Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-23T07:25:58.297Z Has data issue: false hasContentIssue false

Correlated response in body condition and energy mobilisation in rabbits selected for litter size variability

Published online by Cambridge University Press:  28 August 2018

M. L. García*
Affiliation:
Departamento de Tecnología Agroalimentaria, Universidad Miguel Hernández de Elche, Ctra de Beniel Km 3.2, 03312 Orihuela, Spain
A. Blasco
Affiliation:
Institute for Animal Science and Technology, Universitat Politècnica de València, P.O. Box 22012, 46022 Valencia, Spain
M. E. García
Affiliation:
Departamento de Tecnología Agroalimentaria, Universidad Miguel Hernández de Elche, Ctra de Beniel Km 3.2, 03312 Orihuela, Spain
M. J. Argente
Affiliation:
Departamento de Tecnología Agroalimentaria, Universidad Miguel Hernández de Elche, Ctra de Beniel Km 3.2, 03312 Orihuela, Spain
*
Get access

Abstract

A divergent selection experiment on litter size variability (high and low lines) was performed in rabbits over seven generations. The aim of this study was to evaluate the correlated responses to selection in body condition and fat reserves mobilisation. Litter size variability was estimated as phenotypic variance of litter size within female after correcting for the year-season and the parity-lactation status effects. A total of 226 females were used in this study, of which 158 females were used to measure body condition and energy mobilisation. Body condition was measured as BW and perirenal fat thickness. Females were stimulated with the adrenergic isoproterenol. Mobilisation capacity of fat reserves was measured by the lipolytic potential, defined as the increment in non-esterified fatty acids (NEFA) levels from basal concentration until adrenergic stimulation at mating, delivery and 10 days after delivery of the second reproductive cycle. Females were classified as survivor or non-survivor when they were culled for sanitary reasons or died before the third kindling. Data were analysed using Bayesian methodology. Survivor females presented higher BW than the non-survivor females at delivery (238 g, P=1.00) and 10 days after delivery (276 g, P=1.00). They also showed higher perirenal fat thickness at 10 days after delivery (0.62 mm, P=1.00). At delivery, basal NEFA levels was lower in survivor than non-survivor females (−0.18 mmol/l, P=1.00), but their lipolytic potential (∆NEFA) was higher (0.08 mmol/l, P=0.94). Body weight was similar between lines in survivor females. Perirenal fat thickness was lower in the high line than in the low line at delivery (−0.23 mm, P=0.90) and 10 days after delivery (−0.28 mm, P=0.92). The high line exhibited higher NEFA (0.10 mmol/l, P=0.93) and lower ∆NEFA (−0.08 mmol/l, P=0.92) than the low line at delivery. The low line showed a favourable correlated response to selection on body condition and fat reserves mobilisation. In conclusion, the low line selected for litter size variability seems to adapt better to adverse conditions, as it has a greater capacity to mobilise energy reserves at delivery than the high line. Females that adequately manage their body reserves and perform energy mobilisation correctly have a lower risk of dying or being culled.

