V.ISC.2213 - Enhancing animal disease reporting and benchmarking into future feedback
Linking other datasets with carcase data gives you greater insights into performance.
| Project start date: | 10 June 2022 |
| Project end date: | 15 December 2023 |
| Publication date: | 30 January 2024 |
| Project status: | Completed |
| Livestock species: | Grain-fed Cattle, Grass-fed Cattle, Sheep, Goat, Lamb |
| Relevant regions: | National |
Summary
This project focuses on further developing the necessary structures, systems and resources to embed disease and defect reporting that is linked to carcase performance within Future Feedback to provide for robust benchmark reporting. Datasets will be linked to other data such as BOM reports to provide greater insights for regional benchmarking etc. The research will also provide expertise in the field of veterinary medicine assisting producers to interpret and utilise disease and defect data reporting from Future Feedback to make significant and impactful changes on farm to improve overall carcase performance.
Objectives
1. Work with integrated and independent processors to better understand the disease and defect reporting challenge and to identify, test and validate Future Feedback disease and defect benchmark reports.
2. Develop data quality and completeness checking and validation algorithms for internal use at Future Feedback.
3. Develop disease and defect regional baseline risk table.
Key findings
Key comparator groups were identified for disease and defect reporting. Endemic disease is not constant between and within regions, between age classes of livestock, between production systems, and (potentially) between processors. MySQL algorithms were developed, operating on the LDL database for identifying pertinent comparison groups for each animal within a consignment using these group identifiers. This allowed the level of disease within a consignment to be assessed along the spectrum of below-average-above prevalence of disease and it is this relative performance information that provides the most incentive to affected producers. Those identified with above-average levels of disease have incentives to better control disease in their herd whereas those with below-average levels of disease should be encouraged to not invest further in this disease’s control.
Benefits to industry
Optimal endemic disease control will maximise the profit for both producers and processors. Eradication of endemic disease is not possible (or economical) so incentivising those producers with excess disease towards better control whilst reassuring those producers with below-average disease levels will optimise the spend on disease controls by industry and increase the value of animals processed. The key now is to demonstrate this benefit to the processor and producer.
MLA action
The reporting of findings in an incomplete-uptake system must also be examined and systems developed such that participating processors are not unfairly impacted by reporting disease and defect finding to their processors. This will require consideration of LDL data governance, hierarchical myFeedback reporting and monitoring and oversight of disease and defect prevalence within and between processors and regions to ensure the information is trusted, reliable and used appropriately.
Future research
The benefit from relative disease performance information for producers is obvious. However, the benefit to the processor is less apparent; the processor bears the cost of recording and reporting their meat inspection findings to LDL. Whilst less apparent, these benefits are present (through improved lines of cattle, greater offal harvest, less trim and processing and more effective processor purchasing) but need to be specifically developed and presented to the processing sector for the system to generate momentum and become and industry standard practice.
More information
| Project manager: | Demelsa Lollback |
| Contact email: | reports@mla.com.au |
