Prelecionista: Márcia Indyanara Lopes Santiago 

Data: 14/10/2022, às 14h, via Zoom*

Resumo: In eucalyptus, ceratocystis wilt caused by the fungus Ceratocystis fimbriata is a lethal disease that can cause large economic losses. The pathogen dissemination is facilitated by the cultivation of asymptomatic infected plant material, increasing the risks of losses due to the disease. Therefore, early detection of ceratocystis wilt is important to prevent the pathogen spread, especially to areas where the disease is not present yet. Although molecular and serological methods can be applied with this objective, they are destructible, sampling dependent and costly. In this sense, disease detection in asymptomatic periods via reflectance spectroscopy is being widely explored in agricultural studies and applications. Considering this context, the objective of this study was to differentiate inoculated and non-inoculated plants through leaf reflectance spectra and derived vegetation indices, more specifically related with the content of photosynthetic pigments, nitrogen, cellulose, lignin, water or with vegetation stress in general. For that, leaf samples were collected from the apical, middle and basal canopy sections to measure the spectra with an ASD FieldSpec4® spectroradiometer. Evaluations were performed at 0, 12, 24, 48 and 72 hours after inoculation (hai), as well as 30 and 40 days after inoculation (dai). At 12 hai it was possible to observe spectral differences between non-inoculated (NI) and inoculated (I) individuals. In the first hours of evaluation, leaves of the middle and basal sections were more suitable for distinguishing inoculated and non-inoculated individuals, while plants with visual symptoms were better characterized using leaves from the apical section. Wavelengths in the visible (VIS; 400 – 700 nm) and near-infrared (NIR; 700 – 1300 nm) spectral regions were more sensitive to physiological changes at the beginning of pathogen infection while short-wave infrared (SWIR; 1300 – 2500 nm) performed better distinguishing individuals at all times evaluated, mainly in the spectral regions involved in general energy scattering and in specific absorption features caused by proteins. The indices related to the content of nitrogen, chlorophylls, carotenoids, biomass and water content showed significant values (p-value ≤ 0.05) for the distinction between treatments in the different evaluation periods. Through the results obtained in this study, it was confirmed that leaf reflectance has potential to discriminate inoculated and non-inoculated individuals as well as that this methodology could be applied in monitoring frameworks targeting plant disease detection even in the asymptomatic periods of the disease.

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