ReviewNature plants2020
Towards a multiscale crop modelling framework for climate change adaptation assessment.
Review in Nature plants, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
67 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Responses of plant biomass and yield component in rice, wheat, and maize to climatic warming: a meta-analysis.Planta · 2020Pooled it
- GE-BiFormer: bidirectional cross-attention integration of genomic and Enviromic data for genotype-by-environment prediction in maize.Briefings in bioinformatics · 2026Article
- Spatially explicit temperature optima improve climate impact assessment of global crop productivity.Nature communications · 2026Article
- Omics-driven plant breeding through phenomics-enviromics crosstalk.Nature communications · 2026Review
- Improving genomic prediction in wheat with random regression models with genotype-specific phenology-driven environmental covariates.The plant genome · 2026Article
- Leveraging Genetic Diversity for Abiotic Stress Tolerance.International journal of molecular sciences · 2026Article
- MMGS: a novel genomic prediction framework to integrate genotype, environment and their interactions for multi-environment breeding trials.Horticulture research · 2026Article
- Modeling the impact of climate variables on agriculture through the F-transform.Scientific reports · 2026Article
- Quantitative research from the perspective of mathematical and physical crop science: a review of phenotyping, mechanics, and modeling.Plant molecular biology · 2026Review
- Underestimated agricultural losses due to flooding.Science advances · 2026Article
- Back to the future 2: the implications of germplasm structure on the balance between short- and long-term genetic gain in a changing target population of environments.G3 (Bethesda, Md.) · 2026Article
- AI-driven multiscale virtual plant cell modeling: from molecular mechanisms to tissue functions.Planta · 2026Review
- Genome-wide association analysis to identify QTLs and candidate genes associated with grain yield and its related traits under low light conditions in rice (Oryza sativa L.).The plant genome · 2026Article
- A comprehensive UK crop yield dataset incorporating satellite, weather, and soil type information.Scientific data · 2026Article
- Harvesting insights: interpretable machine learning to understand environmental drivers of U.S. maize and soybean yield.Scientific reports · 2026Article
- Mechanistic modeling for agroecological adaptation: genetic potential, uncertainty, andFrontiers in bioinformatics · 2026Article
- Modulating the strigolactone pathway to optimize tomato shoot branching for vertical farming.Journal of integrative plant biology · 2026Article
- A dual-branch perception and hybrid attention integrated framework for temporal remote estimation of wheat leaf biomass.Frontiers in plant science · 2026Article
- Key Challenges in Plant Microbiome Research in the Next Decade.Microorganisms · 2025Review
- Integration of crop modeling and sensing into molecular breeding for nutritional quality and stress tolerance.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
7 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
27 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Predicting the consequences of manipulating genotype (G) and agronomic management (M) on agricultural ecosystem performances under future environmental (E) conditions remains a challenge. Crop modelling has the potential to enable society to assess the efficacy of G × M technologies to mitigate and adapt crop production systems to climate change. Despite recent achievements, dedicated research to develop and improve modelling capabilities from gene to global scales is needed to provide guidance on designing G × M adaptation strategies with full consideration of their impacts on both crop productivity and ecosystem sustainability under varying climatic conditions. Opportunities to advance the multiscale crop modelling framework include representing crop genetic traits, interfacing crop models with large-scale models, improving the representation of physiological responses to climate change and management practices, closing data gaps and harnessing multisource data to improve model predictability and enable identification of emergent relationships. A fundamental challenge in multiscale prediction is the balance between process details required to assess the intervention and predictability of the system at the scales feasible to measure the impact. An advanced multiscale crop modelling framework will enable a gene-to-farm design of resilient and sustainable crop production systems under a changing climate at regional-to-global scales.
Indexed as
Identifiers
32296143What 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.