This study used the land health surveillance framework, which combines ground-sampling schemes based on sentinel site and infrared spectroscopy to select a minimum dataset of soil health indicators to identify key land constraints for maize production and target potential interventions.
We report and discuss results of experiments conducted on three different datasets in infrared spectroscopy and designed in such a way to test the proposed approach by: 1) varying the kind of adopted regression method used to approximate the chemical parameter of interest.
For direct comparison, Cubist was also applied to an equivalent dataset of near infrared spectroscopy (NIRS) measurements.
These data are completed by a new and exhaustive metamorphic dataset obtained by means of thermometry based on Raman Spectroscopy of Carbonaceous Material (RSCM).
Finally, we presented detailed examples of the use of constrained matrix factorization approaches on different spectroscopy data, including X-ray microscopy and scanning probe microscopy datasets.
The noisy dataset simulates an actual experiment, and demonstrates some characteristic features of an ultrafast spectroscopy experiment which may suffer from detector noise and laser pointing instabilities that can cause spectral 'jumps'jumps
(A ) Full dataset (122 complexes), (B ) reliable experimental methods only (stopped-flow, surface plasmon resonance, spectroscopy, isothermal titration calorimetry) (81 complexes), and (C ) non-reliable experimental methods (inhibition assay and fluorescence) (36 complexes).
The core- and elementary capture spectroscopy (ECS -defined shalECS -definedshaleh the wirelithofaciest their location consisted of a training dataset with 1044 setheof data for predicting shale lithofacies by conventional logs.
A better assay of minerals requires a dataset containing samples with a greater variability, which allows for an improvement in the predictive ability of FT-MIR spectroscopy.
