Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/56508
Title: Improving the Survival of Growing Pigs
Contributor(s): Harper, Jo-anne  (author); Bunter, Kim L  (supervisor)orcid ; Collins, Cherie (supervisor); Hermesch, Susanne  (supervisor)orcid 
Conferred Date: 2023-10-26
Copyright Date: 2023-03
Handle Link: https://hdl.handle.net/1959.11/56508
Related Research Outputs: https://hdl.handle.net/1959.11/56509
Abstract: 

Survival of growing pigs through to slaughter age is not only a key driver of profitability but also has implications for animal welfare. The primary objectives of this study were to 1) investigate the non-genetic and genetic factors that influence individual piglet pre- and post-weaning mortality, 2) gain a better understanding of the genetic correlation between purebred and crossbred mortality traits, and 3) explore other avenues for decreasing mortality through selective breeding, such as the relationship between immunity and survival outcomes. In this study a piglet was recorded as a pre-weaning death (PREw) if it was born alive and died up until, and including, the day of weaning (0= alive, 1= dead). A post-weaning death (POSTw) was recorded if the piglet had been weaned and was less than 70 days of age at death and is often referred to as nursery mortality. Piglets born still-born were excluded from examination in this study.

To address objective one, it was hypothesised that both non-genetic and genetic factors were significant contributors to piglet mortality outcomes and in the presence of fostering activities, a nurse sow model would be more informative than a biological dam model. The factors that influence individual piglet pre- and post-weaning mortality traits (non-genetic animal factors in Chapter 3 and genetic factors in Chapter 4) were investigated using a dataset that included purebred and crossbred piglets (total N = 614,573), recorded between March 2009 and December 2019. The availability of a large dataset over a long period of time has allowed the investigations of factors into survival that have been poorly quantified in previous studies, often due to a low number of animals recorded.

Chapter 3 analysed mortality records which included datasets over two time-periods, March 2009 to March 2011 and January 2017 to December 2018. The results presented in this chapter firstly identified that total born (TB) had a strong linear association with piglet birthweight (PBWT). The average piglet birthweight decreased by 37.3 ± 0.0003 grams per piglet for every piglet increase in TB. However, non-linear relationships were evident between PBWT or TB and piglet mortality. For example, a curvilinear relationship was evident between PBWT and PREw up until the fourth decile, after which reductions in mortality were more linear. The effects of TB for PREw was greatly reduced when the effect of PBWT was simultaneously fitted in the model, suggesting that much of the effect of litter size on mortality is a consequence of the effects of litter size on piglet birthweight. From this study it was also evident that successful genetic strategies to increase total born does not universally increase mortality. High total born and low mortality are possible as demonstrated between the time-periods outlined above. Individual piglet birthweight (PBWT) was the main factor associated with the ability of individual piglets to survive. Other factors identified to have significant impacts on survival were piglet genotype, gestation length, biological dam and nurse sow parities, fostering status of the piglet, piglet gender and weaning age. Although these effects on mortality were relatively small, they are generally not known under normal commercial production, and could provide valuable information for management decisions. For example, supporting litters who have been born before 114 days of gestation or to very young or old sows, fostering lightweight piglets who have not established a teat within the first day of life, or avoiding the weaning of individuals before 21 days of age, even when weight based criterion might suggest they are ready to wean.

Following the identification of systematic effects in Chapter 3, alternative models for genetic evaluation of the pre- and post-weaning mortality traits were investigated in Chapter 4. For pre-weaning mortality, the best linear model accounted for direct piglet effects, common litter effects of both the nurse sow and biological dam, repeated records of the nurse sow and the maternal nurse sow genetic effects, in preference to a comparable model based on these effects represented by the biological dam only. For post-weaning mortality, the most parsimonious linear model included only direct piglet effects along with the common litter effects of both the nurse sow and biological dam. After accounting for systematic effects, genes of the piglet contributed to both pre- and post-weaning mortality (direct h2: 0.02 ± 0.002 for PREw and POSTw), whereas the nurse sow genes only contributed to pre-weaning mortality (m2: 0.01 ± 0.002). The heritability and variation obtained from sire threshold models (PREw h2: 0.08 ± 0.007 and POSTw h2: 0.07 ± 0.007) were higher, suggesting the linear animal model estimates were biased downwards and that genetic improvements can be made at both the direct and maternal levels

