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Challenge : Most plant imaging systems focus predominantly on monitoring morphological traits. The challenge is to relate color information to measurements of physiological processes. Question: Can the color of individual leaves be measured and quantified over time to infer physiological information about the plant? Solution: We developed the open source and affordable plant phenotyping software pipeline for Arabidopsis thaliana. SMART (Speedy Measurement of Arabidopsis Rosette Traits) that integrates a new color analysis algorithm to measure leaf surface temperature, leaf wilting and zinc toxicity over time. Data Collection: We used public datasets to develop the algorithm [1] and validate morphological measurements. We also collected top-view images of the Arabidopsis rosette with the Open-Leaf
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Novel method for the quantification of rosette area from images of Arabidopsis seedlings grown on agar plates
Abstract Premise: The agar‐based culture of Arabidopsis seedlings is widely used for quantifying root traits. Shoot traits are generally overlooked in these studies, probably because the rosettes are often askew. A technique to assess the shoot surface area of seedlings grown inside agar culture dishes would facilitate simultaneous root and shoot phenotyping. Methods: We developed an image processing workflow in Python that estimates rosette area of Arabidopsis seedlings on agar culture dishes. We validated this method by comparing its output with other metrics of seedling growth. As part of a larger study on genetic variation in plant responses to nitrogen form and concentration, we measured the rosette areas from more than 2000 plate images. Results: The rosette area measured from plate images was strongly correlated with the rosette area measured from directly overhead and moderately correlated with seedling mass. Rosette area in the large image set was significantly influenced by genotype and nitrogen treatment. The broad‐sense heritability of leaf area measured using this method was 0.28. Discussion: These results indicated that this approach for estimating rosette area produces accurate shoot phenotype data. It can be used with image sets for which other methods of leaf area quantification prove unsuitable.
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- PAR ID:
- 10384532
- Date Published:
- Journal Name:
- Applications in Plant Sciences
- Volume:
- 10
- Issue:
- 6
- ISSN:
- 2168-0450
- Page Range / eLocation ID:
- e11504
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1002/aps3.11504
