic Variance Of The Allocation Coeffic...mentioning

confidence: 95%

Disentangling the dynamics of energy allocation to develop a proxy for robustness of fattening pigs

Lenoir,

Flatres-Grall,

Muñoz-Tamayo

et al. 2023

Genet Sel Evol

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A biological integrity framework for describing animal welfare and wellbeing

Colditz

2023

Anim. Prod. Sci.

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Ethical treatment of animals is the keystone of livestock production. Assessment of welfare is integral to assurance that animals experience a good life. Underpinning assurance are concepts of what constitutes good welfare, a good life and wellbeing. This review examines the concepts of welfare and wellbeing and the frameworks that have been developed for describing their scope. Historically, the tripartite model of welfare (feeling well, functioning well, leading a natural life) has been translated into the Five Freedoms (FF), Five Domains (FD), Good Life (GL), Welfare through Competence (WtC) and OIE World Organisation for Animal Health Welfare Principles frameworks. These frameworks provide scaffolds for numerous welfare assessment schemes. However, the three-part model of wellbeing (eudaimonia, hedonia, social interaction) lacks an explicit assessment framework, although FD, GL and WtC implicitly address aspects of wellbeing. Whereas positive affective (hedonic) experiences are considered to constitute positive welfare, positive aspects of eudaimonic function and social interaction are considered to be aspects of wellbeing above and beyond any indirect contribution they make to positive affective experiences (i.e. positive welfare). In this view, positive health is more than the absence of ill-health and positive social interactions are more than freedom from social isolation. New phenotypes in farm animals identified through analysis of sensor data are providing new perspectives on the functional integrity of biological processes that align well with concepts of wellbeing. These analyses draw on methods in resilience theory to examine stability in complex dynamic systems, specifically, uniformity of trajectories, periodicity of biorhythms and complexity of networks. A framework is proposed that loosely partitions FF, FD, GL and WtC into inputs, opportunities, and outcomes. The framework positions the outcome of biological integrity within the context of input constraints that can generate harms and deficiencies, and environmental opportunities that can foster acquisition of competencies and flourishing. It combines the eudaimonic, hedonic and social aspects of wellbeing within the tripartite terminology of welfare. It is hoped that the framework can help orientate new descriptions of biological function in farm animals derived from sensor data within the broader literature on welfare and wellbeing.

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Disentangling the dynamics of energy allocation to provide a proxy of robustness in fattening pigs

Lenoir

Flatres-Grall²,

Muñoz-Tamayo

et al. 2022

Preprint

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There is a growing need to improve robustness characteristics in fattening pigs, but this trait is difficult to phenotype. Our first objective was to develop a robustness proxy on the basis of modelling of longitudinal energetic allocation coefficient to growth for fattening pigs. Consequently, the environmental variance of this allocation coefficient was considered as a proxy of robustness. The second objective was to estimate its genetic parameters and correlation with traits under selection as well with phenotypes routinely collected on farms. A total of 5848 pigs, from Pietrain NN paternal line, were tested at the AXIOM boar testing station (Azay-sur-Indre, France) from 2015 to 2022. This farm was equipped with automatic feeding system, recording individual weight and feed intake at each visit. We used a dynamic linear regression model to characterize the evolution of the allocation coefficient between cumulative net energy available, estimated from feed intake, and cumulative weight gain during fattening period. Longitudinal energetic allocation coefficients were analysed using a two-step approach, to estimate both its genetic variance and the genetic variance in the residual variance, trait LSR. The LSR trait, that could be interpreted as an indicator of the response of the animal to perturbations/stress, showed low heritability (0.05 +/- 0.01). The trait LSR had high favourable genetic correlations with average daily growth (-0.71+/-0.06) and unfavourable with feed conversion ratio (-0.76+/-0.06) and residual feed intake (-0.83+/-0.06). The analysis of the relationship between estimated breeding values (EBV) LSR quartiles and phenotypes routinely collected on farms shows the most favourable situation for animals from quartile with the weakest EBV LSR, i.e., the most robust. These results show that selection for robustness based on deviation from energetic allocation coefficient to growth can be considered in breeding programs for fattening pigs.

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56. Towards the characterisation of animal robustness by dynamic energy allocation indicators in fattening pigs

Cited by 4 publications

References 6 publications

Disentangling the dynamics of energy allocation to develop a proxy for robustness of fattening pigs

Disentangling the dynamics of energy allocation to develop a proxy for robustness of fattening pigs

A biological integrity framework for describing animal welfare and wellbeing

Disentangling the dynamics of energy allocation to provide a proxy of robustness in fattening pigs

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