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首页> 外文会议>PIAGENG 2013: image processing and photonics for agricultural engineering >Paddy soil nutrient assessment using visible and near infrared reflectance spectroscopy
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Paddy soil nutrient assessment using visible and near infrared reflectance spectroscopy

机译：利用可见和近红外反射光谱法评估稻田土壤养分

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摘要

The ability of obtaining soil properties estimations from time and cost efficient remotely sensed techniques has been identified as a valuable technique as there is a great demand for larger amounts of good quality and inexpensive soil data to be used in environmental monitoring, modelling and precision agriculture. Visible (Vis) and Near Infrared (NIR) spectroscopy provides a good alternative that may be used to enhance or replace conventional methods of soil analysis. The aim of this paper is to evaluate the abilities of Vis (350-700 nm) and near infrared (700-2500 nm) for prediction of soil nutrients. In this instance we implemented Savitzky-Golay algorithm and Stepwise Multiple Linear Regression (SMLR) to construct calibration models. The soil nutrients examined were soil Total Nitrogen (N), Available Phosphorus (P) and Exchangeable Potassium (K). Our results revealed the accuracy of SMLR prediction in each of the Vis and NIR spectral regions. The NIR produced more accurate predictions for N and K; however, higher significant correlation was obtained using the Vis for available P. This work demonstrated Vis and NIR spectroscopy could be considered as a good tool to assess soil nutrients in Malaysian paddy fields.
机译：由于对大量用于环境监测，建模和精确农业的高质量和廉价土壤数据的需求很大，因此从时间和成本效益高的遥感技术中获取土壤特性估计值的能力已被认为是一项有价值的技术。可见（Vis）和近红外（NIR）光谱提供了一种很好的替代方法，可用于增强或替代常规的土壤分析方法。本文的目的是评估可见光（350-700 nm）和近红外（700-2500 nm）预测土壤养分的能力。在这种情况下，我们实施了Savitzky-Golay算法和逐步多元线性回归（SMLR）来构建校准模型。检查的土壤养分为土壤总氮（N），有效磷（P）和可交换钾（K）。我们的结果揭示了在Vis和NIR光谱区域中每个区域的SMLR预测的准确性。 NIR对N和K产生了更准确的预测；但是，使用可见光对可用磷获得了更高的显着相关性。这项工作表明，可见光和近红外光谱可以被视为评估马来西亚稻田土壤养分的良好工具。

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