Fig. 1: Graphical overview of the paper. | Communications Earth & Environment

Fig. 1: Graphical overview of the paper.

From: Exploring crop health and its associations with fungal soil microbiome composition using machine learning applied to remote sensing data

Fig. 1

(1) We estimate crop health/growth as NDVI values from satellite images. (2) We adjust the NDVI values by removing abiotic influence through a Random Forest model. (3) We identify clusters of pre-processed biotic data from soil samples using hierarchical clustering and investigate the link between the residual NDVI values and the derived clusters. (4) We filter rare taxonomy applying IQR bootstrapping, followed by the generation of sparse networks, identifying and investigating nodes of importance from biotic networks of the clusters.

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