Discrimination of grapevine varieties cultivated in the Czech Republic by Artificial Neural Networks

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41340%2F13%3A60393" target="_blank" >RIV/60460709:41340/13:60393 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Discrimination of grapevine varieties cultivated in the Czech Republic by Artificial Neural Networks
Original language description
An artificial neural network approach, based on fractal leaf parameters, and classical ampelography were used to identify nine grapevine varieties cultivated at the St. Claire?s vineyard, Prague Botanic Garden. Fifty healthy, fully-expanded leaves were collected for each variety, scanned using an optical scanner and then elaborated by computer programs. Fourteen phyllometric parameters were qualitatively and quantitatively analysed by the digital image analysis. Comparative frames were constructed for each variety and the relationships among varieties were assessed using artificial neural networks. Results were then compared with the outcome from traditional ampelographic analysis. The Artificial Neural Network technique appears to be a complementary approach to the traditional ampelography methods commonly used for cultivar discrimination, since the equipment necessary for this analysis is very inexpensive and available. Application of the technique led to the distinction of nine sele
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
GE - Plant cultivation
OECD FORD branch
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Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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