Computer image analysis: an additional tool for the identification of processed poultry and mammal protein containing bones

Abstract

The aims of this study were (1) to evaluate the potential of image analysis measurements, in combination with the official analytical methods for the detection of constituents of animal origin in feedstuffs, to distinguish between poultry versus mammals; and (2) to identify possible markers that can be used in routine analysis. For this purpose, 14 mammal and seven poultry samples and a total of 1081 bone fragment lacunae were analysed by combining the microscopic methods with computer image analysis. The distribution of 30 different measured size and shape bone lacunae variables were studied both within and between the two zoological classes. In all cases a considerable overlap between classes meant that classification of individual lacunae was problematic, though a clear separation in the means did allow successful classification of samples on the basis of averages. The variables most useful for classification were those related to size, lacuna area for example. The approach shows considerable promise but will need further study using a larger number of samples with a wider range.

Keywords:

• meat and bone meals
• bone lacunae
• microscopic method
• image analysis
• linear discriminant analysis

Acknowledgements

Part of this work represents collaboration in the framework of the project “SAFEED-PAP – Detection of Presence of Species-Specific Processed Animal Proteins in Animal Feed” (FOOD-CT-2006-036221), supported by the European Commission under the Sixth Framework Programme. This paper was develop within the framework of COST-STSM-ECOST-STSM-FA0802-300111-004920 supported by Feed for Health, COST Action FA0802 (see http://www.feedforhealth.org).