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[玉米叶片的光谱响应及其氮含量预测]

[Spectral response of maize leaves and prediction of their nitrogen content].

作者信息

Chen Zhi-Qiang, Wang Lei, Bai You-Lu, Yang Li-Ping, Lu Yan-Li, Wang He, Wang Zhi-Yong

机构信息

Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences/Key Laboratory of Plant Nutrition and Fertilizer, Ministry of Agriculture, Beijing 100081, China.

出版信息

Guang Pu Xue Yu Guang Pu Fen Xi. 2013 Apr;33(4):1066-70.

Abstract

In the present study, a 2-year maize field experiment with different fertilizer dose was conducted. The spectral response sensitive area of maize leaves in different levels was discussed using hyperspectral technology at booting stage. Based on the correlation analysis of original reflectivity and its first derivation with maize leaf nitrogen contents, prediction models were constructed. The results indicated that under different fertilizer dose spectral response sensitive areas of maize leaves were in visible band around 550 and 761-1 300 nm; under different levels which was in visible band around 550 nm; maize leaf nitrogen contents were significantly correlated with spectral reflectance and its first derivative in 470-760 nm band. Through further comparison and selection, the index prediction models built with spectral indices DSI(564, 681) and DSI(681, 707) were the best prediction models, the prediction accuracy were 93.43% and 93.39%, therefore nitrogen content of maize leaves could be effectively estimated.

摘要

在本研究中,进行了一项为期两年的不同施肥量的玉米田间试验。在孕穗期利用高光谱技术探讨了不同水平下玉米叶片的光谱响应敏感区域。基于原始反射率及其一阶导数与玉米叶片氮含量的相关性分析,构建了预测模型。结果表明,在不同施肥量下,玉米叶片的光谱响应敏感区域在550以及761 - 1300 nm左右的可见光波段;在不同水平下,敏感区域在550 nm左右的可见光波段;玉米叶片氮含量与470 - 760 nm波段的光谱反射率及其一阶导数显著相关。通过进一步比较和筛选,建立的光谱指数DSI(564, 681)和DSI(681, 707)的指标预测模型是最佳预测模型,预测准确率分别为93.43%和93.39%,因此能够有效估算玉米叶片的氮含量。

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