ORCID Profile
0000-0002-6612-7691
Current Organisation
University of Queensland
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Crop and pasture production | Animal reproduction and breeding | Horticultural crop improvement (incl. selection and breeding) | Crop and pasture improvement (incl. selection and breeding) | Agricultural Systems Analysis and Modelling | Crop and Pasture Production | Crop and Pasture Biochemistry and Physiology | Plant biochemistry | Agricultural marine biotechnology | Genetically Modified Field Crops and Pasture | Plant biology | Plant physiology
Sorghum | Expanding Knowledge in the Agricultural and Veterinary Sciences |
Publisher: Springer Science and Business Media LLC
Date: 11-07-2013
DOI: 10.1007/S00216-013-7129-1
Abstract: Two highly branched glucose polymers with similar structures--starch and glycogen--have important relations to human health. Slowly digestible and resistant starches have desirable health benefits, including the prevention and alleviation of metabolic diseases and prevention of colon cancer. Glycogen is important in regulating the use of glucose in the body, and diabetic subjects have an anomaly in their glycogen structure compared with that in healthy subjects. This paper reviews the biosynthesis-structure-property relations of these polymers, showing that polymer characterization produces knowledge which can be useful in producing healthier foods and new drug targets aimed at improving glucose storage in diabetic patients. Ex les include mathematical modeling to design starch with better nutritional values, the effects of amylose fine structures on starch digestibility, the structure of slowly digested starch collected from in vitro and in vivo digestion, and the mechanism of the formation of glycogen α particles from β particles in healthy subjects. A new method to overcome a current problem in the structural characterization of these polymers using field-flow fractionation is also given, through a technique to calibrate evaporative light scattering detection with starch.
Publisher: Cold Spring Harbor Laboratory
Date: 06-07-2022
DOI: 10.1101/2022.07.06.498957
Abstract: Photosynthetic manipulation provides new opportunities for enhancing crop yield. However, understanding and quantifying effectively how the seasonal growth and yield dynamics of target crops might be affected over a wide range of environments is limited. Using a state-of-the-art cross-scale model we predicted crop-level impacts of a broad list of promising photosynthesis manipulation strategies for C 3 wheat and C 4 sorghum. The manipulation targets have varying effects on the enzyme-limited ( A c ) and electron transport-limited ( A j ) rates of photosynthesis. In the top decile of seasonal outcomes, yield gains with the list of manipulations were predicted to be modest, ranging between 0 and 8%, depending on the crop type and manipulation. To achieve the higher yield gains, large increases in both A c and A j are needed. This could likely be achieved by stacking Rubisco function and electron transport chain enhancements or installing a full CO 2 concentrating system. However, photosynthetic enhancement influences the timing and severity of water and nitrogen stress on the crop, confounding yield outcomes. Strategies enhancing A c alone offers more consistent but smaller yield gains across environments, A j enhancement alone offers higher gains but is undesirable in less favourable environments. Understanding and quantifying complex cross-scale interactions between photosynthesis and crop yield will challenge and stimulate photosynthesis and crop research. Leaf–canopy–crop prediction using a state-of-the-art cross-scale model improves understanding of how photosynthetic manipulation alters wheat and sorghum growth and yield dynamics. This generates novel insights for quantifying impacts of photosynthetic enhancement on crop yield across environments.
Publisher: American Chemical Society (ACS)
Date: 05-2014
DOI: 10.1021/JF5011676
Abstract: The molecular structures of amylose and amylopectin have an impact on functional properties of starch-containing food. This is the first study comparing amylose size distributions from various plant sources. Chain-length distributions (CLDs) of amylose and amylopectin branches ("fine structure") are characterized using size-exclusion chromatography [sometimes termed gel permeation chromatography (GPC)] and parametrized by both biosynthesis-based and empirical fits, to understand the starch biosynthesis mechanism and identify associations with starch digestibility. All starches show bimodal amylose weight CLDs, varying with plant sources, with potato tuber and sweet potato root starch having relatively longer branches than the others. The digestograms of all starches fit first-order kinetics. Unlike what has been seen in cooked grains/flours, amylose and amylopectin fine structures have no association with the digestibility of freshly gelatinized starch. This suggests that the observed effect in cooked grains/flours arises from a secondary interaction between amylose fine structure and higher order structural features.
