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Adapting APSIM to model the physiology and genetics of complex adaptive traits in field crops
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Outgoing claims: the papers this work cites, builds on, or argues with.
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An Integrated Systems Approach to Crop Improvement
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Quantitative trait loci for growing degree days to flowering and photoperiod response in Sunflower (Helianthus annuus L.)
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Use of crop models to understand genotype by environment interactions for drought in real-world and simulated plant breeding trials
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Crop model based QTL analysis across environments and QTL based estimation of time to floral induction and flowering in Brassica oleracea
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Genotypic variation in seedling root architectural traits and implications for drought adaptation in wheat (Triticum aestivum L.)
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CERES-Maize: A simulation model of maize growth and development
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Simulation of water use, nitrogen nutrition and growth of a spring wheat crop
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Water and nitrogen limitations in soybean grain production I. Model development
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Effect of nitrogen supply on the comparative productivity of maize and sorghum in a semi-arid tropical environment I. Leaf growth and leaf nitrogen
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Effect of nitrogen supply on the comparative productivity of maize and sorghum in a semi-arid tropical environment II. Radiation interception and biomass accumulation
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Development and evaluation of a sorghum model based on CERES-Maize in a semi-arid tropical environment
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Phenology and leaf-area development in a tropical grain sorghum
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A model to assess nitrogen limitations on the growth and yield of spring wheat
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Modelling genotypic and environmental control of leaf area dynamics in grain sorghum. I. Whole plant level
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Modelling genotypic and environmental control of leaf area dynamics in grain sorghum. II. Individual leaf level
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Water extraction by grain sorghum in a sub-humid environment. I. Analysis of the water extraction pattern
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Assessing climatic risk to sorghum production in water-limited subtropical environments I. Development and testing of a simulation model
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Transpiration-use efficiency of barley
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Modelling protein content and composition in relation to crop nitrogen dynamics for wheat
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Determination of grain number in sorghum
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Modelling environmental effects on phenology and canopy development of diverse sorghum genotypes
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Ecophysiological traits in maize hybrids and their parental inbred lines: Phenotyping of responses to contrasting nitrogen supply levels
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Functional dynamics of the nitrogen balance of sorghum: I. N demand of vegetative plant parts
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Functional dynamics of the nitrogen balance of sorghum. II. Grain filling period
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Detection and use of QTL for complex traits in multiple environments
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Role of crop physiology in predicting gene-to-phenotype relationships
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Root system architecture: opportunities and constraints for genetic improvement of crops
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From dwarves to giants? Plant height manipulation for biomass yield
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Radiation Use Efficiency
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Infusing the use of seasonal climate forecasting into crop management practice in North East Australia using discussion support software
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APSIM's water and nitrogen modules and simulation of the dynamics of water and nitrogen in fallow systems
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Simulating growth, development, and yield of tillering pearl millet
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Reproductive partitioning and seed set efficiency in soybean, sunflower and maize
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Predicting plant leaf area production:
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Floret development in near isogenic wheat lines differing in plant height
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Future contributions of crop modelling—from heuristics and supporting decision making to understanding genetic regulation and aiding crop improvement
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Development of a generic crop model template in the cropping system model APSIM
