Airborne multi-spectral remote sensing of Russian wheat aphid1 injury to wheat

被引:24
作者
Elliott, Norman [1 ]
Mirik, Mustafa [2 ]
Yang, Zhiming [3 ]
Dvorak, Tom
Rao, Mahesh [3 ]
Micheis, Jerry [2 ]
Walker, Thia [4 ]
Catana, Vasile [5 ]
Phoofolo, Mpho [5 ]
Giles, Kris [5 ]
Royer, Tom [5 ]
机构
[1] USDA, ARS, Plant Sci Res Lab, Stillwater, OK 74075 USA
[2] Texas Agr Expt Stn, Bushland, TX 79012 USA
[3] Oklahoma State Univ, Dept Geog, Stillwater, OK 74078 USA
[4] Colorado State Univ, Prowers Cty Cooperat Extens Off, Dept Bioagr Sci & Pest Management, Lamar, CO 81052 USA
[5] Oklahoma State Univ, Dept Entomol & Plant Pathol, Stillwater, OK 74078 USA
关键词
D O I
10.3958/0147-1724-32.4.213
中图分类号
Q96 [昆虫学];
学科分类号
摘要
The Russian wheat aphid (RWA), Diuraphis noxia (Mordvilko), is a severe pest of wheat in the High Plains region of the United States. Remote Sensing may be an effective way to detect RWA infestations in fields for pest management decision-making purposes. We evaluated an airborne multi-spectral remote sensing system for its ability to differentiate varying levels of injury caused by RWA infestation in winter wheat fields. Two fields located in southeastern Colorado were studied in spring 2004 and two fields located in far western Oklahoma were studied in spring 2005. The proportion of wheat stems damaged by RWA in each field was measured in 20 to 24 3x3-m plots with varying levels of RWA infestation. Prior to sampling plots, multispectral imagery was obtained using an SSTCRIS (R) multi-spectral imaging system mounted NADIR in a Cessna 172 aircraft. The multi-spectral data were compared with the intensity of RWA damage to wheat plants within the plots. Correlations between vegetation indices calculated from the multi-spectral data with the proportion of RWA damaged wheat tillers per plot were negative for all vegetation indices. REigressions of vegetation indices versus the proportion of RWA damaged wheat tillers per plot were usually significant and had negative slopes. However, slopes and intercepts of regressions differed significantly among fields. Any one or a combination of differences in time of day, atmospheric conditions, edaphic factors (e.g. soil type and soil moisture), wheat variety, and possibly other factors could have caused the differences observed in regressions.
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页码:213 / 219
页数:7
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