The suitability of the Happy Factor decision support model as the determinant of a targeted selective treatment regime incorporated into an automated weighing and drafting facility was evaluated in a Canterbury environment. One hundred and twenty, six-month-old Coopworth lambs naturally infected with gastrointestinal parasites were weighed and faecal sampled every two weeks for eight weeks. Individual performance targets during each two week period were calculated using the Happy Factor decision support model. Lambs that did not reach their performance target were automatically drafted out and subsequently treated with anthelmintic. Those deemed to benefit from treatment had significantly greater faecal egg count (FEC) than their untreated counterparts at Week 4 only, were lighter on Weeks 2 and 8, but had lower liveweight gains on all four occasions. Overall, the system provided a rapid and reliable method of identifying and separating poorer performing individuals, which were not necessarily those with a high FEC or those that were lighter. Furthermore, the optimum treatment threshold was determined to be 0.74, which is greater than previously published values of 0.66 for Scottish Blackface sheep. This suggests that validation of an optimum Happy Factor treatment threshold for each environment and/or animal genotype may be required.

AW, Greer, RW McAnulty, CM Logan, and SO Hoskin

Proceedings of the New Zealand Society of Animal Production, Volume 70, Palmerston North, 213-216, 2010
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