数字农科院2.0

Comparison of soil exchangeable calcium estimated using five extractants and near-infrared spectroscopy

文献类型： 外文期刊

作者： Zhufeng Wang;Yugang Wang;Fei Peng;Dengchun Xing;Litao Lin;Wenting Feng

作者机构：

关键词： Arid regions;Cation exchange capacity;Exchangeable calcium;Near-infrared spectroscopy;Partial least squares regression

期刊名称： Geoderma Regional

ISSN： 2352-0094

年卷期： 2025 年 40 卷

页码：

收录情况： SCIE（2025版）

摘要： Soil exchangeable Ca (Caex) regulates multiple functions, including nutrient provision for plant growth, soil structure maintenance, and carbon sequestration. However, various chemical extraction methods are currently used worldwide to determine soil Caex, each with different mechanisms and purposes. The inconsistency in assessment methods complicates comparisons and predictions regarding soil Caex functions across different environments. To address this issue, we developed equations to convert soil Caex concentrations obtained from five different methods in arid regions. Furthermore, we evaluated the accuracy of predicting five soil Caex proxies and cation exchange capacity (CEC) using near-infrared reflectance (NIR) spectroscopy. The chemical extractants (i.e., sodium acetate (NaOAc), potassium chloride (KCl), sodium sulfate (Na2SO4), ethylenediaminetetraacetic acid (EDTA), and copper chloride (CuCl2)) were used on 308 soil samples representing a wide range of soil Caex, climate, and edaphic properties in arid regions. Our findings reveal that compared to the commonly used NaOAc extraction, Na2SO4 extracted a similar amount of soil Caex. In contrast, KCl extraction underestimated soil Caex, whereas EDTA and CuCl2 extractions overestimated it. Such discrepancies suggest that EDTA and CuCl2 are inappropriate for soils with Ca-bearing minerals, such as Ca carbonate. Moreover, the quantitative correlation among soil Caex values obtained through five different extractants highlights the need for careful selection based on specific environmental factors (i.e., soil pH and humidity). Notably, NIR-driven partial least squares regression outperformed support vector machine models for the estimation of soil Caex measured by five extractants (0.78 < R2 < 0.90) and CEC (R2 = 0.96). This capability positions NIR spectroscopy as an efficient and reliable tool for rapid assessment of soil Caex and CEC, particularly in arid regions. In conclusion, the quantitative relationships derived from various extraction methods provide a robust framework for comparing soil Caex values and enhancing our ability to predict changes in its functions under differing environmental conditions.

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