Publisher: American Chemical Society (ACS)
Date: 14-05-2015
Publisher: Oxford University Press (OUP)
Date: 2019
DOI: 10.1093/INSILICOPLANTS/DIZ010
Abstract: The potential to add significant value to the rapid advances in plant breeding technologies associated with statistical whole-genome prediction methods is a new frontier for crop physiology and modelling. Yield advance by genetic improvement continues to require prediction of phenotype based on genotype, and this remains challenging for complex traits despite recent advances in genotyping and phenotyping. Crop models that capture physiological knowledge and can robustly predict phenotypic consequences of genotype-by-environment-by-management (G×E×M) interactions have demonstrated potential as an integrating tool. But does this biological reality come with a degree of complexity that restricts applicability in crop improvement? Simple, high-speed, parsimonious models are required for dealing with the thousands of genotypes and environment combinations in modern breeding programs utilizing genomic prediction technologies. In contrast, it is often considered that greater model complexity is needed to evaluate potential of putative variation in specific traits in target environments as knowledge on their underpinning biology advances. Is this a contradiction leading to ergent futures? Here it is argued that biological reality and parsimony do not need to be independent and perhaps should not be. Models structured to readily allow variation in the biological level of process algorithms, while using coding and computational advances to facilitate high-speed simulation, could well provide the structure needed for the next generation of crop models needed to support and enhance advances in crop improvement technologies. Beyond that, the trans-scale and transdisciplinary dialogue among scientists that will be required to construct such models effectively is considered to be at least as important as the models.
Publisher: Elsevier BV
Date: 09-2015
DOI: 10.1016/J.CARBPOL.2015.04.035
Abstract: The molecular structure and gelatinization properties of starches from domesticated African rice (Oryza glaberrima) and its wild progenitor (Oryza barthii) are determined and comparison made with Asian domesticated rice (Oryza sativa), the commonest commercial rice. This suggests possible enzymatic processes contributing to the unique traits of the African varieties. These have similar starch structures, including smaller amylose molecules, but larger amounts of amylose chains across the whole amylose chain-length distribution, and higher amylose contents, than O. sativa. They also show a higher proportion of two- and three-lamellae spanning amylopectin branch chains (degree of polymerization 34-100) than O. sativa, which contributes to their higher gelatinization temperatures. Fitting amylopectin chain-length distribution with a biosynthesis-based mathematical model suggests that the reason for this difference might be because O. glaberrima and O. barthii have more active SSIIIa and/or less active SBEIIb enzymes.
Publisher: Wiley
Date: 20-10-2023
DOI: 10.1111/PCE.14453
Abstract: Photosynthetic manipulation provides new opportunities for enhancing crop yield. However, understanding and quantifying the importance of in idual and multiple manipulations on the seasonal biomass growth and yield performance of target crops across variable production environments is limited. Using a state‐of‐the‐art cross‐scale model in the APSIM platform we predicted the impact of altering photosynthesis on the enzyme‐limited ( A c ) and electron transport‐limited ( A j ) rates, seasonal dynamics in canopy photosynthesis, biomass growth, and yield formation via large multiyear‐by‐location crop growth simulations. A broad list of promising strategies to improve photosynthesis for C 3 wheat and C 4 sorghum were simulated. In the top decile of seasonal outcomes, yield gains were predicted to be modest, ranging between 0% and 8%, depending on the manipulation and crop type. We report how photosynthetic enhancement can affect the timing and severity of water and nitrogen stress on the growing crop, resulting in nonintuitive seasonal crop dynamics and yield outcomes. We predicted that strategies enhancing A c alone generate more consistent but smaller yield gains across all water and nitrogen environments, A j enhancement alone generates larger gains but is undesirable in more marginal environments. Large increases in both A c and A j generate the highest gains across all environments. Yield outcomes of the tested manipulation strategies were predicted and compared for realistic Australian wheat and sorghum production. This study uniquely unpacks complex cross‐scale interactions between photosynthesis and seasonal crop dynamics and improves understanding and quantification of the potential impact of photosynthesis traits (or lack of it) for crop improvement research.
