The largest uranium-phosphate deposit in Brazil also contains considerable levels of rare earth elements (REEs), which allows for the co-mining of these three ores. The most common methods for REE determination are time-consuming and demand complex sample preparation and use of hazardous reagents. Thus, the development of a safer and faster method to predict REEs in soil could aid in the assessment of these elements. We investigated the efficiency of near-infrared (NIR) spectroscopy to predict REEs in the soil of the uranium-phosphate deposit of Itataia, Brazil. We collected 50 composite topsoil samples in a well-distributed sampling grid along the deposit. The NIR measures in the soils ranged from 750 to 2500 nm. Three partial least squares regressions (PLSR) were selected to calibrate the spectra: full-spectrum partial least squares (PLS), interval partial least squares (iPLS), and successive projections algorithms for interval selection in partial least squares (iSPA-PLS). The concentrations of REEs were measured by inductively coupled plasma optical emission spectroscopy (ICP-OES). In addition to raw spectral data, we also used spectral pretreatments to investigate the effects on prediction results: multiplicative scatter correction (MSC), Savitzky-Golay derivatives (SG), and standard normal variate transformation (SNV). Positive results were obtained in PLS for La and ΣLREE using MSC pretreatment and in iSPA-PLS for Nd and Ce using raw data. The accuracy of the measurements was related to the REE concentration in soil; i.e., elements with higher concentrations tended to present more accurate results. The results obtained here aim to contribute to the development of NIR spectroscopy techniques as a tool for mapping the concentrations of REEs in topsoil.

巴西最大的铀-磷酸盐矿床还包含相当数量的稀土元素（REE），这使得这三种矿石可以共同开采。确定REE的最常用方法是耗时且需要复杂的样品制备和危险试剂的使用。因此，开发一种更安全，更快速的方法来预测土壤中的稀土元素可能有助于评估这些元素。我们调查了近红外（NIR）光谱法预测巴西Itataia铀-磷酸盐矿床土壤中REE的效率。我们在沿矿床分布均匀的采样网格中收集了50个复合表土样品。在土壤中的近红外测量范围为750至2500 nm。选择了三个偏最小二乘回归（PLSR）来校准光谱：全光谱偏最小二乘（PLS），区间偏最小二乘（iPLS），以及用于在偏最小二乘中选择间隔的连续投影算法（iSPA-PLS）。REE的浓度通过电感耦合等离子体发射光谱法（ICP-OES）测量。除了原始光谱数据外，我们还使用光谱预处理来研究对预测结果的影响：乘法散射校正（MSC），Savitzky-Golay导数（SG）和标准正态变量转换（SNV）。使用原始数据在La和ΣLREE的PLS中使用MSC预处理获得了积极的结果，在Nd和Ce的iSPA-PLS中使用原始数据获得了积极的结果。测量的准确性与土壤中的稀土元素浓度有关。即，具有较高浓度的元素倾向于呈现更准确的结果。