Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where B. Vautier is active.

Publication


Featured researches published by B. Vautier.


Animal | 2013

Accounting for variability among individual pigs in deterministic growth models.

B. Vautier; Nathalie Quiniou; J. van Milgen; L. Brossard

Inclusion of variation in deterministic nutritional models for growth by repeating simulations using different sets of parameters has been performed in literature without or with only hypothetic consideration of the covariance structure among parameters. However, a description of the structure of links among parameters describing individuals is required to generate realistic sets of parameters. In this study, the mean and covariance structure of model parameters describing feed intake and growth were analyzed from 10 batches of crossbred gilts and barrows. Data were obtained from different crossbreeds, originating from Large White × Landrace sows and nine sire lines. Pigs were group-housed (12 pigs/pen) and performance testing was carried out from 70 days of age to ∼110 kg BW. Daily feed intake (DFI) was recorded using automatic feeding stations and BW was measured at least every 3 weeks. A growth model was used to characterize individual pigs based on the observed DFI and BW. In this model, a Gompertz function was used to describe protein deposition and the resulting BW gain. A gamma function (expressing DFI as multiples of maintenance) was used to express the relationship between DFI and BW. Each pig was characterized through a set of five parameters: BW₇₀ (BW at 70 days of age), B(Gompertz) (a precocity parameter) PDm (mean protein deposition rate) and DFI₅₀ and DFI₁₀₀ (DFI at 50 and 100 kg BW, respectively). The data set included profiles for 1288 pigs for which no eating or growth disorders were observed (e.g. because of disease). All parameters were affected by sex (except for BW₇₀) and batch, but not by the crossbreed (except for PDm). An interaction between sex and crossbreed was observed for PDm (P < 0.01) and DFI₁₀₀ (P = 0.05). Different covariance matrices were computed according to the batch, sex, crossbreed, or their combinations, and the similarity of matrices was evaluated using the Flury hierarchy. As covariance matrices were all different, the unit of covariance (subpopulation) corresponded to the combination of batch, sex and crossbreed. Two generic covariance matrices were compared afterwards, with (median matrix) or without (raw matrix) taking into account the size of subpopulations. The most accurate estimation of observed covariance was obtained with the median covariance matrix. The median covariance matrix can be used, in combination with average parameters obtained on-farm, to generate virtual populations of pigs that account for a realistic description of mean performances and their variability.


Animal | 2015

Phenotypic and genetic relationships between growth and feed intake curves and feed efficiency and amino acid requirements in the growing pig

R. Saintilan; L. Brossard; B. Vautier; P. Sellier; Jean Pierre Bidanel; J. van Milgen; Hélène Gilbert

Improvement of feed efficiency in pigs has been achieved essentially by increasing lean growth rate, which resulted in lower feed intake (FI). The objective was to evaluate the impact of strategies for improving feed efficiency on the dynamics of FI and growth in growing pigs to revisit nutrient recommendations and strategies for feed efficiency improvement. In 2010, three BWs, at 35±2, 63±9 and 107±7 kg, and daily FI during this period were recorded in three French test stations on 379 Large White and 327 French Landrace from maternal pig populations and 215 Large White from a sire population. Individual growth and FI model parameters were obtained with the InraPorc® software and individual nutrient requirements were computed. The model parameters were explored according to feed efficiency as measured by residual feed intake (RFI) or feed conversion ratio (FCR). Animals were separated in groups of better feed efficiency (RFI- or FCR-), medium feed efficiency and poor feed efficiency. Second, genetic relationships between feed efficiency and model parameters were estimated. Despite similar average daily gains (ADG) during the test for all RFI groups, RFI- pigs had a lower initial growth rate and a higher final growth rate compared with other pigs. The same initial growth rate was found for all FCR groups, but FCR- pigs had significantly higher final growth rates than other pigs, resulting in significantly different ADG. Dynamic of FI also differed between RFI or FCR groups. The calculated digestible lysine requirements, expressed in g/MJ net energy (NE), showed the same trends for RFI or FCR groups: the average requirements for the 25% most efficient animals were 13% higher than that of the 25% least efficient animals during the whole test, reaching 0.90 to 0.95 g/MJ NE at the beginning of the test, which is slightly greater than usual feed recommendations for growing pigs. Model parameters were moderately heritable (0.30±0.13 to 0.56±0.13), except for the precocity of growth (0.06±0.08). The parameter representing the quantity of feed at 50 kg BW showed a relatively high genetic correlation with RFI (0.49±0.14), and average protein deposition between 35 and 110 kg had the highest correlation with FCR (-0.76±0.08). Thus, growth and FI dynamics may be envisaged as breeding tools to improve feed efficiency. Furthermore, improvement of feed efficiency should be envisaged jointly with new feeding strategies.