Publisher: Elsevier BV
Date: 08-2020
Publisher: Public Library of Science (PLoS)
Date: 07-06-2013
Publisher: Frontiers Media SA
Date: 13-10-2016
Publisher: Public Library of Science (PLoS)
Date: 27-06-2014
Publisher: Elsevier BV
Date: 2019
DOI: 10.1016/J.TPLANTS.2018.09.005
Abstract: Leaves are a nexus for the exchange of water, carbon, and energy between terrestrial plants and the atmosphere. Research in recent decades has highlighted the critical importance of the underlying biophysical and anatomical determinants of CO
Publisher: CSIRO Publishing
Date: 2013
DOI: 10.1071/CH13397
Abstract: Improving starch-containing materials, whether food, animal feed, high-tech biomaterials, or engineering plastics, is best done by understanding how biosynthetic processes and any subsequent processing control starch structure, and how this structure controls functional properties. Starch structural characterization is central to this. This review examines how information on the three basic levels of the complex multi-scale structure of starch – in idual chains, the branching structure of isolated molecules, and the way these molecules form various crystalline and amorphous arrangements – can be obtained from experiment. The techniques include fluorophore-assisted carbohydrate electrophoresis, multiple-detector size-exclusion chromatography, and various scattering techniques (light, X-ray, and neutron). Some ex les are also given to show how these data provide mechanistic insight into how biosynthetic processes control the structure and how the various structural levels control functional properties.
Publisher: CSIRO Publishing
Date: 2018
DOI: 10.1071/FP17225
Abstract: Photosynthetic manipulation is seen as a promising avenue for advancing field crop productivity. However, progress is constrained by the lack of connection between leaf-level photosynthetic manipulation and crop performance. Here we report on the development of a model of diurnal canopy photosynthesis for well watered conditions by using biochemical models of C3 and C4 photosynthesis upscaled to the canopy level using the simple and robust sun–shade leaves representation of the canopy. The canopy model was integrated over the time course of the day for diurnal canopy photosynthesis simulation. Rationality analysis of the model showed that it simulated the expected responses in diurnal canopy photosynthesis and daily biomass accumulation to key environmental factors (i.e. radiation, temperature and CO2), canopy attributes (e.g. leaf area index and leaf angle) and canopy nitrogen status (i.e. specific leaf nitrogen and its profile through the canopy). This Diurnal Canopy Photosynthesis Simulator (DCaPS) was developed into a web-based application to enhance usability of the model. Applications of the DCaPS package for assessing likely canopy-level consequences of changes in photosynthetic properties and its implications for connecting photosynthesis with crop growth and development modelling are discussed.
Publisher: American Chemical Society (ACS)
Date: 08-11-2010
DOI: 10.1021/BM1010189
Abstract: Modeling the chain-length distributions (CLDs, the molecular weight distributions of in idual branches) in a polymer system can be exploited to obtain information on the underlying (bio)synthesis mechanisms. Such a model is developed for starch (a highly branched glucose polymer), taking into account multiple isoforms of the three types of enzymatic mechanisms contributing directly to the CLD: propagation, branching, and debranching. The resulting CLD is given by two parameters and can thus be represented by a point in a two-dimensional phase diagram. The model implies that all native-starch amylopectin CLDs are confined to a line in this phase diagram, an inference supported by fitting data for a wide range of plants. This gives new ways to classify mutants and suggests useful directions for plant engineering (e.g., which isoforms could be targeted to give long branches, which are nutritionally desirable).
