Soil clay regressions: Looking for the better accuracy (part 3)

 Now we have four calibrations for clay in soil developed with a selection of samples from the LUCAS database (Spanish crop soils). Now we want to see if those calibrations predict with certain accuracy a new set of soil samples (155) from a Spanish region, acquired in a different instrument and at a different laboratory.

In these cases, it is normal to expect a bias or a slope in the predictions, so we can use the model with those adjustments applied, until the database is updated and a new expanded method with new variability (instrument, laboratory, region,) developed.

Well, these are the results of the XY plots  "Lab vs Predictions" for this independent data set:

PLS predictions:

Random Forest Predictions

Cubist Predictions

MBL Predictions

As we see in all the cases some adjustment or calibration update is needed. We can try to reprocess everything trying to find a better configuration which improves these values, but in that case this new set will never be independent again like it is now.