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Estimating photosynthetic quantum yield makes plant phenotyping easy. However, plant samples must be dark-adapted, which is time-consuming and complicates measurement of the ratio of variable to maximum fluorescence (Fv/Fm). A research consortium led by scientists from Jiangnan University has developed an artificial intelligence method, known as least-squares support vector machine model (LSSVM), that makes rapid Fv/Fm calculations without dark adaptation. This high-throughput method saves time, processes complex datasets, and is applicable in the field.
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