Simulating the Yield Impacts of Organ-Level Quantitative Trait Loci Associated With Drought Response in Maize: A “Gene-to-Phenotype” Modeling Approach

No abstract is available for this paper.

• Publication year

  2009

• Venue

  Genetics

• Publication date

  2009-12-01

• Fields of study

  Agricultural and Food Sciences, Medicine, Biology, Environmental Science

• Identifiers
  DOI 10.1534/genetics.109.105429PMID 19786622PMCID PMC2787435
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Modeling Anthesis to Silking in Maize Using a Plant Biomass Framework

  2009cited by this paper
• Modeling QTL for complex traits: detection and context for plant breeding.

  2009cited by this paper
• Use of crop models to understand genotype by environment interactions for drought in real-world and simulated plant breeding trials

  2008cited by this paper
• Drought-induced changes in anthesis-silking interval are related to silk expansion: a spatio-temporal growth analysis in maize plants subjected to soil water deficit.

  2008cited by this paper
• Estimation of light interception in research environments: a joint approach using directional light sensors and 3D virtual plants applied to sunflower (Helianthus annuus) and Arabidopsis thaliana in natural and artificial conditions.

  2008cited by this paper
• A multi-trait multi-environment QTL mixed model with an application to drought and nitrogen stress trials in maize (Zea mays L.)

  2008cited by this paper
• Characterization of drought stress environments for upland rice and maize in central Brazil

  2008cited by this paper
• Short-term responses of leaf growth rate to water deficit scale up to whole-plant and crop levels: an integrated modelling approach in maize.

  2008cited by this paper
• A Mixed-Model Quantitative Trait Loci (QTL) Analysis for Multiple-Environment Trial Data Using Environmental Covariables for QTL-by-Environment Interactions, With an Example in Maize

  2007cited by this paper
• Simulations of virtual plants reveal a role for SERRATE in the response of leaf development to light in Arabidopsis thaliana.

  2007cited by this paper
• Coupling time to silking with plant growth rate in maize

  2007cited by this paper
• Leaf growth rate per unit thermal time follows QTL-dependent daily patterns in hundreds of maize lines under naturally fluctuating conditions.

  2007cited by this paper
• PHENOPSIS, an automated platform for reproducible phenotyping of plant responses to soil water deficit in Arabidopsis thaliana permitted the identification of an accession with low sensitivity to soil water deficit.

  2006cited by this paper
• A Gene‐Based Model to Simulate Soybean Development and Yield Responses to Environment

  2006cited by this paper
• Mapping QTLs and QTL × environment interaction for CIMMYT maize drought stress program using factorial regression and partial least squares methods

  2006cited by this paper
• Models for navigating biological complexity in breeding improved crop plants.

  2006cited by this paper
• Are source and sink strengths genetically linked in maize plants subjected to water deficit? A QTL study of the responses of leaf growth and of Anthesis-Silking Interval to water deficit.

  2006cited by this paper
• QTL methodology for response curves on the basis of non-linear mixed models, with an illustration to senescence in potato

  2006cited by this paper
• Genotype-by-environment interactions under water limited conditions

  2006cited by this paper
• Phylloclimate or the climate perceived by individual plant organs: what is it? How to model it? What for?

  2005cited by this paper
• Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems

  2005cited by this paper
• Gene-to-phenotype models and complex trait genetics

  2005cited by this paper
• Model analysis of flowering phenology in recombinant inbred lines of barley.

  2005cited by this paper
• QTL analysis and QTL-based prediction of flowering phenology in recombinant inbred lines of barley.

  2005cited by this paper
• Statistical models for genotype by environment data: from conventional ANOVA models to eco-physiological QTL models

  2005cited by this paper
• On Systems Thinking, Systems Biology, and the in Silico Plant

  2004cited by this paper
• Kernel Number Determination in Argentinean Maize Hybrids Released between 1965 and 1993

  2004cited by this paper
• Role of crop physiology in predicting gene-to-phenotype relationships.

  2004cited by this paper
• Grain yields with limited water.

