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不同水氮耦合条件下棉花冠层NDVI分析与产量估算 被引量:4

Canopy NDVI analysis and yield estimation of cotton under different nitrogen and irrigation combinations
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摘要 为研究冠层归一化差值植被指数(Normalized difference vegetation index,NDVI)在棉花重要生育时期估算棉花产量的可行性,使用GreenSeeker分别对不同灌水施肥条件下棉花光谱反射率NDVI值进行测定优化,建立NDVI值与产量关系数学模型,并对模型精度进行验证。结果显示:不同水氮组合随着生育期的推移棉花冠层NDVI值变化趋势基本一致,都呈"低-高-低"的变化规律;选取在棉花出苗后80、105和140d冠层NDVI值分别与产量进行相关性分析,得出冠层NDVI值与产量具有明显的正相关关系,相关系数分别为R2=0.376 0,0.093 4,0.363 9。利用独立的试验数据对相关性最高的水氮组合棉花出苗后80d的产量模型进行模型验证,其相关系数R2=0.712 6,均方根误差(Root mean square error,RMSE)561.04kg/hm2。因此,棉花出苗后80d的冠层NDVI值可以估测棉花产量。 In order to study the correlation of NDVI value of canopy to cotton yield during important development stages of cotton, the NDVI values of cotton spectral reflectance under different irrigation and fertilization conditions were optimized by GreenSeeker. A mathematical model of the correlation between NDVI value and yield was established and the accuracy of the model was verified. The results showed:With the development of plant, the change trends of values of the cotton canopy NDVI was relatively consistent under different water and nitrogen combinations,and all displayed "low-high- low" trend. The correlation analysis between cotton canopy NDVI values and yields at 80,105 and 140 d after seedling emergence were tested, and the correlation coefficient (R^2 ) were 0. 376 0, 0. 093 4, 0. 363 9 respectively. Positive correlation between canopy NDVI and yields was significant. Independent experimental data was adopted to evaluate the mathematical model of the correlation between NDVI value and cotton yield at 80 d. The results showed that the correlation coefficient was 0. 712 6, root mean square error (RMSE) was 561.04 kg/hm^2. Therefore, the cotton canopy NDVI of 80 d after seedling emergence was better for cotton yields estimation.
出处 《中国农业大学学报》 CAS CSCD 北大核心 2016年第1期33-38,共6页 Journal of China Agricultural University
基金 "十二五"国家科技支撑计划项目(2014BAD11B02) 国家"863"计划项目(2013AA100307)
关键词 水氮耦合 归一化差值植被指数 估测模型 产量 棉花 coupling effects of water and nitrogen normalized difference vegetation index estimation models yield cotton
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