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Comparing predictive ability of laser-induced breakdown spectroscopy to visible near-infrared spectroscopy for soil property determination

机译:将激光诱导击穿光谱的预测能力与土壤性质测定的可见近红外光谱法相比

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Soil organic carbon (SOC) and particle size fractions have a practical value for agronomy and the environment. Thus, alternative techniques to replace the expensive conventional analyses of soil are needed. Visible near-infrared reflectance spectroscopy (vis NIRS) has already shown potential for becoming an alternative method for soil analysis since it is faster and cheaper than conventional methods. Laser-induced breakdown spectroscopy (LIBS) is another cost-effective technique with potential for rapid analysis of elements present in the soil. In this study, the feasibility of using LIBS to determine SOC, clay, silt and sand contents of Danish agricultural soils was tested and compared with the vis NIRS method. First, country-scale Partial Least Squares (PLS) regression models on soils collected across Denmark (N = 78) were built and validated using independent field samples (N = 54). Secondly, the country-scale calibration data set was spiked with 14 representative samples from the fields and validated with the 54 field samples. Generated country-scale LIBS models exhibited similar and not significantly different (p > 0.05) results to vis NIRS for all soil properties except a significantly higher (p = 0.0305) predictive ability for sand. Spiking improved the accuracy of most of the LIBS and vis NIRS models, indicating the importance of similarities between the calibration and the validation data sets. No significant differences (p > 0.05) were found between the LIBS and vis NIRS spiked country-scale models. Lower prediction errors for most properties were obtained using LIBS, rendering it an equally good or even a more accurate technique for soil properties determination than the well-established vis NIRS method. (C) 2017 IAgrE. Published by Elsevier Ltd. All rights reserved.
机译:土壤有机碳(SOC)和粒度级分具有农艺和环境的实用价值。因此,需要更换昂贵的常规分析土壤的替代技术。可见的近红外反射光谱(Vis Nirs)已经示出了成为成为土壤分析的替代方法的可能性,因为它比常规方法更快和便宜。激光诱导的击穿光谱(LIBS)是另一种具有巨大性有效的技术,可快速分析土壤中存在的元素。在这项研究中,测试了使用Libs确定SoC,Clay,Silt和丹麦农业土壤的沙子含量的可行性,并与VIRS方法进行比较。首先,使用独立的字段样本(n = 54)构建和验证丹麦收集的土壤中收集的土壤的国家规模的偏最小二乘(PLS)回归模型(n = 54)。其次,将国家规模的校准数据集掺入了来自场的14个代表性样本,并用54个字段样本验证。生成的国家尺度libs模型表现出类似的,而不是显着不同(p> 0.05)结果,以获得所有土壤属性的NIR,除了显着更高(P = 0.0305)砂的预测能力。尖峰提高了大多数LIBS和VIRS模型的准确性,表明校准与验证数据集之间的相似性的重要性。在LIBS和VIRS之间发现了没有显着差异(p> 0.05)尖刺的国家规模模型。使用Libs获得大多数属性的降低预测误差,使其同样好甚至更准确的土壤性质确定,而不是建立良好的VIRS方法。 (c)2017年IAGRE。 elsevier有限公司出版。保留所有权利。

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