• 中文核心期刊
  • CSCD来源期刊
  • 中国科技核心期刊
  • CA、CABI、ZR收录期刊

利用近红外漫反射光谱(NIRS)技术建立甘薯茎叶重金属预测模型

Near-Infrared Diffuse Reflectance Spectroscopy for Heavy Metal Determination of Sweet Potato Leaves and Stems

  • 摘要: 植物样品中的无机离子以一定形式与具有近红外吸收的有机基团结合,因而可以借助近红外光谱技术测测其含量。探讨研究了近红外光谱法快速预测甘薯叶和茎镉、铜、锌含量的可行性,以不同肥料种植的甘薯叶和茎样品各67份,利用偏最小二乘回归法(PLS)对甘薯叶和茎中水分、蛋白质、镉、铜、锌含量进行预测分析。结果表明:所建模型可用于快速预测甘薯叶和茎样品中镉、铜、锌含量趋势,但模型精确度还有待提高。

     

    Abstract: Inorganic ions in plants can be determined by using the near-infrared spectral(NIRS)technique,because they combine with the organic groups that have NIRS absorptions.The present study explored the feasability of applying near-infrared diffuse reflectance spectrometry for rapid determination of Cu,Zn and Cd contents in sweet potato leaves and stems.Sixty-seven leaf and same number of stem samples were collected from sweet potato plants grown under different fertilizations.The partial least square method was used for calibrating spectral data with their corrsponding water,protein,Cd,Cu and Zn contents of the sweet potatoes.The results showed that the established models could rapidly predict the contents of Cu,Cd and Zn in the leaves and stems.However,the model needed to be refined further for accurate applications.

     

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