We are developing an optical microscope to visualize water, lipid, and lignocellulose content in plants and grasses using a quantum imaging approach (quantum ghost imaging, QGI) that exploits entangled photon pairs. A primary power of this approach is that the wavelength used for probing the sample can be in the near or mid infrared (where image contrast can be generated from vibrational absorption) and the detection/imaging is done with visible light, for which high-efficiency and low-noise imaging detectors are available. By using two detectors (a single element bucket detector for the probing photons) and a time-resolved (or fast-gated) imaging detector for image formation with the visible, entangled photon, one can greatly reduce noise in image formation by only counting coincidence photon events. As such, images can be formed under extremely low light conditions—with an excitation light flux less than ambient starlight. This work also will exploit a unique time-resolved single photon counting imaging detector developed at Los Alamos for National Security purposes. This image forming single photon sensor (previously termed a Remote Ultra Low-Light Imager, RULI or Nocturnal camera, Ncam) will enable measuring coincidence photon events with an order of magnitude better timing resolution (~100 ps) over the current state of the art (several nanoseconds) in wide-field QGI. These new imaging approaches will be tested in transmission and reflection geometries on two plant species which demonstrate different mechanisms and pathways for carbon storage: a grass (sorghum) and a dicot (Camelina). Our initial focus is on measuring an important and largely abundant plant constituent with a large mid-IR absorption: water. However, we aim to mature this technology towards nearly simultaneous measures of plant lipid, protein, and lignocellulose content over the course of the proposed research, ultimately leading to more informative measurements of plant environmental responses.

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