AbstractThe complex web of interactions in biological communities is an area of study that requires large multifactorial experiments with sufficient statistical power. The use of automated tools can reduce the time and labor associated with experiment setup, data collection, and analysis in experiments aimed at untangling these webs. Here we demonstrate 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 1,000 different nutrient environments. The use of our 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 of up to 11,520 experimental units and can be adapted to studies with other small organisms.
