ArticlePlant physiology2021
Resources for image-based high-throughput phenotyping in crops and data sharing challenges.
Article in Plant physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed.
- Quantitative research from the perspective of mathematical and physical crop science: a review of phenotyping, mechanics, and modeling.Plant molecular biology · 2026Review
- Multimodal deep learning improves cross-environment prediction of durum wheat yield components.BMC plant biology · 2026Article
- Printing technologies for monitoring crop health.Nature communications · 2026Review
- Multitask ST-LSTM model based on UAV hyperspectral remote sensing for wheat yield prediction.Frontiers in plant science · 2026Article
- Post-transcriptional regulation of light-stress responses and predictive modeling in vegetableFrontiers in plant science · 2026Review
- Deep learning in plant phenotyping: the first ten years.Plant phenomics (Washington, D.C.) · 2025Review
- Predictive modeling, pattern recognition, and spatiotemporal representations of plant growth in simulated and controlled environments: A comprehensive review.Plant phenomics (Washington, D.C.) · 2025Review
- Artificial intelligence in plant science: from image-based phenotyping to yield and trait prediction.Frontiers in plant science · 2025Review
- Precise 3D geometric phenotyping and phenotype interaction network construction of maize kernels.Frontiers in plant science · 2025Article
- Epistasis and pleiotropy-induced variation for plant breeding.Plant biotechnology journal · 2024Review
- Automatic Root Length Estimation from Images Acquired In Situ without Segmentation.Plant phenomics (Washington, D.C.) · 2024Article
- Review
- More eyes on the prize: open-source data, software and hardware for advancing plant science through collaboration.AoB PLANTS · 2023Review
- Ensemble machine learning-based recommendation system for effective prediction of suitable agricultural crop cultivation.Frontiers in plant science · 2023Article
- The Global Assessment of Oilseed Brassica Crop Species Yield, Yield Stability and the Underlying Genetics.Plants (Basel, Switzerland) · 2022Review
- Biotechnological Advances to Improve Abiotic Stress Tolerance in Crops.International journal of molecular sciences · 2022Review
- Capturing crop adaptation to abiotic stress using image-based technologies.Open biology · 2022Review
- Advances in field-based high-throughput photosynthetic phenotyping.Journal of experimental botany · 2022Review
- Bridging the Gap Between Remote Sensing and Plant Phenotyping-Challenges and Opportunities for the Next Generation of Sustainable Agriculture.Frontiers in plant science · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-throughput phenotyping (HTP) platforms are capable of monitoring the phenotypic variation of plants through multiple types of sensors, such as red green and blue (RGB) cameras, hyperspectral sensors, and computed tomography, which can be associated with environmental and genotypic data. Because of the wide range of information provided, HTP datasets represent a valuable asset to characterize crop phenotypes. As HTP becomes widely employed with more tools and data being released, it is important that researchers are aware of these resources and how they can be applied to accelerate crop improvement. Researchers may exploit these datasets either for phenotype comparison or employ them as a benchmark to assess tool performance and to support the development of tools that are better at generalizing between different crops and environments. In this review, we describe the use of image-based HTP for yield prediction, root phenotyping, development of climate-resilient crops, detecting pathogen and pest infestation, and quantitative trait measurement. We emphasize the need for researchers to share phenotypic data, and offer a comprehensive list of available datasets to assist crop breeders and tool developers to leverage these resources in order to accelerate crop breeding.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.