ORCID Profile
0000-0002-8491-2984
Current Organisation
University of Queensland - Gatton Campus
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Crop and Pasture Improvement (Selection and Breeding) | Quantitative Genetics (incl. Disease and Trait Mapping Genetics) | Crop and Pasture Production | Crop and Pasture Biochemistry and Physiology
Sorghum |
Publisher: Wiley
Date: 10-12-2007
DOI: 10.1111/J.1365-3040.2007.01772.X
Abstract: Physiological and genetic studies of leaf growth often focus on short-term responses, leaving a gap to whole-plant models that predict biomass accumulation, transpiration and yield at crop scale. To bridge this gap, we developed a model that combines an existing model of leaf 6 expansion in response to short-term environmental variations with a model coordinating the development of all leaves of a plant. The latter was based on: (1) rates of leaf initiation, appearance and end of elongation measured in field experiments and (2) the hypothesis of an independence of the growth between leaves. The resulting whole-plant leaf model was integrated into the generic crop model APSIM which provided dynamic feedback of environmental conditions to the leaf model and allowed simulation of crop growth at canopy level. The model was tested in 12 field situations with contrasting temperature, evaporative demand and soil water status. In observed and simulated data, high evaporative demand reduced leaf area at the whole-plant level, and short water deficits affected only leaves developing during the stress, either visible or still hidden in the whorl. The model adequately simulated whole-plant profiles of leaf area with a single set of parameters that applied to the same hybrid in all experiments. It was also suitable to predict biomass accumulation and yield of a similar hybrid grown in different conditions. This model extends to field conditions existing knowledge of the environmental controls of leaf elongation, and can be used to simulate how their genetic controls flow through to yield.
Publisher: Wiley
Date: 15-01-2020
DOI: 10.1002/CCHE.10252
Publisher: Wiley
Date: 23-09-2015
DOI: 10.1111/GCB.13022
Abstract: Characterization of drought environment types (ETs) has proven useful for breeding crops for drought-prone regions. Here, we consider how changes in climate and atmospheric carbon dioxide (CO2 ) concentrations will affect drought ET frequencies in sorghum and wheat systems of northeast Australia. We also modify APSIM (the Agricultural Production Systems Simulator) to incorporate extreme heat effects on grain number and weight, and then evaluate changes in the occurrence of heat-induced yield losses of more than 10%, as well as the co-occurrence of drought and heat. More than six million simulations spanning representative locations, soil types, management systems, and 33 climate projections led to three key findings. First, the projected frequency of drought decreased slightly for most climate projections for both sorghum and wheat, but for different reasons. In sorghum, warming exacerbated drought stresses by raising the atmospheric vapor pressure deficit and reducing transpiration efficiency (TE), but an increase in TE due to elevated CO2 more than offset these effects. In wheat, warming reduced drought stress during spring by hastening development through winter and reducing exposure to terminal drought. Elevated CO2 increased TE but also raised radiation-use efficiency and overall growth rates and water use, thereby offsetting much of the drought reduction from warming. Second, adding explicit effects of heat on grain number and grain size often switched projected yield impacts from positive to negative. Finally, although average yield losses associated with drought will remain generally higher than that for heat stress for the next half century, the relative importance of heat is steadily growing. This trend, as well as the likely high degree of genetic variability in heat tolerance, suggests that more emphasis on heat tolerance is warranted in breeding programs. At the same time, work on drought tolerance should continue with an emphasis on drought that co-occurs with extreme heat.