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An overview of APSIM, a model designed for farming systems simulation
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Virtual plants: modelling as a tool for the genomics of tolerance to water deficit
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Radiation interception and radiation use efficiency of near-isogenic wheat lines with different height
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Gene-to-phenotype models and complex trait genetics
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Flowering time control: gene network modelling and the link to quantitative genetics
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What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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inferred← citeshttps://doi.org/10.1007/s10705-025-10403-xopenalex-snapshot
Informing APSIM using 15N recovery data to establish fertiliser N budgets in grain systems
inferred← citeshttps://doi.org/10.1007/s11104-025-07459-7openalex-snapshot
Faba bean genetics and crop growth models – progress to date and opportunities for integration
inferred← citeshttps://doi.org/10.1007/s11356-020-08846-6openalex-snapshot
Assessing the climate change impacts and adaptation strategies for rice production in Punjab, Pakistan
inferred← citeshttps://doi.org/10.1007/s11368-020-02794-xopenalex-snapshot
Potential N mineralization and availability to maize in black soils in response to soil fertility improvement in Northeast China
inferred← citeshttps://doi.org/10.1007/s11540-020-09456-yopenalex-snapshot
Parameterization and Evaluation of a Simple Simulation Model (SSM-iCrop2) for Potato (Solanum tuberosum L.) Growth and Yield in Iran
inferred← citeshttps://doi.org/10.1007/s11540-024-09713-4openalex-snapshot
Response of Potato Growth and Yield to Drought Scenarios Based on APSIM-Potato in the Single-Cropping Region in Northern China
inferred← citeshttps://doi.org/10.1007/s11707-015-0534-3openalex-snapshot
Comparison of winter wheat yield sensitivity to climate variables under irrigated and rain-fed conditions
inferred← citeshttps://doi.org/10.1007/s11707-016-0584-1openalex-snapshot
Impact of thermal time shift on wheat phenology and yield under warming climate in the Huang-Huai-Hai Plain, China
inferred← citeshttps://doi.org/10.1007/s11738-015-1844-5openalex-snapshot
Physiological requirements for wheat ideotypes in response to drought threat
inferred← citeshttps://doi.org/10.1007/s12571-016-0632-4openalex-snapshot
Comparison of the modeled potential yield versus the actual yield of maize in Northeast China and the implications for national food security
inferred← citeshttps://doi.org/10.1007/s13593-013-0170-9openalex-snapshot
Agronomic model uses to predict cultivar performance in various environments and cropping systems. A review
inferred← citeshttps://doi.org/10.1007/s13593-014-0272-zopenalex-snapshot
Multiple cropping systems as drivers for providing multiple ecosystem services: from concepts to design
inferred← citeshttps://doi.org/10.1007/s13593-023-00869-wopenalex-snapshot
Modeling adaptation of sorghum in Ethiopia with APSIM—opportunities with G×E×M
inferred← citeshttps://doi.org/10.1007/s13593-023-00909-5openalex-snapshot
APSIM-based modeling approach to understand sorghum production environments in Mali
inferred← citeshttps://doi.org/10.1007/s13593-024-00959-3openalex-snapshot
APSIM’s origins and the forces shaping its first 30 years of evolution: A review and reflections
inferred← citeshttps://doi.org/10.1007/s40484-017-0110-9openalex-snapshot
ePlant for quantitative and predictive plant science research in the big data era —Lay the foundation for the future model guided crop breeding, engineering and agronomy
inferred← citeshttps://doi.org/10.1007/s40710-018-0300-0openalex-snapshot
Sweet Sorghum Canopy Development in Relation to Radiation and Water Use
inferred← citeshttps://doi.org/10.1007/s42106-020-00116-2openalex-snapshot
Full Parameterisation Matters for the Best Performance of Crop Models: Inter-comparison of a Simple and a Detailed Maize Model
inferred← citeshttps://doi.org/10.1007/s42106-025-00348-0openalex-snapshot
Design and Evaluation of Fertilization Rule-Based Strategy with APSIM-Wheat Model: For a Climate Responsive and Risk Proofing Fertilization in Morocco
inferred← citeshttps://doi.org/10.1016/b978-0-12-417104-6.00014-5openalex-snapshot
Model-assisted phenotyping and ideotype design
inferred← citeshttps://doi.org/10.1016/b978-0-12-417104-6.00015-7openalex-snapshot
Crop phenotyping for physiological breeding in grain crops: A case study for maize
inferred← citeshttps://doi.org/10.1016/b978-0-12-801926-9.00007-8openalex-snapshot
Breeding Methods for Winter Sorghum Improvement
inferred← citeshttps://doi.org/10.1016/bs.agron.2025.07.005openalex-snapshot
Integrating genetic and ecophysiology frameworks for crop adaptation
inferred← citeshttps://doi.org/10.1016/j.agrformet.2013.10.012openalex-snapshot
Quantifying potential benefits of drought and heat tolerance in rainy season sorghum for adapting to climate change
inferred← citeshttps://doi.org/10.1016/j.agrformet.2016.07.004openalex-snapshot
Yield trends under varying environmental conditions for sorghum and wheat across Australia
inferred← citeshttps://doi.org/10.1016/j.agrformet.2016.07.021openalex-snapshot
Assessing climate adaptation options and uncertainties for cereal systems in West Africa
inferred← citeshttps://doi.org/10.1016/j.agrformet.2016.10.004openalex-snapshot
How variable are non-linear developmental responses to temperature in two perennial forage species?
