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Model-Based Analysis of Lactuca sativa Root Growth under the Action of Herbicides in Milli-Channel Arrays with In Situ Imaging.

Maia R LescanoJoana MacagnoClaudio Luis Alberto Berli
Published in: Journal of agricultural and food chemistry (2023)
Extracting practical information from the large amounts of data gathered during the live imaging analysis of plant organs is a challenging issue. The present work investigates the use of the logistic growth model to analyze experimental data from root elongation assays performed in milli-fluidic devices with in situ imaging. Lactuca sativa was used as a bioindicator and was subjected to wide concentration ranges of four different herbicides: 2,4-D, atrazine, glyphosate, and paraquat. The model parameters were directly connected to standard indicators of toxicity and plant development, such as the LD 50 and the absolute growth rate, respectively. In addition, it was found that realistic predictions of the maximum root length can be achieved about 60 h before the bioassay end point, which could significantly shorten the turnaround time. The combination of milli-fluidic devices, real-time imaging, and model-based data analysis becomes a powerful tool for environmental studies and ecotoxicity testing.
Keyphrases
  • data analysis
  • high resolution
  • healthcare
  • high throughput
  • climate change
  • deep learning
  • social media