ArticlePeerJ2017
PlantCV v2: Image analysis software for high-throughput plant phenotyping.
Article in PeerJ, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
137 citing papers in PubMed.
- Temporal phenotypic responses of early vegetative maize to heat, drought, and combined stresses.The Plant journal : for cell and molecular biology · 2026Article
- Shaping kale morphology and physiology using precision LED light recipes.Journal of experimental botany · 2026Article
- Harnessing artificial intelligence in plant breeding: innovations in digital phenotyping and breeding methodologies.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- Beyond high-throughput: leveraging plant phenotyping to improve understanding and prediction of plant growth through process-based models.The New phytologist · 2026Review
- Exogenous Hormone Treatments Reveal Species-Specific Regulation of Individual Components of Root Architecture and Salt Ion Accumulation in Cultivated and Wild Tomatoes.Plant direct · 2026Article
- Remote Sensing of Endogenous Pigmentation by Inducible Synthetic Circuits in Grasses.Plant biotechnology journal · 2026Article
- Deep learning-based precision phenotyping of spine curvature identifies novel genetic risk loci for scoliosis in the UK Biobank.NPJ digital medicine · 2026Article
- Open RGB imaging workflow for morphological and morphometric analysis of fruits using deep learning: a case study on almonds.GigaScience · 2026Article
- Root system architecture reorganization under decreasing soil phosphorus lowers root system conductance of Zea mays.Annals of botany · 2025Article
- Deep learning in plant phenotyping: the first ten years.Plant phenomics (Washington, D.C.) · 2025Review
- High-throughput plant phenotyping identifies and discriminates biotic and abiotic stresses in tomato.Plant phenomics (Washington, D.C.) · 2025Article
- Genome-wide association study reveals candidate loci for resistance to anthracnose in blueberry.G3 (Bethesda, Md.) · 2025Article
- Seed-Derived Synthetic Microbial Communities (SynComs) fromMicroorganisms · 2025Article
- Genetic suppressors of the growth-immunity trade-off in the Arabidopsis salicylic acid-accumulating dmr6 dlo1 mutant.The Plant journal : for cell and molecular biology · 2025Article
- B4 Raf-like MAPKKK RAF24 regulates Arabidopsis thaliana flowering time through HISTONE MONO-UBIQUITINATION 2.The New phytologist · 2025Article
- OpenPheno: an open-access, user-friendly, and smartphone-based software platform for instant plant phenotyping.Plant methods · 2025Article
- Determination of Optimal Harvest Time inPlants (Basel, Switzerland) · 2025Article
- Digitally Quantifying Growth and Verdancy ofPlants (Basel, Switzerland) · 2025Article
- It's all in the timing: vegetative phase change alters selection under drought and contributes to local adaptation.bioRxiv : the preprint server for biology · 2025Article
- Article
77 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here we present the details and rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.
Indexed as
Identifiers
What OpenQuestion holds
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.