inferred← citeshttps://doi.org/10.1016/j.agrformet.2017.08.023openalex-snapshot
Characterising production environments for maize in eastern and southern Africa using the APSIM Model
inferred← citeshttps://doi.org/10.1016/j.agrformet.2017.11.012openalex-snapshot
Improving maize growth processes in the community land model: Implementation and evaluation
inferred← citeshttps://doi.org/10.1016/j.agrformet.2023.109821openalex-snapshot
Dual ensemble approach to predict rice heading date by integrating multiple rice phenology models and machine learning-based genetic parameter regression models
inferred← citeshttps://doi.org/10.1016/j.agsy.2013.06.002openalex-snapshot
Simulation analysis of factors affecting sorghum yield at selected sites in eastern and southern Africa, with emphasis on increasing temperatures
inferred← citeshttps://doi.org/10.1016/j.agsy.2016.10.010openalex-snapshot
Next generation crop models: A modular approach to model early vegetative and reproductive development of the common bean (Phaseolus vulgaris L)
inferred← citeshttps://doi.org/10.1016/j.agsy.2016.12.017openalex-snapshot
Yield comparison of simulated rainfed wheat and barley across Middle-East
inferred← citeshttps://doi.org/10.1016/j.agsy.2021.103278openalex-snapshot
Performance of a wheat yield prediction model and factors influencing the performance: A review and meta-analysis
inferred← citeshttps://doi.org/10.1016/j.agsy.2022.103459openalex-snapshot
Calibrating APSIM for forage sorghum using remote sensing and field data under sub-optimal growth conditions
inferred← citeshttps://doi.org/10.1016/j.agsy.2024.104087openalex-snapshot
FACE-ing climate change: Propagation of risks and opportunities for cropping systems in mid-high-latitude regions: A case study between U.S. and China corn belts
inferred← citeshttps://doi.org/10.1016/j.agsy.2024.104213openalex-snapshot
Review of APSIM's soil nitrogen modelling capability for agricultural systems analyses
inferred← citeshttps://doi.org/10.1016/j.agsy.2025.104430openalex-snapshot
A novel approach to accelerate ideotyping using model-aided envirotyping
inferred← citeshttps://doi.org/10.1016/j.agsy.2025.104470openalex-snapshot
Residue return and nitrogen application optimization can not balance crop yield increase and reducing emission in semi-arid region
inferred← citeshttps://doi.org/10.1016/j.agsy.2026.104775openalex-snapshot
Integrated design of climate-resilient cotton cultivars and sowing strategies in arid Xinjiang using a crop model
inferred← citeshttps://doi.org/10.1016/j.agsy.2026.104875openalex-snapshot
Evaluating the yield gap of cropping systems: A comparison of alternative approaches across regions
inferred← citeshttps://doi.org/10.1016/j.agwat.2016.08.021openalex-snapshot
Simulating yield and water use of a sorghum–cowpea intercrop using APSIM
inferred← citeshttps://doi.org/10.1016/j.agwat.2018.03.010openalex-snapshot
Grain sorghum production functions under different irrigation capacities
inferred← citeshttps://doi.org/10.1016/j.agwat.2018.04.016openalex-snapshot
Field measurements of bare soil evaporation and crop transpiration, and transpiration efficiency, for rainfed grain crops in Australia – A review
inferred← citeshttps://doi.org/10.1016/j.agwat.2020.106424openalex-snapshot
Exploring the effect of tillers on the water economy, plant growth and kernel set of low-density maize crops
inferred← citeshttps://doi.org/10.1016/j.atech.2026.101936openalex-snapshot
Machine learning approaches for wheat yield prediction integrating biophysical modeling and remote sensing: Effects of sample size, dimensionality, and transferability
