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水稻中稗草光譜分析與識別
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    摘要:

    利用ASD光譜儀在室內(nèi)分別測量了水稻、稗草在350~2500nm波段內(nèi)的反射率。以各波長點處的反射率與綠色反射峰處(555 nm)的反射率的比值為變量,,運用SAS統(tǒng)計軟件的STEPDISC過程篩選能夠區(qū)分作物和雜草的變量,;判別模型中加入篩選得到的變量,,利用DISCRIM過程進行判別分析。實驗結(jié)果表明,利用4個波長點比率395/555、535/555,、705/555和1105/555可有效地從水稻中識別出稗草,其識別率為100%,。紅邊內(nèi)波長點705nm處的反射率與555nm處反射率的比值對模型貢獻最大,。

    Abstract:

    The spectral reflectance of rice and barnyard-grass was determined in the range from 350 to 2500nm using the Analytical Spectral Device Full Range FieldSpec Pro (ASD) on laboratory. The discrimination analysis was carried out with the statistical software package SAS. The spectral reflectance at the green peak (555nm) was chosen as denominator, and wavelength ratios were calculated as variables to discriminate. Wavelength ratios were selected using the STEPDISC procedure. With the selected variables, the discrimination models were developed using the DISCRIM procedure in SAS. Four wavelength ratios including 395/555, 535/555, 705/555 and 1105/555, were utilized to gain good classification performance (100% accuracy) for distinguishing barnyard-grass from rice. The ratio of spectral reflectance at 705nm in the red edge to spectral reflectance at 555nm contributes more to the discrimination model.  

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陳樹人,栗移新,毛罕平,沈?qū)殗?水稻中稗草光譜分析與識別[J].農(nóng)業(yè)機械學(xué)報,2008,39(9):96-99.[J]. Transactions of the Chinese Society for Agricultural Machinery,2008,39(9):96-99.

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