Animal Production Science | 2014

Comparison of in vivo and in silico growth performance and variability in pigs when applying a feeding strategy designed by simulation to control the variability of slaughter weight

L. Brossard; B. Vautier; J. van Milgen; Yvon Salaün; Nathalie Quiniou

Variability in bodyweight (BW) among pigs complicates the management of feeding strategies and slaughter. Including variability among individuals in modelling approaches can help to design feeding strategies to control performance level, but also its variability. The InraPorc model was used to perform simulations on 10 batches of 84 crossbred pigs each to characterise the effect of feeding strategies differing in amino acid supply or feed allowance on the mean and variation in growth rate. Results suggested that a feed restriction reduces the coefficient of variation of BW at first departure for slaughter (BW1) by 34%. Growth performance obtained from an in silico simulation using ad libitum and restricted feeding plans was compared with results obtained in an in vivo experiment on a batch of 168 pigs. Pigs were offered feed ad libitum or were restricted (increase in feed allowance by 27 g/day up to a maximum of 2.4 and 2.7 kg/day for gilts and barrows, respectively). A two-phase feeding strategy was applied, with 0.9 and 0.7 g of digestible lysine per MJ of net energy (NE) in diets provided before or after 65 kg BW, respectively. Actual growth was similar to that obtained by simulation. Coefficient of variation of BW1 was similar in vivo and in silico for the ad libitum feeding strategy but was underestimated by 1 percentage point in silico for the restriction strategy. This study confirms the relevance of using simulations performed to predict the level and variability in performance of group housed pigs.


46e Journées de la Recherche Porcine en France, Paris, France, 4-5 February, 2014. | 2014

Application of a feeding strategy designed by simulation from a virtual population of pigs to control the variability of weight at the end of fattening - comparison of in vivo and in silico growth performance.

L. Brossard; J. van Milgen; B. Vautier; Nathalie Quiniou


46e Journées de la Recherche Porcine en France, Paris, France, 4-5 February, 2014. | 2014

Body composition evolution studied by computer tomography (CT) on ad libitum or restrictively fed growing pigs.

M. Monziols; A. Hemonic; B. Vautier; L. Brossard; J. van Milgen; Nathalie Quiniou


46. Journées de la Recherche Porcine | 2014

Mise en œuvre d’un plan d’alimentation élaboré par simulations à partir d’une population virtuelle de porcs pour permettre une maîtrise de la variabilité du poids en fin d’engraissement.

L. Brossard; Jacob Van Milgen; B. Vautier; Nathalie Quiniou


46. Journées de la Recherche Porcine | 2014

Utilisation de la tomographie RX pour étudier l'évolution de la composition corporelle au cours de la croissance chez des porcs alimentés à volonté ou rationnés

Mathieu Monziols; Anne Hemonic; B. Vautier; L. Brossard; Jacob Van Milgen; Nathalie Quiniou


45e Journées de la Recherche Porcine, Paris, France, 5-6 February, 2013. | 2013

Modeling the effect of feeding strategy and feed prices on performance, variation among pigs, and nitrogen excretion in a population of pigs.

Nathalie Quiniou; B. Vautier; Yvon Salaün; J. van Milgen; L. Brossard


63. Annual Meeting of the European Association for Animal Production | 2012

Modeling the effect of feeding strategy and feed prices on a population of pigs

Nathalie Quiniou; B. Vautier; Yvon Salaün; Jacob Van Milgen; L. Brossard


44e Journées de la Recherche Porcine en France, Paris, France, 7-8 February 2012. | 2012

From one pig to a group of pigs: accounting for links among individual parameters in growth modeling at the population scale.

B. Vautier; L. Brossard; J. van Milgen; Nathalie Quiniou

Collaboration


Dive into the B. Vautier's collaboration.

Top Co-Authors

Avatar

L. Brossard

Institut national de la recherche agronomique

View shared research outputs
Top Co-Authors

Avatar

Nathalie Quiniou

Institut national de la recherche agronomique

View shared research outputs
Top Co-Authors

Avatar

J. van Milgen

Institut national de la recherche agronomique

View shared research outputs
Top Co-Authors

Avatar

Jacob Van Milgen

Institut national de la recherche agronomique

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Jean Pierre Bidanel

Institut national de la recherche agronomique

View shared research outputs
Top Co-Authors

Avatar

P. Sellier

Institut national de la recherche agronomique

View shared research outputs
Top Co-Authors

Avatar

R. Saintilan

Institut national de la recherche agronomique

View shared research outputs
Researchain Logo
Decentralizing Knowledge