Mark Cooper

A methodology for analysis of sugarcane productivity trends. I. Analysis across districts

Publisher: CSIRO Publishing

Date: 2001

DOI: 10.1071/AR00130

Abstract: Historically, few articles have addressed the use of district level mill production data for analysing the effect of varietal change on sugarcane productivity trends. This appears to be due to lack of compiled district data sets and appropriate methods by which to analyse these data. Recently, varietal data on tonnes of sugarcane per hectare (TCH), sugar content (CCS), and their product, tonnes of sugar content per hectare (TSH) on a district basis, have been compiled. This study was conducted to develop a methodology for regular analysis of such data from mill districts to assess productivity trends over time, accounting for variety and variety environment interaction effects for 3 mill districts (Mulgrave, Babinda, and Tully) from 1958 to 1995. Restricted maximum likelihood methodology was used to analyse the district level data and best linear unbiased predictors for random effects, and best linear unbiased estimates for fixed effects were computed in a mixed model analysis. In the combined analysis over districts, Q124 was the top ranking variety for TCH, and Q120 was top ranking for both CCS and TSH. Overall production for TCH increased over the 38-year period investigated. Some of this increase can be attributed to varietal improvement, although the predictors for TCH have shown little progress since the introduction of Q99 in 1976. Although smaller gains have been made in varietal improvement for CCS, overall production for CCS decreased over the 38 years due to non-varietal factors. Varietal improvement in TSH appears to have peaked in the mid-1980s. Overall production for TSH remained stable over time due to the varietal increase in TCH and the nonvarietal decrease in CCS.

Combining ability variation for osmotic adjustment among a selected range of grain sorghum (Sorghum bicolor L. Moench) lines

Publisher: Elsevier BV

Date: 09-1994

DOI: 10.1016/0378-4290(94)90086-8

Utility of repeated checks for hierarchical classification of data from plant breeding trials

Publisher: Elsevier BV

Date: 07-1992

DOI: 10.1016/0378-4290(92)90058-H

Modeling QTL for complex traits: detection and context for plant breeding

Publisher: Elsevier BV

Date: 04-2009

DOI: 10.1016/J.PBI.2009.01.006

Abstract: The genetic architecture of a trait is defined by the set of genes contributing to genetic variation within a reference population of genotypes together with information on their location in the genome and the effects of their alleles on traits, including intra-locus and inter-locus interactions, environmental dependencies, and pleiotropy. Accumulated evidence from trait mapping studies emphasizes that plant breeders work within a trait genetic complexity continuum. Some traits show a relatively simple genetic architecture while others, such as grain yield, have a complex architecture. An important advance is that we now have empirical genetic models of trait genetic architecture obtained from mapping studies (multi-QTL models including various genetic effects that may vary in relation to environmental factors) to ground theoretical investigations on the merits of alternative breeding strategies. Such theoretical studies indicate that as the genetic complexity of traits increases the opportunities for realizing benefits from molecular enhanced breeding strategies increase. To realize these potential benefits and enable the plant breeder to increase rate of genetic gain for complex traits it is anticipated that the empirical genetic models of trait genetic architecture used for predicting trait variation will need to incorporate the effects of genetic interactions and be interpreted within a genotype-environment-management framework for the target agricultural production system.

Improving Drought Tolerance in Maize

Publisher: Wiley

Date: 14-02-2005

DOI: 10.1002/9780470650301.CH7

Retrospective analysis of the relationships among the test environments of the Southern Queensland sugarcane breeding programme

Publisher: Springer Science and Business Media LLC

Date: 08-1994

DOI: 10.1007/BF01253974

Tackling G × E × M interactions to close on-farm yield-gaps: creating novel pathways for crop improvement by predicting contributions of genetics and management to crop productivity

Publisher: Springer Science and Business Media LLC

Date: 18-03-2021

DOI: 10.1007/S00122-021-03812-3

Abstract: Climate change and Genotype-by-Environment-by-Management interactions together challenge our strategies for crop improvement. Research to advance prediction methods for breeding and agronomy is opening new opportunities to tackle these challenges and overcome on-farm crop productivity yield-gaps through design of responsive crop improvement strategies. Genotype-by-Environment-by-Management (G × E × M) interactions underpin many aspects of crop productivity. An important question for crop improvement is “How can breeders and agronomists effectively explore the erse opportunities within the high dimensionality of the complex G × E × M factorial to achieve sustainable improvements in crop productivity?” Whenever G × E × M interactions make important contributions to attainment of crop productivity, we should consider how to design crop improvement strategies that can explore the potential space of G × E × M possibilities, reveal the interesting Genotype–Management (G–M) technology opportunities for the Target Population of Environments (TPE), and enable the practical exploitation of the associated improved levels of crop productivity under on-farm conditions. Climate change adds additional layers of complexity and uncertainty to this challenge, by introducing directional changes in the environmental dimension of the G × E × M factorial. These directional changes have the potential to create further conditional changes in the contributions of the genetic and management dimensions to future crop productivity. Therefore, in the presence of G × E × M interactions and climate change, the challenge for both breeders and agronomists is to co-design new G–M technologies for a non-stationary TPE. Understanding these conditional changes in crop productivity through the relevant sciences for each dimension, Genotype, Environment, and Management, creates opportunities to predict novel G–M technology combinations suitable to achieve sustainable crop productivity and global food security targets for the likely climate change scenarios. Here we consider critical foundations required for any prediction framework that aims to move us from the current unprepared state of describing G × E × M outcomes to a future responsive state equipped to predict the crop productivity consequences of G–M technology combinations for the range of environmental conditions expected for a complex, non-stationary TPE under the influences of climate change.

