Global demand for soil information has led to investigations that have adopted ways to estimate soil attributes quickly and effectively. In this context, magnetic susceptibility (χ) has gained prominence because it is a technique capable of estimating other attributes that are more difficult to acquire. This study aimed to (a) evaluate the performance of χ for the prediction of sand, silt, clay, hue, hematite/(hematite + goethite) ratio, Fe content of pedogenic iron oxides, and remaining phosphorus and (b) develop maps of χ, soil attributes and attributes predicted by χ in the state of Rio Grande do Sul (RS), Brazil. Here, 198 soil samples under forest and native pasture were used for testing the potential of χ as a predictive technique, separating the data into calibration (n_c = 149) and validation sets (n_v = 49). Linear regression was used to obtain the pedotransfer equations according to soil classes and lithology. To visualize the distribution of the values of χ and other soil attributes in RS, maps were made with the real values of χ and the real and estimated values of soil attributes. The great range of the χ values and related attributes was associated with the lithological and pedological influence, allowing the construction of predictive models that encompass a large gradient of χ. In the predictions made in groups, the attributes of Oxisols and Ultisols were best estimated by χ; however, among the lithology groups, the extrusive igneous rocks stood out.

中文翻译：

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磁化率在巴西南部土壤属性预测中的应用

全球对土壤信息的需求导致了调查，这些调查采取了快速有效地估算土壤属性的方法。在这种情况下，磁化率（χ）得到了重视，因为它是一种能够估计更难获得的其他属性的技术。这项研究旨在（a）评估χ的性能，以预测沙子，粉砂，粘土，色相，赤铁矿/（赤铁矿+针铁矿）比率，成岩性铁氧化物的Fe含量以及剩余磷的含量，以及（b）绘制χ，巴西里约格兰德州（RS）州的土壤属性和由χ预测的属性。在这里，使用198种森林和天然草场下的土壤样品作为预测技术来测试χ的潜力，将数据分为校准值（n _c = 149）和验证集（n _v  = 49）。根据土壤类别和岩性，使用线性回归来获得土壤传质方程。为了可视化RS中χ值和其他土壤属性的分布，绘制了包含χ的实际值以及土壤属性的实际值和估计值的地图。较大的χ值范围和相关属性与岩性和岩性的影响有关，从而可以构建包含较大χ梯度的预测模型。在分组预测中，用χ可以最好地估计Oxisols和Ultisols的属性。然而，在岩性组中，突出的火成岩突出。