ArticlePlant physiology2014
Integrated Analysis Platform: An Open-Source Information System for High-Throughput Plant Phenotyping.
Article in Plant physiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 papers.
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Who cites it
92 citing papers in PubMed.
- Automated Phenotyping Unveils Trait-Specific Genotypic Variation in Arbuscular Mycorrhiza Responsiveness in Maize (Zea mays).Plant, cell & environment · 2026Article
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- Effects of Different Plant Growth Regulators on Growth Physiology and Photosynthetic Characteristics ofPlants (Basel, Switzerland) · 2025Article
- panomiX: Investigating mechanisms of trait emergence through multi-omics data integration.Plant phenomics (Washington, D.C.) · 2025Article
- A high-throughput phenotyping dataset for GWAS analysis of maize under combined drought and heat stress.Data in brief · 2025Article
- Seed-Derived Synthetic Microbial Communities (SynComs) fromMicroorganisms · 2025Article
- Integrating metabolomics and high-throughput phenotyping to elucidate metabolic and phenotypic responses to early-season drought stress in Nordic spring wheat.BMC plant biology · 2025Article
- Predicting plant trait dynamics from genetic markers.Nature plants · 2025Article
- Implementation of theoretical non-photochemical quenching (NPQScientific reports · 2024Article
- Mapping parental DMRs predictive of local and distal methylome remodeling in epigenetic F1 hybrids.Life science alliance · 2024Article
- Article
- A CNN-based model to count the leaves of rosette plants (LC-Net).Scientific reports · 2024Article
- Broad-spectrum resistance to fungal foliar diseases in wheat: recent efforts and achievements.Frontiers in plant science · 2024Review
- Engaging Precision Phenotyping to Scrutinize Vegetative Drought Tolerance and Recovery in Chickpea Plant Genetic Resources.Plants (Basel, Switzerland) · 2023Article
- Novel exotic alleles of EARLY FLOWERING 3 determine plant development in barley.Journal of experimental botany · 2023Article
- Haplotype-Based Genome-Wide Association Analysis Using Exome Capture Assay and Digital Phenotyping Identifies Genetic Loci Underlying Salt Tolerance Mechanisms in Wheat.Plants (Basel, Switzerland) · 2023Article
- PlantInfoCMS: Scalable Plant Disease Information Collection and Management System for Training AI Models.Sensors (Basel, Switzerland) · 2023Article
- Integration of high-throughput phenotyping, GWAS, and predictive models reveals the genetic architecture of plant height in maize.Molecular plant · 2023Article
- Integrated phenotyping of root and shoot growth dynamics in maize reveals specific interaction patterns in inbreds and hybrids and in response to drought.Frontiers in plant science · 2023Article
- Article
32 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-throughput phenotyping is emerging as an important technology to dissect phenotypic components in plants. Efficient image processing and feature extraction are prerequisites to quantify plant growth and performance based on phenotypic traits. Issues include data management, image analysis, and result visualization of large-scale phenotypic data sets. Here, we present Integrated Analysis Platform (IAP), an open-source framework for high-throughput plant phenotyping. IAP provides user-friendly interfaces, and its core functions are highly adaptable. Our system supports image data transfer from different acquisition environments and large-scale image analysis for different plant species based on real-time imaging data obtained from different spectra. Due to the huge amount of data to manage, we utilized a common data structure for efficient storage and organization of data for both input data and result data. We implemented a block-based method for automated image processing to extract a representative list of plant phenotypic traits. We also provide tools for build-in data plotting and result export. For validation of IAP, we performed an example experiment that contains 33 maize (Zea mays 'Fernandez') plants, which were grown for 9 weeks in an automated greenhouse with nondestructive imaging. Subsequently, the image data were subjected to automated analysis with the maize pipeline implemented in our system. We found that the computed digital volume and number of leaves correlate with our manually measured data in high accuracy up to 0.98 and 0.95, respectively. In summary, IAP provides a multiple set of functionalities for import/export, management, and automated analysis of high-throughput plant phenotyping data, and its analysis results are highly reliable.
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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.