Projects per year
Abstract
Many efforts are being made to cope with negative consequences of climate change on livestock. Among them, selective breeding of resilient animals to climate change is presented as an opportunity to maintain high levels of performance regardless of variation in weather. In the present work, we proposed a set of breeding strategies to improve weather resilience in dairy goats raised in north-western European Atlantic conditions and dairy sheep raised in Mediterranean conditions while improving production efficiency at the same time. Breeding strategies differed in the selection emphasis placed on resilience traits, ranging from 0 to 40% in the index. Simulations were carried out mimicking real breeding programmes including: milk yield, length of productive life, age at first kidding and mastitis incidence in dairy goats and milk, fat and protein yields, and fertility for dairy sheep. Considering the particular climatic conditions in the two regions, the predicted future climate scenarios, and genetic correlations among breeding objectives, resilience was defined as stability to weather changes for dairy goats and as the ability to improve performance under heat stress for dairy sheep. A strategy giving a selection weight of 10% and 20% for goat and sheep resilience, respectively, resulted in the best overall genetic response in terms of both, production and resilience ability. Not considering resilience in breeding programs could lead to a major production loss in future climate scenarios, whereas putting too much emphasis on resilience would results in a limited progress in milk production.
Original language | English |
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Article number | 692121 |
Number of pages | 11 |
Journal | Frontiers in Genetics |
Volume | 12 |
Early online date | 3 Sept 2021 |
DOIs | |
Publication status | First published - 3 Sept 2021 |
Keywords
- resilience
- climate change
- breeding strategies
- Dairy
- Ruminants
- ruminants
- dairy
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- 1 Finished
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iSAGE Innovation for sustainable sheep and goat production in Europe
Banos, G. (PI), Conington, J. (CoI), Lambe, N. (CoI), Wall, E. (CoI) & Topp, K. (CoI)
1/03/16 → 31/03/20
Project: Research