Soil is a highly scattering media that inhibits imaging of plant-microbial-mineral interactions that are essential to plant health and soil carbon sequestration. However, wavefront shaping can be used to focus light through or even deep inside highly scattering objects. In this work, we seek to overcome the fundamental challenges of imaging through soil minerals by developing a custom wavefront shaping method for a multiphoton microscope. We use the adaptive stochastic parallel gradient descent optimization algorithm combined with Hadamard basis to correct the aberration and the scattering in order to focus through the soil.
We have developed a novel multiphoton nonlinear microscopy with a highly integrated optical imaging system that offers numerous label-free techniques including two-photon excited fluorescence, second-harmonic generation, third-harmonic generation, fluorescence lifetime imaging, and spectral focusing coherent anti-Stokes Raman scattering in one platform. We have applied our system to investigate plant-microbe-mineral interactions in the rhizosphere. The system provides time efficient monitoring of the rhizosphere, offering an array of simultaneous biomolecular information without staining, three-dimensional sub-micron resolution with deeper penetration , and less photodamage. We believe that multiphoton nonlinear optical microscopy will become a valuable imaging tool in the rhizosphere and soil mineral sciences.
Soil is a highly scattering media that inhibits imaging of plant-microbial-mineral interactions that are essential to plant health and soil carbon sequestration. In this work, we seek to overcome the fundamental challenges of imaging through soil minerals by developing a custom wavefront sensor-less adaptive optics (AO) system for a multiphoton microscope. We are using a combined experimental and modeling approach, characterizing mineral optical characteristics with scatterometry, modeling the wavefront distortion and the image quality degradation after imaging through the soil medium, simulating the image quality improvement with AO correction, and experimentally testing our models with a stand-alone AO testbed.
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