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Design of analysis and measurement methodology for evaluation of dynamic physiological changes in plants
Rumlerová, Tereza ; Provazník, Valentine (oponent) ; Kolář, Radim (vedoucí práce)
This master's thesis, entitled "Design of Analysis and Measurement Methodology for Evaluation of Dynamic Physiological Changes in Plants," investigates the development and application of an innovative algorithm for the frequency analysis of oscillatory signals in plant responses, utilizing Fourier transformation. The algorithm, specifically tailored for use within the C# environment and integrated into the FluorCam10 software toolbox by Photon Systems Instruments (PSI), significantly enhances chlorophyll fluorescence imaging capabilities—an essential measure of plant health and photosynthetic efficiency. The research establishes a solid theoretical foundation in plant phenotyping and chlorophyll fluorescence imaging, reviewing existing methodologies and setting the stage for advanced exploration of photosynthetic dynamics. The core of the thesis delves into the technical intricacies of Fourier Transform applications in decomposing oscillatory signals to assess the physiological impacts of environmental changes on plant mechanisms. This involves a thorough evaluation of multiple FFT libraries to identify the most efficient and accurate integration for the algorithm, ensuring optimal performance in processing plant physiological data. Practical applications are demonstrated through the integration of the algorithm with the FluorCam10 software, developed by PSI. This integration facilitates detailed pixel-wise and ROI-wise analysis, enhancing the software’s functionality and allowing for a granular examination of plant responses under dynamic environmental conditions. Furthermore, the incorporation of the FC10 software with the PlantScreen SW toolbox, also developed by PSI, extends the software's functionality to support high-throughput measurements and manage complex, multi-protocol experiments in a fully automated and scalable framework. The thesis also outlines a comprehensive methodology for standardizing experimental setups to study plant responses, detailing the development of measuring and acquisition protocols to ensure robust data collection that accurately reflects physiological changes due to defined environmental variables. Experimental validation is provided through studies on Arabidopsis thaliana and tomato plants, demonstrating the algorithm’s efficacy in detecting significant physiological responses to varied light oscillation frequencies and contributing insights into genetic variability under environmental stress. This work advances the field of dynamic physiological plant studies by seamlessly integrating academic research with practical industrial applications. It lays the groundwork for future research collaborations aimed at further exploring and refining our understanding of dynamic plant responses. These efforts hold the potential to significantly enhance the accuracy and applicability of photosynthesis measurement in real-world conditions. The thesis underscores the emerging field of dynamic high-throughput phenotyping as a promising area of study with substantial implications for both academic research and practical agricultural applications.
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