Publisher: Elsevier BV
Date: 08-2015
DOI: 10.1016/J.CARBPOL.2015.03.081
Abstract: This study examines the relationships between genetics (single nucleotide polymorphisms (SNPs) in GBSSI and SSIIa genes), starch structure (amylose and amylopectin fine structures), and starch properties (relating to gelatinization). GBSSI and SSIIa SNPs did not alter the starch content of rice grains. GBSSI SNPs can affect the amylose content, but they are incapable of altering the chain-lengths of amylopectin and amylose. The amounts of both long and short amylose branches changed with the same trend as amylose content, and they appeared to affect starch gelatinization properties. SSIIa synthesizes intermediate single-lamella amylopectin chains (DP 16-21), and consequently impacts the gelatinization temperature. Mathematical modelling suggests that the reduction in SSIIa activity significantly increases the activity of SBEII, resulting in a decreased activity ratio of SS to SBE in the enzyme set governing an appropriate chain-length distribution range. This application of the genetics-structure-property paradigm provides selection strategies to produce rice varieties with improved qualities.
Publisher: Elsevier BV
Date: 11-2019
DOI: 10.1016/J.CARBPOL.2019.115134
Abstract: Amylose has a small but significant number of long-chain branches. Two-dimensional size-exclusion chromatography is used to obtain the first measurement of the average number of branches per amylose molecule (from potato tubers) as a function of molecular size. Molecular weight dispersity, average chain length and average amylose molecular weight all increase with increasing size. However, the average number of branches of amylose molecules is weakly, if at all, dependent on size, with 2-4 per molecule except perhaps for the very largest molecules, although for these, the data may suffer from artifacts. Differences in the sizes of amylose molecules is mostly ascribed to variations in chain length. This observation is consistent with the postulate that most branching events occur in the early stage of amylose synthesis, and afterwards the branches are further elongated by granule-bound starch synthases. This gives improved mechanistic understanding of amylose biosynthesis.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 2022
Abstract: Sorghum, a genetically erse C 4 cereal, is an ideal model to study natural variation in photosynthetic capacity. Specific leaf nitrogen (SLN) and leaf mass per leaf area (LMA), as well as, maximal rates of Rubisco carboxylation ( V cmax ), phosphoenolpyruvate (PEP) carboxylation ( V pmax ), and electron transport ( J max ), quantified using a C 4 photosynthesis model, were evaluated in two field-grown training sets ( n = 169 plots including 124 genotypes) in 2019 and 2020. Partial least square regression (PLSR) was used to predict V cmax ( R 2 = 0.83 ), V pmax ( R 2 = 0.93 ), J max ( R 2 = 0.76 ), SLN ( R 2 = 0.82 ), and LMA ( R 2 = 0.68 ) from tractor-based hyperspectral sensing. Further assessments of the capability of the PLSR models for V cmax , V pmax , J max , SLN, and LMA were conducted by extrapolating these models to two trials of genome-wide association studies adjacent to the training sets in 2019 ( n = 875 plots including 650 genotypes) and 2020 ( n = 912 plots with 634 genotypes). The predicted traits showed medium to high heritability and genome-wide association studies using the predicted values identified four QTL for V cmax and two QTL for J max . Candidate genes within 200 kb of the V cmax QTL were involved in nitrogen storage, which is closely associated with Rubisco, while not directly associated with Rubisco activity per se . J max QTL was enriched for candidate genes involved in electron transport. These outcomes suggest the methods here are of great promise to effectively screen large germplasm collections for enhanced photosynthetic capacity.
