Fast and Simultaneous Determination of Soil Properties Using Laser-Induced Breakdown Spectroscopy (LIBS): A Case Study of Typical Farmland Soils in China
Fast and Simultaneous Determination of Soil Properties Using Laser-Induced Breakdown Spectroscopy (LIBS): A Case Study of Typical Farmland Soils in China
复制标题
使用激光诱导击穿光谱 (LIBS) 快速同时测定土壤特性：以中国典型农田土壤为例
DOI：
10.3390/soilsystems3040066
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发表时间：
2019-12-01
期刊：
影响因子：
3.5
通讯作者：
Zhou, Jianmin
中科院分区：
文献类型：
--
作者：
Xu, Xuebin;Du, Changwen;Zhou, Jianmin
准确管理土壤养分和快速、同时获取土壤特性对可持续农业的发展至关重要。然而，传统的土壤分析方法通常是劳动密集型的，环境不友好的，以及耗时和成本。激光诱导击穿光谱（LIBS）是一种“超级明星”技术，在各种材料的元素分析中取得了出色的结果。然而，其在农田土壤分析中的应用面临着基质效应的挑战，缺乏具有独特来源和性质的大规模土壤样品，以及同时测定多种土壤性质的问题。为此，采用LIBS技术结合偏最小二乘回归（PLSR）方法，对中国200种不同类型农田土壤的pH、阳离子交换量（CEC）、有机质（SOM）、全氮（TN）、全磷（TP）、全钾（TK）、速效磷（AP）和速效钾（AK）进行了同时测定。对全谱和特征谱线的预测性能进行了评价和比较。基于全光谱，pH、CEC、SOM、TN和TK的预测能力较好，残差预测偏差（RPDV）均大于2.0; TP的预测能力较好，RPDV为1.993。然而，使用特征线只提高了SOM的预测精度，但降低了TN，TP和TK的预测精度。此外，全光谱和特征谱线的RPDV值均小于1.4，对土壤AP和AK的预测效果较差。常规分析的土壤AP和AK与土壤LIBS光谱之间的相关性较弱，这是导致土壤AP和AK含量预测能力较差的原因。这项研究的结果表明，LIBS技术与多变量方法相结合是快速和同时检测某些性质（即，pH和CEC）和营养物含量（即，土壤有机质、全氮、总磷和全钾），因为这些属性的预测性能非常出色。
Accurate management of soil nutrients and fast and simultaneous acquisition of soil properties are crucial in the development of sustainable agriculture. However, the conventional methods of soil analysis are generally labor-intensive, environmentally unfriendly, as well as time- and cost-consuming. Laser-induced breakdown spectroscopy (LIBS) is a “superstar” technique that has yielded outstanding results in the elemental analysis of a wide range of materials. However, its application for analysis of farmland soil faces the challenges of matrix effects, lack of large-scale soil samples with distinct origin and nature, and problems with simultaneous determination of multiple soil properties. Therefore, LIBS technique, in combination with partial least squares regression (PLSR), was applied to simultaneously determinate soil pH, cation exchange capacity (CEC), soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), available phosphorus (AP), and available potassium (AK) in 200 soils from different farmlands in China. The prediction performances of full spectra and characteristic lines were evaluated and compared. Based on full spectra, the estimates of pH, CEC, SOM, TN, and TK achieved excellent prediction abilities with the residual prediction deviation (RPDV) values > 2.0 and the estimate of TP featured good performance with RPDV value of 1.993. However, using characteristic lines only improved the predicted accuracy of SOM, but reduced the prediction accuracies of TN, TP, and TK. In addition, soil AP and AK were predicted poorly with RPDV values of < 1.4 based on both full spectra and characteristic lines. The weak correlations between conventionally analyzed soil AP and AK and soil LIBS spectra are responsible for the poor prediction abilities of AP and AK contents. Findings from this study demonstrated that the LIBS technique combined with multivariate methods is a promising alternative for fast and simultaneous detection of some properties (i.e., pH and CEC) and nutrient contents (i.e., SOM, TN, TP, and TK) in farmland soils because of the extraordinary prediction performances achieved for these attributes.