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Early deviations in performance, metabolic and immunological indicators affect stayability in rabbit females

Published online by Cambridge University Press:  24 October 2019

M. Penadés
Affiliation:
Pathology group, PASAPTA, Facultad de Veterinaria, Universidad Cardenal Herrera-CEU, CEU Universities, Av. Seminario s/n, 46113 Moncada, Valencia, Spain
A. Arnau-Bonachera
Affiliation:
Pathology group, PASAPTA, Facultad de Veterinaria, Universidad Cardenal Herrera-CEU, CEU Universities, Av. Seminario s/n, 46113 Moncada, Valencia, Spain
L. Selva
Affiliation:
Pathology group, PASAPTA, Facultad de Veterinaria, Universidad Cardenal Herrera-CEU, CEU Universities, Av. Seminario s/n, 46113 Moncada, Valencia, Spain
D. Viana
Affiliation:
Pathology group, PASAPTA, Facultad de Veterinaria, Universidad Cardenal Herrera-CEU, CEU Universities, Av. Seminario s/n, 46113 Moncada, Valencia, Spain
T. Larsen
Affiliation:
Department of Animal Science, Integrative Physiology, Aarhus University, Blichers Allé 20, 8830 Tjele, Denmark
J.M. Corpa
Affiliation:
Pathology group, PASAPTA, Facultad de Veterinaria, Universidad Cardenal Herrera-CEU, CEU Universities, Av. Seminario s/n, 46113 Moncada, Valencia, Spain
J.J. Pascual*
Affiliation:
Institute for Animal Science and Technology, Universitat Politècnica de València, Camino de Vera 14, 46071 Valencia, Spain
D. Savietto
Affiliation:
GenPhySE, Université de Toulouse, INRA, ENVT, 31320, Castanet Tolosan, France
*
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Abstract

The main purpose of this study was to find several early factors affecting stayability in rabbit females. To reach this goal, 203 females were used from their first artificial insemination to their sixth parturition. Throughout that period, 48 traits were recorded, considered to be performance, metabolic and immunological indicators. These traits were initially recorded in females’ first reproductive cycle. Later, removed females due to death or culling and those that were non-removed were identified. A first analysis was used to explore whether it was possible to classify females between those reaching and those not reaching up to the mean lifespan of a rabbit female (the fifth reproductive) cycle using information from the first reproductive cycle. The analysis results showed that 97% of the non-removed females were classified correctly, whereas only 60% of the removed females were classified as animals to be removed. The reason for this difference lies in the model’s characteristics, which was designed using early traits and was able to classify only the cases in which females would be removed due to performance, metabolic or immunologic imbalances in their early lives. Our results suggest that the model defines the necessary conditions, but not the sufficient ones, for females to remain alive in the herd. The aim of a second analysis was to find out the main early differences between the non-removed and removed females. The live weights records taken in the first cycle indicated that the females removed in their first cycle were lighter, while those removed in their second cycle were heavier with longer stayability (−203 and +202 g on average, respectively; P < 0.05). Non-removed females showed higher glucose and lower beta-hydroxybutyrate concentrations in the first cycle than the removed females (+4.8 and −10.7%, respectively; P < 0.05). The average lymphocytes B counts in the first cycle were 22.7% higher in the non-removed females group (P < 0.05). The females removed in the first reproductive cycle presented a higher granulocytes/lymphocytes ratio in this cycle than those that at least reached the second cycle (4.81 v. 1.66; P < 0.001). Consequently, non-removed females at sixth parturition offered adequate body development and energy levels, less immunological stress and a more mature immune function in the first reproductive cycle. The females that deviated from this pattern were at higher risk of being removed from the herd.