In pursuit of a better world: crop improvement and the CGIAR

Publisher: Oxford University Press (OUP)

Date: 22-05-2021

DOI: 10.1093/JXB/ERAB226

Abstract: The CGIAR crop improvement (CI) programs, unlike commercial CI programs, which are mainly geared to profit though meeting farmers’ needs, are charged with meeting multiple objectives with target populations that include both farmers and the community at large. We compiled the opinions from & experts in the private and public sector on key strategies, methodologies, and activities that could the help CGIAR meet the challenges of providing farmers with improved varieties while simultaneously meeting the goals of: (i) nutrition, health, and food security (ii) poverty reduction, livelihoods, and jobs (iii) gender equality, youth, and inclusion (iv) climate adaptation and mitigation and (v) environmental health and bio ersity. We review the crop improvement processes starting with crop choice, moving through to breeding objectives, production of potential new varieties, selection, and finally adoption by farmers. The importance of multidisciplinary teams working towards common objectives is stressed as a key factor to success. The role of the distinct disciplines, actors, and their interactions throughout the process from crop choice through to adoption by farmers is discussed and illustrated.

An investigation of the grain yield adaptation of advanced CIMMYT wheat lines to water stress environments in Queensland. I. Crop physiological analysis

Publisher: CSIRO Publishing

Date: 1994

DOI: 10.1071/AR9940965

Abstract: Wheat improvement in Australia has made extensive use of germplasm developed by the International Maize and Wheat Improvement Center (CIMMYT). The opportunity for further yield improvement in Queensland was investigated by comparing CIMMYT lines and Queensland cultivars in irrigated and dryland environments at three locations. CIMMYT lines were identified, with greater than 20% yield advantage in in idual environments and between 15 and 20% yield advantage over the six environments. The line mean repeatability for yield was moderate (0.492), with the variance component for line by environment (L x E) interaction 4.2 times that for lines. Therefore, while the CIMMYT lines expressed considerable L x E interaction, there was scope for further yield improvement. The water stress differential between the irrigated and dryland environments at the three locations strongly influenced L x E interaction for grain yield. Pre-anthesis water stress generated more L x E interaction for grain yield than post-anthesis stress. At the two locations where pre-anthesis water stress was severe in the dryland environment, there was no association (P 0.05) between yield under irrigated and dryland conditions. However, at the location where there was little pre-anthesis stress and a degree of post-anthesis stress there was a strong association (P 0.01) between yield under irrigated and dryland conditions. Grain yield was positively associated with the yield component grain number per unit area in all environments. Grain weight showed little L x E interaction across environments and the majority of L x E interaction for grain yield resulted from L x E interaction associated with grain number per unit area. Grain number per unit area was positively associated with the component grains per fertile tiller but not tiller number per unit area. Grains per fertile tiller was in turn positively associated with total dry matter at anthesis however, there was no direct association between total dry matter at anthesis and grain number per unit area. There was a weak association between days to anthesis and grain yield in four of the six environments.

Advantage of single-trial models for response to selection in wheat breeding multi-environment trials

Publisher: Springer Science and Business Media LLC

Date: 20-12-2003

DOI: 10.1007/S00122-003-1541-4

Abstract: An investigation was conducted to evaluate the impact of experimental designs and spatial analyses (single-trial models) of the response to selection for grain yield in the northern grains region of Australia (Queensland and northern New South Wales). Two sets of multi-environment experiments were considered. One set, based on 33 trials conducted from 1994 to 1996, was used to represent the testing system of the wheat breeding program and is referred to as the multi-environment trial (MET). The second set, based on 47 trials conducted from 1986 to 1993, s led a more erse set of years and management regimes and was used to represent the target population of environments (TPE). There were 18 genotypes in common between the MET and TPE sets of trials. From indirect selection theory, the phenotypic correlation coefficient between the MET and TPE single-trial adjusted genotype means [ r(p(MT))] was used to determine the effect of the single-trial model on the expected indirect response to selection for grain yield in the TPE based on selection in the MET. Five single-trial models were considered: randomised complete block (RCB), incomplete block (IB), spatial analysis (SS), spatial analysis with a measurement error (SSM) and a combination of spatial analysis and experimental design information to identify the preferred (PF) model. Bootstrap-res ling methodology was used to construct multiple MET data sets, ranging in size from 2 to 20 environments per MET s le. The size and environmental composition of the MET and the single-trial model influenced the r(p(MT)). On average, the PF model resulted in a higher r(p(MT)) than the IB, SS and SSM models, which were in turn superior to the RCB model for MET sizes based on fewer than ten environments. For METs based on ten or more environments, the r(p(MT)) was similar for all single-trial models.

