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Proposed methodology examines chlorophyll fluorescence in indicator plants, suggesting neural networks enhance agricultural research outcomes.
The paper presents the authors' methodology for conducting studies of chlorophyll fluorescence induction by fluorometers developed at the Institute of Cybernetics of the National Academy of Sciences of Ukraine. The methodology based on a number of experiments conducted at the Institute. It includes the selection of the indicator plant, plant cultivation, conducting of the CFI measurements and data logging, calculation of the CFI curve parameters, graphical and statistical data analysis and application of the neural network approach. Paper will be interesting for specialists in automatization of ecological and agricultural researches that using the effect of chlorophyll fluorescence induction with application statistical and neural network approaches.
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Antonova et al. (2025) studied this question.
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