Community Research and Development Information Service - CORDIS

Deliverable: multivariate classification of the harvest location of cod

Three hundred seventy-two variables were extracted from each of the 1100 individual cod collected for optimising the techniques from wild populations and from two cod farms. An additional 220 cod were collected in a double-blind manner to independently test the accuracy of the techniques. Three changes were made in optimising the CODTRACE techniques. Allozymes could not be uniformly extracted across individuals producing too space of a data set; ultimately this technique was not useful for traceability of cod in this study. The data from otolith core and edge microchemistry was combined given the broad similarity of the data produced; this proved more effective towards traceability than using each of the data sets in isolation.

As the specific DNA locus (Syp I) proved only useful for isolating the Icelandic populations from others, and this information was largely redundant to the microsatellite date, it was not necessary to use this locus data. The limits of optimisation (highest percent correct classification) for each technique were determined, and across seasons and locations the highest correct placement was as follows: body morphometry (84.7%), parasite assemblage (80.4%), bacterial assemblage (78.3%), microsatellite loci (70.1%), otolith morphometry (68.0%), and otolith microchemistry (66.9%). This successfully accomplished the objective of optimising each technique; the absolute classification limit for each technique was established, and no individual technique was able to confer 100% classification (perfect traceability) upon the collected cod.

Another objective was to optimise the method for combining analytical and statistical results into a more powerful classification tool. For the combined analyses, the size of large resultant data set needed to be reduced to allow for statistical confidence in the results. The data generated by each technique were reduced to probabilities representing the likelihood of each cod belonging to each source population, in two steps. First, each cod was classified as being of wild or farmed origin using logistic regression of individuals known to belong to wild or farmed populations. Second, if a fish was classified as being of wild origin, it was assigned to one of the five wild populations using multinomial logistic regression. This step was conducted separated for cod classified as being of farmed origin, using logistic regression for assignment. Using the same multivariate model for all seasons and years sampled, 100% of cod were correctly placed to their population of origin.

Reported by

UNIVERSITY COLLEGE DUBLIN
DEPARTMENT OF ZOOLOGY
Dublin 4 BELFIELD
Ireland
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