Guo Jie-Bin, Huang Chong, Wang Hai-Guang, Sun Zhen-Yu, Ma Zhan-Hong
State Key Lab of Plant Pathology, Ministry of Agriculture, Department of Plant Pathology, China Agricultural University, Beijing 100094, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2009 Dec;29(12):3353-7.
It is becoming more and more important to use mixed wheat varieties to control wheat stripe rust. Different wheat varieties were planted in field and stripe rust was caused by artificial inoculation. Disease index (DI) was assessed and the canopy reflection data of wheat canopy were obtained by ASD FieldSpec HandHeld FR(325-1 075 nm) made by ASD Company. The correlation analysis between DI and spectral data (reflectance and the first derivative) was conducted, and the estimation models between DI and reflection data (reflectance at 690 and 850 nm, SDr, NDVI and RVI) were built using linear regression method. The results showed that different combinations of wheat varieties had the similar variation at different disease index. DI has positive correlation with reflectance of wheat canopy in visible region, and has significant negative correlation in the near infrared region. DI has stable negative correlation with the first derivative in the region of 700-760 nm and with big fluctuation in other regions. The correlation was compared between DI and hyperspectral derivative index, and SDr has the best correlation with DI. DI estimation models were built based on the canopy reflectance at 690 and 850 nm, SDr, NDVI and RVI. The determinant coefficient of the models is between 0.588 and 0.855, 0.669 and 0.911, 0.534 and 0.773, and 0.587 and 0.751, respectively, and all the models were fit well. The results indicated that DI of wheat stripe rust could be inverted using hyperspectral remote sensing technique and that the inversion effect was hardly influenced by the different combinations of wheat varieties.
使用混种小麦品种来控制小麦条锈病变得越来越重要。在田间种植不同的小麦品种,并通过人工接种引发条锈病。评估病害指数(DI),并使用美国ASD公司生产的ASD FieldSpec HandHeld FR(325 - 1075纳米)获取小麦冠层的冠层反射数据。进行了DI与光谱数据(反射率和一阶导数)之间的相关性分析,并使用线性回归方法建立了DI与反射数据(690和850纳米处的反射率、SDr、归一化植被指数(NDVI)和比值植被指数(RVI))之间的估算模型。结果表明,不同小麦品种组合在不同病害指数下具有相似的变化。DI与小麦冠层在可见光区域的反射率呈正相关,在近红外区域呈显著负相关。DI在700 - 760纳米区域与一阶导数呈稳定负相关,在其他区域波动较大。比较了DI与高光谱导数指数之间的相关性,SDr与DI的相关性最佳。基于690和850纳米处的冠层反射率、SDr、NDVI和RVI建立了DI估算模型。这些模型的决定系数分别在0.588至0.855、0.669至0.911、0.534至0.773以及0.587至0.751之间,且所有模型拟合良好。结果表明,利用高光谱遥感技术可以反演小麦条锈病的DI,且反演效果几乎不受小麦品种不同组合的影响。