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RESEARCH ARTICLE

Economic implications of environmental variation observed in a pig nucleus farm in Australia

S. Hermesch A D , R. Sokolinski B , R. Johnston B and S. Newman C
+ Author Affiliations
- Author Affiliations

A Animal Genetics and Breeding Unit, a joint venture of NSW DPI and University of New England, Armidale, NSW 2351.

B PIC Australia, Grong Grong, NSW 2652.

C Genus plc, Hendersonville, TN 37075.

D Corresponding author. Email: Susanne.Hermesch@une.edu.au

Animal Production Science 55(12) 1466-1466 https://doi.org/10.1071/ANv55n12Ab066
Published: 11 November 2015

The performance of a group of pigs, adjusted for other known systematic and genetic effects, can be used to quantify environmental variation (EnVar) on farms. Using such an approach, Li and Hermesch (2015) found variation between environments for average daily gain (ADG) and backfat (BF) in nucleus herds with good management and high health status that was similar to the genetic variation. In that study, EnVar for daily feed intake (DFI) and feed conversion ratio (FCR) could not be assessed because data for DFI were not available. The economic implications of EnVar may be evaluated by multiplying differences in group means for each trait by the corresponding economic value (EV) (Hermesch et al. 2014). An EV for a trait quantifies the change in profit when the trait is changed by one unit. It is independent from other EVs and can be applied to other non-genetic factors. We hypothesised that EnVar exists in a nucleus farm for ADG, BF, DFI and FCR leading to economic differences between environments.

Data were obtained from 90,524 growing pigs from seven lines recorded from 2008 to 2014. The ADG and BF were measured at an average live weight of 96.7 kg. A proportion of pigs (3,045) had DFI records along with the associated traits of test daily gain (TDG) and FCR. An animal model was applied using ASReml (Gilmour et al. 2009) and fitting common litter effect as an additional random effect. Fixed effects were birth week or birth month, sex (ADG, BF), line, line by sex interaction (ADG), birth farm and weight at recording as a linear covariable (BF). Variation in weekly or monthly estimates (solutions) may also have been due to systematic changes over time like a change in target market weight. For ADG, birth week or birth month was fitted within two separate time periods to account for differences in market weight. Birth week or birth month estimates, centred on zero for each trait, were the environmental variables describing environmental conditions (EADG, EBF, EDFI, ETDG, EFCR). Using EVs of Hermesch et al. (2014), economic indexes ($/pig) were derived to quantify economic implications of EnVar: IDFI is a function of EADG, EBF and EDFI; and IFCR is a function of EADG, EBF and EFCR.

Considerable variation in environmental conditions was observed for all traits (Table 1), which was similar to the results of Li and Hermesch (2015) for ADG and BF. Environmental variables differed more for weekly groups than monthly groups, partly due to better accounting of environmental conditions and partly due to larger sampling effects of weekly groups. Standard errors doubled for EADG and EBF and tripled for EDFI, ETDG or EFCR for weekly versus monthly groups. Environments differed more for EDFI than EFCR, which may indicate that DFI captures differences in environments better. As a result economic indexes including DFI varied more, differing by $17.41/pig for IDFI in comparison to $11.78/pig for IFCR for monthly groups. These differences in economic indexes need to be multiplied by the number of pigs per group to quantify economic implications of variation in environmental conditions for groups of pigs. Results from this study suggest that investing in improvement of environmental conditions on farms, practising good health and management, should be considered by producers.


Table 1.  The number of groups (N), standard deviations (SD), average standard errors (SE), and maximum range (Range) of estimates for birth month or birth week for each trait (Etrait) and each economic index
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References

Gilmour AR, Gogel BJ, Cullis BR, Thompson R (2009) ‘ASReml user guide. Release 3.0.’ (VSN International Ltd: Hemel Hempstead)

Hermesch S, Ludemann CI, Amer PR (2014) Journal of Animal Science 92, 5358–5366.
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Li L, Hermesch S (2015) Animal Production Science
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