Using spectroscopy to scale carbon fraction data to build a soil risk index across European soils... nature.com/articles/s4146…

Lots of model exploration here using the LUCAS VNIR library - single property v multi-property deep learning, stacking of preprocessing methods, all with good discussion of model interpretation... sciencedirect.com/science/articl…

Federated learning applications in soil spectroscopy - learning without having to share data. sciencedirect.com/science/articl…

🟠Day 2 Wrap-Up from the #SoilHealthNow! Conference: A Deep Dive into Europe's Innovation Paradox 🌍💡 🌾During yesterday’s panel on The Soil Data Revolution: How Earth Observation, Spectroscopy, and AI are Changing Soil Use Forever, experts showcased how cutting-edge

Remote sensing and environmental covariates improves predictions of soil properties from VNIR spectroscopy alone sciencedirect.com/science/articl…

Fantastic free resource from the Food and Agriculture Organization Global Soil Partnership led by Alexandre Wadoux et al. - A course on applied data analytics for soil analysis with infrared spectroscopy openknowledge.fao.org/handle/20.500.…

Pedological features affecting carbon accumulation in submerged-soils using VNIR spectroscopy... sciencedirect.com/science/articl…

From the editorial board at Biogeochemistry "As global citizen scientists, we must therefore continue to advocate for the value of science" link.springer.com/article/10.100…

More deep learning applied to the LUCAS spectral database... GhostNet and soil pH journals.plos.org/plosone/articl…

After almost 3 years of data preparation, testing, optimization, we have finished the v1 of the 30 m resolution global #soilcarbon density, soil carbon content, pH, texture fractions, bulk density and soil types (USDA subgroups). Soil carbon and soil pH are mapped as dynamic soil

Exploring Generative Artificial Intelligence and Data Augmentation Techniques for Spectroscopy Analysis | Chemical Reviews pubs.acs.org/doi/full/10.10…

A must read by Wadoux & Ramirez-Lopez. Uncertainty of predictions in absorption spectroscopy sciencedirect.com/science/articl…

Proficiency tests for soil analysis services via proximal sensing sciencedirect.com/science/articl…

workforcenow.adp.com/mascsr/default… We're looking for a talented data/code wrangler to join our rangeland carbon research program to understand the climate benefits of regenerative grazing practices across millions of acres of grasslands.

Effective spectral pre-processing methods enhance accuracy of soil property prediction by NIR spectroscopy link.springer.com/article/10.100…

Nice paper by a great team working across multiple soil spectral libraries to produce quality predictions from field measurements - good harmonization & standardization methods are the key sciencedirect.com/science/articl…

MIR spectroscopy was used as a diagnostic tool to better understand what each Pyrogenic Carbon method was actually isolating.

Soil Organic Carbon Prediction Using an Efficient Channel Attention‐Enhanced CNN‐LSTM Model With LUCAS Spectral Library bsssjournals.onlinelibrary.wiley.com/doi/abs/10.111…

Combining digital microscopy with VNIR spectroscopy to estimate aggregation sciencedirect.com/science/articl…

Application of calibration transfer techniques between different mid‐infrared spectrometers/modules to improve accuracy in estimating soil properties in Soil Science Society of America Journal acsess.onlinelibrary.wiley.com/doi/10.1002/sa…