inferred← citeshttps://doi.org/10.1016/j.compag.2023.107688openalex-snapshot
Multi-view triangulation without correspondences
inferred← citeshttps://doi.org/10.1016/j.compag.2025.110383openalex-snapshot
In-silico optimization of peanut production in India through envirotyping and ideotyping
inferred← citeshttps://doi.org/10.1016/j.compag.2026.111440openalex-snapshot
Modifying water absorption process to enhance model performance on biomass accumulation under soil water and salt stresses
inferred← citeshttps://doi.org/10.1016/j.compag.2026.111725openalex-snapshot
Crop models as decision support tools in digital agriculture: The APSIM-based RotationARM tool in Australia
inferred← citeshttps://doi.org/10.1016/j.cpb.2020.100149openalex-snapshot
An integrated research framework combining genomics, systems biology, physiology, modelling and breeding for legume improvement in response to elevated CO2 under climate change scenario
inferred← citeshttps://doi.org/10.1016/j.eja.2011.10.003openalex-snapshot
Analysis of improvements in nitrogen use efficiency associated with 75 years of spring barley breeding
inferred← citeshttps://doi.org/10.1016/j.eja.2013.09.020openalex-snapshot
Contributions of cultivars, management and climate change to winter wheat yield in the North China Plain in the past three decades
inferred← citeshttps://doi.org/10.1016/j.eja.2016.08.010openalex-snapshot
A comparison of cardinal temperatures estimated by linear and nonlinear models for germination and bulb growth of forage brassicas
inferred← citeshttps://doi.org/10.1016/j.eja.2017.12.007openalex-snapshot
Modelling the nitrogen dynamics of maize crops – Enhancing the APSIM maize model
inferred← citeshttps://doi.org/10.1016/j.eja.2018.01.007openalex-snapshot
Leveraging biological insight and environmental variation to improve phenotypic prediction: Integrating crop growth models (CGM) with whole genome prediction (WGP)
inferred← citeshttps://doi.org/10.1016/j.eja.2018.02.002openalex-snapshot
Crop model improvement in APSIM: Using wheat as a case study
inferred← citeshttps://doi.org/10.1016/j.eja.2018.02.005openalex-snapshot
Bringing genetics and biochemistry to crop modelling, and vice versa
inferred← citeshttps://doi.org/10.1016/j.eja.2018.04.008openalex-snapshot
Key variables for simulating leaf area and N status: Biomass based relations versus phenology driven approaches
inferred← citeshttps://doi.org/10.1016/j.eja.2018.10.009openalex-snapshot
Recent advances in crop modelling to support sustainable agricultural production and food security under global change
inferred← citeshttps://doi.org/10.1016/j.eja.2022.126487openalex-snapshot
Performance of the SSM-iCrop model for predicting growth and nitrogen dynamics in winter wheat
inferred← citeshttps://doi.org/10.1016/j.eja.2022.126629openalex-snapshot
Combined Use of Apsim and Logistic Regression Models to Predict the Quality Characteristics of Maize Grain
inferred← citeshttps://doi.org/10.1016/j.eja.2024.127391openalex-snapshot
Integrating genomics with crop modelling to predict maize yield and component traits: Towards the next generation of crop models
inferred← citeshttps://doi.org/10.1016/j.envexpbot.2025.106113openalex-snapshot
Plant plasticity in the face of climate change – CO2 offsetting effects to warming and water deficit in wheat. A review
inferred← citeshttps://doi.org/10.1016/j.envexpbot.2025.106301openalex-snapshot
Beyond light quantity: Intermittent shading affects growth and yield more than constant shading in rice cultivars
inferred← citeshttps://doi.org/10.1016/j.envsoft.2014.07.009openalex-snapshot
APSIM – Evolution towards a new generation of agricultural systems simulation