  2004cited by this paper
• Mapping As You Go

  2004cited by this paper
• Improving drought tolerance in maize: a view from industry

  2004cited by this paper
• From genome to crop: integration through simulation modeling

  2004cited by this paper
• Genotype by environment effects and selection for drought tolerance in tropical maize. I. Two mode pattern analysis of yield

  2004cited by this paper
• Genomic regions associated with grain yield and aspects of post-flowering drought tolerance in pearl millet across stress environments and tester background

  2004cited by this paper
• Simulating the effects of dominance and epistasis on selection response in the CIMMYT wheat breeding program using QuCim

  2004cited by this paper
• Dealing with the genotype x environment interaction via a modelling approach: a comparison of QTLs of maize leaf length or width with QTLs of model parameters.

  2004cited by this paper
• An overview of APSIM, a model designed for farming systems simulation

  2003cited by this paper
• Evaluating Plant Breeding Strategies by Simulating Gene Action and Dryland Environment Effects

  2003cited by this paper
• Virtual plants: modelling as a tool for the genomics of tolerance to water deficit.

  2003cited by this paper
• Crop modeling, QTL mapping, and their complementary role in plant breeding

  2003cited by this paper
• Combining Quantitative Trait Loci Analysis and an Ecophysiological Model to Analyze the Genetic Variability of the Responses of Maize Leaf Growth to Temperature and Water Deficit1

  2003cited by this paper
• Future contributions of crop modelling—from heuristics and supporting decision making to understanding genetic regulation and aiding crop improvement

  2002cited by this paper
• Development of a generic crop model template in the cropping system model APSIM

  2002cited by this paper
• Functional mapping of quantitative trait loci underlying the character process: a theoretical framework.

  2002cited by this paper
• Seed number as a function of growth. A comparative study in soybean, sunflower, and maize

  2001cited by this paper
• Analyzing Variety by Environment Data Using Multiplicative Mixed Models and Adjustments for Spatial Field Trend

  2001cited by this paper
• Coupling estimated effects of QTLs for physiological traits to a crop growth model: predicting yield variation among recombinant inbred lines in barley

  2000cited by this paper
• Genotype by environment interactions affecting grain sorghum. II. Frequencies of different seasonal patterns of drought stress are related to location effects on hybrid yields.

  2000cited by this paper
• AFLP mapping of quantitative trait loci for yield-determining physiological characters in spring barley

  1999cited by this paper
• Selection Improves Drought Tolerance in Tropical Maize Populations: II. Direct and Correlated Responses among Secondary Traits

  1999cited by this paper
• Kernel Number Determination in Maize

  1999influential reference
• Computer simulation of a selection strategy to accommodate genotype environment interactions in a wheat recurrent selection programme

  1999cited by this paper
• Selection Improves Drought Tolerance in Tropical Maize Populations: I. Gains in Biomass, Grain Yield, and Harvest Index

  1999cited by this paper
• Modelling leaf expansion in a fluctuating environment: are changes in specific leaf area a consequence of changes in expansion rate?

  1999cited by this paper
• QU-GENE: a simulation platform for quantitative analysis of genetic models

  1998cited by this paper
• Control of Leaf Expansion Rate of Droughted Maize Plants under Fluctuating Evaporative Demand (A Superposition of Hydraulic and Chemical Messages?)

  1997cited by this paper
• Identification of quantitative trait loci under drought conditions in tropical maize. 2. Yield components and marker-assisted selection strategies

  1997cited by this paper
• Genotype by environment effects and selection for drought tolerance in tropical maize. II. Three-mode pattern analysis

  1997cited by this paper
• Accounting for natural and extraneous variation in the analysis of field experiments

  1997cited by this paper
• A strategy for yield improvement of wheat which accommodates large genotype by environment interactions

  1996cited by this paper
• Characterizing environmental challenges using models.

  1996cited by this paper
• Plant Adaptation and Crop Improvement

  1996cited by this paper
• Positive interpretation of genotype by environment interactions in relation to sustainability and biodiversity.

