ArticleThe New phytologist2019
Dealing with multi-source and multi-scale information in plant phenomics: the ontology-driven Phenotyping Hybrid Information System.
Article in The New phytologist, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 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.
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.
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Who cites it
33 citing papers in PubMed.
- Hyperspectral imaging meets 3D Gaussian Splatting: A novel approach beyond 3D plant morphology.Plant phenomics (Washington, D.C.) · 2026Article
- Sharing big data for sustainable agri-food innovation.Nature biotechnology · 2026Article
- Improving annotation, access, and comparison of nutritional composition data for underutilized crops.Database : the journal of biological databases and curation · 2026Article
- LIDB: A multi-omics database ofBioinformation · 2026Article
- Targeted integrating hyperspectral and metabolomic data with spectral indices and metabolite content models for efficient salt-tolerant phenotype discrimination inPlant phenomics (Washington, D.C.) · 2025Article
- BrAPI v2: real-world applications for data integration and collaboration in the breeding and genetics community.Database : the journal of biological databases and curation · 2025Article
- AgTC and AgETL: open-source tools to enhance data collection and management for plant science research.Frontiers in plant science · 2024Article
- Toward a data infrastructure for the Plant Cell Atlas.Plant physiology · 2023Review
- Phenotyping ofPlant phenomics (Washington, D.C.) · 2023Article
- Preparation and Curation of Phenotypic Datasets.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Opportunities and limits of controlled-environment plant phenotyping for climate response traits.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Review
- The field phenotyping platform's next darling: Dicotyledons.Frontiers in plant science · 2022Review
- The INCREASE project: Intelligent Collections of food-legume genetic resources for European agrofood systems.The Plant journal : for cell and molecular biology · 2021Review
- Crop breeding for a changing climate: integrating phenomics and genomics with bioinformatics.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Review
- Data management challenges for artificial intelligence in plant and agricultural research.F1000Research · 2021Article
- Applications of Multi-Omics Technologies for Crop Improvement.Frontiers in plant science · 2021Review
- UAS-Based Plant Phenotyping for Research and Breeding Applications.Plant phenomics (Washington, D.C.) · 2021Review
- Phenomics-based GWAS analysis reveals the genetic architecture for drought resistance in cotton.Plant biotechnology journal · 2020Article
- A systems genetics approach reveals environment-dependent associations between SNPs, protein coexpression, and drought-related traits in maize.Genome research · 2020Article
- Decoding Plant-Environment Interactions That Influence Crop Agronomic Traits.Plant & cell physiology · 2020Review
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Phenomic datasets need to be accessible to the scientific community. Their reanalysis requires tracing relevant information on thousands of plants, sensors and events. The open-source Phenotyping Hybrid Information System (PHIS) is proposed for plant phenotyping experiments in various categories of installations (field, glasshouse). It unambiguously identifies all objects and traits in an experiment and establishes their relations via ontologies and semantics that apply to both field and controlled conditions. For instance, the genotype is declared for a plant or plot and is associated with all objects related to it. Events such as successive plant positions, anomalies and annotations are associated with objects so they can be easily retrieved. Its ontology-driven architecture is a powerful tool for integrating and managing data from multiple experiments and platforms, for creating relationships between objects and enriching datasets with knowledge and metadata. It interoperates with external resources via web services, thereby allowing data integration into other systems; for example, modelling platforms or external databases. It has the potential for rapid diffusion because of its ability to integrate, manage and visualize multi-source and multi-scale data, but also because it is based on 10 yr of trial and error in our groups.
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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.