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Identification of Potato Genotypes Using Digital Image Analysis
Máté CSÁK
; University of Pannonia, Georgikon Fakulty,Department of Economic Methodology, Tel: +36 83/545- 275
Géza HEGEDŰS
Zsolt POLGÁR
Sažetak
Based on the fractal analysis of digital images, a new classifying system has been
proposed at the Potato Research Centre of Keszthely. It is a qualifying system
generating objective values to distinguish potato varieties or detect quality differences
within the genotype in a relatively simple way.
The goal of the research project was to investigate whether Spectral Fractal
Dimension (SFD) value of digital images is applicable to describe various quality
characters of potato tubers and whether SFD values could be used for the
identification of certain varieties – if so, which conditions were the most important to
enable this process.
Considering the above aims, we developed an evaluation computer program which
determines the SFD values of the 4 conditions of potato tubers: skin colour; raw
flesh-colour; boiled flesh-colour; greying of flesh-colour after 24 hours in RGB
spectrum and in all of its sub-spectrums (R, G, B). In total 2080 digital images of 13
varieties from 4 examining periods were analysed.
Based on our results we can conclude that SFD analysis can be used in potato
breeding only when digital images were made under well-determined, standardized
conditions.
Detailed statistical analysis (hypothesis tests, principal component analysis and
non-hierarchic cluster analysis) showed that SFD was not suitable for qualifying tuber
characters within a genotype. When images were examined for different years and
the same genotype, it became evident, that there are significant deviations between
years and within same genotypes. We could conclude that the identification of
genotypes should be related not to one particular SFD value, but to the control of the
given year with the known value.
When analyzing the differences between genotypes on yearly basis, irrespective of
characteristics or the studied spectrum, we could not significantly separate
genotypes, although there were some that could be separated, even though
genotypes and their characteristics changed every year. It cannot be stated either
that by combination of the values of different characteristics and spectrums,
separation is not possible. We used non-hierarchic cluster analysis to solve this
problem. As a result of the method, the separation of genotypes was successful
every year, so by summarising the joint RGB SFD value of 4 characters with the
values of additional spectrum the separation will be complete.
The system could be utilized for research purposes and further research is needed to
achieve practical applicability.
Ključne riječi
digital image analysis; fractal; spectral fractal dimension; potato breeding; genotype identification; cluster analysis; non-hierarchic cluster analysis
Hrčak ID:
70991
URI
Datum izdavanja:
13.7.2011.
Posjeta: 1.426 *