inferred← citeshttps://doi.org/10.1016/j.envsoft.2014.12.013openalex-snapshot
Agricultural production systems modelling and software: Current status and future prospects
inferred← citeshttps://doi.org/10.1016/j.envsoft.2018.02.002openalex-snapshot
APSIM Next Generation: Overcoming challenges in modernising a farming systems model
inferred← citeshttps://doi.org/10.1016/j.fcr.2011.06.013openalex-snapshot
Role of early vigor in adaptation of rice to water-saving aerobic culture: Effects of nitrogen utilization and leaf growth
inferred← citeshttps://doi.org/10.1016/j.fcr.2011.06.021openalex-snapshot
A simple model for chickpea development, growth and yield
inferred← citeshttps://doi.org/10.1016/j.fcr.2011.07.005openalex-snapshot
Decrease in sorghum grain yield due to the dw3 dwarfing gene is caused by reduction in shoot biomass
inferred← citeshttps://doi.org/10.1016/j.fcr.2012.10.020openalex-snapshot
Drought stress characterization of post-rainy season (rabi) sorghum in India
inferred← citeshttps://doi.org/10.1016/j.fcr.2013.01.014openalex-snapshot
Optimizing triticale sowing densities across the Mediterranean Basin
inferred← citeshttps://doi.org/10.1016/j.fcr.2013.05.002openalex-snapshot
Comparing solar radiation interception and use efficiency for the energy crops giant reed (Arundo donax L.) and sweet sorghum (Sorghum bicolor L. Moench)
inferred← citeshttps://doi.org/10.1016/j.fcr.2013.05.005openalex-snapshot
Sorghum dwarfing genes can affect radiation capture and radiation use efficiency
inferred← citeshttps://doi.org/10.1016/j.fcr.2013.05.006openalex-snapshot
Simulation of genotype performances across a larger number of environments for rice breeding using ORYZA2000
inferred← citeshttps://doi.org/10.1016/j.fcr.2013.05.023openalex-snapshot
Screening field pea for adaptation to water and heat stress: Associations between yield, crop growth rate and seed abortion
inferred← citeshttps://doi.org/10.1016/j.fcr.2013.12.016openalex-snapshot
Developing phosphorus-efficient crop varieties—An interdisciplinary research framework
inferred← citeshttps://doi.org/10.1016/j.fcr.2014.06.027openalex-snapshot
Reprint of “Developing phosphorus-efficient crop varieties—An interdisciplinary research framework”
inferred← citeshttps://doi.org/10.1016/j.fcr.2014.10.019openalex-snapshot
A comparison of four wheat models with respect to robustness and transparency: Simulation in a temperate, sub-humid environment
inferred← citeshttps://doi.org/10.1016/j.fcr.2014.11.003openalex-snapshot
Sorghum genotypes differ in high temperature responses for seed set
inferred← citeshttps://doi.org/10.1016/j.fcr.2015.07.013openalex-snapshot
Physiological basis of yield variation in response to row spacing and plant density of mungbean grown in subtropical environments
inferred← citeshttps://doi.org/10.1016/j.fcr.2016.02.012openalex-snapshot
Multi-scale modelling to synergise Plant Systems Biology and Crop Science
inferred← citeshttps://doi.org/10.1016/j.fcr.2016.07.025openalex-snapshot
Genetic improvement in density and nitrogen stress tolerance traits over 38 years of commercial maize hybrid release
inferred← citeshttps://doi.org/10.1016/j.fcr.2016.08.006openalex-snapshot
Combining genome-wide prediction and a phenology model to simulate heading date in spring barley
inferred← citeshttps://doi.org/10.1016/j.fcr.2016.12.025openalex-snapshot
Modelling maize yield response to plant density and water and nitrogen supply in a semi-arid region
inferred← citeshttps://doi.org/10.1016/j.fcr.2017.06.012openalex-snapshot
Quantifying high temperature risks and their potential effects on sorghum production in Australia