Publisher: Elsevier BV
Date: 12-2014
DOI: 10.1016/J.CARBPOL.2014.08.001
Abstract: The analysis of starch chain-length distributions (CLDs) is important for understanding starch biosythesis-structure-property relations. It is obtained by analyzing the number distribution of the linear glucan chains released by enzymatic debranching of starch α-(1→6) glycosidic bonds for subsequent characterization by techniques such as fluorophore-assisted carbohydrate electrophoresis (FACE) or size-exclusion chromatography (SEC). Current literature pretreatments for debranching prior to CLD determination involve varying protocols, which might yield artifactual results. This paper examines the two widely used starch dissolution treatments with dimethyl sulfoxide (DMSO) containing 0.5% (w/w) lithium bromide (DMSO-LiBr) at 80°C and with aqueous alkaline (i.e. NaOH) solvents at 100 ˚C. Analyses by FACE with a very high range of degree of polymerization, and by SEC, of the CLD of barley starches with different structures show the following. (1) The NaOH treatment, even at a dilute concentration, causes significant degradation at higher degrees of polymerization, leading to quantitatively incorrect CLD results in longer amylopectin and in amylose chains. (2) Certain features in both amylopectin and amylose fractions of the CLD reduced to bumps or are missing with NaOH treatment. (3) Overestimation of amylose chains in starch CLD due to incomplete amylopectin dissolution with dilute NaOH concentration. These results indicate starch dissolution with DMSO-LiBr is the method of choice for minimizing artifacts. An improved pretreatment protocol is presented for starch CLD analysis by FACE and SEC.
Publisher: Springer Science and Business Media LLC
Date: 15-04-2020
DOI: 10.1038/S41477-020-0625-3
Abstract: Predicting the consequences of manipulating genotype (G) and agronomic management (M) on agricultural ecosystem performances under future environmental (E) conditions remains a challenge. Crop modelling has the potential to enable society to assess the efficacy of G × M technologies to mitigate and adapt crop production systems to climate change. Despite recent achievements, dedicated research to develop and improve modelling capabilities from gene to global scales is needed to provide guidance on designing G × M adaptation strategies with full consideration of their impacts on both crop productivity and ecosystem sustainability under varying climatic conditions. Opportunities to advance the multiscale crop modelling framework include representing crop genetic traits, interfacing crop models with large-scale models, improving the representation of physiological responses to climate change and management practices, closing data gaps and harnessing multisource data to improve model predictability and enable identification of emergent relationships. A fundamental challenge in multiscale prediction is the balance between process details required to assess the intervention and predictability of the system at the scales feasible to measure the impact. An advanced multiscale crop modelling framework will enable a gene-to-farm design of resilient and sustainable crop production systems under a changing climate at regional-to-global scales.
Publisher: Oxford University Press (OUP)
Date: 2021
DOI: 10.1093/INSILICOPLANTS/DIAA012
Abstract: Maize is considered less drought-tolerant than sorghum, but sorghum is commonly grown as a short triple dwarf (3dwarf) type, so difference in plant height confounds the species comparison. The objectives of this study were to experimentally determine effects of species and plant height differences on transpiration efficiency (TE) and transpiration rate per unit green leaf area (TGLA) and use findings to explain input parameters in a simulation study on the comparative adaptation of 3dwarf sorghum and maize in environments with contrasting water availability. Maize, tall double dwarf (2dwarf) and short 3dwarf sorghum genotypes were grown in two lysimeter experiments in 2011 in SE Queensland, Australia. Each plant was harvested after anthesis and total transpiration, shoot and root dry mass were measured to estimate TE. Daily TGLA was used to compare transpiration rates. Species and height had limited effect on TE, but significantly affected TGLA. This was associated with differences in biomass allocation. The similar TE but higher TGLA in maize compared with 3dwarf sorghum meant it potentially produces more biomass, consistent with published differences in biomass accumulation and radiation use efficiency (RUE). The simulation study, which used similar TE for maize and 3dwarf sorghum, but captured differences in TGLA through differences in RUE, predicted crossover interactions for grain yield between species and total water use. The greater TGLA of maize decreased grain yield in water-limited environments, but increased yields in well-watered situations. Results highlight that similarity in TE and differences in TGLA can influence comparative adaptation to water limitation.
