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作 者:杨庆锋[1] 王纪华 莫良玉[1] 黄文江[2] 刘良云[2]
机构地区:[1]广西大学农学院,广西南宁530005 [2]国家农业信息技术研究中心,北京100097
出 处:《安徽农业科学》2008年第24期10436-10438,共3页Journal of Anhui Agricultural Sciences
基 金:国家863课题(2007AA10Z201;2007AA10Z202);精准农业科委重大主题(D07060500860701)
摘 要:[目的]分析了小麦光谱特征与干物质积累量的相关关系。[方法]通过对冬小麦不同品种的干物质积累量、叶面积等参数和冬小麦冠层光谱反射率、光谱一阶微分和光谱比值植被指数(RVI)的相关分析,确立了冬小麦干物质积累量的敏感波段,并建立了预测模型。[结果]开花期350~700nm和1420~1520nm冠层光谱反射率和灌浆期350~1750nm冠层光谱反射率分别与干物质积累量显著相关;比值植被指数Rw(560,1220)与干物质积累量的相关性较好;确立的冬小麦干物质积累量预测模型为:干物质积累量=-186.94×RVI(560,1220)-2242.2(R^2=0.7138),说明通过遥感手段监测冬小麦的群体质量是可行的。[结论]该研究为高光谱遥感技术在监测小麦的群体质量的应用提供参考依据。[Objective] The study aimed to analyze the correlation between wheat spectral characteristic and dry matter accumulation. [Method] The sensitive band of dry matter accumulation in the winter wheat and its prediction models were established through the correlation analysis on the parameters such as dry matter accumulation and leaf area in the different varieties of winter wheat and the spectral reflectance of wheat eanopy,the frrst derivative spectra and the ratio of vegetation index (RVI). [ Result] The spectral reflectance of wheat canopy of 350 - 700 run and 1 420 - 1 520 nm in the flowering period and that of 350 - 1 750 um in filling stage were significantly related to the dry matter accumulatian in their corresponding stages. The ratio of vegetation index RVI (560,1220) had better correlation to the dry matter accumulatian.The prediction model for dry matter accumulation of winter wheat was established as: dry matter accumulation = - 186.94 × RV/(560,1220) - 2 242.2( R^2 =0.713 8) ,showing that it could be feasible to monitor the population quality of winter wheat by means of remote sensing. [Conclusion] This study provides the reference basis for application of high spectra remote sensing technique in monitoring the population quality of winter wheat.
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