Genotypic variation for drought stress response traits in soybean. II. Inter-relations between epidermal conductance, osmotic potential, relative water content, and plant survival

Publisher: CSIRO Publishing

Date: 2008

DOI: 10.1071/AR07160

Abstract: As part of a project exploring the potential for using leaf physiological traits to improve drought tolerance in soybean, studies were conducted to explore whether epidermal conductance (ge), osmotic potential (π), and relative water content (RWC) influenced turgor maintenance and ultimately the survival of droughted plants. In a glasshouse study, plants of 8 soybean genotypes that showed different expression of the traits were grown in well watered soil-filled beds for 21 days and then exposed to terminal water deficit stress. The trends in each trait were then monitored periodically until plant death. Genotypic differences were observed in the rate of decline in RWC as the soil dried, in the temporal patterns of change in ge and π, in the duration of survival after watering ceased, and in the critical relative water content (RWCC) at which plants died. In general, ge became smaller and π became more negative as RWC declined and plants acclimated to the increasing stress. Genotypic differences in ge remained broadly consistent as RWC declined. In contrast, the genotypic rankings for π in stressed plants were poorly correlated with those for well watered plants, indicating differential genotypic capacity for osmotic adjustment (OA) in response to stress. Survival times among genotypes after stress commenced ranged from 27 to 41 days, while RWCC ranged from 49% down to 41%. The differences in survival time among the genotypes were able to be explained by genotypic differences in the rate of decline in RWC and in the RWCC, using a multiple linear regression relationship (R 2 = 0.94**). In turn, genotypic differences in the rate of decline in RWC were positively correlated (r = 0.75*) with ge at 70% RWC, and with OA over the drying period (r = 0.98**). In a second study in a controlled environment facility, leaf area retention at 90% soil water extraction was greatest in the one genotype that combined low ge, high OA, and low RWCC. Overall, the responses from the two studies were consistent with the hypothesis that turgor maintenance and ultimately leaf and plant survival of different genotypes during advanced stages of drought stress are enhanced by low ge, high OA capacity, and low RWCC.

Genotypic variation of osmotic adjustment and desiccation tolerance in contrasting sorghum inbred lines

Publisher: Elsevier BV

Date: 10-1993

DOI: 10.1016/0378-4290(93)90136-B

Genotypic variation for drought stress response traits in soybean. III. Broad-sense heritability of epidermal conductance, osmotic potential, and relative water content

Publisher: CSIRO Publishing

Date: 2008

DOI: 10.1071/AR07161

Abstract: The broad-sense heritability of 3 traits related to leaf survival in severely stressed plants was studied in several hybrid soybean populations. The 3 traits were epidermal conductance (ge), osmotic potential (π), and relative water content (RWC). The populations were generated by hybridising unrelated parental genotypes previously shown to differ in the 3 traits. ge (mm/s) was measured on well watered plants from 10 populations involving all combinations of 5 parental lines, grown in soil-filled beds in the glasshouse. π (MPa) and RWC (%) were measured on severely stressed plants of 3 populations involving all combinations of 3 different parents, growing into a terminal water deficit under a rainout shelter in the field. Broad-sense heritability for ge was significantly different from zero (P 0.05) in all 10 populations and ranged from 60% to 93%. Heritability estimates for π70 (the tissue osmotic potential at 70% RWC) ranged from 33% to 71%. Only two estimates were statistically significant (P 0.05) because of large standard errors and the fact that parental differences were smaller than previously observed. Broad-sense heritability for RWC of severely stressed plants ranged from 40% to 74%, and was statistically significant (P 0.05) for 2 of the 3 populations. For all 3 traits, F2 progeny distributions were consistent with quantitative inheritance with a high degree of additive gene action. It was concluded that capacity exists to breed varieties with low ge, low π70, and high RWC in stressed plants. However, in the case of osmotic potential, genotypes with lower π70 combined with greater precision of measurement would be needed than proved possible in these studies. Further, specific strategies would be needed to select for the critical RWC, the minimal RWC at which leaf tissues die and which provides a measure of tissue dehydration tolerance. More research is also needed to characterise the dynamic relations between ge, π, and RWC in influencing leaf survival in soybean, before they could be confidently used in a breeding program to improve drought tolerance.

