146 related articles for article (PubMed ID: 34539710)
1. A Deep Learning-Based Method for Automatic Assessment of Stomatal Index in Wheat Microscopic Images of Leaf Epidermis.
Zhu C; Hu Y; Mao H; Li S; Li F; Zhao C; Luo L; Liu W; Yuan X
Front Plant Sci; 2021; 12():716784. PubMed ID: 34539710
[TBL] [Abstract][Full Text] [Related]
2. A Deep Learning Method for Fully Automatic Stomatal Morphometry and Maximal Conductance Estimation.
Gibbs JA; Mcausland L; Robles-Zazueta CA; Murchie EH; Burgess AJ
Front Plant Sci; 2021; 12():780180. PubMed ID: 34925424
[TBL] [Abstract][Full Text] [Related]
3. Microscope image based fully automated stomata detection and pore measurement method for grapevines.
Jayakody H; Liu S; Whitty M; Petrie P
Plant Methods; 2017; 13():94. PubMed ID: 29151841
[TBL] [Abstract][Full Text] [Related]
4. What is the influence of ordinary epidermal cells and stomata on the leaf plasticity of coffee plants grown under full-sun and shady conditions?
Pompelli MF; Martins SC; Celin EF; Ventrella MC; Damatta FM
Braz J Biol; 2010 Nov; 70(4):1083-8. PubMed ID: 21180918
[TBL] [Abstract][Full Text] [Related]
5. Direct Observation and Automated Measurement of Stomatal Responses to Pseudomonas syringae pv. tomato DC3000 in Arabidopsis thaliana.
Hirata R; Takagi M; Toda Y; Mine A
J Vis Exp; 2024 Feb; (204):. PubMed ID: 38407316
[TBL] [Abstract][Full Text] [Related]
6. Automated estimation of stomatal number and aperture in haskap (Lonicera caerulea L.).
Meng X; Nakano A; Hoshino Y
Planta; 2023 Sep; 258(4):77. PubMed ID: 37673805
[TBL] [Abstract][Full Text] [Related]
7. From leaf to label: A robust automated workflow for stomata detection.
Meeus S; Van den Bulcke J; Wyffels F
Ecol Evol; 2020 Sep; 10(17):9178-9191. PubMed ID: 32953053
[TBL] [Abstract][Full Text] [Related]
8. Accelerating Automated Stomata Analysis Through Simplified Sample Collection and Imaging Techniques.
Millstead L; Jayakody H; Patel H; Kaura V; Petrie PR; Tomasetig F; Whitty M
Front Plant Sci; 2020; 11():580389. PubMed ID: 33101348
[TBL] [Abstract][Full Text] [Related]
9. Genetic association of stomatal traits and yield in wheat grown in low rainfall environments.
Shahinnia F; Le Roy J; Laborde B; Sznajder B; Kalambettu P; Mahjourimajd S; Tilbrook J; Fleury D
BMC Plant Biol; 2016 Jul; 16(1):150. PubMed ID: 27378125
[TBL] [Abstract][Full Text] [Related]
10. StomataCounter: a neural network for automatic stomata identification and counting.
Fetter KC; Eberhardt S; Barclay RS; Wing S; Keller SR
New Phytol; 2019 Aug; 223(3):1671-1681. PubMed ID: 31059134
[TBL] [Abstract][Full Text] [Related]
11. Image-Based Quantification of Arabidopsis thaliana Stomatal Aperture from Leaf Images.
Takagi M; Hirata R; Aihara Y; Hayashi Y; Mizutani-Aihara M; Ando E; Yoshimura-Kono M; Tomiyama M; Kinoshita T; Mine A; Toda Y
Plant Cell Physiol; 2023 Dec; 64(11):1301-1310. PubMed ID: 36943732
[TBL] [Abstract][Full Text] [Related]
12. RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures.
Yasrab R; Atkinson JA; Wells DM; French AP; Pridmore TP; Pound MP
Gigascience; 2019 Nov; 8(11):. PubMed ID: 31702012
[TBL] [Abstract][Full Text] [Related]
13. Automatic Detection and Counting of Wheat Spikelet Using Semi-Automatic Labeling and Deep Learning.
Qiu R; He Y; Zhang M
Front Plant Sci; 2022; 13():872555. PubMed ID: 35707612
[TBL] [Abstract][Full Text] [Related]
14. Genetic Diversity in Stomatal Density among Soybeans Elucidated Using High-throughput Technique Based on an Algorithm for Object Detection.
Sakoda K; Watanabe T; Sukemura S; Kobayashi S; Nagasaki Y; Tanaka Y; Shiraiwa T
Sci Rep; 2019 May; 9(1):7610. PubMed ID: 31110228
[TBL] [Abstract][Full Text] [Related]
15. StomataScorer: a portable and high-throughput leaf stomata trait scorer combined with deep learning and an improved CV model.
Liang X; Xu X; Wang Z; He L; Zhang K; Liang B; Ye J; Shi J; Wu X; Dai M; Yang W
Plant Biotechnol J; 2022 Mar; 20(3):577-591. PubMed ID: 34717024
[TBL] [Abstract][Full Text] [Related]
16. An Affordable Image-Analysis Platform to Accelerate Stomatal Phenotyping During Microscopic Observation.
Toda Y; Tameshige T; Tomiyama M; Kinoshita T; Shimizu KK
Front Plant Sci; 2021; 12():715309. PubMed ID: 34394171
[TBL] [Abstract][Full Text] [Related]
17. Detection and analysis of wheat spikes using Convolutional Neural Networks.
Hasan MM; Chopin JP; Laga H; Miklavcic SJ
Plant Methods; 2018; 14():100. PubMed ID: 30459822
[TBL] [Abstract][Full Text] [Related]
18. Cell expansion not cell differentiation predominantly co-ordinates veins and stomata within and among herbs and woody angiosperms grown under sun and shade.
Carins Murphy MR; Jordan GJ; Brodribb TJ
Ann Bot; 2016 Nov; 118(6):1127-1138. PubMed ID: 27578763
[TBL] [Abstract][Full Text] [Related]
19. Stomatal development in the context of epidermal tissues.
Torii KU
Ann Bot; 2021 Jul; 128(2):137-148. PubMed ID: 33877316
[TBL] [Abstract][Full Text] [Related]
20. Measuring stomatal and guard cell metrics for plant physiology and growth using StoManager1.
Wang J; Renninger HJ; Ma Q; Jin S
Plant Physiol; 2024 Apr; 195(1):378-394. PubMed ID: 38298139
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]