Publisher: Wiley
Date: 17-07-2023
Abstract: It has been suggested that amylopectin can contain small but significant amounts of extra‐long chains (ELCs), which could affect functional properties, and also would have implications for the mechanism of starch biosynthesis. However, current evidence for the existence of ELCs is ambiguous. The amylose/amylopectin separation and the characterization techniques used for the investigation of ELCs are reviewed, problems in those techniques are examined, and studies of ELCs of amylopectin are discussed. A model for the biosynthesis of amylopectin chains in terms of conventional biosynthesis enzymes, which provides an excellent fit to a large amount of experimental data, is used to provide a rigorous definition of ELCs. In addition, current investigations of ELCs, involving separation, is hindered by the lack of a method to quantitatively separate all the amylopectin from starch without any traces of residual amylose (which would have long chains). Unambiguous evidence for the existence of ELCs can be obtained using two‐dimensional (2D) characterization, these dimensions being the degree of polymerization of a chain and the size of the whole molecule. Available 2D data indicate that there are no ELCs present in currently detectable quantities in native rice starches. However, concluding this more rigorously requires improvements in the resolution of current 2D methods.
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: Springer Science and Business Media LLC
Date: 07-08-2022
DOI: 10.1007/S00122-022-04167-Z
Abstract: Leaf width was correlated with plant-level transpiration efficiency and associated with 19 QTL in sorghum, suggesting it could be a surrogate for transpiration efficiency in large breeding program. Enhancing plant transpiration efficiency (TE) by reducing transpiration without compromising photosynthesis and yield is a desirable selection target in crop improvement programs. While narrow in idual leaf width has been correlated with greater intrinsic water use efficiency in C 4 species, the extent to which this translates to greater plant TE has not been investigated. The aims of this study were to evaluate the correlation of leaf width with TE at the whole-plant scale and investigate the genetic control of leaf width in sorghum. Two lysimetry experiments using 16 genotypes varying for stomatal conductance and three field trials using a large sorghum ersity panel ( n = 701 lines) were conducted. Negative associations of leaf width with plant TE were found in the lysimetry experiments, suggesting narrow leaves may result in reduced plant transpiration without trade-offs in biomass accumulation. A wide range in width of the largest leaf was found in the sorghum ersity panel with consistent ranking among sorghum races, suggesting that environmental adaptation may have a role in modifying leaf width. Nineteen QTL were identified by genome-wide association studies on leaf width adjusted for flowering time. The QTL identified showed high levels of correspondence with those in maize and rice, suggesting similarities in the genetic control of leaf width across cereals. Three a priori candidate genes for leaf width, previously found to regulate dorsoventrality, were identified based on a 1-cM threshold. This study provides useful physiological and genetic insights for potential manipulation of leaf width to improve plant adaptation to erse environments.
Publisher: CSIRO Publishing
Date: 28-04-2023
DOI: 10.1071/FP23010
Abstract: Grain yield improvement in globally important staple crops is critical in the coming decades if production is to keep pace with growing demand so there is increasing interest in understanding and manipulating plant growth and developmental traits for better crop productivity. However, this is confounded by complex cross-scale feedback regulations and a limited ability to evaluate the consequences of manipulation on crop production. Plant/crop modelling could hold the key to deepening our understanding of dynamic trait–crop–environment interactions and predictive capabilities for supporting genetic manipulation. Using photosynthesis and crop growth as an ex le, this review summarises past and present experimental and modelling work, bringing about a model-guided crop improvement thrust, encompassing research into: (1) advancing cross-scale plant/crop modelling that connects across biological scales of organisation using a trait dissection–integration modelling principle (2) improving the reliability of predicted molecular–trait–crop–environment system dynamics with experimental validation and (3) innovative model application in synergy with cross-scale experimentation to evaluate G × M × E and predict yield outcomes of genetic intervention (or lack of it) for strategising further molecular and breeding efforts. The possible future roles of cross-scale plant/crop modelling in maximising crop improvement are discussed.