To address objective two, it was hypothesised that genetic correlations between purebred and crossbred mortality would be high when they are recorded in the same production environment and are represented through some common parents. Chapter 5 explored the relationships between purebred and crossbred PREw and POSTw, where bivariate analyses were conducted to estimate genetic correlations. The dataset used for this study had records for purebred and crossbred animals, who were recorded together on the same farm and experiencing similar production conditions, which is very rare to find in the literature for any trait. As the incidence of mortality was similar between purebred and crossbred PREw, the estimated variance components were also similar. Likewise, variance component estimates also reflected the incidence of mortality for POSTw, as crossbred mortality was approximately half that of purebreds. The estimates of the additive genetic correlations between purebred and crossbred performances were high (PREw ra: 0.78 ± 0.097 and POSTw ra: 0.94 ± 0.112), indicating that purebred and crossbred mortality traits are controlled by the same genes. The high correlations, within this population and environment, demonstrate that survival traits of crossbred pigs can be improved using genetic evaluation and selection based on purebred records.

To address objective three, it was hypothesised that the immune phenotype measures of mature boars would be associated with survival of their progeny reared in commercial environments, based on the assumptions that immune phenotypes are both variable and heritable. The ability to link immune phenotypes and progeny survival is novel as there is very little literature published, due to the number of progeny required to conduct this type of research. A pilot study conducted on nine mature boars, presented in Chapter 6, found that simple testing procedures could be developed which used commercially available vaccines, containing tetanus toxoid as a model antigen. Vaccination was used to induce measurable immune responses that can be used to assess the immune phenotype measures of mature boars. Using these procedures, a further 87 boars were assessed for their ability to mount antibody (Ab-IR) and cell (Cell-IR) mediated immune responses. The associations between boar Ab-IR and Cell-IR immune phenotypes with their own estimated breeding values (EBVs) for direct (sPREd) and maternal (sPREm) components of preweaning mortality and direct post-weaning (sPOSTd) mortality were tested. These EBVs were estimated from accurate evaluation of the progeny these boars sired and are presented in this thesis as survival percentages. Also, the ability of these boars daughters to rear progeny in their first litter and the ability of their progeny to mount their own antibody mediated immune response were verified.

The results presented in Chapter 7 showed that as sire Cell-IR responses increased, there was an increase in independent estimates of breeding values for sPREd and sPOSTd survival. It was unexpected that there was no association between Ab-IR and sPOSTd based on sire EBVs. Results demonstrated that variation in immune phenotype measures of boars were associated with the survival of their progeny, reared in commercial environments. Results also suggested that CellIR phenotype had a greater influence on sPREd and sPOSTd than Ab-IR in the animals studied. Further to this, an enhanced boar immune phenotype was reflected in a higher maternal performance of daughters in their first parity by improving their progeny survival and therefore the number of piglets weaned. And finally, immune phenotypes of sires was associated with the ability of their progeny to mount an antibody mediated immune response to the same model antigen. These results provide encouraging evidence that the model developed for immune phenotype testing was informative and more extensive testing of selection candidates should be carried out to obtain estimates of genetic parameters and understand the impact on other economically important traits. This would require assessment of suitable testing protocols for selection candidates.

In conclusion the research conducted in this thesis has shown that progeny survival is the outcome of complex non-genetic and genetic interactions between the piglet, the biological dam, the nurse sow and the environment, including management decisions such as fostering. Although heritabilities for direct and maternal effects on survival are low, there is potential for genetic improvement to be delivered to the commercial tier of the breeding pyramid due to high correlations between purebred and crossbred animals, independent of other important traits such as birthweight, gestation length and litter size. Finally, selection for immune phenotype measures has the potential to further improve survival of growing pigs.

Publication Type: Thesis Doctoral
Fields of Research (FoR) 2020: 300302 Animal management
300305 Animal reproduction and breeding
300306 Animal welfare
Socio-Economic Objective (SEO) 2020: 100410 Pigs
109902 Animal welfare
280101 Expanding knowledge in the agricultural, food and veterinary sciences
HERDC Category Description: T2 Thesis - Doctorate by Research
Description: Please contact rune@une.edu.au if you require access to this thesis for the purpose of research or study.
Appears in Collections:Animal Genetics and Breeding Unit (AGBU)
School of Environmental and Rural Science
Thesis Doctoral

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