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首页> 外文期刊>Clean >Discrimination of Soils and Assessment of Soil Fertility Using Information from an Ion Selective Electrodes Array and Artificial Neural Networks
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Discrimination of Soils and Assessment of Soil Fertility Using Information from an Ion Selective Electrodes Array and Artificial Neural Networks

机译：利用离子选择电极阵列和人工神经网络的信息进行土壤判别和土壤肥力评估

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摘要

Multichannel sensor measurements combined with advanced treatment is the departure point for a new concept in sensorics, the electronic tongue. Our setup worked with an array of 20 ion selective electrodes plus an artificial neural network used as a pattern recognition method applied to soil analysis. With this design, we got a versatile tool which was able to perform qualitative and quantitative determinations. As first application, the qualitative discrimination between six distinct soil types based on their extractable components was attempted. The procedure was simplified to a single extraction step before measurements. Water, a BaCl2 saline solution and an acetic acid extract were evaluated as extracting agents. The best performance was reached with the acetic acid extraction method with a correct classification rate and sensitivity both of 94%, and a specificity of 100%. In addition, a quantitative determination of several physicochemical properties of agricultural interest, such as organic carbon content and selected cations (like Kþ or Mg2þ) and anions (like NO3 u0002 or Clu0002) was also demonstrated, showing satisfactory agreement with the reference methods.
机译：多通道传感器测量与高级处理相结合，是电子舌技术新概念的出发点。我们的装置使用了20个离子选择性电极阵列以及一个人工神经网络作为用于土壤分析的模式识别方法。通过这种设计，我们得到了一种能够执行定性和定量测定的通用工具。作为首次应用，尝试了基于六种不同土壤类型的可提取成分的定性区分。测量之前，该程序简化为单个提取步骤。评价水，BaCl 2盐溶液和乙酸提取物作为提取剂。用乙酸萃取法可获得最佳性能，正确的分类率和灵敏度均为94％，特异性为100％。此外，还证明了对农业感兴趣的几种理化性质的定量测定，例如有机碳含量和选择的阳离子（如Kþ或Mg2 +）和阴离子（如NO3 u0002或Clu0002），与参考方法令人满意。

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  • 来源
    《Clean》 |2014年第12期|1808-1815|共8页
  • 作者

    Aitor Mimendia; Juan M. Gutiérrez; Josep M. Alcañiz; Manel del Valle;

  • 作者单位

    Sensors and Biosensors Group, Department of Chemistry, Universitat Autònoma de Barcelona, Bellaterra, Spain;

    Bioelectronics Section, Department of Electrical Engineering, CINVESTAV, Mexico, Mexico;

    CREAF (Centre for Ecological Research and Forestry Applications), Department of Animal and Plant Biology and Ecology, Universitat Autònoma de Barcelona, Bellaterra, Spain;

    Sensors and Biosensors Group, Department of Chemistry, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Electronic tongue; Organic matter; Pattern recognition; Soil analysis; Soil sensing;

    机译：电子舌有机物;模式识别;土壤分析;土壤感测;

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