Type
Research Article
Copyright
© The Animal Consortium 2019 

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References

Baselga, M 2004. Genetic improvement of meat rabbits. Programmes and diffusion. In Proceedings of the 8th World Rabbit Congress, 7–10 September 2004, Puebla, Mexico, pp. 1–13.Google Scholar
Bauman, DE and Currie, WB 1980. Partitioning of nutrients during pregnancy and lactation: a review of mechanisms Involving homeostasis and homeorhesis. Journal of Dairy Science 63, 15141529.CrossRefGoogle ScholarPubMed
Davis, AK, Maney, DL and Maerz, JC 2008. The use of leukocyte profiles to measure stress in vertebrates: a review for ecologists. Functional Ecology 22, 760772.CrossRefGoogle Scholar
Davis, WC and Hamilton, MJ 2008. Use of flow cytometry to develop and characterize a set of monoclonal antibodies specific for rabbit leukocyte differentiation molecules. Journal of Veterinary Science 9, 5166.CrossRefGoogle ScholarPubMed
Dufort, F 2012. Contribution of glucose metabolism to the B lymphocyte responses. PhD thesis, Boston College, Boston, MA, USA.Google Scholar
Fernández-Carmona, J, Blas, E, Pascual, JJ, Maertens, L, Gidenne, T, Xiccato, G and García, J 2005. Recommendations and guidelines for applied nutrition experiments in rabbits. World Rabbit Science 13, 209228.Google Scholar
Friggens, NC, Brun-Lafleur, L, Faverdin, P, Sauvant, D and Martin, O 2013. Advances in predicting nutrient partitioning in the dairy cow: recognizing the central role of genotype and its expression through time. Animal 7, 89101.CrossRefGoogle ScholarPubMed
García-Quirós, A, Arnau-Bonachera, A, Penadés, M, Cervera, C, Martínez-Paredes, E, Ródenas, L, Selva, L, Viana, D, Corpa, JM and Pascual, JJ 2014. A robust rabbit line increases leucocyte counts at weaning and reduces mortality by digestive disorder during fattening. Veterinary Immunology and Immunopathology 161, 123131.CrossRefGoogle ScholarPubMed
Gross, WB and Siegel, HS 1983. Evaluation of the heterophil/lymphocyte ratio as a measure of stress in chickens. Avian Diseases 27, 972979.CrossRefGoogle ScholarPubMed
Guerrero, I, Ferrian, S, Blas, E, Pascual, JJ, Cano, JL and Corpa, JM 2011. Evolution of the peripheral blood lymphocyte populations in multiparous rabbit does with two reproductive management rhythms. Veterinary Immunology and Immunopathology 140, 7581.CrossRefGoogle ScholarPubMed
Harano, Y, Ohtsuki, M, Ida, M, Kojima, H, Harada, M, Okanishi, T, Kashiwagi, A, Ochi, Y, Uno, S and Shigeta, Y 1985. Direct automated assay method for serum or urine levels of ketone bodies. Clinica Chimica Acta 151, 177183.CrossRefGoogle ScholarPubMed
Jacobsen, CN, Aasted, B, Broe, MK and Petersen, JL 1993. Reactivities of 20 anti-human monoclonal antibodies with leucocytes from ten different animal species. Veterinary Immunology and Immunopathology 39, 461466.CrossRefGoogle ScholarPubMed
Jasper, PJ, Zhai, SK, Kalis, SL, Kingzette, M and Knight, KLB 2003. Lymphocyte development in rabbit: progenitor B cells and waning of B lymphopoiesis. The Journal of Immunology 171, 63726380.CrossRefGoogle ScholarPubMed
Jeklova, E, Leva, L and Faldyna, M 2007a. Lymphoid organ development in rabbits: major lymphocyte subsets. Developmental and Comparative Immunology 31, 632644.CrossRefGoogle ScholarPubMed
Jeklova, E, Leva, L, Knotigova, P and Faldyna, M 2009. Age-related changes in selected haematology parameters in rabbits. Research in Veterinary Science 86, 525528.CrossRefGoogle ScholarPubMed
Jeklova, E, Leva, L, Kudlackova, H, and Faldyna, M 2007b. Functional development of immune response in rabbits. Veterinary Immunology and Immunopathology 118, 221228.CrossRefGoogle ScholarPubMed
