光谱学与光谱分析, 2019, 39 (9): 2829, 网络出版: 2019-09-28  

基于高光谱分析的玉米叶片氮含量分层诊断研究

Nitrogen Nutrition Diagnostic Based on Hyperspectral Analysis about Different Layers Leaves in Maize
作者单位
农业农村部植物营养与肥料重点实验室, 中国农业科学院农业资源与农业区划研究所, 北京 100081
摘要
为了明确不同生育时期进行玉米氮素营养诊断的叶片层位, 建立准确稳健的玉米氮素营养诊断模型, 以达到合理追施氮肥, 提高氮肥利用率的目的。 试验采用单因素盆栽试验设计, 以玉米(郑单958)为研究对象, 应用高光谱技术, 分析了不同氮营养水平下不同生育时期不同层位玉米叶片的氮含量分布和变化规律及光谱响应特征; 并依据叶片氮含量与光谱反射率的相关关系, 叶片氮含量与全波段(400~2 000 nm)任意两两波段组合构建的比值光谱指数(RSI)的回归关系, 初步确定了不同生育时期进行氮素营养高光谱诊断的目标叶片, 筛选出最优的比值光谱指数, 建立了叶片氮素含量估算模型。 结果表明: 玉米叶片氮含量: 上层>中层>下层; 随着玉米的生长, 在低氮条件下上层叶片氮含量呈先减少后增加(追肥)再减少趋势, 在高氮条件下呈减少趋势, 中下层叶片氮含量呈递减趋势。 六叶期下层玉米叶片光谱反射率敏感范围较大, 相关性较强; 九叶期和灌浆期上层玉米叶片的光谱反射率敏感范围较广, 相关性较强; 开花吐丝期中层叶片的光谱反射率敏感范围较大, 相关性较强。 六叶期选取下层叶作为诊断目标叶, 选取最佳比值光谱指数RSI(1 811, 1 842)建立线性估算模型, 九叶期和灌浆期选取上层叶片作为诊断目标叶, 选取的最佳比值光谱指数分别为RSI(720, 557), RSI(600, 511)建立线性估算模型, 开花吐丝期选取中层叶片作为诊断目标叶, 选取比值光谱指数RSI(688, 644)建立线性估算模型。 研究结果可为快速准确地利用光谱技术进行玉米叶片氮素营养诊断提供理论依据。
Abstract
In order to clarify the location of nitrogen nutrient diagnosis of maize leaves at different growth stages, and to establish an accurate and robust model to diagnose maize’s nitrogen nutrition, which aims to guide rational fertilization and improve recovery rate, in this experiment, a single factor pot experiment was designed, and maize (Zhengdan 958) was used as the research object to study the distribution and variation of nitrogen content in different layers of leaf under different nitrogen nutrition levels. The distribution and variation of N content and the spectral response characteristics of maize leaves were analyzed. And the correlation relationship between nitrogen content and spectral reflectance of different layers leaves at different growth stages was investigated. Moreover, the regression relationship between the leaf nitrogen content and the ratio spectral index (RSI) which was composed of any two bands between 400~2 000 nm was explored. According to these analyses, leaf layer, optimal RSI and estimation models were initially determined at different stages for nitrogen nutrition diagnosis by spectral technique. The main results are as follows: The results indicate that the maize’s nitrogen content in different layers is as follows: the upper layer>the middle layer>the lower layer; and that as the stages of growth forward, leaves’ nitrogen content in upper layer, under the condition of low-nitrogen, appears to first decrease and then increase (after manuring) and decrease again while keeping the tendency of decrease under the condition of high-nitrogen, with the leaves’ nitrogen content in the levels of middle and low appearing to decrease. At the Six-leaf stage, the lower layer of leaves has a larger sensitivity range and a stronger correlation coefficient. At Nine-leaf and Filling stage, spectral reflectance of the upper layer maize leaves was more sensitive and correlated. At the flowering and silking stage, spectral reflectance of the middle layer leaves was more sensitive and relevant. SO the lower leaves were selected as the diagnosis target at the Six-leaf stage, and the optimal ratio spectral index RSI (1 811, 1 842) was selected to establish the linear estimation model. The upper leaves were selected as the diagnostic target at the Nine-leaf stage and the Filling stage, and the optimal ratio spectral indices were RSI (720, 557), RSI (600, 511) to establish the linear estimation model, respectively. The middle leaves were selected as the diagnostic target during the anthesis-silking stage, and the RSI (688, 644) spectral index was selected to establish the estimation model. The research results could provide a theoretical basis for rapid and accurate nitrogen nutrition spectrum diagnosis method in maize or other crop.

张银杰, 王磊, 白由路, 杨俐苹, 卢艳丽, 张静静, 李格. 基于高光谱分析的玉米叶片氮含量分层诊断研究[J]. 光谱学与光谱分析, 2019, 39(9): 2829. ZHANG Yin-jie, WANG Lei, BAI You-lu, YANG Li-ping, LU Yan-li, ZHANG Jing-jing, LI Ge. Nitrogen Nutrition Diagnostic Based on Hyperspectral Analysis about Different Layers Leaves in Maize[J]. Spectroscopy and Spectral Analysis, 2019, 39(9): 2829.

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