Detection of downy mildew of opium poppy using high-resolution multi-spectral and thermal imagery acquired with an unmanned aerial vehicle

Downy mildew (DM) caused by the biotrophic obligate oomycete Peronospora arborescens (Berk.) is one of the most economically limiting diseases of opium poppy (Papaver somniferum L.) worldwide. The first symptoms appear as small chlorotic leaf lesions, which can evolve to curled and thickened tissues that become deformed and necrotic as the disease develops. The present study explored the use of high-resolution thermal and multi-spectral imagery as an indicator of DM infection. Work was conducted in two opium poppy field plots artificially infected by P. arborescens. Airborne thermal and multi-spectral imagery were acquired at 200 mm resolution on three dates in spring of 2009 using an unmanned aerial vehicle (UAV). Leaf reflectance and transmittance spectra of DM asymptomatic and symptomatic opium poppy leaves were measured using an integrating sphere. Simulation work was conducted with the coupled PROSPECT + SAILH radiative transfer model to assess the effects of the variability found in an opium poppy plot developing a DM epidemic on the normalized difference vegetation index (NDVI) and the green/red index (R550/R670) calculated from the multi-spectral imagery. The airborne flights enabled DM detection by using image-derived canopy temperature (Tc) normalized by air temperature (Tc − Ta) and the green/red index (R550/R670). Tmin for each grid unit was calculated to estimate pure-vegetation temperature removing background and soil effects. Tmin − Ta and R550/R670 were assessed as a function of aggregated NDVI clusters to compare asymptomatic and symptomatic plants normalized by similar growth levels. Results demonstrated that Tc − Ta and the R550/R670 index were related to physiological stress caused by DM infection. In addition, Tmin − Ta was found to decrease as the NDVI increased and symptomatic plants reached significantly higher (P < 0.05) temperatures for an NDVI ≥0.6. The R550/R670 index was positively correlated with the NDVI, showing significantly higher values (P < 0.05) in symptomatic plants with an NDVI ≥0.5. These results demonstrate the feasibility of detecting P. arborescens infection in opium poppy plants using high-resolution thermal and multi-spectral imagery acquired with an UAV.

[1]  John R. Miller,et al.  Assessing vineyard condition with hyperspectral indices: Leaf and canopy reflectance simulation in a row-structured discontinuous canopy , 2005 .

[2]  J. A. Schell,et al.  Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation. [Great Plains Corridor] , 1973 .

[3]  Kazunobu Ishii,et al.  Remote-sensing Technology for Vegetation Monitoring using an Unmanned Helicopter , 2005 .

[4]  H. Ramon,et al.  Early Disease Detection in Wheat Fields using Spectral Reflectance , 2003 .

[5]  Pablo J. Zarco-Tejada,et al.  Mapping canopy conductance and CWSI in olive orchards using high resolution thermal remote sensing imagery , 2009 .

[6]  James A. Brass,et al.  Imaging from an unmanned aerial vehicle: agricultural surveillance and decision support , 2004 .

[7]  Richard W. Michelmore,et al.  The Downy Mildews , 1988 .

[8]  F. Baret,et al.  PROSPECT: A model of leaf optical properties spectra , 1990 .

[9]  C. Barton,et al.  Advances in remote sensing of plant stress , 2011, Plant and Soil.

[10]  B. Landa,et al.  A nested-polymerase chain reaction protocol for detection and population biology studies of Peronospora arborescens, the downy mildew pathogen of opium poppy, using herbarium specimens and asymptomatic, fresh plant tissues. , 2009, Phytopathology.

[11]  C. Gueymard Parameterized transmittance model for direct beam and circumsolar spectral irradiance , 2001 .

[12]  B. Landa,et al.  Phylogenetic Analysis of Downy Mildew Pathogens of Opium Poppy and PCR-Based In Planta and Seed Detection of Peronospora arborescens. , 2007, Phytopathology.

[13]  B. Landa,et al.  Real-Time PCR Quantification of Peronospora arborescens, the Opium Poppy Downy Mildew Pathogen, in Seed Stocks and Symptomless Infected Plants. , 2011, Plant disease.

[14]  J. V. Stafford,et al.  Digital infrared thermography for the assessment of leaf pathogens. , 2005 .

[15]  Gunter Menz,et al.  Multi-temporal wheat disease detection by multi-spectral remote sensing , 2007, Precision Agriculture.

[16]  Pablo J. Zarco-Tejada,et al.  Detecting water stress effects on fruit quality in orchards with time-series PRI airborne imagery , 2010 .

[17]  H. Nilsson Remote sensing and image analysis in plant pathology. , 1995, Annual review of phytopathology.

[18]  Hans R. Schultz,et al.  Early pathogen detection under different water status and the assessment of spray application in vineyards through the use of thermal imagery , 2008, Precision Agriculture.

[19]  Jose A. Jiménez-Berni,et al.  A new era in remote sensing of crops with unmanned robots , 2008 .

[20]  B. Landa,et al.  First Report of Downy Mildew of Opium Poppy Caused by Peronospora arborescens in Spain. , 2005, Plant disease.

[21]  J. V. Stafford,et al.  Precision Agriculture '05 , 2005 .

[22]  Pablo J. Zarco-Tejada,et al.  Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[23]  U. Steiner,et al.  Spectral signatures of sugar beet leaves for the detection and differentiation of diseases , 2010, Precision Agriculture.

[24]  Application of Distance Based Vegetation index For Agricultural Crops Discrimination , 2004 .

[25]  Reza Ehsani,et al.  Review: A review of advanced techniques for detecting plant diseases , 2010 .

[26]  Hans R. Schultz,et al.  Exploring the sensitivity of thermal imaging for Plasmopara viticola pathogen detection in grapevines under different water status. , 2008, Functional plant biology : FPB.

[27]  P. Zarco-Tejada,et al.  Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera , 2012 .

[28]  U. Steiner,et al.  Journal of Experimental Botany Advance Access published May 19, 2006 Journal of Experimental Botany, Page 1 of 12 , 2022 .

[29]  W. Verhoef Light scattering by leaf layers with application to canopy reflectance modeling: The Scattering by Arbitrarily Inclined Leaves (SAIL) model , 1984 .

[30]  B. Landa,et al.  Role of oospores as primary inoculum for epidemics of downy mildew caused by Peronospora arborescens in opium poppy crops in Spain , 2009 .

[31]  C. Rush,et al.  Comparison of Visual and Multispectral Radiometric Disease Evaluations of Cercospora Leaf Spot of Sugar Beet. , 2005, Plant disease.

[32]  D. Moshou,et al.  The potential of optical canopy measurement for targeted control of field crop diseases. , 2003, Annual review of phytopathology.

[33]  L. Plümer,et al.  Original paper: Early detection and classification of plant diseases with Support Vector Machines based on hyperspectral reflectance , 2010 .

[34]  L. Kapoor Opium Poppy , 1995 .

[35]  Chenghai Yang,et al.  Comparison of Airborne Multispectral and Hyperspectral Imagery for Estimating Grain Sorghum Yield , 2009 .

[36]  Ulrike Steiner,et al.  Effect of downy mildew development on transpiration of cucumber leaves visualized by digital infrared thermography. , 2005, Phytopathology.