  1996cited by this paper
• The importance of the anthesis-silking interval in breeding for drought tolerance in tropical maize

  1996influential reference
• Quantitative analysis of the combined effects of temperature, evaporative demand and light on leaf elongation rate in well-watered field and laboratory-grown maize plants

  1996cited by this paper
• Identification of quantitative trait loci under drought conditions in tropical maize. 1. Flowering parameters and the anthesis-silking interval

  1996cited by this paper
• Causes for Silk Delay in a Lowland Tropical Maize Population

  1993cited by this paper
• Eight cycles of selection for drought tolerance in lowland tropical maize. II. Responses in reproductive behavior

  1993cited by this paper
• The origins of order

  1993cited by this paper
• THE DEVELOPMENT OF PLANT-TO-PLANT VARIABILITY IN MAIZE AT DIFFERENT PLANTING DENSITIES

  1979cited by this paper

• GS4PB: An R Shiny application to facilitate a genomic selection pipeline for plant breeding

  2025cites this paper
• Understanding rates of genetic gain in sorghum [Sorghum bicolor (L.) Moench] in the United States

  2025cites this paper
• Breeding perspectives on tackling trait genome-to-phenome (G2P) dimensionality using ensemble-based genomic prediction

  2025cites this paper
• Toward a general framework for AI-enabled prediction in crop improvement

  2025cites this paper
• APSIM’s origins and the forces shaping its first 30 years of evolution: A review and reflections

  2024cites this paper
• Crop traits and production under drought

  2024influential citation
• Impact of calibrating a low-cost capacitance-based soil moisture sensor on AquaCrop model performance.

  2024cites this paper
• Remote sensing for estimating genetic parameters of biomass accumulation and modeling stability of growth curves in alfalfa

  2024cites this paper
• Integrating biophysical crop growth models and whole genome prediction for their mutual benefit: A case study in wheat phenology.

  2023cites this paper
• Upcycling rice yield trial data using a weather-driven crop growth model

  2023cites this paper
• Climate change impacts on crop yields

  2023cites this paper
• Recent advances in artificial intelligence, mechanistic models and speed breeding offer exciting opportunities for precise and accelerated genomics-assisted breeding.

  2023cites this paper
• Current data and modeling bottlenecks for predicting crop yields in the United Kingdom

  2023cites this paper
• Dissecting durum wheat time to anthesis into physiological traits using a QTL-based model

  2023cites this paper
• Modelling Neglected and Underutilised Crops: A Systematic Review of Progress, Challenges, and Opportunities

  2022cites this paper
• Growth and yield estimation of banana through mathematical modelling: a systematic review

  2022cites this paper
• Ecophysiological Crop Modelling Combined with Genetic Analysis Is a Powerful Tool for Ideotype Design

  2022cites this paper
• Digital phenotyping and genotype-to-phenotype (G2P) models to predict complex traits in cereal crops

  2022cites this paper
• Improving crop yield potential: Underlying biological processes and future prospects

  2022cites this paper
• Linking genetic markers with an eco-physiological model to pyramid favourable alleles and design wheat ideotypes.

  2022cites this paper
• Improving drought tolerance in maize: Tools and techniques

  2022cites this paper
• Framework to guide modeling single and multiple abiotic stresses in arable crops

  2022cites this paper
• Environment Characterization in Sorghum (Sorghum bicolor L.) by Modeling Water-Deficit and Heat Patterns in the Great Plains Region, United States

  2022cites this paper
• Can we harness digital technologies and physiology to hasten genetic gain in United States maize breeding?

  2021cites this paper
• An analysis of simulated yield data for pepper shows how genotype × environment interaction in yield can be understood in terms of yield components and their QTLs

  2021cites this paper
• Genotype-specific P-spline response surfaces assist interpretation of regional wheat adaptation to climate change

  2021cites this paper
• Got All the Answers! What Were the Questions? Avoiding the Risk of “Phenomics” Slipping into a Technology Spree

  2021cites this paper
• Can We Harness “Enviromics” to Accelerate Crop Improvement by Integrating Breeding and Agronomy?

  2021cites this paper
• Perspectives on Applications of Hierarchical Gene-To-Phenotype (G2P) Maps to Capture Non-stationary Effects of Alleles in Genomic Prediction

  2021cites this paper
• Incorporating realistic trait physiology into crop growth models to support genetic improvement

  2021cites this paper
• Interdisciplinary strategies to enable data-driven plant breeding in a changing climate

  2021cites this paper
• Yield dissection models to improve yield: a case study in tomato

  2021cites this paper
• New challenges for sunflower ideotyping in changing environments and more ecological cropping systems

  2021cites this paper
• Evolution and application of digital technologies to predict crop type and crop phenology in agriculture

  2021cites this paper
• Climate change impact uncertainty assessment and adaptations for sustainable maize production using multi-crop and climate models

  2021cites this paper
• Can we harness digital technologies and physiology to hasten genetic gain in U.S. maize breeding?

