Visual clone identification of Penicillium commune isolates |
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Authors: | Hansen Michael Edberg Lund Flemming Carstensen Jens Michael |
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Institution: | Informatics and Mathematical Modelling, Richard Petersens Plads, Building 321, Technical University of Denmark, DK-2800 Kgs Lyngby, Denmark. meh@imm.dtu.dk |
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Abstract: | A method for visual clone identification of Penicillium commune isolates was developed. The method is based on images of fungal colonies acquired after growth on a standard medium and involves a high degree of objectivity, which in future studies will make it possible for non-experts to perform a qualified identification of different species as well as clones within a species. A total of 77 P. commune isolates from a cheese dairy were 3-point inoculated on Yeast Extract Sucrose (YES) agar and incubated for 7 days at 25 degrees C. After incubation, the isolates were classified into groups containing the same genotype determined by DNA fingerprinting (AFLP). Each genotype also has a specific phenotype such as different colony colours. By careful image acquisition, colours were measured in a reproducible way. Prior to image analysis, each image was corrected with respect to colour, geometry and self-illumination, thereby gaining a set of directly comparable images. A method for automatic extraction of a given number of concentric regions was used. Using the positions of the regions, a number of relevant features--capturing colour and colour-texture from the surface of the fungal colonies--was extracted for further analysis. We introduced the Jeffreys-Matusitas (JM) distance between the feature distributions to express the similarity between regions in two colonies, and to evaluate the overall (weighted) similarity. The nearest neighbour (NN) classification rule was used. On a dataset from 137 isolates, we obtained a "leave-one-out" cross-validation identification rate of approximately 93-98% compared with the result of DNA fingerprinting. |
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