Inheritance of anthracnose resistance in the tropical pasture legume Stylosanthes hamata

Publisher: CSIRO Publishing

Date: 1995

DOI: 10.1071/AR9951353

Abstract: Eight tetraploid accessions of the tropical pasture legume Stylosanthes hamata with varying levels of response to the anthracnose pathogen (Colletotrichum gloeosporioides) were crossed in a half diallel scheme. Based on mean disease severity ratings (MDR), two parents, 55830 and 75164, were grouped as resistant (R), 55828 and 65365 were susceptible (S), and the remaining four, cvv. Verano and Amiga and 65371 and 75162 were moderately resistant (MR). Of these, the two resistant parents appear to carry different genes for resistance. The MDR of 20 of the 28 F2 populations was significantly different from their mid-parent MDR and the expression of resistance, in most cases, was recessive. Only a limited number of the F2 distributions for crosses between RxS, RxMR and MRxS parents conformed to a single gene model. The inheritance patterns observed were considered to be predominantly quantitative. Variation for general combining ability, was as large as or larger than that for specific combining ability suggesting that a large proportion of the genetic differences among the parents was additive. The finding that the resistance is inherited as a quantitative trait is consistent with results on the epidemiology of anthracnose in tetraploid S. hamata.

Variation among low rainfall white clover (Trifolium repens L.) accessions for morphological attributes and herbage yield

Publisher: CSIRO Publishing

Date: 1995

DOI: 10.1071/EA9951109

Abstract: The importance of passport data on rainfall at collection sites of accessions as a guide to identifying germplasm to be used in the genetic improvement was assessed by using 40 white clover accessions from the germplasm collection at Glen Innes, New South Wales. This set together with 2 standard cultivars, Haifa and Huia, were evaluated in the field. The objectives were to: (i) estimate the magnitude of genotypic variation among accessions for morphological attributes and herbage yield in a dryland summer rainfall environment and (ii) compare estimates of genotypic variation for, and correlations among, the attributes and herbage yield for the 40 accessions with results from a study based on a random s le of accessions from the same collection. Herbage yield was measured in 4 seasons (autumn 1992-summer 1993) together with stolon and other plant attributes which were measured in 1 season (summer 1993). There was significant (P .05) variation for herbage yield among accessions. Hierarchical agglomerative classification was used to group the accessions based on herbage yield. This identified a single member group with greater herbage yield than the 2 groups which contained the cultivars Haifa and Huia. There was no association between the composition of the accession groups identified by classification and the passport data on average annual rainfall at the collection sites of accessions. There was some consistency between the estimates of repeatability, genotypic variation and genotypic correlations obtained from the low rainfall set of accessions used in this study and the random s le previously examined. It was concluded that selection of accessions from the collection for use in genetic improvement of herbage yield and the morphological attributes for dryland summer rainfall environments of the Northern Tablelands of New South Wales. should not be confined to specific groups originating from low rainfall regions.

Reproductive resilience but not root architecture underpin yield improvement in maize (Zea mays L.)

Publisher: Cold Spring Harbor Laboratory

Date: 10-2020

DOI: 10.1101/2020.09.30.320937

Abstract: Plants capture soil resources to produce the grains required to feed a growing population. Because plants capture water and nutrients through roots, it was proposed that changes in root systems architecture (RSA) underpin the three-fold increase in maize grain yield over the last century 1,2,3,4 . Within this framework, improvements in reproductive resilience due to selection are caused by increased water capture 1 . Here we show that both root architecture and yield have changed with decades of maize breeding, but not the water capture. Consistent with Darwinian agriculture 5 theory, improved reproductive resilience 6,7 enabled farmers increase the number of plants per unit land 8,9,10 , capture soil resources, and produced more dry matter and grain. Throughout the last century, selection operated to adapt roots to crowding, enabling reallocation of C from large root systems to the growing ear and the small roots of plants cultivated in high plant populations in modern agriculture.

Leaf water potential and osmotic adjustment as physiological traits to improve drought tolerance in rice

Publisher: Elsevier BV

Date: 07-2002

DOI: 10.1016/S0378-4290(02)00036-9

Revolutionizing agriculture with synthetic biology

Publisher: Springer Science and Business Media LLC

Date: 18-11-2019

DOI: 10.1038/S41477-019-0539-0

Abstract: Synthetic biology is here to stay and will transform agriculture if given the chance. The huge challenges facing food, fuel and chemical production make it vital to give synthetic biology that chance-notwithstanding the shifts in mindset, training and infrastructure investment this demands. Here, we assess opportunities for agricultural synthetic biology and ways to remove barriers to their realization.