Publisher: Elsevier BV
Date: 03-2009
Publisher: Wiley
Date: 2009
Publisher: Elsevier BV
Date: 09-2017
Publisher: Oxford University Press (OUP)
Date: 16-04-2010
DOI: 10.1093/JXB/ERQ095
Abstract: Progress in molecular plant breeding is limited by the ability to predict plant phenotype based on its genotype, especially for complex adaptive traits. Suitably constructed crop growth and development models have the potential to bridge this predictability gap. A generic cereal crop growth and development model is outlined here. It is designed to exhibit reliable predictive skill at the crop level while also introducing sufficient physiological rigour for complex phenotypic responses to become emergent properties of the model dynamics. The approach quantifies capture and use of radiation, water, and nitrogen within a framework that predicts the realized growth of major organs based on their potential and whether the supply of carbohydrate and nitrogen can satisfy that potential. The model builds on existing approaches within the APSIM software platform. Experiments on erse genotypes of sorghum that underpin the development and testing of the adapted crop model are detailed. Genotypes differing in height were found to differ in biomass partitioning among organs and a tall hybrid had significantly increased radiation use efficiency: a novel finding in sorghum. Introducing these genetic effects associated with plant height into the model generated emergent simulated phenotypic differences in green leaf area retention during grain filling via effects associated with nitrogen dynamics. The relevance to plant breeding of this capability in complex trait dissection and simulation is discussed.
Publisher: Oxford University Press (OUP)
Date: 21-02-2018
DOI: 10.1093/JXB/ERY059
Abstract: Following advances in genetics, genomics, and phenotyping, trait selection in breeding is limited by our ability to understand interactions within the plant and with the environment, and to identify traits of most relevance to the target population of environments. We propose an integrated approach that combines insights from crop modelling, physiology, genetics, and breeding to characterize traits valuable for yield gain in the target population of environments, develop relevant high-throughput phenotyping platforms, and identify genetic controls and their value in production environments. This paper uses transpiration efficiency (biomass produced per unit of water used) as an ex le of a complex trait of interest to illustrate how the approach can guide modelling, phenotyping, and selection in a breeding programme. We believe that this approach, by integrating insights from erse disciplines, can increase the resource use efficiency of breeding programmes for improving yield gains in target populations of environments.
Publisher: Elsevier BV
Date: 2003
Publisher: Wiley
Date: 11-01-2022
DOI: 10.1111/GCBB.12919
Abstract: Regional‐scale estimations of sorghum biomass production allow identification of optimum genotype×environment×management (G×E×M) combinations for bioenergy generation. The objective of this study was to determine the degree of contributions of G, E, and M toward variability in sorghum biomass in the United States. Using the Agricultural Production Systems sIMulator in a grid computing platform, biomass was simulated for irrigated and rainfed conditions for 30 years across the United States for four sorghum varietal types (grain—GS, sudangrass—SS, photosensitive—PS, and photo‐insensitive—PI). Simulated biomass was assessed by environments clustered using the sum of intercepted solar radiation ( ir ), mean of temperature stress factor ( tp ) and water stress factor ( sw ). Simulated biomass ranged from 5.8 t ha −1 (GS‐rainfed) to 27.5 t ha −1 (PI‐irrigated). Under high‐temperature environments (mean annual temperature = 25°C), rainfed biomass between 40 and 80 days after planting (DAP) was strongly correlated with sw ( r = 0.64–0.86) and irrigated biomass with ir ( r = 0.68–0.81). Under low‐temperature environments (mean annual temperature = 18°C) after 40 DAP, tp and ir had greater effects than sw ( r = 0.55–0.82). Biomass variance was mainly explained by varietal type (50%–76%) in all environments×irrigation combinations, except in the high‐ and mid‐temperature environments under rainfed conditions where rainfall had the major effect (25%–45%). However, when mean temperature during the growing season decreased from 25°C (high environments) to 18°C (low environments), the contribution of mean temperature to biomass variance increased from 7% to 34% (rainfed) and from 4% to 36% (irrigated). Varietal type had the larger interactions with other factors independently of the environment and irrigation. We demonstrated a need to quantify (i) the main G×E×M drivers of biomass variability based on environmental stress factors and (ii) the variance contribution of these drivers on sorghum biomass. Our regional‐scale estimations are key inputs for future robust biomass projections of energy sorghum genotypes integrating G×E×M under climate change scenarios.