inferred← citeshttps://doi.org/10.1016/j.fcr.2017.12.012openalex-snapshot
Application of the APSIM model to exploit G × E × M interactions for maize improvement in Ethiopia
inferred← citeshttps://doi.org/10.1016/j.fcr.2018.10.007openalex-snapshot
Stay-green associates with low water soluble carbohydrates at flowering in oat
inferred← citeshttps://doi.org/10.1016/j.fcr.2018.10.010openalex-snapshot
Understanding the diversity in yield potential and stability among commercial sorghum hybrids can inform crop designs
inferred← citeshttps://doi.org/10.1016/j.fcr.2019.06.009openalex-snapshot
Sorghum drought and heat stress patterns across the Argentinean temperate central region
inferred← citeshttps://doi.org/10.1016/j.fcr.2019.107563openalex-snapshot
Dissection of mechanisms for high yield in two elite rice cultivars
inferred← citeshttps://doi.org/10.1016/j.fcr.2019.107581openalex-snapshot
A model-based approach to analyse genetic variation in potato using standard cultivars and a segregating population. I. Canopy cover dynamics
inferred← citeshttps://doi.org/10.1016/j.fcr.2019.107685openalex-snapshot
Improving sorghum productivity under changing climatic conditions: A modelling approach
inferred← citeshttps://doi.org/10.1016/j.fcr.2019.107697openalex-snapshot
Using a novel PLS approach for envirotyping of barley phenology and adaptation
inferred← citeshttps://doi.org/10.1016/j.fcr.2021.108254openalex-snapshot
On the needs for combining physiological principles and mathematics to improve crop models
inferred← citeshttps://doi.org/10.1016/j.fcr.2021.108422openalex-snapshot
An APSIM-powered framework for post-rainy sorghum-system design in India
inferred← citeshttps://doi.org/10.1016/j.fcr.2023.108922openalex-snapshot
Sorghum producer yield contest: A synthesis-analysis of major management and environmental drivers
inferred← citeshttps://doi.org/10.1016/j.fcr.2023.108955openalex-snapshot
APSIM next generation mungbean model: A tool for advancing mungbean production
inferred← citeshttps://doi.org/10.1016/j.fcr.2025.109858openalex-snapshot
Integrating yield gap analysis to capture genotype by environment by management interactions for Australian broadacre sorghum cropping systems
inferred← citeshttps://doi.org/10.1016/j.fcr.2026.110387openalex-snapshot
Four decades of crop improvement decreased specific leaf nitrogen and reshaped canopy trait profiles in maize
inferred← citeshttps://doi.org/10.1016/j.indcrop.2017.02.026openalex-snapshot
A model for evaluating production and environmental performance of kenaf in rotation with conventional row crops
inferred← citeshttps://doi.org/10.1016/j.jclepro.2023.137367openalex-snapshot
Quantitative analysis of abandonment and grain production loss under armed conflict in Ukraine
inferred← citeshttps://doi.org/10.1016/j.jclepro.2026.148007openalex-snapshot
Site-specific design of sustainable cropping systems: Linking agronomic structure to long-term performance
inferred← citeshttps://doi.org/10.1016/j.jcs.2014.01.006openalex-snapshot
Adapting wheat in Europe for climate change
inferred← citeshttps://doi.org/10.1016/j.jia.2023.07.034openalex-snapshot
Combining field data and modeling to better understand maize growth response to phosphorus (P) fertilizer application and soil P dynamics in calcareous soils
inferred← citeshttps://doi.org/10.1016/j.jia.2026.03.040openalex-snapshot
System-level optimization of cultivar, sowing, and water–nitrogen management enhances cotton yield and resource efficiency under future warming in Xinjiang, China
inferred← citeshttps://doi.org/10.1016/j.pbi.2011.02.002openalex-snapshot
Water deficit and growth. Co-ordinating processes without an orchestrator?
