13 citations as recorded by crossref.

1. Soil organic matter and clay predictions by laboratory spectroscopy: Data spatial correlation D. Silva-Sangoi et al. 10.1016/j.geodrs.2022.e00486
2. Application of generalized linear geostatistical model for regional soil organic matter mapping: The effect of sampling density M. Zhang et al. 10.1016/j.geoderma.2023.116446
3. Do model choice and sample ratios separately or simultaneously influence soil organic matter prediction? K. John et al. 10.1016/j.iswcr.2021.11.003
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5. Spectral Data Processing for Field-Scale Soil Organic Carbon Monitoring J. Reyes & M. Ließ 10.3390/s24030849
6. Explainable Machine Learning to Unveil Detection Mechanisms with Au Nanoisland-Based Surface-Enhanced Raman Scattering for SARS-CoV-2 Antigen Detection W. Pazin et al. 10.1021/acsanm.3c05848
7. Errors induced by spectral measurement positions and instrument noise in soil organic carbon prediction using vis-NIR on intact soil X. Sun 10.1016/j.geoderma.2020.114731
8. Variability of soil mapping accuracy with sample sizes, modelling methods and landform types in a regional case study X. Sun et al. 10.1016/j.catena.2022.106217
9. Using machine learning and an electronic tongue for discriminating saliva samples from oral cavity cancer patients and healthy individuals D. Braz et al. 10.1016/j.talanta.2022.123327
10. On-the-Go Vis-NIR Spectroscopy for Field-Scale Spatial-Temporal Monitoring of Soil Organic Carbon J. Reyes & M. Ließ 10.3390/agriculture13081611
11. Best performances of visible–near-infrared models in soils with little carbonate – a field study in Switzerland S. Oberholzer et al. 10.5194/soil-10-231-2024
12. A loss function to evaluate agricultural decision-making under uncertainty: a case study of soil spectroscopy T. Breure et al. 10.1007/s11119-022-09887-2
13. Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon Modeling S. Semella et al. 10.3390/s22072749