ReviewTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2021
Crop breeding for a changing climate: integrating phenomics and genomics with bioinformatics.
Review in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 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
32 citing papers in PubMed, 89 citations in OpenAlex.
- Omics-driven plant breeding through phenomics-enviromics crosstalk.Nature communications · 2026Review
- Omics Technologies in Molecular Biology.International journal of molecular sciences · 2026Article
- Three-dimensional phenotyping: Technological advances and applications in genomics-assisted crop breeding.Plant communications · 2026Review
- Benchmarking Feature Selection Methods and Prediction Models for Flowering Time Prediction in Maize.International journal of molecular sciences · 2026Article
- Bioinformatics in crop research: using genomic data for crop improvement.Frontiers in plant science · 2026Review
- Next-generation translational genomics for developing future crops.Functional & integrative genomics · 2025Review
- Foliar disease resistance phenomics of fungal pathogens: image-based approaches for mapping quantitative resistance in cereal germplasm.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Integrating multi-omics and machine learning for disease resistance prediction in legumes.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Exploring genomic feature selection: A comparative analysis of GWAS and machine learning algorithms in a large-scale soybean dataset.The plant genome · 2025Article
- Article
- Cotton under heat stress: a comprehensive review of molecular breeding, genomics, and multi-omics strategies.Frontiers in genetics · 2025Review
- Beyond the genome: the role of functional markers in contemporary plant breeding.Frontiers in plant science · 2025Review
- From data to decisions: a paradigm shift in fruit agriculture through the integration of multi-omics, modern phenotyping, and cutting-edge bioinformatic tools.Frontiers in plant science · 2025Review
- Omics-Driven Strategies for Developing Saline-Smart Lentils: A Comprehensive Review.International journal of molecular sciences · 2024Review
- Elevated atmospheric COScientific reports · 2024Article
- Meta-QTL and Candidate Gene Analyses of Agronomic Salt Tolerance and Related Traits in an RIL Population Derived fromInternational journal of molecular sciences · 2024Article
- Drought stress inPhysiology and molecular biology of plants : an international journal of functional plant biology · 2024Review
- Article
- Can the Wild Perennial, Rhizomatous Rice Species Oryza longistaminata be a Candidate for De Novo Domestication?Rice (New York, N.Y.) · 2023Review
- Phenomics as an approach to Comparative Developmental Physiology.Frontiers in physiology · 2023Article
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 at 1 institution in 1 country.
Funding
Abstract
key messageSafeguarding crop yields in a changing climate requires bioinformatics advances in harnessing data from vast phenomics and genomics datasets to translate research findings into climate smart crops in the field. Climate change and an additional 3 billion mouths to feed by 2050 raise serious concerns over global food security. Crop breeding and land management strategies will need to evolve to maximize the utilization of finite resources in coming years. High-throughput phenotyping and genomics technologies are providing researchers with the information required to guide and inform the breeding of climate smart crops adapted to the environment. Bioinformatics has a fundamental role to play in integrating and exploiting this fast accumulating wealth of data, through association studies to detect genomic targets underlying key adaptive climate-resilient traits. These data provide tools for breeders to tailor crops to their environment and can be introduced using advanced selection or genome editing methods. To effectively translate research into the field, genomic and phenomic information will need to be integrated into comprehensive clade-specific databases and platforms alongside accessible tools that can be used by breeders to inform the selection of climate adaptive traits. Here we discuss the role of bioinformatics in extracting, analysing, integrating and managing genomic and phenomic data to improve climate resilience in crops, including current, emerging and potential approaches, applications and bottlenecks in the research and breeding pipeline.
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.