首页|Study Data from South China Agricultural University Update Knowledge of Machine Learning (Research On Predicting Photosynthetic Pigments In Tomato Seedling Leav es Based On Nearinfrared Hyperspectral Imaging and Machine Learning)
Study Data from South China Agricultural University Update Knowledge of Machine Learning (Research On Predicting Photosynthetic Pigments In Tomato Seedling Leav es Based On Nearinfrared Hyperspectral Imaging and Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - A new study on Machine Learning is now available. According to news reportingoriginating in Guangzhou, People’s Repub lic of China, by NewsRx journalists, research stated, “Conventionalchemical app roaches could be limited in monitoring the concentration of pigments in plants i nhigh volumes. To overcome these limitations, researchers often turn to non-inv asive, high-throughput,and real-time monitoring techniques, such as spectroscop y and hyperspectral imaging, which allow for theassessment of pigment concentra tion in plants without the need for destructive sampling and offer theability t o monitor large volumes of plants efficiently.”
GuangzhouPeople’s Republic of ChinaA siaBiological FactorsBiological PigmentsCarotenoidsChlorophyllChloroph yllidesCyborgsEmerging TechnologiesMachine LearningMetalloporphyrinsPo rphyrinsSouth China Agricultural University
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