Type
Research Article
Copyright
© The Animal Consortium 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Amat, JA, Aguilera, E and Visser, GH 2007. Energetic and developmental costs of mounting an immune response in greenfinches (Carduelis chloris). Ecological Research 22, 282287.Google Scholar
Bareille, N, Beaudeau, F, Billon, S, Robert, A and Faverdin, P 2003. Effects of health disorders on feed intake and milk production in dairy cows. Livestock Production Science 83, 5362.Google Scholar
Blache, D, Terlouw, C and Maloney, SK 2011. Physiology. In Animal welfare (ed. MC Appleby, BO Hughes, A Joy and JA Mench), pp. 155182. CAB International, Wallingford, UK.Google Scholar
Blasco, A. 2017. Bayesian data analysis for animal scientists. Springer, New York, NY, USA.Google Scholar
Blasco, A, Martínez-Álvaro, M, Garcia, ML, Capcarova, M, Zbynovska, K, Petruska, P, Ibáñez-Escriche, N and Argente, MJ 2018. Selection for genetic environmental sensitivity of litter size changes resilience in rabbits. In 11th World Congress on Genetics Applied to Livestock Production, 11–16 February 2018, Auckland, New Zealand.Google Scholar
Blasco, A, Martínez-Álvaro, M, Garcia, ML, Ibáñez-Escriche, N and Argente, MJ 2017. Selection for environmental variance of litter size in rabbits. Genetic Selection Evolution 49, 48.Google Scholar
Broom, MD 2009. Consequences of biological engineering for resource allocation and welfare. In Resource allocation theory applied to farm animal production (ed. WM Rauw), pp. 261274. CAB International, Wallingford, UK.Google Scholar
Chilliard, Y 1993. Dietary fat and adipose tissue metabolism in ruminants, pigs and rodents: a review. Journal Dairy Science 76, 38973931.Google Scholar
Feugier, A and Fortun-Lamothe, L 2006. Extensive reproductive rhythm and early weaning improve body condition and fertility of rabbit does. Animal Research 55, 459470.Google Scholar
Fortun, L, Prunier, A, Etienne, M and Lebas, F 1994. Influence of nutritional deficit on foetal survival and growth and blood metabolites in rabbit does. Reproduction, Nutrition, Development 34, 201211.Google Scholar
Fortun-Lamothe, L 2006. Energy balance and reproductive performance in rabbits does. Animal Reproduction Science 93, 115.Google Scholar
Friggens, NC 2003. Body lipid reserves and reproductive cycle: towards a better understanding. Livestock Production Science 83, 219236.Google Scholar
García, ML, Argente, MJ, Muelas, R, Birlanga, V and Blasco, A 2012. Effect of divergent selection for residual variance of litter size on health status and welfare. In Proceedings of the 10th World Rabbit Congress, 3–6 September 2012, Sharm El-Sheikh, Egypt, pp. 103106.Google Scholar
Garnsworthy, PC 2006. BCS in dairy cows: targets for production and fertility. In Recent advances in animal nutrition (ed. PG Garnsworthy and J Wiseman), pp. 6186. Nottingham University Press, Nottingham, UK.Google Scholar
Gellrich, K, Sigl, T, Mayer, HHD and Wiedemann, S 2015. Cortisol levels in skimmed milk during the first 22 weeks of lactation and response to short-term metabolic stress and lameness in dairy cows. Journal of Animal Science and Biotechnology 6, 3138.Google Scholar
Geyer, CM 1992. Practical markow chain Monte Carlo (with discussion). Statistical Science 7, 467511.Google Scholar
Johnson, RW 1998. Immune and endocrine regulation of food intake in sick animals. Domestic Animal Endocrinology 15, 309319.Google Scholar
Martinez-Paredes, E, Ródenas, L, Martínez-Vallespín, B, Cervera, C, Blas, E, Brecchia, G, Boiti, C and Pascual, JJ 2012. Effects of feeding programme on the performance and energy balance of nulliparous rabbit does. Animal 6, 10861095.Google Scholar
Pascual, JJ, Blanco, J, Piquer, O and Quevedo, F, Cervera 2004. Ultrasound measurements of perirenal fat thickness to estimate the body condition of reproducing rabbit does in different physiological status. World Rabbit Science 12, 722.Google Scholar
Pascual, JJ, Castella, F, Cervera, C, Blas, E and Fernández-Carmona, J 2000. The use of ultrasound measurement of perirenal fat thickness to estimate changes in body condition of young female rabbits. Animal Science 70, 435442.Google Scholar
Pilorz, V, Jäckel, M, Knudsen, K and Trillmich, F 2005. The cost of a specific immune response in young guinea pigs. Physiology & Behavior 85, 205211.Google Scholar
Roche, JR, Friggens, NC, Kay, JK, Fisher, MW, Stafford, KJ and Berry, DP 2009. Invited review: body condition score and its association with dairy cow productivity, health, and welfare. Journal Dairy Science 92, 57695801.Google Scholar
Rosell, JM and de la Fuente, LF 2009. Culling and mortality in breeding rabbits. Preventive Veterinary Medicine 88, 120127.Google Scholar
Rosell, JM and de la Fuente, LF 2016. Causes of mortality in breeding rabbits. Preventive Veterinary Medicine 127, 5663.Google Scholar
Savietto, D, Cervera, C, Blas, E, Baselga, M, Larsen, T, Friggens, NC and Pascual, JJ 2013. Environmental sensitivity differs between rabbit lines selected for reproductive intensity and longevity. Animal 7, 19691977.Google Scholar
Sorensen, D and Gianola, D 2002. Likelihood, bayesian, and MCMC methods. Quantitative genetics, 1st edition. Springer-Verlag, New York, NY, USA.Google Scholar
Theilgaard, P, Baselga, M, Blas, E, Friggens, NC, Cercera, C and Pascual, JJ 2009. Differences in productive robustness in rabbits selected for reproductive longevity or litter size. Animal 3, 637646.Google Scholar
Theilgaard, P, Facila, S, Blas, E, Baselga, M and Pascual, JJ 2005. Time and dose response of blood non-esterified fatty acids to adrenergic stimulation in rabbit does. World Rabbit Science 13, 189195.Google Scholar
Theilgaard, P, Sánchez, JP, Pascual, JJ, Friggens, NC and Baselga, M 2006. Effect of body fatness and selection for prolificacy on survival of rabbit does assessed using a cryopreserved control population. Livestock Science 103, 6573.Google Scholar
Webster-Marketon, JI and Glaser, R 2008. Stress hormones and immune function. Cell Immunology 252, 1626.Google Scholar