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Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Marine & Wildlife Remediation Sign in to save

Accelerated high-throughput imaging and phenotyping system for small organisms

PLoS ONE 2023 9 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Anna O'Brien, Anna O'Brien, Tiago F. Lins, Talha Köse, Talha Köse, Tiago F. Lins, Tiago F. Lins, Tiago F. Lins, Anna O'Brien, Anna O'Brien, Tiago F. Lins, Tiago F. Lins, Tiago F. Lins, Tiago F. Lins, Tiago F. Lins, Tiago F. Lins, Tiago F. Lins, Anna O'Brien, Tiago F. Lins, Anna O'Brien, Anna O'Brien, Tiago F. Lins, Anna O'Brien, Talha Köse, Tiago F. Lins, Jessie Wang, Jessie Wang, Anna O'Brien, David Sinton Megan E. Frederickson, Megan E. Frederickson, Tiago F. Lins, Tiago F. Lins, Anna O'Brien, David Sinton David Sinton David Sinton David Sinton David Sinton David Sinton David Sinton David Sinton Megan E. Frederickson, David Sinton Megan E. Frederickson, David Sinton

Summary

This paper describes a high-throughput imaging and phenotyping system for studying duckweed plant-microbe interactions across thousands of experimental conditions. It is not about microplastics and is not relevant to microplastic research.

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.

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