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Do maize models capture the impacts of heat and drought stresses on yield? Using algorithm ensembles to identify successful approaches.
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- Global Change Biology, 2016, v. 22, n. 9, p. 3112, doi. 10.1111/gcb.13376
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- Article
Velocity of temperature and flowering time in wheat - assisting breeders to keep pace with climate change.
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- Global Change Biology, 2016, v. 22, n. 2, p. 921, doi. 10.1111/gcb.13118
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- Article
The shifting influence of drought and heat stress for crops in northeast Australia.
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- Global Change Biology, 2015, v. 21, n. 11, p. 4115, doi. 10.1111/gcb.13022
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- Article
Breeding for the future: what are the potential impacts of future frost and heat events on sowing and flowering time requirements for Australian bread wheat ( Triticum aestivium) varieties?
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- Global Change Biology, 2012, v. 18, n. 9, p. 2899, doi. 10.1111/j.1365-2486.2012.02724.x
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- Article
Using a gene-based phenology model to identify optimal flowering periods of spring wheat in irrigated mega-environments.
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- Journal of Experimental Botany, 2021, v. 72, n. 20, p. 7203, doi. 10.1093/jxb/erab326
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- Article
Improving process-based crop models to better capture genotype×environment×management interactions.
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- Journal of Experimental Botany, 2019, v. 70, n. 9, p. 2389, doi. 10.1093/jxb/erz092
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- Article
Modelling impact of early vigour on wheat yield in dryland regions.
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- Journal of Experimental Botany, 2019, v. 70, n. 9, p. 2535, doi. 10.1093/jxb/erz069
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- Article
Projected impact of future climate on water-stress patterns across the Australian wheatbelt.
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- Journal of Experimental Botany, 2017, v. 68, n. 21/22, p. 5907, doi. 10.1093/jxb/erx368
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- Article
Frost trends and their estimated impact on yield in the Australian wheatbelt.
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- Journal of Experimental Botany, 2015, v. 66, n. 12, p. 3611, doi. 10.1093/jxb/erv163
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- Article
Quantification of the effects of VRN1 and Ppd-D1 to predict spring wheat (Triticum aestivum) heading time across diverse environments.
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- Journal of Experimental Botany, 2013, v. 64, n. 12, p. 3747, doi. 10.1093/jxb/ert209
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- Article
Vernalisation and photoperiod responses of diverse wheat genotypes.
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- Crop & Pasture Science, 2023, v. 74, n. 5, p. 405, doi. 10.1071/CP22213
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- Article
Recent changes in southern Australian frost occurrence: implications for wheat production risk.
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- Crop & Pasture Science, 2016, v. 67, n. 8, p. 801, doi. 10.1071/CP16056
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- Article
Crop design for specific adaptation in variable dryland production environments.
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- Crop & Pasture Science, 2014, v. 65, n. 7, p. 614, doi. 10.1071/CP14088
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- Article
The Development of Spatial Positions Between Mother and Calf of Yangtze Finless Porpoises (Neophocaena asiaeorientalis asiaeorientalis) Maintained in Captive and Seminatural Environments.
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- Aquatic Mammals, 2012, v. 38, n. 2, p. 127, doi. 10.1578/AM.38.2.2012.127
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- Article
From QTLs to Adaptation Landscapes: Using Genotype-To-Phenotype Models to Characterize G×E Over Time.
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- Frontiers in Plant Science, 2019, v. 10, p. 1, doi. 10.3389/fpls.2019.01540
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- Article
Combining Crop Growth Modeling and Statistical Genetic Modeling to Evaluate Phenotyping Strategies.
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- Frontiers in Plant Science, 2019, v. 10, p. 1, doi. 10.3389/fpls.2019.01491
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- Article
Integrating a crop growth model and radiative transfer model to improve estimation of crop traits based on deep learning.
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- Journal of Experimental Botany, 2022, v. 73, n. 19, p. 6558, doi. 10.1093/jxb/erac291
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- Article
Phenological optimization of late reproductive phase for raising wheat yield potential in irrigated mega-environments.
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- Journal of Experimental Botany, 2022, v. 73, n. 12, p. 4236, doi. 10.1093/jxb/erac144
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- Article
The Value of Tactical Adaptation to El Niño–Southern Oscillation for East Australian Wheat.
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- Climate (2225-1154), 2018, v. 6, n. 3, p. 77, doi. 10.3390/cli6030077
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- Article
Optimizing soil-coring strategies to quantify root-length-density distribution in field-grown maize: virtual coring trials using 3-D root architecture models.
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- Annals of Botany, 2018, v. 121, n. 5, p. 809, doi. 10.1093/aob/mcx117
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- Article
Designing crops for adaptation to the drought and high‐temperature risks anticipated in future climates.
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- Crop Science, 2020, v. 60, n. 2, p. 605, doi. 10.1002/csc2.20110
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- Article
Linking genetic maps and simulation to optimize breeding for wheat flowering time in current and future climates.
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- Crop Science, 2020, v. 60, n. 2, p. 678, doi. 10.1002/csc2.20113
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- Article
Identification of Earliness Per Se Flowering Time Locus in Spring Wheat through a Genome-Wide Association Study.
