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A new NIR technique for rapid determination of soil moisture content

机译:一种快速测定土壤水分含量的新奈德技术

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As soil moisture prediction model with the whole near-infrared spectral regions is complex and the single-band prediction model is susceptible to environmental impact, a dual-band method for measuring soil moisture content (MC) rapidly was proposed in this study. A total of 116 soil samples were collected and the NIR reflectance spectra of all soil samples were measured. The spectral data were transformed to new spectral data with logarithmic transformation and logarithmic of reciprocal transformation. The spectral bands of the new spectral data and the original spectral data that is sensitive and insensitive to soil moisture content were achieved by correlation coefficient method. The models for prediction of soil MC were developed based on single linear regression (SLR) with the sensitive spectral band and insensitive spectral band. The results show that the prediction precision of the models was high and the highest correlation coefficient of the models reached 0.9913 with the root mean square error of prediction RMSEP of 1.1983%. Thus, it is concluded that the methods used in this paper are available methods for rapid detection of soil MC and also provides theoretical basis for developing a low-cost portable near-infrared moisture meter.
机译:随着具有整个近红外光谱区的土壤水分预测模型是复杂的,并且单带预测模型易受环境影响的影响,在本研究中提出了一种用于测量土壤水分含量(MC)的双频带方法。收集总共116个土壤样品,并测量所有土壤样品的NIR反射光谱。频谱数据被转换为具有对数变换和互易转换的对数的新光谱数据。通过相关系数法实现了新的光谱数据和对土壤水分含量敏感和不敏感的原始光谱数据的光谱带。基于单线性回归(SLR)与敏感光谱带和不敏感光谱带开发了土壤MC预测模型。结果表明,模型的预测精度高,模型的最高相关系数达到0.9913,具有1.1983%的预测RMSEP的根均线误差。因此,得出结论,本文中使用的方法是用于快速检测土壤MC的可用方法,并为开发低成本便携式近红外水分仪提供理论依据。

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