If birds are being raised on or in close proximity to the hot spot, tissues from these animals should be collected for chemical analysis.
Pre-sample Preparations
- Locate birds from the site being studied
- Identify a butcher to help with sample collection
- Prepare safety gear
- Fill out field data sheet
- Prepare sampling jars
Clean Bird Tissue Sampling Equipment
- Put on gloves, rinse gloves with clean water
- First scrub butchering equipment with sparkleen
- Rinse with clean water (3×)
- Rinse with acetone
- Rinse with hexane
Bird Tissue Sample Processing Steps
Bird samples are collected in a similar manner to fish. As with fish it is important to ensure that sampled birds are from the site being studied. Also specify to the person doing the butchering that the birds are to be left intact (i.e., feathers and feet are to be left on birds); however, birds should be bled.
Field staff should work with the person responsible for butchering to ensure birds are not contaminated due to poor sample handling. If possible clean all butchering tools with sparkleen soap, acetone and hexane prior to butchering. It will be important that all staff wear safety glasses and a facial mask as a precaution against bird flu. If possible a blood sample should be collected while the bird is being bled.
Before dissecting the bird, ensure that skin on the left thigh is intact. First remove feathers from much of the thigh. Then cut a rectangle approximately 50 mm by 30mm. Remove skin using forceps, rinse with distilled water, and place into a labeled 125 or 250 ml jar.
The skin sample collected should be approximately 50g. If the bird is lean, and there is little fat associated with the skin, additional skin may have to be collected. Once the skin sample is collected, remove approximately 50 g of thigh muscle tissue. Livers should be removed with the assistance of the person performing the butchering.
Next Steps
back to a list of specific sampling methodology protocols
information on soil, sediment and biological sample handling
information on the number of samples needed
information on data quality analysis and management