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

机译:使用无人飞行器获取的高分辨率多光谱和热像仪检测罂粟的霜霉病

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摘要

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 (R-550/R-670) 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 (R-550/R-670). T-min for each grid unit was calculated to estimate pure-vegetation temperature removing background and soil effects. T-min - Ta and R-550/R-670 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 R-550/R-670 index were related to physiological stress caused by DM infection. In addition, T-min - Ta was found to decrease as the NDVI increased and symptomatic plants reached significantly higher (P 0.05) temperatures for an NDVI a parts per thousand yen0.6. The R-550/R-670 index was positively correlated with the NDVI, showing significantly higher values (P 0.05) in symptomatic plants with an NDVI a parts per thousand yen0.5. 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.
机译:由生物营养性专性卵菌卵轴虫(Peronospora arborescens,Berk。)引起的霜霉病(DM)是全世界最经济限制的罂粟(Papaver somniferum L.)疾病之一。最初的症状表现为小小的褪绿叶病变,随着病变的发展,其可能演变成卷曲和增厚的组织,并逐渐变形和坏死。本研究探索了高分辨率热成像和多光谱成像作为DM感染指标的用途。在两个被乔木假单胞菌人工感染的罂粟田地中进行了工作。 2009年春季,使用无人飞行器(UAV)在三个日期以200毫米的分辨率获取了机载热图像和多光谱图像。使用积分球测量了无症状和有症状鸦片罂粟叶片的叶片反射率和透射光谱。使用耦合的PROSPECT + SAILH辐射转移模型进行了模拟工作,以评估在DM流行的罂粟田中发现的变异性对归一化植被指数(NDVI)和绿色/红色指数(R-550 / R-670)由多光谱图像计算得出。机载飞行通过使用由空气温度(Tc-Ta)和绿色/红色指数(R-550 / R-670)归一化的图像得出的顶篷温度(Tc),能够进行DM检测。计算每个网格单位的T-min,以估算去除背景和土壤影响的纯植被温度。将T-min-Ta和R-550 / R-670评估为聚集NDVI簇的函数,以比较通过相似生长水平归一化的无症状和有症状植物。结果表明,Tc-Ta和R-550 / R-670指数与DM感染引起的生理应激有关。此外,发现当NDVI增加时,T-min-Ta随NDVI的增加而降低,而有症状的植物达到明显更高的温度(P <0.05)(千分之0.6)。 R-550 / R-670指数与NDVI呈正相关,在具有NDVI a千分之0.5的有症状植物中显示出明显更高的值(P <0.05)。这些结果证明了使用通过无人机获得的高分辨率热图像和多光谱图像在罂粟植物中检测侧柏假单胞菌感染的可行性。

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