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- Crop Science, 2016, v. 56, n. 6, p. 2962, doi. 10.2135/cropsci2016.01.0066
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- Article
A reduced‐tillering trait shows small but important yield gains in dryland wheat production.
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- Global Change Biology, 2020, v. 26, n. 7, p. 4056, doi. 10.1111/gcb.15105
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- Article
Applications of a Hyperspectral Imaging System Used to Estimate Wheat Grain Protein: A Review.
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- Frontiers in Plant Science, 2022, v. 13, p. 1, doi. 10.3389/fpls.2022.837200
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- Article
Comparison of Modelling Strategies to Estimate Phenotypic Values from an Unmanned Aerial Vehicle with Spectral and Temporal Vegetation Indexes.
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- Remote Sensing, 2021, v. 13, n. 14, p. 2827, doi. 10.3390/rs13142827
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Isolation and sequencing of a single copy of an introgressed chromosome from a complex genome for gene and SNP identification.
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- Theoretical & Applied Genetics, 2022, v. 135, n. 4, p. 1279, doi. 10.1007/s00122-022-04030-1
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- Article
EasyPCC: Benchmark Datasets and Tools for High-Throughput Measurement of the Plant Canopy Coverage Ratio under Field Conditions.
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- Sensors (14248220), 2017, v. 17, n. 4, p. 798, doi. 10.3390/s17040798
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- Article
Coupling of machine learning methods to improve estimation of ground coverage from unmanned aerial vehicle (UAV) imagery for high-throughput phenotyping of crops.
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- Functional Plant Biology, 2021, v. 48, n. 8, p. 766, doi. 10.1071/FP20309
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- Article
Comparison of ground cover estimates from experiment plots in cotton, sorghum and sugarcane based on images and ortho-mosaics captured by UAV.
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- Functional Plant Biology, 2017, v. 44, n. 1, p. 169, doi. 10.1071/FP16123
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- Article
Do wheat breeders have suitable genetic variation to overcome short coleoptiles and poor establishment in the warmer soils of future climates?
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- Functional Plant Biology, 2016, v. 43, n. 10, p. 961, doi. 10.1071/FP15362
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- Article
Responses of wheat kernel weight to diverse allelic combinations under projected climate change conditions.
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- Frontiers in Plant Science, 2023, v. 14, p. 1, doi. 10.3389/fpls.2023.1138966
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- Article
Genotype-specific P-spline response surfaces assist interpretation of regional wheat adaptation to climate change.
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- In Silico Plants, 2021, p. 1, doi. 10.1093/insilicoplants/diab018
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- Article
Integrating crop growth models with remote sensing for predicting biomass yield of sorghum.
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- In Silico Plants, 2021, v. 3, n. 1, p. 1, doi. 10.1093/insilicoplants/diab001
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A generic approach to modelling, allocation and redistribution of biomass to and from plant organs.
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- In Silico Plants, 2019, v. 1, n. 1, p. 1, doi. 10.1093/insilicoplants/diy004
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- Article
Uncovering the Drivers and Regional Variability of Cotton Yield in China.
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- Agriculture; Basel, 2023, v. 13, n. 11, p. 2132, doi. 10.3390/agriculture13112132
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- Article
Improving Grain Yield via Promotion of Kernel Weight in High Yielding Winter Wheat Genotypes.
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- Biology (2079-7737), 2022, v. 11, n. 1, p. 42, doi. 10.3390/biology11010042
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- Article
Understanding the Effects of Growing Seasons, Genotypes, and Their Interactions on the Anthesis Date of Wheat Sown in North China.
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- Biology (2079-7737), 2021, v. 10, n. 10, p. 955, doi. 10.3390/biology10100955
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- Article
Aerial Imagery Analysis – Quantifying Appearance and Number of Sorghum Heads for Applications in Breeding and Agronomy.
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- Frontiers in Plant Science, 2018, p. N.PAG, doi. 10.3389/fpls.2018.01544
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- Article
Assessment of the influence of global dimming on the photosynthetic production of rice based on three-dimensional modeling.
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- SCIENCE CHINA Earth Sciences, 2011, v. 54, n. 2, p. 290, doi. 10.1007/s11430-010-4097-6
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- Article
Assessment of the Potential Impacts of Wheat Plant Traits across Environments by Combining Crop Modeling and Global Sensitivity Analysis.
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- PLoS ONE, 2016, v. 11, n. 1, p. 1, doi. 10.1371/journal.pone.0146385
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- Article
The Agro-Pastoral Transitional Zone in Northern China: Continuously Intensifying Land Use Competition Leading to Imbalanced Spatial Matching of Ecological Elements.
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- Land (2012), 2024, v. 13, n. 5, p. 654, doi. 10.3390/land13050654
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- Article
Accuracy assessment of plant height using an unmanned aerial vehicle for quantitative genomic analysis in bread wheat.
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- Plant Methods, 2019, v. 15, n. 1, p. N.PAG, doi. 10.1186/s13007-019-0419-7
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- Article