TY - GEN
T1 - Managing Consequences of Increasing Litter Size
T2 - APSA 2009: 12th Biennial Conference of the Australasian Pig Science Association
AU - Bunter, Kim L
PY - 2009
Y1 - 2009
N2 - Selection for efficient lean growth and litter size can have detrimental consequences for piglet survival. However, survival traits themselves are lowly heritable, making it possible to select for improved survival directly in breeding programs. The generally low magnitudes of unfavourable genetic correlations between traits indicate it is possible to achieve genetic gains in production, litter size and survival traits concurrently. To select for piglet survival successfully requires the implementation of extensive data recording for individual mortality, combined with best-linear unbiased prediction (BLUP) genetic evaluation methodology. Accurate genetic evaluation of piglet mortality is complicated by the categorical nature of some trait definitions, low heritability, the large scale of recording required, population specific management and cross-fostering effects, and potentially the presence of both piglet and sow related genetic and environmental components affecting outcomes. In addition, while prenatal, postnatal and late lactation phases of piglet survival are not strictly independent events, the best approach to selection might differ depending on the relative contributions of each phase to piglet deaths. It is unlikely that there is a generic approach which is universally optimal for all breeding operations. The combination of high performance computing and inexpensive data storage has increased capabilities to apply more complex genetic evaluation procedures, which continue to alter possibilities for selection in this area. However, the efficacy of the chosen strategy should be validated in commercial populations. All breeding companies agree that a balanced breeding goal will include strategies to reduce piglet losses.
AB - Selection for efficient lean growth and litter size can have detrimental consequences for piglet survival. However, survival traits themselves are lowly heritable, making it possible to select for improved survival directly in breeding programs. The generally low magnitudes of unfavourable genetic correlations between traits indicate it is possible to achieve genetic gains in production, litter size and survival traits concurrently. To select for piglet survival successfully requires the implementation of extensive data recording for individual mortality, combined with best-linear unbiased prediction (BLUP) genetic evaluation methodology. Accurate genetic evaluation of piglet mortality is complicated by the categorical nature of some trait definitions, low heritability, the large scale of recording required, population specific management and cross-fostering effects, and potentially the presence of both piglet and sow related genetic and environmental components affecting outcomes. In addition, while prenatal, postnatal and late lactation phases of piglet survival are not strictly independent events, the best approach to selection might differ depending on the relative contributions of each phase to piglet deaths. It is unlikely that there is a generic approach which is universally optimal for all breeding operations. The combination of high performance computing and inexpensive data storage has increased capabilities to apply more complex genetic evaluation procedures, which continue to alter possibilities for selection in this area. However, the efficacy of the chosen strategy should be validated in commercial populations. All breeding companies agree that a balanced breeding goal will include strategies to reduce piglet losses.
KW - Animal Breeding
UR - http://trove.nla.gov.au/work/11098901
M3 - Conference contribution
SN - 9780980688009
T3 - Manipulating Pig Production
SP - 149
EP - 156
BT - Proceedings of the Twelfth Biennial Conference of the Australasian Pig Science Association (APSA)
A2 - J van Barneveld, Robert
PB - Australasian Pig Science Association Inc
CY - Werribee, Australia
Y2 - 22 November 2009 through 25 November 2009
ER -