Transgene by Germplasm Interactions Can Impact Transgene Evaluation

Publisher: Cold Spring Harbor Laboratory

Date: 23-10-2022

DOI: 10.1101/2022.10.22.513364

Abstract: Transgenes have been successfully commercialized for qualitatively inherited insect and herbicide resistance traits that show similar effects across genetic backgrounds. However, for quantitative traits like yield, genetic background may affect the measured transgene value. In this paper, we evaluated whether different genetic backgrounds impact the estimated value of a transgene for grain yield, ear height, and anthesis-silking interval for maize by developing isogenic pairs of lines with and without a transgene and testing them in hybrid combination with non-transgenic lines from a complementary heterotic group across eleven environments in the USA. Over all hybrid combinations, the transgene increased yield by 0.2 Mg ha −1 . Across multiple non-transgenic lines of the opposing heterotic group, the transgene effect within a line pair ranged from an increase of 0.8 Mg ha −1 for the NSS4 and SS7 transgenic lines to a reduction of 0.3 Mg ha −1 for the NSS5 transgenic line when compared to their non-transgenic isoline. Transgenic hybrids were often taller than non-transgenic hybrids (P .05). Anthesis to silking interval was reduced by 4□C growing degree units overall, but no transgene × genotype interaction was detected among line pairs. Our results show the importance of testing transgene efficacy across a large s le of elite hybrid pairs to assess the gene’s value. By only testing in a specific hybrid background, as may be done for qualitative traits like insect resistance, transgenes could be erroneously advanced or eliminated.

Breeding for low input conditions and consequences for participatory plant breeding: Examples from tropical maize and wheat

Publisher: Springer Science and Business Media LLC

Date: 2001

DOI: 10.1023/A:1017510928038

Evaluation of experimental designs and spatial analyses in wheat breeding trials

Publisher: Springer Science and Business Media LLC

Date: 2000

DOI: 10.1007/S001220050002

Evaluation of white clover (Trifolium repens L.) populations for summer moisture stress adaptation in Australia

Publisher: CSIRO Publishing

Date: 1999

DOI: 10.1071/A98141

Abstract: A genetic experiment was conducted using 80 full-sib families in irrigated and dryland treatments under the summer moisture stress conditions of the Northern Tablelands of New South Wales, over 3 years. This paper reports on the effects of climatic and soil moisture conditions, the genetic variation for stolon attributes and seasonal herbage yield, and the development of new recombinant genotypes in relation to the association between stolon attributes and herbage yield. Large components of variance were estimated for genotype-by-environment-by-year interactions for the attributes stolon density, number of branches, number of nodes, number of rooted nodes, stolon thickness, root diameter, internode length, and summer herbage yield. The combined analysis of variance across environments and years indicated the presence of genetic variation for the stolon attributes stolon density, number of branches, number of nodes, stolon thickness, internode length, and herbage yield. Crossing of the morphologically contrasting cultivars El Lucero × Tahora × Duron, and Barbian × El Lucero, resulted in generating genotypic recombinants with new associations between herbage yield and stolon density, number of branches, number of nodes, and number of rooted nodes. Evaluation of the full-sib families and check cultivars (cvv. Haifa and Huia) identified 5 full-sib families with relatively higher herbage yield, stolon density, number of branches, number of nodes, and number of rooted nodes than cultivars Haifa and Huia.

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

Publisher: Cold Spring Harbor Laboratory

Date: 14-10-2020

DOI: 10.1101/2020.10.13.338301

Abstract: Plant breeding programs are designed and operated over multiple cycles to systematically change the genetic makeup of plants to achieve improved trait performance for a Target Population of Environments (TPE). Within each cycle, selection applied to the standing genetic variation within a structured reference population of genotypes (RPG) is the primary mechanism by which breeding programs make the desired genetic changes. Selection operates to change the frequencies of the alleles of the genes controlling trait variation within the RPG. The structure of the RPG and the TPE has important implications for the design of optimal breeding strategies. The breeder’s equation, together with the quantitative genetic theory behind the equation, informs many of the principles for design of breeding programs. The breeder’s equation can take many forms depending on the details of the breeding strategy. Through the genetic changes achieved by selection, the cultivated varieties of crops (cultivars) are improved for use in agriculture. From a breeding perspective, selection for specific trait combinations requires a quantitative link between the effects of the alleles of the genes impacted by selection and the trait phenotypes of plants and their breeding value. This gene-to-phenotype link function provides the G2P map for one to many traits. For complex traits controlled by many genes, the infinitesimal model for trait genetic variation is the dominant G2P model of quantitative genetics. Here we consider motivations and potential benefits of using the hierarchical structure of crop models as CGM-G2P trait link functions in combination with the infinitesimal model for the design and optimisation of selection in breeding programs.