Kotani, M, Yamamura, Y, Tamatani, T, Kitamura, F and Miyasaka, M 1993a. Generation and characterization of monoclomal antibodies against rabbit CD4, CD5 and CD11a antigens. Journal of Immunological Methods 157, 241252.CrossRefGoogle Scholar
Kotani, M, Yamamura, Y, Tamatani, T, Kitamura, F and Miyasaka, M 1993b. Generation of monoclonal antibodies to the rabbit interleukin-2 receptor alpha chain (CD25) and its distribution in HTLV-1 transformed rabbit T cells. Japanese Journal of Cancer Research 84, 770775.CrossRefGoogle ScholarPubMed
Martin, O and Sauvant, D 2010. A teleonomic model describing performance (body, milk and intake) during growth and over repeated reproductive cycles throughout the lifespan of dairy cattle. 2. Voluntary intake and energy partitioning. Animal 4, 20482056.CrossRefGoogle ScholarPubMed
Martínez-Paredes, E, Ródenas, L, Pascual, JJ and Savietto, D 2018. Early development and reproductive lifespan of rabbit females: implications of growth rate, rearing diet and body condition at first mating. Animal 12, 23472355.CrossRefGoogle ScholarPubMed
Mehrzad, J and Zhao, X 2008. T lymphocyte proliferative capacity and CD4+/CD8+ ratio in primiparous and pluriparous lactating cows. Journal of Dairy Research 75, 457465.CrossRefGoogle ScholarPubMed
Miller, JP and Cancro, MP 2007. B cells and aging: balancing the homeostatic equation. Experimental Gerontology 42, 396399.CrossRefGoogle ScholarPubMed
Neeteson-van Nieuwenhoven, A-M, Knap, P and Avendano, S 2013. The role of sustainable commercial pig and poultry breeding for food security. Animal Frontiers 3, 5257.CrossRefGoogle Scholar
O’Dowd, S, Hoste, S, Mercer, JT, Fowler, VR and Edwards, SA 1997. Nutritional modification of body composition and the consequences for reproductive performance and longevity in genetically lean sows. Livestock Production Science 52, 155165.CrossRefGoogle 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.CrossRefGoogle Scholar
Pascual, JJ, Cervera, C, Blas, E and Fernández-Carmona, J 1998. Effect of high fat diets on the performance and food intake of primiparous and multiparous rabbit does. Animal Science 66, 491499.CrossRefGoogle Scholar
Piles, M, Garreau, H, Rafel, O, Larzul, C, Ramon, J and Ducrocq, V 2006. Survival analysis in two lines of rabbits selected for reproductive traits. Journal of Animal Science 84, 16581665.CrossRefGoogle ScholarPubMed
Quevedo, F, Cervera, C, Blas, E, Baselga, M and Pascual, JJ 2006. Long-term effect of selection for litter size and feeding programme on the performance of reproductive rabbit does 2. Lactation and growing period. Animal Science 82, 751762.CrossRefGoogle Scholar
Rauw, WM 2009. Introduction. In Resource allocation theory applied to farm animal production (ed. Rauw, WM), pp. 121. CABI Publishing, Wallingford, UK.Google Scholar
Rosell, JM and de la Fuente, LF 2009. Culling and mortality in breeding rabbits. Preventive Veterinary Medicine 88, 120127.CrossRefGoogle ScholarPubMed
Sauvant, D, Soyeux, Y and Chilliard, Y 1983. Réflexions sur l’étiopathogénie des maladies de la nutrition. Bulletin Technique CRZV Theix INRA 53, 117121.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.CrossRefGoogle ScholarPubMed
Tarrés, J, Tibau, J, Piedrafita, J, Fàbrega, E and Reixach, J 2006. Factors affecting longevity in maternal Duroc swine lines. Livestock Science 100, 121131.CrossRefGoogle Scholar
ten Napel, J, van der Veen, AA, Oosting, SJ and Koerkamp, PWGG 2011. A conceptual approach to design livestock production systems for robustness to enhance sustainability. Livestock Science 139, 150160.CrossRefGoogle 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.CrossRefGoogle Scholar
Xiccato, G 1996. Nutrition of lactation does. In Proceedings of the 6th World Rabbit Congress, 9–12 July 1996, Toulouse, France, pp. 29–47.Google Scholar
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