Quality assurance guidelines
To ensure that the quality of the information provided to industry is of the highest order, set procedures and minimum standards apply to the entry of data before it can be accepted for analysis and reporting.
The quality assurance system consists of four key elements:
1. Data collection and supply
A QA Check List is required to be submitted with each dataset to verify that the relevant QA procedures have been met. Scanners, fleece testers, service and data handling providers must be accredited.
Laboratories undertaking faecal egg counts (FEC) must use NEMESIS protocols. Breeders are required to have QA procedures training, and any breeder reporting data directly to the database needs to meet QA standards.
2. Data integrity checking
The integrity of each dataset submitted is subject to checking before it enters the master database.
Any concerns identified will be raised with the user who submitted the data. Data cannot proceed into the master database unless all relevant QA procedures have been met.
3. Data processing
Evaluation of genetic performance utilizes sophisticated software – OVIS – developed at the University of New England by the Animal Genetics and Breeding Unit. OVIS has recently been further developed to accommodate the wide diversity of genetic types, and enhancement of analytical procedures will be ongoing.
Groups of progeny that can be compared on an across-flock basis will have trait performance reported
as an ASBV with a percentage accuracy figure. Groups of progeny that cannot be compared to other across-flock groups will have trait performance described as an FBV and will be distinguishable as they will be reported without a trait accuracy.