High-resolution hyperspectral and thermal imagery acquired from UAV platforms for early detection of Verticillium wilt using fluorescence, temperature and narrow-band índices

Trabajo presentado en el Workshop on UAV-based Remote Sensing Methods for Monitoring Vegetation, celebrado en Colonia (Alemania) el 9 y 10 de septiembre de 2013. Más información en http://www.tr32db.uni-koeln.de/workshops/proceedings.php?wsID=3.

Verticillium wilt (VW) caused by the soil-borne fungus Verticillium dahliae Kleb, is the most limiting disease in all traditional olive-growing regions worldwide. This pathogen colonizes the vascular system of plants, blocking water flow and eventually inducing water stress. The present study explored the use of high-resolution thermal imagery, chlorophyll fluorescence, structural and physiological indices (xanthophyll, chlorophyll a+b, carotenoids and B/G/R indices) calculated from multispectral and hyperspectral imagery acquired from a fixed-wing UAV platform as early indicators of water stress caused by VW infection and severity. The study was conducted in two olive orchards naturally infected with V. dahliae. Time series of airborne thermal, multispectral and hyperspectral imagery were conducted with 2-m and 5-m wingspan electric Unmanned Aerial Vehicles (UAVs) operated by the Spanish Laboratory for Research Methods in Quantitative Remote Sensing (Quantalab, IAS-CSIC, Spain) in three consecutive years and related to VW severity at the time of the flights. Concurrently to the airborne campaigns, field measurements conducted at leaf and tree crown levels showed a significant increase in crown temperature (Tc) minus air temperature (Ta) and a decrease in leaf stomatal conductance (G) across VW severity levels, identifying VW-infected trees at early stages of the disease. Higher Tc-Ta and G values measured in the field were associated with higher VW severity levels. At leaf level, the reduction in G caused by VW infection was associated with a significant increase in the Photochemical Reflectance Index (PRI570) and a decrease in chlorophyll fluorescence. The airborne flights enabled the early detection of VW by using canopy-level image-derived airborne Tc-Ta, Crop Water Stress Index (CWSI) calculated from the thermal imagery, blue / green / red ratios (B/BG/BR indices) and chlorophyll fluorescence, confirming the results obtained in the field. Airborne Tc-Ta showed rising temperatures with a significant increase of ~2K at low VW severity levels, and was significantly correlated with G (R2=0.76, P=0.002) and PRI570 (R2=0.51, P=0.032). Early stages of disease development could be differentiated based on CWSI increase as VW developed, obtaining a strong correlation with G (R2=0.83, P<0.001). Likewise, the canopy-level chlorophyll fluorescence dropped at high VW severity levels, showing a significant increase as disease progressed at early VW severity levels. These results demonstrate the feasibility of early detection of V. dahliae infection and discrimination of VW severity levels using remote sensing. Indicators based on crown temperature, CWSI, and visible ratios B/BG/BR as well as fluorescence were effective in detecting VW at early stages of disease development. On affected plants, the structural indices, PRI, chlorophyll and carotenoid indices, and the R/G ratio were good indicators to assess the damage caused by the disease.

Peer Reviewed