inferred← citeshttps://doi.org/10.1016/j.pce.2022.103199openalex-snapshot
Review of current models and approaches used for maize crop yield forecasting in sub-Saharan Africa and their potential use in early warning systems
inferred← citeshttps://doi.org/10.1016/j.plantsci.2016.05.018openalex-snapshot
Gravimetric phenotyping of whole plant transpiration responses to atmospheric vapour pressure deficit identifies genotypic variation in water use efficiency
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2017.06.002openalex-snapshot
An assessment of yield gains under climate change due to genetic modification of pearl millet
inferred← citeshttps://doi.org/10.1016/j.still.2024.106433openalex-snapshot
Synergistic effects of bio-organic fertilizer and different soil amendments on salt reduction, soil fertility, and yield enhancement in salt-affected coastal soils
inferred← citeshttps://doi.org/10.1016/j.stress.2024.100549openalex-snapshot
Sorghum landraces perform better than a commonly used cultivar under terminal drought, especially on sandy soil
inferred← citeshttps://doi.org/10.1016/j.tplants.2017.02.003openalex-snapshot
Contribution of Crop Models to Adaptation in Wheat
inferred← citeshttps://doi.org/10.1016/j.tplants.2021.03.011openalex-snapshot
Addressing Research Bottlenecks to Crop Productivity
inferred← citeshttps://doi.org/10.1016/j.tplants.2025.09.001openalex-snapshot
Reassessing data management in increasingly complex phenotypic datasets
inferred← citeshttps://doi.org/10.1016/j.tplants.2026.06.005openalex-snapshot
Digital twins for plant and crop improvement
inferred← citeshttps://doi.org/10.1017/s1751731113000748openalex-snapshot
Whole-farm models to quantify greenhouse gas emissions and their potential use for linking climate change mitigation and adaptation in temperate grassland ruminant-based farming systems
inferred← citeshttps://doi.org/10.1038/nclimate1832openalex-snapshot
The critical role of extreme heat for maize production in the United States
inferred← citeshttps://doi.org/10.1038/s41467-022-30872-wopenalex-snapshot
Physiological adaptive traits are a potential allele reservoir for maize genetic progress under challenging conditions
inferred← citeshttps://doi.org/10.1038/s41467-023-42298-zopenalex-snapshot
Robotized indoor phenotyping allows genomic prediction of adaptive traits in the field
inferred← citeshttps://doi.org/10.1038/s41477-019-0398-8openalex-snapshot
Quantifying impacts of enhancing photosynthesis on crop yield
inferred← citeshttps://doi.org/10.1038/s41477-020-0625-3openalex-snapshot
Towards a multiscale crop modelling framework for climate change adaptation assessment
inferred← citeshttps://doi.org/10.1038/s41588-019-0414-yopenalex-snapshot
Genomic prediction of maize yield across European environmental conditions
inferred← citeshttps://doi.org/10.1038/s41588-026-02744-2openalex-snapshot
Crop legacies as genetic targets for sustainable farming systems
inferred← citeshttps://doi.org/10.1038/s41598-018-20628-2openalex-snapshot
Predicting optimum crop designs using crop models and seasonal climate forecasts
inferred← citeshttps://doi.org/10.1038/s41598-021-02668-3openalex-snapshot
Wheat (Triticum aestivum) adaptability evaluation in a semi-arid region of Central Morocco using APSIM model
inferred← citeshttps://doi.org/10.1038/s43016-020-00187-4openalex-snapshot
Educated big data to study sensitivity to drought
inferred← citeshttps://doi.org/10.1071/cp11250openalex-snapshot
A modelling analysis to identify plant traits for enhanced water-use efficiency of pasture
inferred← citeshttps://doi.org/10.1071/cp13013openalex-snapshot
Adding genotypic differences in reproductive partitioning and grain set efficiency for estimating sorghum grain number
inferred← citeshttps://doi.org/10.1071/cp13074openalex-snapshot
Process-based modelling to understand which ryegrass characteristics can increase production and decrease leaching in grazed grass–legume pastures
inferred← citeshttps://doi.org/10.1071/cp13452openalex-snapshot
Simulation of water-limited growth of the forage shrub saltbush (Atriplex nummularia Lindl.) in a low-rainfall environment of southern Australia
inferred← citeshttps://doi.org/10.1071/cp14088openalex-snapshot
Crop design for specific adaptation in variable dryland production environments
