Prediction of chlorophyll relative content in tea plant canopy using optimize GRNN algorithm and RPA multispectral images
Qingyan Zhou,
Jincheng Zhang,
Tangwei Wei
et al.
Abstract:To quickly and accurately assess tea plant growth, this study aims to find a new way to predict the chlorophyll content in tea plant canopies using machine learning. Using remotely piloted aircraft equipped with multispectral cameras, images of tea plantation areas are captured and reflectance from four spectral bands is extracted, leading to the calculation of vegetation indices. Simultaneously, chlorophyll relative content in the tea plant canopies was collected on the ground using a detector. Four models, n… Show more
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