Industry‐Scale Evaluation of Maize Hybrids Selected for Increased Yield in Drought‐Stress Conditions of the US Corn Belt

Publisher: Wiley

Date: 07-2015

DOI: 10.2135/CROPSCI2014.09.0654

Grain nitrogen concentration differences among three sorghum hybrids with similar grain yield

Publisher: CSIRO Publishing

Date: 1999

DOI: 10.1071/A98029

Abstract: The differences in grain nitrogen (N) concentration among 3 sorghum (Sorghum bicolor (L.) Moench) hybrids with similar grain yield were examined under N-limiting conditions in relation to the availability of assimilate and N to grain. Several manipulation treatments [N fertiliser application, lower leaves shading, thinning (reduced plant population), whole canopy shading, canopy opening, spikelet removal] were imposed to alter the relative N and assimilate availability to grain under full irrigation supply. Grain N concentration increased by either increased grain N availability or yield reduction while maintaining N uptake. Grain N concentration, however, did not decrease in the treatments where relative abundance of N compared with assimilate was intended to be reduced. The minimum levels of grain N concentration differed from 0.95% (ATx623/RTx430) to 1.14% (DK55plus) in these treatments. Regardless of the extent of variation in assimilate and N supply to grain, the ranking of hybrids on grain N concentration was consistent across the manipulation treatments. For the 3 hybrids examined, higher grain N concentration was associated with higher N uptake during grain filling and, to a lesser extent, with higher N mobilisation. Hybrids with larger grain N accumulation had a larger number of grains. There was no tradeoff between grain N concentration and yield, suggesting that grain protein concentration can be improved without sacrificing yield potential.

Using crop simulation to generate genotype by environment interaction effects for sorghum in water-limited environments

Publisher: CSIRO Publishing

Date: 2002

DOI: 10.1071/AR01070

Abstract: Multi-environment trials (METs) used to evaluate breeding lines vary in the number of years that they s le. We used a cropping systems model to simulate the target population of environments (TPE) for 6 locations over 108 years for 54 ‘near-isolines’ of sorghum in north-eastern Australia. For a single reference genotype, each of 547 trials was clustered into 1 of 3 ‘drought environment types’ (DETs) based on a seasonal water stress index. Within sequential METs of 2 years duration, the frequencies of these drought patterns often differed substantially from those derived for the entire TPE. This was reflected in variation in the mean yield of the reference genotype. For the TPE and for 2-year METs, restricted maximum likelihood methods were used to estimate components of genotypic and genotype by environment variance. These also varied substantially, although not in direct correlation with frequency of occurrence of different DETs over a 2-year period. Combined analysis over different numbers of seasons demonstrated the expected improvement in the correlation between MET estimates of genotype performance and the overall genotype averages as the number of seasons in the MET was increased.

Preface to Special Issue: Complex traits and plant breeding—can we understand the complexities of gene-to-phenotype relationships and use such knowledge to enhance plant breeding outcomes?

Publisher: CSIRO Publishing

Date: 2005

DOI: 10.1071/AR05151

Gene-to-phenotype models and complex trait genetics

Publisher: CSIRO Publishing

Date: 2005

DOI: 10.1071/AR05154

Abstract: The premise that is explored in this paper is that in some cases, in order to make progress in the design of molecular breeding strategies for complex traits, we will need a theoretical framework for quantitative genetics that is grounded in the concept of gene-networks. We seek to develop a gene-to-phenotype (G→P) modelling framework for quantitative genetics that explicitly deals with the context-dependent gene effects that are attributed to genes functioning within networks, i.e. epistasis, gene × environment interactions, and pleiotropy. The E(NK) model is discussed as a starting point for building such a theoretical framework for complex trait genetics. Applying this framework to a combination of theoretical and empirical G→P models, we find that although many of the context-dependent effects of genetic variation on phenotypic variation can reduce the rate of genetic progress from breeding, it is possible to design molecular breeding strategies for complex traits that on average will outperform phenotypic selection. However, to realise these potential advantages, empirical G→P models of the traits will need to take into consideration the context-dependent effects that are a consequence of epistasis, gene × environment interactions, and pleiotropy. Some promising G→P modelling directions are discussed.

Enhanced interpretation of pattern analyses of environments: the use of blocks

Publisher: Elsevier BV

Date: 04-1994

DOI: 10.1016/0378-4290(94)90078-7

Modelling the nitrogen dynamics of maize crops – Enhancing the APSIM maize model

Publisher: Elsevier BV

Date: 10-2018

DOI: 10.1016/J.EJA.2017.12.007

Graphene and boron nitride lateral heterostructures for atomically thin circuitry