Publisher: CSIRO Publishing
Date: 2008
DOI: 10.1071/EA06103
Abstract: This paper reports on the use of APSIM – Maize for retrospective analysis of performance of a high input, high yielding maize crop and analysis of predicted performance of maize grown with high inputs over the long-term ( years) for specified scenarios of environmental conditions (temperature and radiation) and agronomic inputs (sowing date, plant population, nitrogen fertiliser and irrigation) at Boort, Victoria, Australia. It uses a high yielding (17 400 kg/ha dry grain, 20 500 kg/ha at 15% water) commercial crop grown in 2004–05 as the basis of the study. Yield for the agronomic and environmental conditions of 2004–05 was predicted accurately, giving confidence that the model could be used for the detailed analyses undertaken. The analysis showed that the yield achieved was close to that possible with the conditions and agronomic inputs of 2004–05. Sowing dates during 21 September to 26 October had little effect on predicted yield, except when combined with reduced temperature. Single year and long-term analyses concluded that a higher plant population (11 plants/m2) is needed to optimise yield, but that slightly lower N and irrigation inputs are appropriate for the plant population used commercially (8.4 plants/m2). Also, compared with changes in agronomic inputs increases in temperature and/or radiation had relatively minor effects, except that reduced temperature reduces predicted yield substantially. This study provides an approach for the use of models for both retrospective analysis of crop performance and assessment of long-term variability of crop yield under a wide range of agronomic and environmental conditions.
Publisher: CSIRO Publishing
Date: 2008
DOI: 10.1071/EA06104
Abstract: Maize may assume a more significant role in grain crop production systems in north-east Australia if the probability of producing low yields associated with given amounts of available water can be reduced. Growing hybrids with very early maturity provides a possible way to achieve this. Simulation studies of dryland maize production in areas of highly variable rainfall in north-east Australia were undertaken using long-term weather data input to the APSIM model configured for quick to medium maturity maize. The studies focussed on sowing time options, population density, cultivars, and water availability at sowing. Simulation outputs included predicted mean and median yield, measures of yield variability, and the probability of producing low to very low yield ( t/ha). The study showed that optimum sowing date varied with location, and that low populations gave more reliable production, despite some potential yield losses in favourable years. The results of the simulation study provide estimates of yield and thus economic viability of maize production that are interpreted in terms of seasonal variability. They indicate that maize is a viable dryland cropping option provided that cultivar, sowing time and starting water conditions are optimised. Non-optimal conditions of water supply at sowing should be avoided, as greater variability in yield and reduced viability are predicted.
Publisher: Elsevier BV
Date: 2019
Publisher: Oxford University Press (OUP)
Date: 12-2009
DOI: 10.1534/GENETICS.109.105429
Abstract: Under drought, substantial genotype–environment (G × E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this “gene-to-phenotype” gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G × E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such “leafy” genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G × E interactions for complex traits such as drought tolerance.
Publisher: Wiley
Date: 03-2020
DOI: 10.1002/CSC2.20128
Abstract: Sorghum [ Sorghum bicolor (L.) Moench] is an important dryland crop in the semiarid tropics, and temperature and photoperiod are the main environmental factors affecting its phenology and thus adaptation. The objectives of this study were to quantify the response of development rate to temperature and photoperiod for 19 erse Ethiopian sorghum genotypes, and to determine if differences in these responses could be linked to racial grouping or agroecological adaptation. The genotypes, representing four major sorghum races and adaptation to four agroecological zones, were sown on 12 dates at two locations in Ethiopia with contrasting altitude. This created a range in photoperiod and temperatures relevant to Ethiopian conditions. Days from emergence to flag leaf appearance, anthesis, and maturity were recorded. A predictive phenology modeling framework was used to fit the effects of photoperiod and temperature on the rate of development for both the pre‐ and post‐anthesis periods. Results indicated that the pre‐anthesis development rate was independent of photoperiod for the range tested. This result differed from West African germplasm and likely reflects differences in agroecological adaptation and racial background. Significant genotypic differences were observed for the base temperature (0–9.8 °C) and for the optimum rate of development (0.011–0.022 d –1 , with low value indicating late anthesis), with differences related to agroecology and racial type. Post‐anthesis differences in the temperature response were minor. The observed differences in pre‐anthesis base temperature can positively affect sorghum breeding programs globally, especially in temperate regions where suitability for early spring plantings is often restricted by low temperatures.