  2021cites this paper
• Using Crop Modelling to Improve Chickpea Adaptation in Variable Environments

  2021cites this paper
• Genetic and Genomic Approaches for Adaptation of Grapevine to Climate Change

  2020cites this paper
• Marker-based crop model assisted ideotype design to improve avoidance of abiotic stress in bread wheat.

  2020cites this paper
• Use of transcriptomic data to inform biophysical models via Bayesian networks

  2020cites this paper
• Towards a multiscale crop modelling framework for climate change adaptation assessment

  2020cites this paper
• Spectral Vegetation Indices to Track Senescence Dynamics in Diverse Wheat Germplasm

  2020cites this paper
• Special issue in honour of Prof. Reto J. Strasser - Phenotyping with fast fluorescence sensors approximates yield component measurements in pepper (Capsicum annuum L.)

  2020cites this paper
• Simulating the effect of flowering time on maize individual leaf area in contrasting environmental scenarios

  2020cites this paper
• Modelling selection response in plant breeding programs using crop models as mechanistic gene-to-phenotype (CGM-G2P) multi-trait link functions

  2020cites this paper
• Rapid Chlorophyll a Fluorescence Light Response Curves Mechanistically Inform Photosynthesis Modeling1[OPEN]

  2020cites this paper
• Grand challenges for the 21st century: what crop models can and can't (yet) do

  2020cites this paper
• CGIAR modeling approaches for resource‐constrained scenarios: I. Accelerating crop breeding for a changing climate

  2020influential citation
• Modelling selection response in plant-breeding programs using crop models as mechanistic gene-to-phenotype (CGM-G2P) multi-trait link functions

  2020cites this paper
• A data-driven simulation platform to predict cultivars’ performances under uncertain weather conditions

  2020cites this paper
• University of São Paulo “Luiz de Queiroz” College of Agriculture Generalizations of the AMMI and GGE models to understand the interaction between genotypes and environments and between QTL and environments

  2020cites this paper
• Are crop and detailed physiological models equally ‘mechanistic’ for predicting the genetic variability of whole-plant behaviour? The nexus between mechanisms and adaptive strategies

  2020cites this paper
• Genomic Designing of Climate-Smart Fruit Crops

  2020cites this paper
• Sorghum: General Crop-Modelling Tools Guiding Principles and Use of Crop Models in Support of Crop Improvement Programs in Developing Countries

  2020cites this paper
• Linking genetic maps and simulation to optimize breeding for wheat flowering time in current and future climates

  2020cites this paper
• Toward a Better Understanding of Genotype × Environment × Management Interactions—A Global Wheat Initiative Agronomic Research Strategy

  2020cites this paper
• Environmental and trophic determinism of fruit abscission and outlook with climate change in tropical regions

  2020cites this paper
• Gene-Based Crop Models

  2019cites this paper
• Combining Crop Growth Modeling and Statistical Genetic Modeling to Evaluate Phenotyping Strategies

  2019cites this paper
• Genotype by Environment Interaction and Adaptation

  2019cites this paper
• Plant and crop simulation models: powerful tools to link physiology, genetics, and phenomics.

  2019cites this paper
• Controlling the speed and trajectory of evolution with counterdiabatic driving

  2019cites this paper
• Heliaphen, an Outdoor High-Throughput Phenotyping Platform for Genetic Studies and Crop Modeling

  2019cites this paper
• Tailoring parameter distributions to specific germplasm: impact on crop model-based ideotyping

  2019cites this paper
• Enhancing Genetic Gain through Genomic Selection: From Livestock to Plants

  2019cites this paper
• Biological reality and parsimony in crop models—why we need both in crop improvement!

