Mohammed S, Yen J, Hsu Y, Chou H, Natarajan S, Eybishitz A
Plants (Basel). 2025; 14(4).
PMID: 40006792
PMC: 11858947.
DOI: 10.3390/plants14040533.
Mass V, Alirezazadeh P, Seidl-Schulz J, Leipnitz M, Fritzsche E, Ibraheem R
Data Brief. 2025; 58:111271.
PMID: 39895663
PMC: 11783052.
DOI: 10.1016/j.dib.2025.111271.
Huang G, Li Y, Zhang Y, Wen W, Zhao C, Guo X
Adv Sci (Weinh). 2025; 12(10):e2415606.
PMID: 39887899
PMC: 11904986.
DOI: 10.1002/advs.202415606.
Karim M, Ahmed S, Reza M, Lee K, Sung J, Chung S
J Imaging. 2025; 11(1.
PMID: 39852318
PMC: 11766997.
DOI: 10.3390/jimaging11010005.
Mensah E, Oh H, Song J, Baek J
Plants (Basel). 2024; 13(23).
PMID: 39683240
PMC: 11644830.
DOI: 10.3390/plants13233447.
PanicleNeRF: Low-Cost, High-Precision In-Field Phenotyping of Rice Panicles with Smartphone.
Yang X, Lu X, Xie P, Guo Z, Fang H, Fu H
Plant Phenomics. 2024; 6:0279.
PMID: 39639877
PMC: 11617619.
DOI: 10.34133/plantphenomics.0279.
Meta-analysis unravels common responses of seed oil fatty acids to temperature for a wide set of genotypes of different plant species.
Alberio C, Aguirrezabal L
Front Plant Sci. 2024; 15:1476311.
PMID: 39619846
PMC: 11604464.
DOI: 10.3389/fpls.2024.1476311.
Advances in viticulture smart phenotyping: current progress and future directions in tackling soil copper accumulation.
Pii Y, Orzes G, Mazzetto F, Sambo P, Cesco S
Front Plant Sci. 2024; 15:1459670.
PMID: 39559771
PMC: 11570286.
DOI: 10.3389/fpls.2024.1459670.
Automated image registration of RGB, hyperspectral and chlorophyll fluorescence imaging data.
Bethge H, Weisheit I, Dortmund M, Landes T, Zabic M, Linde M
Plant Methods. 2024; 20(1):175.
PMID: 39551746
PMC: 11572093.
DOI: 10.1186/s13007-024-01296-y.
Harnessing Multi-Omics Strategies and Bioinformatics Innovations for Advancing Soybean Improvement: A Comprehensive Review.
Haidar S, Hooker J, Lackey S, Elian M, Puchacz N, Szczyglowski K
Plants (Basel). 2024; 13(19).
PMID: 39409584
PMC: 11478702.
DOI: 10.3390/plants13192714.
MRI-Seed-Wizard: combining deep learning algorithms with magnetic resonance imaging enables advanced seed phenotyping.
Plutenko I, Radchuk V, Mayer S, Keil P, Ortleb S, Wagner S
J Exp Bot. 2024; 76(2):393-410.
PMID: 39383098
PMC: 11714760.
DOI: 10.1093/jxb/erae408.
An integrated method for phenotypic analysis of wheat based on multi-view image sequences: from seedling to grain filling stages.
Sun S, Zhu Y, Liu S, Chen Y, Zhang Y, Li S
Front Plant Sci. 2024; 15:1459968.
PMID: 39224846
PMC: 11366606.
DOI: 10.3389/fpls.2024.1459968.
The evolution of plant phenomics: global insights, trends, and collaborations (2000-2021).
Awada L, Phillips P, Bodan A
Front Plant Sci. 2024; 15:1410738.
PMID: 39104843
PMC: 11298374.
DOI: 10.3389/fpls.2024.1410738.
Development of a deep-learning phenotyping tool for analyzing image-based strawberry phenotypes.
Ndikumana J, Lee U, Yoo J, Yeboah S, Park S, Lee T
Front Plant Sci. 2024; 15:1418383.
PMID: 39077512
PMC: 11284602.
DOI: 10.3389/fpls.2024.1418383.
A 3D printed plant model for accurate and reliable 3D plant phenotyping.
Bomer J, Esser F, Marks E, Rosu R, Behnke S, Klingbeil L
Gigascience. 2024; 13.
PMID: 38897734
PMC: 11186670.
DOI: 10.1093/gigascience/giae035.
Regulation of root growth and elongation in wheat.
Alrajhi A, Alharbi S, Beecham S, Alotaibi F
Front Plant Sci. 2024; 15:1397337.
PMID: 38835859
PMC: 11148372.
DOI: 10.3389/fpls.2024.1397337.
Image analysis and polyphenol profiling unveil red-flesh apple phenotype complexity.
Bouillon P, Fanciullino A, Belin E, Breard D, Boisard S, Bonnet B
Plant Methods. 2024; 20(1):71.
PMID: 38755652
PMC: 11100172.
DOI: 10.1186/s13007-024-01196-1.
Application of electronic nose and machine learning used to detect soybean gases under water stress and variability throughout the daytime.
Herrmann P, Dos Santos Luccas M, Ferreira E, Torre Neto A
Front Plant Sci. 2024; 15:1323296.
PMID: 38645391
PMC: 11026621.
DOI: 10.3389/fpls.2024.1323296.
Plant responses to climate change, how global warming may impact on food security: a critical review.
Janni M, Maestri E, Gulli M, Marmiroli M, Marmiroli N
Front Plant Sci. 2024; 14:1297569.
PMID: 38250438
PMC: 10796516.
DOI: 10.3389/fpls.2023.1297569.
A Remote Sensing Approach for Assessing Daily Cumulative Evapotranspiration Integral in Wheat Genotype Screening for Drought Adaptation.
Gomez-Candon D, Bellvert J, Pelecha A, Lopes M
Plants (Basel). 2023; 12(22).
PMID: 38005768
PMC: 10675030.
DOI: 10.3390/plants12223871.