曹仕, 刘湘南, 曹珊. 成熟期水稻砷污染胁迫光谱诊断空间模型研究[J]. 中国生态农业学报(中英文), 2010, 18(4): 843-846. DOI: 10.3724/SP.J.1011.2010.00843
引用本文: 曹仕, 刘湘南, 曹珊. 成熟期水稻砷污染胁迫光谱诊断空间模型研究[J]. 中国生态农业学报(中英文), 2010, 18(4): 843-846. DOI: 10.3724/SP.J.1011.2010.00843
CAO Shi, LIU Xiang-Nan, CAO Shan. Spectral space model for diagnosing As stress in mature rice[J]. Chinese Journal of Eco-Agriculture, 2010, 18(4): 843-846. DOI: 10.3724/SP.J.1011.2010.00843
Citation: CAO Shi, LIU Xiang-Nan, CAO Shan. Spectral space model for diagnosing As stress in mature rice[J]. Chinese Journal of Eco-Agriculture, 2010, 18(4): 843-846. DOI: 10.3724/SP.J.1011.2010.00843

成熟期水稻砷污染胁迫光谱诊断空间模型研究

Spectral space model for diagnosing As stress in mature rice

  • 摘要: 以分别表征不同生理特征的NDVI等12种高光谱指数为基础, 结合成熟期水稻叶片实测砷含量, 利用相关分析法提取PSNDa(R= -0.89)、DSWI(R= -0.79)、SIPI(R=0.91)作为单级光谱诊断参数, 并以此为因子 组成砷污染胁迫光谱参数诊断空间(PSNDa-DSWI、PSNDa-SIPI、DSWI-SIPI), 其中以表征叶绿素和细胞结构的PSNDa-SIPI组合空间的诊断效果最佳。利用主成分分析综合各光谱参数信息, 从中提取出主成分F1、F2, 其累积贡献率达88%, 由此建立砷污染胁迫主成分诊断空间(F1-F2), 不同污染程度对应不同诊断空间, 高度污染: F1<1.95, F2>0.75; 中度污染: 1.95<F1<3.15, 0.75>F2>0.40; 轻度污染: F1>3.15, F2<0.40。由此从不同层面构成一个严密的水稻砷污染胁迫诊断系统, 为系统、全面、有效监测大面积水稻砷污染提供多元化诊断依据。

     

    Abstract: Sixty leaf samples of mature rice were scanned by ASD field pro3 for optical data and analyzed for As content using atomic absorption spectrometry. A space model for diagnosing As contamination in rice based on 12 hyperspectral potentially sensitive indices of As stress was used in this paper. In the first step, single diagnosis indices (PSNDa, DSWI, SIPI) representing different rice physiological parameters were determined using correlation analysis between hyper-spectral indices and As content, and then two-dimension diagnosis spaces (PSNDa-DSWI, PSNDa-SIPI, DSWI-SIPI) were constructed, of which PSNDa-SIPI representing chlorophyll and cell structure shows a more effective prediction of As contamination in rice. In the second step, another diagnosis space (F1-F2) was built from principal component analysis of the 12 hyperspectral indices, whose accumulative contribution rate was 88%. This was an exact predictor of As pollution in rice; where F1<1.95 and F2>0.75 represents high pollution, 1.95<F1<3.15 and 0.75>F2>0.40 represent medium pollution, and F1>3.15 and F2<0.40 represent low pollution. These diagnosis spaces form a comprehensive diagnosis space model that services for monitoring large-scale As contamination in rice from different levels.

     

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