Publisher: Springer Science and Business Media LLC

Date: 08-2012

DOI: 10.1038/NATURE11408

Abstract: Precise spatial control over the electrical properties of thin films is the key capability enabling the production of modern integrated circuitry. Although recent advances in chemical vapour deposition methods have enabled the large-scale production of both intrinsic and doped graphene, as well as hexagonal boron nitride (h-BN), controlled fabrication of lateral heterostructures in these truly atomically thin systems has not been achieved. Graphene/h-BN interfaces are of particular interest, because it is known that areas of different atomic compositions may coexist within continuous atomically thin films and that, with proper control, the bandgap and magnetic properties can be precisely engineered. However, previously reported approaches for controlling these interfaces have fundamental limitations and cannot be easily integrated with conventional lithography. Here we report a versatile and scalable process, which we call 'patterned regrowth', that allows for the spatially controlled synthesis of lateral junctions between electrically conductive graphene and insulating h-BN, as well as between intrinsic and substitutionally doped graphene. We demonstrate that the resulting films form mechanically continuous sheets across these heterojunctions. Conductance measurements confirm laterally insulating behaviour for h-BN regions, while the electrical behaviour of both doped and undoped graphene sheets maintain excellent properties, with low sheet resistances and high carrier mobilities. Our results represent an important step towards developing atomically thin integrated circuitry and enable the fabrication of electrically isolated active and passive elements embedded in continuous, one-atom-thick sheets, which could be manipulated and stacked to form complex devices at the ultimate thickness limit.

Limited‐Transpiration Trait May Increase Maize Drought Tolerance in the US Corn Belt

Publisher: Wiley

Date: 11-2015

DOI: 10.2134/AGRONJ15.0016

Variation Among Maize Hybrids in Response to High Vapor Pressure Deficit at High Temperatures

Publisher: Wiley

Date: 2016

DOI: 10.2135/CROPSCI2015.02.0134

Global wheat production could benefit from closing the genetic yield gap

Publisher: Springer Science and Business Media LLC

Date: 07-07-2022

DOI: 10.1038/S43016-022-00540-9

Identification of research to improve the efficiency of breeding strategies for white clover in Australia - a review

Publisher: CSIRO Publishing

Date: 2002

DOI: 10.1071/AR01110

Abstract: A major challenge faced by today’s white clover breeder is how to manage resources within a breeding program. It is essential to utilise these resources with sufficient flexibility to build on past progress from conventional breeding strategies, but also take advantage of emerging opportunities from molecular breeding tools such as molecular markers and transformation. It is timely to review white clover breeding strategies. This background can then be used as a foundation for considering how to continue conventional plant improvement activities and complement them with molecular breeding opportunities. In this review, conventional white clover breeding strategies relevant to the Australian dryland target population environments are considered. Attention is given to: (i) availability of genetic variation, (ii) characterisation of germplasm collections, (iii) quantitative models for estimation of heritability, (iv) the role of multi-environment trials to accommodate genotype-by-environment interactions, (v) interdisciplinary research to understand adaptation to dryland environments, (vi) breeding and selection strategies, and (vii) cultivar structure. Current achievements in biotechnology with specific reference to white clover breeding in Australia are considered, and computer modelling of breeding programs is discussed as a useful integrative tool for the joint evaluation of conventional and molecular breeding strategies and optimisation of resource use in breeding programs. Four areas are identified as future research priorities: (i) capturing the potential genetic ersity among introduced accessions and ecotypes that are adapted to key constraints such as summer moisture stress and the use of molecular markers to assess the genetic ersity, (ii) understanding the underlying physiological/morphological root and shoot mechanisms involved in water use efficiency of white clover, with the objective of identifying appropriate selection criteria, (iii) estimation of quantitative genetic parameters of important morphological hysiological attributes to enable prediction of response to selection in target environments, and (iv) modelling white clover breeding strategies to evaluate the opportunities for integration of molecular breeding strategies with conventional breeding programs.

Yield response of rice (Oryza sativa L.) genotypes to drought under rainfed lowlands

Publisher: Elsevier BV

Date: 10-2004

DOI: 10.1016/J.FCR.2004.02.007

Back to the future: Implications of genetic complexity for hybrid breeding strategies

Publisher: Cold Spring Harbor Laboratory

Date: 22-10-2020

DOI: 10.1101/2020.10.21.349332

Abstract: Commercial hybrid breeding operations can be described as decentralized networks of smaller, more or less isolated breeding programs. There is further a tendency for the disproportionate use of successful inbred lines for generating the next generation of recombinants, which has led to a series of significant bottlenecks, particularly in the history of the North American and European maize germplasm. Both the decentralization and the disproportionate inbred use reduce effective population size and constrain the accessible genetic space. Under these conditions, long term response to selection is not expected to be optimal under the classical infinitesimal model of quantitative genetics. In this study we therefore aim to propose an alternative rational for the success of large breeding operations in the context of genetic complexity arising from the structure and properties of interactive genetic networks. For this we use simulations based on the NK model of genetic architecture. We indeed found that constraining genetic space and reducing effective population size, through program decentralization and disproportionate inbred use, is required to expose additive genetic variation and thus facilitate heritable genetic gains. These results introduce new insights into why the historically grown structure of hybrid breeding programs was successful in improving the yield potential of hybrid crops over the last century. We also hope that a renewed appreciation for “why things worked” in the past can guide the adoption of novel technologies and the design of future breeding strategies for navigating biological complexity.

