Proceedings ArticleDOI
Analysis of SEM Images of Stomata of Different Tomato Cultivars Based on Morphological Features
P. Sanyal,Ujjwal Bhattacharya,Samir Kumar Bandyopadhyay +2 more
- pp 890-894
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TLDR
Results of the recent study of morphological features of stomata of different tomato cultivars based on their scanning electron microscopy (SEM) images are reported and are supported by the protein binding pattern of the seeds of respective cultivars.Abstract:
Tomato is one of the important cash crops in the world. There are several varieties of tomato cultivars. Their identifications as well as taxonomy had been studied in the literature using different laboratory methods. Both morphological and/or genetical characteristics were considered in these available studies. However, to the best of our knowledge, there does not exist any study employing an image analysis based approach. Also, morphological features of stomata of tomato cultivars had not been studied before for the present purpose. In this article, we report results of our recent study of morphological features of stomata of different tomato cultivars based on their scanning electron microscopy (SEM) images. Interestingly, these results of the present study are supported by the protein binding pattern of the seeds of respective cultivars.read more
Citations
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Journal ArticleDOI
Microscope image based fully automated stomata detection and pore measurement method for grapevines
TL;DR: The proposed fully automated solution for stomata detection and measurement is able to produce results far superior to existing automatic and semi-automatic methods, and can process thousands of stomATA in minutes, thereby accelerating the process of analysing plant health.
Proceedings ArticleDOI
Image-based plant stornata phenotyping
TL;DR: This work proposes a fully automatic approach for image-based plant stornata phenotyping that will enable plant biologists to perform large scale analysis ofStornata morphology, which in turn will help in developing understanding and controlling plant's response to various environmental stresses.
Journal ArticleDOI
LabelStoma: A tool for stomata detection based on the YOLO algorithm
Ángela Casado-García,Arantza del-Canto,Álvaro Sanz-Sáez,Usue Pérez-López,Amaia Bilbao-Kareaga,Felix B. Fritschi,Jon Miranda-Apodaca,Alberto Muñoz-Rueda,Anna Sillero-Martínez,Ander Yoldi-Achalandabaso,Maite Lacuesta,Jónathan Heras +11 more
TL;DR: The analysis of plant stomata of different species will be more reliable and comparable; the developed tools will help to advance the understanding of CO2 and H2O dynamics in plants, such as photosynthesis and transpiration, and ecosystems related processes.
Journal ArticleDOI
Automatic segmentation and measurement methods of living stomata of plants based on the CV model
TL;DR: The proposed automated segmentation and measurement method for living stomata is superior to the existing methods based on the threshold and skeletonization in terms of versatility and can automatically discriminate whether the pore region is independent or not and perform pore area extraction.
Posted ContentDOI
A Stomata Classification and Detection System in Microscope Images of Maize Cultivars
Alexandre Hild Aono,James Shiniti Nagai,Gabriella da S. M. Dickel,Rafaela Cabral Marinho,Paulo Eugênio Oliveira,Fabio Augusto Faria +5 more
TL;DR: A new methodology for automatic stomata classification and a new detection system in microscope images for maize cultivars are proposed, with an approximated accuracy of 97.1% in the identification ofStomata regions using classifiers based on deep learning features, which figures out as a nearly perfect classification system.
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