Publisher: Elsevier BV
Date: 11-2018
Publisher: CSIRO Publishing
Date: 2005
DOI: 10.1071/AR04128
Abstract: In recent years, many sorghum producers in the more marginal ( mm annual rainfall) cropping areas of Queensland and northern New South Wales have used skip row configurations in an attempt to improve yield reliability and reduce sorghum production risk. This paper describes modifications made to the APSIM sorghum module to account for the difference in water usage and light interception between alternative crop planting configurations, and then demonstrates how this new model can be used to quantify the long-term benefits of skip sorghum production. Detailed measurements of light interception and water extraction from sorghum crops grown in solid, single and double skip row configurations were collected from on-farm experiments in southern Qld and northern NSW. These measurements underpinned changes to the APSIM-Sorghum model so that it accounted for the elliptical water uptake pattern below the crop row and the reduced total light interception associated with skip row configurations. Long-term simulation runs using long-term weather files for locations near the experimental sites were used to determine the value of skip row sorghum production as a means of maintaining yield reliability. These simulations showed a trade-off between long-term average production (profitability) and annual yield reliability (risk of failure this year). Over the long term, the production of sorghum in a solid configuration produced a higher average yield compared with sorghum produced in a skip configuration. This difference in average yield is a result of the solid configuration having a higher yield potential compared with the skip configurations. Skip configurations limit the yield potential as a safeguard against crop failure. To achieve the higher average yield in the solid configuration the producer suffers some total failures. Skip configurations reduce the chance of total failure by capping the yield potential, which in turn reduces the long-term average yield. The decision on what row configuration to use should be made tactically and requires consideration of the starting soil water, the soil’s plant-available water capacity (PAWC), and the farm family’s current attitude to risk.
Publisher: Informa UK Limited
Date: 18-12-2017
Publisher: Springer Science and Business Media LLC
Date: 03-03-2013
DOI: 10.1038/NCLIMATE1832
Publisher: CSIRO Publishing
Date: 2019
DOI: 10.1071/FP18177
Abstract: Water scarcity can limit sorghum (Sorghum bicolor (L.) Moench) production in dryland agriculture, but increased whole-plant transpiration efficiency (TEwp, biomass production per unit of water transpired) can enhance grain yield in such conditions. The objectives of this study were to quantify variation in TEwp for 27 sorghum genotypes and explore the linkages of this variation to responses of the underpinning leaf-level processes to environmental conditions. In idual plants were grown in large lysimeters in two well-watered experiments. Whole-plant transpiration per unit of green leaf area (TGLA) was monitored continuously and stomatal conductance and maximum photosynthetic capacity were measured during sunny conditions on recently expanded leaves. Leaf chlorophyll measurements of the upper five leaves of the main shoot were conducted during early grain filling. TEwp was determined at harvest. The results showed that diurnal patterns in TGLA were determined by vapour pressure deficit (VPD) and by the response of whole-plant conductance to radiation and VPD. Significant genotypic variation in the response of TGLA to VPD occurred and was related to genotypic differences in stomatal conductance. However, variation in TGLA explained only part of the variation in TEwp, with some of the residual variation explained by leaf chlorophyll readings, which were a reflection of photosynthetic capacity. Genotypes with different genetic background often differed in TEwp, TGLA and leaf chlorophyll, indicating potential differences in photosynthetic capacity among these groups. Observed differences in TEwp and its component traits can affect adaptation to drought stress.
