Phenotyping
This is a wheat breeding phenotyping and yield dataset, including canopy height (CH, m), canopy volume (CV, m3), and leaf area index (LAI) collected in the field; vegetation index (VI) generated by multispectral data acquired by UAV remote sensing; trial site weather (Weather); and yield (Yield, kg). The data comes from field trials.
Data acquisition and processing are described in the relevant part of the manuscript.
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Smart farming is the targeted use of phenotyping for the rapid, continuous, and accurate assessment of plant health in the field. Bioimpedance monitoring can play a role in smart farming as a phenotyping method, which is now accessible thanks to recent efforts to commoditize and miniaturize electronics. Here, we demonstrate that bioimpedance measurements reflect the physiological changes in live plant tissue with induced alterations in their environmental conditions.
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This dataset was collected with the goal of providing researchers with access to a collection of hundreds of images for efficient classification of plant attributes and multi-instance plant localisation and detection. There are two folders, i.e. Side view and Top View.Each folder includes label files and image files in the.jpg format (.txt format). Images of 30 plants grown in 5 hydroponic systems have been collected for 66 days. Thirty plants of three species (Petunia, Pansy and Calendula) were grown in a hydroponic system for the purpose of collecting and analysing images.
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