Smart soils track the formation of pH gradients across the rhizosphere

Abstract Aims Our understanding of the rhizosphere is limited by lack techniques for in situ live microscopy. Current are either destructive or unsuitable observing chemical changes within pore space. To address this limitation, we have developed artificial substrates, termed smart soils, that enable acquisition and 3D reconstruction sensors attached to soil particles. Methods The transparency soils was achieved using polymer particles with refractive index matching water. surface modified both retain water act as a local sensor report on space pH via fluorescence emissions. Multispectral signals were acquired from light sheet microscope, machine learning algorithms predicted spatial distribution at Results technique able predict ± 0.5 units true value. could be reconstructed across volume several cubic centimetres around plant roots 10 μm resolution. Using different composition, revealed how root exudation structure create variability properties. Conclusion Smart captured gradients forming growing root. Future developments technology include fine tuning physicochemical properties, addition improved data processing. Hence, play critical role advancing our complex processes.