Publisher: Elsevier BV
Date: 12-2002
Publisher: Oxford University Press (OUP)
Date: 12-02-2013
DOI: 10.1093/AOB/MCT028
Publisher: Elsevier BV
Date: 10-2018
Publisher: Elsevier BV
Date: 02-2013
Publisher: Springer Science and Business Media LLC
Date: 26-03-2014
DOI: 10.1038/NCLIMATE2140
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/CP14088
Abstract: Climatic variability in dryland production environments (E) generates variable yield and crop production risks. Optimal combinations of genotype (G) and management (M) depend strongly on E and thus vary among sites and seasons. Traditional crop improvement seeks broadly adapted genotypes to give best average performance under a standard management regime across the entire production region, with some subsequent manipulation of management regionally in response to average local environmental conditions. This process does not search the full spectrum of potential G × M × E combinations forming the adaptation landscape. Here we examine the potential value (relative to the conventional, broad adaptation approach) of exploiting specific adaptation arising from G × M × E. We present an in-silico analysis for sorghum production in Australia using the APSIM sorghum model. Crop design (G × M) is optimised for subsets of locations within the production region (specific adaptation) and is compared with the optimum G across all environments with locally modified M (broad adaptation). We find that geographic subregions that have frequencies of major environment types substantially different from that for the entire production region show greatest advantage for specific adaptation. Although the specific adaptation approach confers yield and production risk advantages at industry scale, even greater benefits should be achievable with better predictors of environment-type likelihood than that conferred by location alone.
Publisher: Wiley
Date: 03-2017
DOI: 10.1002/CSC2.20110
Abstract: Climate risks pervade agriculture and generate major consequences on crop production. We do not know what the next season will be like, let alone the season 30 years hence. Yet farmers need to decide on g enotype and m anagement (G×M) combinations in advance of the season and in the face of this e nvironment risk. Beyond that, breeders must target traits for future genotypes up to 10 years ahead of their release. Here we present the case for next generation design of G×M×E for crop adaptation in future climates. We focus on adaptation to drought and high‐temperature shock in sorghum [ Sorghum bicolor (L.) Moench] in Australia, but the concepts are generic. The considerable knowledge of climate, both past and future, gives us insight into climate variability and trends. We know that CO 2 and temperature are increasing, and this influences drought and high‐temperature risks for crops. We also have considerable knowledge of crop growth and development responses to CO 2 , drought, and high temperature that have been integrated into advanced crop simulation models. Here we explore by simulation the design of crops best suited to current and future environments. A yield–risk framework is used to identify adapted G×M combinations. The results in this case study indicate the urgent need for high‐temperature tolerance to effects on seed set. Further, existing approaches to G×M for effective use of water through the crop cycle will not be adequate to maintain productivity once global warming of ∼2°C is reached. Improvement in transpiration efficiency offered the avenue with best potential for advancing adaptation relevant to future climates.
Publisher: IOP Publishing
Date: 10-2014
Publisher: CSIRO Publishing
Date: 2014
DOI: 10.1071/FP13355
Abstract: Post-rainy sorghum (Sorghum bicolor (L.) Moench) production underpins the livelihood of millions in the semiarid tropics, where the crop is affected by drought. Drought scenarios have been classified and quantified using crop simulation. In this report, variation in traits that hypothetically contribute to drought adaptation (plant growth dynamics, canopy and root water conducting capacity, drought stress responses) were virtually introgressed into the most common post-rainy sorghum genotype, and the influence of these traits on plant growth, development, and grain and stover yield were simulated across different scenarios. Limited transpiration rates under high vapour pressure deficit had the highest positive effect on production, especially combined with enhanced water extraction capacity at the root level. Variability in leaf development (smaller canopy size, later plant vigour or increased leaf appearance rate) also increased grain yield under severe drought, although it caused a stover yield trade-off under milder stress. Although the leaf development response to soil drying varied, this trait had only a modest benefit on crop production across all stress scenarios. Closer dissection of the model outputs showed that under water limitation, grain yield was largely determined by the amount of water availability after anthesis, and this relationship became closer with stress severity. All traits investigated increased water availability after anthesis and caused a delay in leaf senescence and led to a ‘stay-green’ phenotype. In conclusion, we showed that breeding success remained highly probabilistic maximum resilience and economic benefits depended on drought frequency. Maximum potential could be explored by specific combinations of traits.
Publisher: Wiley
Date: 07-2003
Location: Australia
Start Date: 01-2019
End Date: 12-2023
Amount: $605,000.00
Funder: Australian Research Council
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