Multispectral band selection for imaging sensor design for vineyard disease detection: case of Flavescence Dorée

Abstract : Disease detection and control is thus one of the main objectives of vineyard research in France. Monitoring diseases manually is fastidious and time consuming, so current research aims to develop an automatic detection of vineyard diseases. This project explored the use of a high-resolution multi-spectral camera embedded on a UAV (Unmanned Aerial Vehicle) to identify the infected zones in a field. In-field spectrometry studies were performed to identify the best spectral bands for the sensor design. The best models were found to be the function of the grapevine variety considered and the 520-600-650-690-730-750-800 nm bands were found to be the most efficient for all types of grapevines, with an overall classification accuracy of more than 94%.
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Submitted on : Friday, April 20, 2018 - 3:48:58 PM
Last modification on : Monday, September 17, 2018 - 2:54:01 PM

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Hania Al Saddik, Jean-Claude Simon, Olivier Brousse, Frédéric Cointault. Multispectral band selection for imaging sensor design for vineyard disease detection: case of Flavescence Dorée. Advances in Animal Biosciences, Cambridge University Press, 2017, 8 (02), pp. 150 - 155. ⟨10.1017/S2040470017000802⟩. ⟨hal-01772773⟩

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