首页> 外文期刊>Sensor Letters: A Journal Dedicated to all Aspects of Sensors in Science, Engineering, and Medicine >New Reflectance Spectral Vegetation Indices for Estimating Rice Nitrogen Nutrition III: Development of a New Vegetation Index Based on Canopy Red-Edge Reflectance Spectra to Monitor Rice Canopy Leaf Nitrogen Concentration
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New Reflectance Spectral Vegetation Indices for Estimating Rice Nitrogen Nutrition III: Development of a New Vegetation Index Based on Canopy Red-Edge Reflectance Spectra to Monitor Rice Canopy Leaf Nitrogen Concentration

机译:估计水稻氮营养的新反射光谱植被指数III:基于冠层红边反射光谱的新型植被指数的开发,用于监测水稻冠层叶片氮含量

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Three field experiments were conducted to study the response of a new vegetation index to nitrogen (N) concentration in rice. The N concentration and hyper spectral canopy reflectance of rice leaves were tested at different growth stages. This was done to select a reflectance spectra wavelength position and to develop better algorithms for estimating N content. We developed the new red-edge reflectance spectra index (RERI), which uses data in three redear-infrared wavebands centered at 681.499, 729.232 and 765.399 nm. Compared to other common spectra vegetation indices (e.g., normalized difference and ratio vegetation indices), our RERI correlated better with chlorophyll and N concentrations, and decreased with decreasing N fertilizer levels. Regression models were built to estimate the N content using RERI. The correlation between measured and predicted N concentrations suggested that RERI sensitively measures the canopy leaf N content.
机译:进行了三个田间试验,以研究新的植被指数对水稻中氮(N)浓度的响应。在不同的生育阶段测试了水稻叶片的氮含量和高光谱冠层反射率。这样做是为了选择反射光谱的波长位置,并开发出更好的算法来估算N含量。我们开发了新的红边反射光谱指数(RERI),该数据使用三个以681.499、729.232和765.399 nm为中心的红/近红外波段的数据。与其他常见光谱植被指数(例如归一化差异和比率植被指数)相比,我们的RERI与叶绿素和N浓度的相关性更好,而随着N肥料水平的降低而降低。建立了回归模型以使用RERI估算N含量。测得的氮含量与预测的氮含量之间的相关性表明,RERI可以灵敏地测量冠层叶片的氮含量。

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