[HTML][HTML] Multi-Sensor Soil Probe and Machine Learning Modeling for Predicting Soil Properties
We present a data-driven, in situ proximal multi-sensor digital soil mapping approach to
develop digital twins for multiple agricultural fields. A novel Digital Soil CoreTM (DSC) Probe …
develop digital twins for multiple agricultural fields. A novel Digital Soil CoreTM (DSC) Probe …
Quantification of spectral measurement errors to guide preprocessing method selection: a case study on cannabinoid prediction across multiple NIR instruments
This study investigates the influence of spectral measurement errors on the accuracy and
reliability of Near-Infrared (NIR) spectroscopy in predicting cannabinoid content, specifically …
reliability of Near-Infrared (NIR) spectroscopy in predicting cannabinoid content, specifically …
[HTML][HTML] Building a near-infrared (NIR) soil spectral dataset and predictive machine learning models using a handheld NIR spectrophotometer
This near-infrared spectral dataset consists of 2,106 diverse mineral soil samples scanned,
on average, on six different units of the same low-cost commercially available handheld …
on average, on six different units of the same low-cost commercially available handheld …
[PDF][PDF] Multi-Sensor Soil Probe and Machine Learning Modeling
S Grunwald, MOF Murad, S Farrington, W Wallace… - 2024 - preprints.org
We present a data-driven, in situ proximal multi-sensor digital soil mapping approach to
develop digital twins for multiple agricultural fields. A novel Digital Soil CoreTM (DSC) Probe …
develop digital twins for multiple agricultural fields. A novel Digital Soil CoreTM (DSC) Probe …