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水稻叶片反射光谱诊断氮素营养敏感波段的研究 被引量:26

Sensitive band ranges of leaf spectral reflectance in diagnosis of rice nitrogen nutrition.
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摘要 田间小区试验叶色差异明显而生育期相似的两品种第一和第三完全展开叶片光谱反射率与氮素营养相关性分析表明,不同品种同一叶位之间这种相关性变化规律一致,然而在不同叶位之间相关性变化不尽一致.进一步对比分析大田区域试验和小区试验叶片光谱反射率与氮素营养相关性发现两区域样本相同叶位之间相关性变化规律相同.分析第一、三完全展开叶叶片光谱反射率处理之间差异显著性表明,存在差异显著的波段范围主要集中在绿光(525~605nm)、黄光(605~655nm)和短波近红外光(750~1100nm)范围内.和叶片氮素含量之间相关性最大的波段主要为绿光(525~605nm)和黄光(605~655nm)范围,而短波近红外光范围与叶片氮素含量之间相关性最小.因此和IKONOS2、IKONOS4、MSS4、MSS6、MSS7、SPOT1、SPOT3、TM2、TM4、AVHRRCH1、AVHRRCH2相对应的绿光(525~605nm)、黄光(605~655nm)和短波近红外光(750~1100nm)是叶片反射光谱诊断氮素营养的敏感波段范围. The rice samples came from two experimental designs with different condition. From those samples the most upper expanded fully leaf and the third one were selected to measure leaf spectral reflectance using FieldSpec FR (350-2500 nm). Differences of leaf spectral reflectance among three N levels were analyzed by F test at tiller stage, booting stage, heading stage and milky stage respectively. And the correlation between leaf spectral reflectance and leaf nitrogen content based on dry weight were also analyzed. from the study of significant difference and the significant (insignificant) correlation, three sensitive band ranges were revealed which corresponded to the green, yellow and short wave near infrared (SW-NIR) regions. And they were as important as universal satellites bands IKONOS2, IKONOS4, MSS4, MSS6, MSS7, SPOT1, SPOT3, TM2, TM4, AVHRRCH1, and AVHRRCH2.
出处 《浙江大学学报(农业与生命科学版)》 CAS CSCD 北大核心 2004年第3期340-346,共7页 Journal of Zhejiang University:Agriculture and Life Sciences
基金 国家自然科学基金项目(30070444 40101014).
关键词 水稻叶片 氮素营养 敏感波段 nitrogen nutrition rice leaf sensitive band ranges
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  • 1Curran P J, Remote sensing of foliar chemistry[J].Remote Sens Environ, 1989,30: 271 278.
  • 2Yoder B J, Pettigrew-Crosby, Predicting nitrogen and chlorophyll content and concentrations from reflectance spectra (400-2500 nm) at leaf and canopy scales[J]. Remote Sensing of Environment, 1995, 53:199-211.
  • 3Curran P J, Dungan J L, Macler B A,et al. Reflectance spectroscopy of fresh whole leaves for the estimation of chemical concentration[J]. Remote Sensing of Environment, 1992,39:153-166.
  • 4Lee F Johnson. Nitrogen influence on fresh-leaf NIR spectra[J]. Remote sensing of environment, 2001,78:314-320.
  • 5Grossman Y L, Ustin S L, Jacquemoud S. Critique of stepwise multiple linear regression for the extraction of leaf biochemistry information from leaf reflectance data [J]. Remote Sensing of Environment, 1996,56:182 193.
  • 6Fourty T, Baret F. On spectral estimates of fresh leaf biochemistry [J]. International Journal of Remote Sensing, 1998,19:1283-1297.
  • 7Fourty Th, Baret F, Jacquemoud S. et al. Leaf optical properties with explicit description of its biochemical composition:direct and inverse problems[J]. Remote sens Environ, 1996,56:104-117.
  • 8BAO Shi-dan(鲍士旦).Soil chemicalanalysis(土壤农化分析)[M].Beijing:China Agriculture Press,2002.(in Chinese)
  • 9Analytical Spectral Devices, Inc. (ASD) Technical Guide: 101.
  • 10WANG Ren-cho,HUANG Jing-feng(王人潮,黄敬峰).Rice yield estimation using remote sensing data (水稻遥感估产)[M].Beijing:China Agriculture Press,2002:38-46.(in Chinese)

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