Xavier Averós

Dr. Xavier Averós


Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 October 2016 in Animals
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Journal Article
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NSNeila Ben Sassi
Neila Ben Sassi
XAXavier Averós
Xavier Averós
IEInma Estevez
Inma Estevez
Consideration of animal welfare is essential to address the consumers’ demands and for the long term sustainability of commercial poultry. However, assessing welfare in large poultry flocks, to be able to detect potential welfare risks and to control or minimize its impact is difficult. Current developments in technology and mathematical modelling open new possibilities for real-time automatic monitoring of animal welfare and health. New technological innovations potentially adaptable to commercial poultry are appearing, although their practical implementation is still being defined. In this paper, we review the latest technological developments with potential to be applied to poultry welfare, especially for broiler chickens and laying hens. Some of the examples that are presented and discussed include the following: sensors for farm environmental monitoring, movement, or physiological parameters; imaging technologies such as optical flow to detect gait problems and feather pecking; infrared technologies to evaluate birds’ thermoregulatory features and metabolism changes, that may be indicative of welfare, health and management problems. All these technologies have the potential to be implemented at the commercial level to improve birds’ welfare and to optimize flock management, therefore, improving the efficiency of the system in terms of use of resources and, thus, long term sustainability.

1 November 2010 in Applied Animal Behaviour Science
Verified
Journal Article
Closed access
XAXavier Averós
Xavier Averós
LBLudovic Brossard
Ludovic Brossard
JDJean-Yves Dourmad
Jean-Yves Dourmad
KGKarel H. de Greef
Karel H. de Greef
HEHelen L. Edge
Helen L. Edge
MMMarie-Christine Meunier-Salaün
Marie-Christine Meunier-Salaün

1 August 2006 in Meat Science
Verified
Journal Article
Closed access
LGL.F. Gosálvez
L.F. Gosálvez
XAXavier Averós
Xavier Averós
JVJ.J. Valdelvira
J.J. Valdelvira
AHA. Herranz
A. Herranz

27 September 2008 in Veterinary Record
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Journal Article
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XAXavier Averós
Xavier Averós
TKT. Knowles
T. Knowles
SBS. N. Brown
S. N. Brown
PWP. D. Warriss
P. D. Warriss
LGL. F. Gosálvez
L. F. Gosálvez
A multilevel logistic regression model was used to identify and quantify the effects of factors affecting the mortality of pigs being transported to slaughter under commercial conditions. A survey of 739 journeys to 37 slaughterhouses in five eu countries was carried out, and information potentially related to the welfare and mortality of the pigs and the number of injuries were recorded. The average temperature during the journey, its duration, the average loading time per pig, the recorded injuries, fasting before transport, and the interaction between fasting and journey duration were used in the final model. The average mortality was 0·11 per cent and the average proportion of injured pigs was 0·36 per cent, and these figures were significantly correlated (P<0·001). In 29 per cent of the journeys the pigs were not fasted before being loaded, which doubled the risk of mortality irrespective of whether the pigs were injured or not. The risk of mortality increased with average temperature. In journeys with fasted pigs that did not have any recorded injury, average temperature was more important than the duration of the journey. The risk of mortality increased as the average time taken to load them decreased, and the risk was highest when the pigs were not fasted and when injuries were recorded. Other factors such as the country, loading density, availability of drinking water and type of ventilation did not affect the risk of mortality.

31 August 2007 in Veterinarni Medicina
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Journal Article
Open access
XAXavier Averós
Xavier Averós
AHA. Herranz
A. Herranz
RSR. Sanchez
R. Sanchez
JCJ.X. Comella
J.X. Comella
LGL.F. Gosalvez
L.F. Gosalvez
» Articles | Agricultural Journals

1 January 2010 in Animal
Verified
Journal Article
Open access
PDF file
XAXavier Averós
Xavier Averós
LBL. Brossard
L. Brossard
JDJ. Y. Dourmad
J. Y. Dourmad
KGK. H. de Greef
K. H. de Greef
HEH. L. Edge
H. L. Edge
MMM. C. Meunier-Salaün
M. C. Meunier-Salaün
To obtain quantitative information that can be later used in animal welfare modelling, the relationship between the lying behaviour of growing-finishing pigs (initial body weight (BW) between 19 and 87 kg) and different factors related to the housing conditions, with a potential negative effect on their welfare, was studied by means of a meta-analytical approach. Data from 22 experiments reported in 21 scientific publications were collected. The space allowance, expressed on an allometric basis by means of a k-value (m2/BW0.667), the group size (n) and the floor characteristics (fully and partly slatted v. non-slatted floor), as well as their significant two-way interactions were used as fixed effects, and the experiment was used as a random factor to take into account the interexperiment effect. Further regression analyses were performed on the predicted values of observations in order to improve the adjustment of data. A significant quadratic relationship was established between space allowance (k-value, P < 0.05; squared k-value, P < 0.01) and the percentage of time spent lying. A significant interaction between the k-value and the floor type was also found (P < 0.05), showing that the relationship between space allowance and lying behaviour is affected by the presence or absence of slats. Threshold k-values were obtained using broken-line analyses, being about 0.039 for slatted floors and almost double for non-slatted floors. Compared to other studies, these values suggest that the ability to rest as space availability decreases may be compromised before a reduced performance becomes apparent. Group size did not show a significant effect. Additional information should be added to the model, as further data become available, to adjust the proposed parameters as well as to try to include the effect of other important aspects such as that of ambient temperature.