» Articles » PMID: 23451789

Future Scenarios for Plant Phenotyping

Overview
Date 2013 Mar 5
PMID 23451789
Citations 276
Authors
Affiliations
Soon will be listed here.
Abstract

With increasing demand to support and accelerate progress in breeding for novel traits, the plant research community faces the need to accurately measure increasingly large numbers of plants and plant parameters. The goal is to provide quantitative analyses of plant structure and function relevant for traits that help plants better adapt to low-input agriculture and resource-limited environments. We provide an overview of the inherently multidisciplinary research in plant phenotyping, focusing on traits that will assist in selecting genotypes with increased resource use efficiency. We highlight opportunities and challenges for integrating noninvasive or minimally invasive technologies into screening protocols to characterize plant responses to environmental challenges for both controlled and field experimentation. Although technology evolves rapidly, parallel efforts are still required because large-scale phenotyping demands accurate reporting of at least a minimum set of information concerning experimental protocols, data management schemas, and integration with modeling. The journey toward systematic plant phenotyping has only just begun.

Citing Articles

Integrative Trait Analysis for Enhancing Heat Stress Resilience in Tomato ( L.): A Focus on Root, Physiological, and Yield Adaptations.

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.


Annotated image dataset with different stages of European pear rust for UAV-based automated symptom detection in orchards.

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.


Overcoming Challenges in Plant Biomechanics: Methodological Innovations and Technological Integration.

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.


Geometric Feature Characterization of Apple Trees from 3D LiDAR Point Cloud Data.

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.


Exploring Imaging Techniques for Detecting Tomato Spotted Wilt Virus (TSWV) Infection in Pepper ( spp.) Germplasms.

Mensah E, Oh H, Song J, Baek J Plants (Basel). 2024; 13(23).

PMID: 39683240 PMC: 11644830. DOI: 10.3390/plants13233447.