Search Results - agricultural+%26+plant+biology+research

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A Device for the Direct Measurement of Solar-Induced Chlorophyll Fluorescence in the Far-Red Spectral Range (SIF-SBR) (Case No. 2024-183)
Summary: UCLA researchers in the Department of Atmospheric and Oceanic Sciences have developed a novel and compact device for direct, real-time measurement of solar-induced chlorophyll fluorescence, enabling accurate monitoring of plant photosynthetic activity without complex calibration or spectral retrieval procedures. Background: Accurate monitoring...
Published: 5/8/2026   |   Updated: 5/8/2026   |   Inventor(s): Jochen Stutz, Jonas Kuhn
Keywords(s): Agricultural & plant biology research, Agriculture, Chemical, concentrated solar radiation, Ecosystem monitoring, Fluorescence, low-power architecture, low-power device, low-power sensor, operating range, Photon, photosynthetic activity, photosynthetic monitoring, Plant fluorescence, Plant proximal remote sensing, Precision Agriculture, Proximal remote sensing, real-time, real-time sensing/monitoring/tracking, Signal Processing, Signal-To-Noise Ratio, Solar Energy, spectral density
Category(s): Energy & Environment, Energy & Environment > Energy Efficiency, Energy & Environment > Carbon Capture, Energy & Environment > Water Monitoring & Treatment, Life Science Research Tools, Life Science Research Tools > Research Methods, Optics & Photonics, Optics & Photonics > Remote Sensing, Optics & Photonics > Spectroscopy, Life Science Research Tools > Field Equipment
Bio-Aerosol Detection Using Mobile Microscopy and Machine Learning (Case No. 2019-722)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed an air analysis instrument and accompanying virtual aerosol detection method that combines imaging and deep learning to sense and classify airborne particles without external labeling or post processing steps. Background: Air quality management, particularly...
Published: 7/17/2025   |   Updated: 11/7/2023   |   Inventor(s): Aydogan Ozcan
Keywords(s): aerosol, Agricultural & plant biology research, air quality measurement, bioaerosol, Bioterrorism detection, Deep Learning, Deep learning-based sensing, Digital Holography, Holography, Indoor air quality monitoring, Industrial applications: food processing, fermentation, label-free sensing, pollen detection, real-time sensing/monitoring/tracking, smart sensing
Category(s): Software & Algorithms > Artificial Intelligence & Machine Learning, Life Science Research Tools > Microscopy And Imaging, Chemical > Chemical Sensors