12 citations as recorded by crossref.

1. Nitrogen pools in páramo soils under green onion cropping: vertical distribution, prediction, and management implications D. Rey-Romero et al.
2. The site‐specific selection of the infiltration model based on the global dataset and random forest algorithm S. Kim et al.
3. Topsoil Texture Regionalization for Agricultural Soils in Germany—An Iterative Approach to Advance Model Interpretation A. Gebauer et al.
4. Spatial prediction of organic carbon in German agricultural topsoil using machine learning algorithms A. Sakhaee et al.
5. Method of pedotransfer modeling of soil moisture supply on sloping lands V. Belolipsky et al.
6. Incorporating machine learning models and remote sensing to assess the spatial distribution of saturated hydraulic conductivity in a light-textured soil M. Rezaei et al.
7. Guidelines and a supporting toolbox for parameterising key soil hydraulic properties in hydrological studies and broader integrated modelling N. Dang et al.
8. Machine Learning With GA Optimization to Model the Agricultural Soil-Landscape of Germany: An Approach Involving Soil Functional Types With Their Multivariate Parameter Distributions Along the Depth Profile M. Ließ et al.
9. Towards a cost-effective framework for estimating soil nitrogen pools using pedotransfer functions and machine learning L. Laurence et al.
10. Spatial Prediction of Organic Matter Quality in German Agricultural Topsoils A. Sakhaee et al.
11. Hydro-pedotransfer functions: a roadmap for future development T. Weber et al.
12. Pedotransfer functions and machine learning: Advancements and challenges in tropical soils L. de Castro Moreira da Silva et al.