  2019cites this paper
• PART OF A SPECIAL ISSUE ON BIOENERGY CROPS FOR FUTURE CLIMATES Modelling tiller growth and mortality as a sink-driven process using Ecomeristem: implications for biomass sorghum ideotyping

  2019cites this paper
• A model-based approach to analyse genetic variation in potato using standard cultivars and a segregating population. I. Canopy cover dynamics

  2019cites this paper
• Modelling strategies for assessing and increasing the effectiveness of new phenotyping techniques in plant breeding.

  2019cites this paper
• Upland rice breeding led to increased drought sensitivity in Brazil

  2019cites this paper
• Modelling tiller growth and mortality as a sink-driven process using Ecomeristem: implications for biomass sorghum ideotyping.

  2019cites this paper
• Improving process-based crop models to better capture genotype×environment×management interactions.

  2019cites this paper
• Bayesian estimation and use of high-throughput remote sensing indices for quantitative genetic analyses of leaf growth

  2018cites this paper
• Role of Modelling in International Crop Research: Overview and Some Case Studies

  2018cites this paper
• Integrating modelling and phenotyping approaches to identify and screen complex traits: transpiration efficiency in cereals

  2018cites this paper
• Mapping and Predicting Non-Linear Brassica rapa Growth Phenotypes Based on Bayesian and Frequentist Complex Trait Estimation

  2018cites this paper
• Varietal improvement options for higher rice productivity in salt affected areas using crop modelling

  2018cites this paper
• Dissecting the rootstock control of scion transpiration using model-assisted analyses in grapevine

  2018cites this paper
• Issues for cropping and agricultural science in the next 20 years

  2018cites this paper
• Characterization of Target Population of Environments for East African Highland Banana Using a Multi-criteria Decision Methods

  2018cites this paper
• The Physiological Basis of Drought Tolerance in Crop Plants: A Scenario-Dependent Probabilistic Approach.

  2018cites this paper
• Crop Models as Tools for Agroclimatology

  2018cites this paper
• Accelerating crop genetic gains with genomic selection

  2018cites this paper
• Heliaphen, an outdoor high-throughput phenotyping platform designed to integrate genetics and crop modeling

  2018cites this paper
• Drought affects abortion of reproductive organs by exacerbating developmentally driven processes via expansive growth and hydraulics

  2018cites this paper
• An overview of statistical methods to detect and understand genotype-by-environment interaction and QTL-by-environment interaction

  2018influential citation
• Improvement of Drought Tolerance in Rice (Oryza sativa L.): Genetics, Genomic Tools, and the WRKY Gene Family

  2018cites this paper
• Decadal analysis of impact of future climate on wheat production in dry Mediterranean environment: A case of Jordan.

  2018cites this paper
• Multi-scale modelling to synergise Plant Systems Biology and Crop Science

  2017influential citation
• Trait-based model development to support breeding programs. A case study for salt tolerance and rice

  2017cites this paper
• Analyse et modélisation de la variabilité phénotypique du sorgho biomasse pour l’exploration d’idéotypes dans un contexte de diversification des usages

  2017cites this paper
• Leveraging biological insight and environmental variation to improve phenotypic prediction: Integrating crop growth models (CGM) with whole genome prediction (WGP)

  2017cites this paper
• Nitrogen nutrition index predicted by a crop model improves the genomic prediction of grain number for a bread wheat core collection

  2017cites this paper
• QTL Modelling: An Adaptation Option in Spring Wheat for Drought Stress

  2017cites this paper
• Next generation crop models: A modular approach to model early vegetative and reproductive development of the common bean (Phaseolus vulgaris L)

  2017cites this paper
• Problems with Estimating Anthesis Phenology Parameters in Zea mays: Consequences for Combining Ecophysiological Models with Genetics

  2017cites this paper
• Plasticity of Sorghum Stem Biomass Accumulation in Response to Water Deficit: A Multiscale Analysis from Internode Tissue to Plant Level

  2017cites this paper
• Characterisation of chickpea cropping systems in Australia for major abiotic production constraints

  2017cites this paper
• Crop model parameter estimation and sensitivity analysis for large scale data using supercomputers

  2017cites this paper
• Predictable 'meta-mechanisms' emerge from feedbacks between transpiration and plant growth and cannot be simply deduced from short-term mechanisms.

  2017cites this paper