StomaAI: an efficient and user-friendly tool for measurement of stomatal pores and density using deep computer vision.
applied deep learning
computer vision
convolutional neural network
phenotyping
stomata
Journal
The New phytologist
ISSN: 1469-8137
Titre abrégé: New Phytol
Pays: England
ID NLM: 9882884
Informations de publication
Date de publication:
04 2023
04 2023
Historique:
received:
31
10
2022
accepted:
23
12
2022
pubmed:
24
1
2023
medline:
21
3
2023
entrez:
23
1
2023
Statut:
ppublish
Résumé
Using microscopy to investigate stomatal behaviour is common in plant physiology research. Manual inspection and measurement of stomatal pore features is low throughput, relies upon expert knowledge to record stomatal features accurately, requires significant researcher time and investment, and can represent a significant bottleneck to research pipelines. To alleviate this, we introduce StomaAI (SAI): a reliable, user-friendly and adaptable tool for stomatal pore and density measurements via the application of deep computer vision, which has been initially calibrated and deployed for the model plant Arabidopsis (dicot) and the crop plant barley (monocot grass). SAI is capable of producing measurements consistent with human experts and successfully reproduced conclusions of published datasets. SAI boosts the number of images that can be evaluated in a fraction of the time, so can obtain a more accurate representation of stomatal traits than is routine through manual measurement. An online demonstration of SAI is hosted at https://sai.aiml.team, and the full local application is publicly available for free on GitHub through https://github.com/xdynames/sai-app.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
904-915Informations de copyright
© 2023 The Authors. New Phytologist © 2023 New Phytologist Foundation.
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