inferred← citeshttps://doi.org/10.1071/cp14361openalex-snapshot
Assessing the place and role of crop simulation modelling in Australia
inferred← citeshttps://doi.org/10.1071/cp16027openalex-snapshot
Interactions between water and nitrogen in Australian cropping systems: physiological, agronomic, economic, breeding and modelling perspectives
inferred← citeshttps://doi.org/10.1071/cp21209openalex-snapshot
Canopy and reproductive development in mungbean (Vigna radiata)
inferred← citeshttps://doi.org/10.1071/fp13149openalex-snapshot
Water: the most important ‘molecular’ component of water stress tolerance research
inferred← citeshttps://doi.org/10.1071/fp13355openalex-snapshot
Modelling the effect of plant water use traits on yield and stay-green expression in sorghum
inferred← citeshttps://doi.org/10.1071/fp15308openalex-snapshot
Hybrid variation for root system efficiency in maize: potential links to drought adaptation
inferred← citeshttps://doi.org/10.1071/fp16154openalex-snapshot
Genotypic variation in soil water use and root distribution and their implications for drought tolerance in chickpea
inferred← citeshttps://doi.org/10.1071/fp17225openalex-snapshot
Simulating daily field crop canopy photosynthesis: an integrated software package
inferred← citeshttps://doi.org/10.1071/fp18177openalex-snapshot
Genotypic variation in whole-plant transpiration efficiency in sorghum only partly aligns with variation in stomatal conductance
inferred← citeshttps://doi.org/10.1071/fp23010openalex-snapshot
Modelling plants across scales of biological organisation for guiding crop improvement
inferred← citeshttps://doi.org/10.1071/fp26008openalex-snapshot
Transpiration response to vapour pressure deficit, transpiration efficiency (TE), and their putative link: retrospectives and prospectives on new opportunities to increase TE
inferred← citeshttps://doi.org/10.1073/pnas.1718326115openalex-snapshot
Genomic and environmental determinants and their interplay underlying phenotypic plasticity
inferred← citeshttps://doi.org/10.1073/pnas.1720716115openalex-snapshot
Maize yields over Europe may increase in spite of climate change, with an appropriate use of the genetic variability of flowering time
inferred← citeshttps://doi.org/10.1080/09064710.2017.1418018openalex-snapshot
The impact of drought on sorghum production, and farmer's varietal and trait preferences, in the north eastern Ethiopia: implications for breeding
inferred← citeshttps://doi.org/10.1088/1748-9326/9/10/104006openalex-snapshot
Robust features of future climate change impacts on sorghum yields in West Africa
inferred← citeshttps://doi.org/10.1088/1748-9326/ace7e3openalex-snapshot
Short-term extreme heat at flowering amplifies the impacts of climate change on maize production
inferred← citeshttps://doi.org/10.1093/aob/mcad011openalex-snapshot
Differences in temperature responses among phenological processes in diverse Ethiopian sorghum germplasm can affect their specific adaptation to environmental conditions
inferred← citeshttps://doi.org/10.1093/aob/mcaf328openalex-snapshot
A generic model for individual leaf size in maize, sorghum and pearl millet
inferred← citeshttps://doi.org/10.1093/aob/mcq264openalex-snapshot
A functional–structural model of rice linking quantitative genetic information with morphological development and physiological processes
inferred← citeshttps://doi.org/10.1093/aob/mcr119openalex-snapshot
NEMA, a functional–structural model of nitrogen economy within wheat culms after flowering. I. Model description
inferred← citeshttps://doi.org/10.1093/aob/mcu127openalex-snapshot
Linking ecophysiological modelling with quantitative genetics to support marker-assisted crop design for improved yields of rice (Oryza sativa) under drought stress
inferred← citeshttps://doi.org/10.1093/aob/mcz038openalex-snapshot
Modelling tiller growth and mortality as a sink-driven process using Ecomeristem: implications for biomass sorghum ideotyping
inferred← citeshttps://doi.org/10.1093/insilicoplants/diaa011openalex-snapshot
Are crop and detailed physiological models equally ‘mechanistic’ for predicting the genetic variability of whole-plant behaviour? The nexus between mechanisms and adaptive strategies
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