Accelerated high-throughput imaging and phenotyping system for small organisms

Studying the complex web of interactions in biological communities requires large multifactorial experiments with sufficient statistical power. Automation tools reduce the time and labor associated with setup, data collection, and analysis in experiments that untangle these webs. We developed tools for high-throughput experimentation (HTE) in duckweeds, small aquatic plants that are amenable to autonomous experimental preparation and image-based phenotyping. We showcase the abilities of our HTE system in a study with 6,000 experimental units grown across 2,000 treatments. These automated tools facilitated the collection and analysis of time-resolved growth data, which revealed finer dynamics of plant-microbe interactions across environmental gradients. Altogether, our HTE system can run experiments with up to 11,520 experimental units and can be adapted for other small organisms., , , # Title of Dataset: Data from: Accelerated high-throughput imaging and phenotyping system for small organisms

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This dataset contains the phenotypic data from an experiment in which the growth of one clonal genotype of the duckweed Lemna minor was measured across ten nitrogen concentrations for ten days, in both the presence and absence of microbes.

## Description of the Data and file structure

The .csv file contains the following data:

block: temporal block (range 1-4)

daycol: day of the experiment (range 0-10)

nitr_N: nitrogen treatment level in mg/L (range 0-45)

inoc: inoculated (l+) or not inoculated (l-) with microbes isolated from field-collected duckweeds from the same site as the focal duckweed genotype

edge: whether the well is at the edge (TRUE) or in the interior (FALSE) of the well plate

well: The ID of the individual well in the 96-well plate

plate_number: A unique ID for each 96-well plate (range 1-16)

sqmm: The area in square millimeters of duckweed fronds i...