Publisher: Springer Science and Business Media LLC
Date: 08-04-2019
DOI: 10.1038/S41477-019-0398-8
Abstract: Enhancing photosynthesis is widely accepted as critical to advancing crop yield. However, yield consequences of photosynthetic manipulation are confounded by feedback effects arising from interactions with crop growth, development dynamics and the prevailing environment. Here, we developed a cross-scale modelling capability that connects leaf photosynthesis to crop yield in a manner that addresses the confounding factors. The model was validated using data on crop biomass and yield for wheat and sorghum from erse field experiments. Consequences for yield were simulated for major photosynthetic enhancement targets related to leaf CO
Publisher: Springer Science and Business Media LLC
Date: 17-06-2015
DOI: 10.1186/S12284-015-0055-4
Abstract: It has been shown from the chain length distributions (CLDs) that amylose chains can be ided into at least two groups: long and short amylose chains. These molecular structures influence some functional properties of starch, such as digestibility and mouth-feel. GBSSI is the key enzyme for the elongation of amylose chains however, the effect of other starch biosynthesis enzymes in amylose synthesis is still not fully understood. Two advanced starch characterization techniques, size exclusion chromatography (SEC) and fluorophore-assissted carbohydrate electrophoresis (FACE), together with a newly developed starch biosynthesis model, are used to improve understanding of amylose biosynthesis. SEC and FACE were used to determine the CLD of amylose and amylopectin in various native and mutant rice starches. The types of starch branching enzymes (SBEs) involved in the synthesis of the distinct features seen for shorter degrees of polymerization, DP, 2000, and longer (DP 2000) amylose chains are identified by combining these data with a mathematical model of amylopectin biosynthesis. The model enables each feature in the amylopectin CLD to be parameterized in terms of relative SBE activities, which are used to explain differences in the genotypes. The results suggest that while GBSSI is the predominant enzyme controlling the synthesis of longer amylose chains, some branching enzymes (such as BEI and BEIIb) also play important roles in the synthesis of shorter amylose chains.
Publisher: MDPI AG
Date: 20-02-2020
DOI: 10.3390/FOODS9020222
Abstract: This paper examines if, in maize, starch structure and starch-dependent properties might be altered by pleiotropic effects arising from genetic modifications that are not directly related to starch synthesis. The molecular structure, specifically the starch chain-length distributions (CLDs), of two maize lines transformed with Bar (bialaphos resistance) and Cry1c genes (an artificial gene, encoding proteinaceous insecticidal δ-endotoxins) were compared to those of their control lines. The two transgenes are responsible for herbicidal resistance and insect tolerance, respectively. The starch CLDs were measured by enzymatic debranching and measuring the molecular weight distributions of the resulting linear chains. It was found that although all the lines had similar amylose contents, the CLDs of both amylopectin and amylose for Cry1c were noticeably different from the others, having more short amylopectin and long amylose chains. These CLDs are known to affect functional properties, and indeed it was found that the Cry1c transgenic lines showed a lower gelatinization temperature and faster digestion rate than the control or Bar lines. However, a slower digestion rate is nutritionally desirable. Thus, pleiotropic effects from genetic modifications can indirectly but significantly affect the starch synthesis pathway and thus change functional properties of significance for human health.
Publisher: Public Library of Science (PLoS)
Date: 13-04-2015
Publisher: Annual Reviews
Date: 29-04-2019
DOI: 10.1146/ANNUREV-ARPLANT-042817-040305
Abstract: The ratio of plant carbon gain to water use, known as water use efficiency (WUE), has long been recognized as a key constraint on crop production and an important target for crop improvement. WUE is a physiologically and genetically complex trait that can be defined at a range of scales. Many component traits directly influence WUE, including photosynthesis, stomatal and mesophyll conductances, and canopy structure. Interactions of carbon and water relations with erse aspects of the environment and crop development also modulate WUE. As a consequence, enhancing WUE by breeding or biotechnology has proven challenging but not impossible. This review aims to synthesize new knowledge of WUE arising from advances in phenotyping, modeling, physiology, genetics, and molecular biology in the context of classical theoretical principles. In addition, we discuss how rising atmospheric CO 2 concentration has created and will continue to create opportunities for enhancing WUE by modifying the trade-off between photosynthesis and transpiration.
Start Date: 2021
End Date: 12-2024
Amount: $461,249.00
Funder: Australian Research Council
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End Date: 12-2027
Amount: $5,000,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 03-2023
End Date: 03-2024
Amount: $682,749.00
Funder: Australian Research Council
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