基于多角度反射与叶绿素荧光协同的小麦白粉病监测方法研究

白粉病为黄淮麦区主要病害，对其发生过程监测和早期预报是预防病害、减轻危害的关键。田间小麦具有明显各向异性，多角度遥感具有探测冠层深度的优势；叶绿素荧光能反映植株生理“内在性”，是植物光合机构功能受损的早期探针。本研究采用多角度高光谱反射和叶绿素荧光遥感技术手段，将光谱精量分析、植物病理学与小麦生理生态相结合，研究不同小麦品种、白粉病等级对植株形态生理参数、冠层多角度反射与叶绿素荧光发射的影响，解析反射率与荧光光谱—形态生理特征—病害发生及危害之间关联机制，基于反射光谱与荧光参数间信息解译及融合提取适宜表征小麦病害形态生理、发病阶段及等级的专属性遥感参数，明确白粉病发生的遥感识别及早期诊断指标，构建基于多角度反射与叶绿素荧光协同的病害等级及相关参数的定量监测模型。研究结果不仅可丰富作物病害无损监测理论，而且拓宽病害遥感识别和早期诊断方法，提高作物病害精确防治水平和效率，实现农药减施增效环保。

Wheat powdery mildew is one of the main diseases that endanger the safe production of wheat, and forecast and monitoring is the most cost-effective measures to control this disease. Earth observation systems provide timely and high-quality information about our changing planet. Most earth surfaces generate spectral reflectance signatures that are anisotropic with respect to illumination and view angles. Multi-angle remote sensing has the advantages of detecting canopy depth, and chlorophyll fluorescence reflects the physiological "intrinsic" characteristics of plants and is an early probe for the impairment of photosynthetic organ function in plants. The study investigated temporal and spatial dynamic characteristics of plant morphology, physiological index, canopy multi-angle reflectance spectra and chlorophyll fluorescence with adopting a new fusion technique of spectral analysis, physiology of crop cultivation and plant pathology with different winter wheat cultivars under different pressure of vaccination. The project clarify effects of powdery mildew on multi-angle reflectance spectral, chlorophyll fluorescence and physiological index of winter wheat, and explain covariant relationship of multi-angle reflectance, chlorophyll fluorescence, disease severity, crop morphology and physiology. The sensitive spectrum parameters are extracted to identify plant shape, physiological characters, infection progress and disease severity degree on the basis of mechanical interpretation between reflectance spectrum and fluorescence parameters. The indirect approach of early distinguishing wheat powdery mildew were developed, and quantitative model of disease severity and related parameters based on multi-angle reflection and chlorophyll fluorescence, which provided the theory basis and the key technology for monitoring and precisely managing and evaluating wheat growth characteristics under different disease stress. The results of this project not only can enrich crop diseases nondestructive monitoring theory, and broaden the disease recognition and early diagnosis method, which improve the level and efficiency of crop disease precise control to promote pesticide reduction, yield loss inhibition and environmental protection.