Information on soil properties is crucial for soil preservation, the improvement of food security, and the provision of ecosystem services. In particular, for the African continent, spatially explicit information on soils and their ability to sustain these services is still scarce. To address data gaps, infrared spectroscopy has achieved great success as a cost-effective solution to quantify soil properties in recent decades.
Here, we present a mid-infrared soil spectral library SSL for central Africa CSSL that can predict key soil properties, allowing for future soil estimates with a minimal need for expensive and time-consuming wet chemistry.
For this last strategy we introduce a method for spiking MBL models. The ratio of performance to the interquartile distance RPIQ pred ranged between 0. While the effect of the second strategy compared to the first strategy was mixed, the third strategy, spiking with samples from the target regions, could clearly reduce the RMSE pred to 3.
RPIQ pred values were increased to ranges of 1. In general, predicted TC and TN for soils of each of the six regions were accurate; the effect of spiking and avoiding geographical extrapolation was noticeably large. We conclude that our CSSL adds valuable soil diversity that can improve predictions for the Congo Basin region compared to using the continental AfSIS SSL alone; thus, analyses of other soils in central Africa will be able to profit from a more diverse spectral feature space.
Given these promising results, the library comprises an important tool to facilitate economical soil analyses and predict soil properties in an understudied yet critical region of Africa. Our SSL is openly available for application and for enlargement with more spectral and reference data to further improve soil diagnostic accuracy and cost-effectiveness.
