Dr. Svetla N. Maneva Profile

Dr. Svetla N. Maneva

Associate Researcher at Plant Protection Institute

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Proceedings Article | 23 October 2012 Paper

Hyperspectral remote sensing applications for monitoring and stress detection in cultural plants: viral infections in tobacco plants

Dora Krezhova, Nikolai Petrov, Svetla Maneva

Proceedings Volume 8531, 85311H (2012) https://doi.org/10.1117/12.974722

KEYWORDS: Reflectivity, Remote sensing, Viruses, Statistical analysis, Near infrared, Vegetation, Agriculture, Spectroscopy, Visible radiation, Soil science

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The objectives of this study were to reveal the presence of viral infections in two varieties of tobacco plants (Nicotiana tabacum L.) as well as to discriminate the levels of the disease using hyperspectral leaf reflectance. Data sets were collected from two tobacco cultivars, Xanthi and Rustica, known as most widespread in Bulgaria. Experimental plants were grown in a greenhouse under controlled conditions. At growth stage 4-6 expanded leaf plants of cultivar Xanthi were inoculated with Potato virus Y (PVY) while the Rustica plants were inoculated with Tomato spotted wilt virus (TSWV). These two viruses are worldwide distributed and cause significant yield losses in many economically important crops. In the course of time after inoculation the concentration of the viruses in plant leaves was assessed by erological analysis via DAS-ELISA and RT-PCR techniques. Hyperspectral reflectance data were collected by a portable fibreoptics spectrometer in the visible and near-infrared spectral ranges (450-850 nm). As control plants healthy untreated tobacco plants were used. The significance of the differences between reflectance spectra of control and infected leaves was analyzed by means of Student’s t-criterion at p<0.05. The analyses were performed at ten wavebands selected to cover the green (520-580 nm), red (640-680 nm), red edge (690-720 nm) and near infrared (720-780 nm) spectral ranges. Changes in SRC were found for both viral treatments and comparative analysis showed that the influence of PVY was stronger. The discrimination of disease intensity was achieved by derivative analysis of the red edge position.

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