Classifying genotypic data from plant breeding trials: a preliminary investigation using repeated checks

Publisher: Springer Science and Business Media LLC

Date: 12-1992

DOI: 10.1007/BF00222328

The Selective Values of Alleles in a Molecular Network Model Are Context Dependent

Publisher: Oxford University Press (OUP)

Date: 04-2004

DOI: 10.1534/GENETICS.166.4.1715

Abstract: Classical quantitative genetics has applied linear modeling to the problem of mapping genotypic to phenotypic variation. Much of this theory was developed prior to the availability of molecular biology. The current understanding of the mechanisms of gene expression indicates the importance of nonlinear effects resulting from gene interactions. We provide a bridge between genetics and gene network theories by relating key concepts from quantitative genetics to the parameters, variables, and performance functions of genetic networks. We illustrate this methodology by simulating the genetic switch controlling galactose metabolism in yeast and its response to selection for a population of in iduals. Results indicate that genes have heterogeneous contributions to phenotypes and that additive and nonadditive effects are context dependent. Early cycles of selection suggest strong additive effects attributed to some genes. Later cycles suggest the presence of strong context-dependent nonadditive effects that are conditional on the outcomes of earlier selection cycles. A single favorable allele cannot be consistently identified for most loci. These results highlight the complications that can arise with the presence of nonlinear effects associated with genes acting in networks when selection is conducted on a population of in iduals segregating for the genes contributing to the network.

A selection strategy to accommodate genotype-by-environment interaction for grain yield of wheat: managed-environments for selection among genotypes

Publisher: Springer Science and Business Media LLC

Date: 03-1995

DOI: 10.1007/BF00221995

Transpiration Response of Maize Hybrids to Atmospheric Vapour Pressure Deficit

Publisher: Wiley

Date: 07-12-2012

DOI: 10.1111/JAC.12010

Genotype-by-management interactions for grain yield and grain protein concentration of wheat

Publisher: Elsevier BV

Date: 2001

DOI: 10.1016/S0378-4290(00)00131-3

Genetic analysis of variation for grain yield and protein concentration in two wheat crosses

Publisher: CSIRO Publishing

Date: 1997

DOI: 10.1071/A96152

Abstract: Grain yield and protein concentration are two of the more important criteria for wheat breeding in Queensland. Three aspects of the inheritance of both of these traits can have an impact on achieving genetic progress: (i) the magnitude and form of the genetic correlation between the traits, (ii) the magnitude of genetic variation and genotype × environment interactions, and (iii) the importance of epistasis in genetic variation. These 3 factors were examined for 2 crosses in a multi- environment trial conducted in Queensland in 1989. Negative genetic correlations were found between grain yield and protein concentration in both crosses. Genetic variation and genotype × environment interactions were found to be important for both traits. There was little evidence for the existence of significant additive × additive epistasis for either trait and the genotype × environment interactions were predominantly additive × environment in nature. From both crosses, progeny combining the high yield and high protein levels of the parents were identified. This suggests that there was a degree of independent segregation of the genes controlling grain yield and protein concentration in both crosses. Therefore, simultaneous genetic progress for yield and protein concentration is possible in Queensland environments.

Can we harness digital technologies and physiology to hasten genetic gain in U.S. maize breeding?

Publisher: Cold Spring Harbor Laboratory

Date: 25-02-2021

DOI: 10.1101/2021.02.23.432477

Abstract: Genetic gain in breeding programs depends on the predictive skill of genotype-to-phenotype algorithms and precision of phenotyping, both integrated with well-defined breeding objectives for a target population of environments (TPE). The integration of physiology and genomics could improve predictive skill by capturing additive and non-additive interaction effects of genotype (G), environment (E), and management (M). Precision phenotyping at managed stress environments (MSEs) can elicit physiological expression of processes that differentiate germplasm for performance in target environments, thus enabling algorithm training. Gap analysis methodology enables design of GxM technologies for target environments by assessing the difference between current and attainable yields within physiological limits. Harnessing digital technologies such as crop growth model-whole genome prediction (CGM-WGP) and gap analysis, and MSEs, can hasten genetic gain by improving predictive skill and definition of breeding goals in the U.S. maize production TPE. A half-diallel maize experiment resulting from crossing 9 elite maize inbreds was conducted at 17 locations in the TPE and 6 locations at MSEs between 2017 and 2019. Analyses over 35 families represented by 2367 hybrids demonstrated that CGM-WGP offered a predictive advantage ( y ) compared to WGP that increased with occurrence of drought as measured by decreasing whole-season evapotranspiration (ET log( y ) = 0.80(±0.6) − 0.006(±0.001) × ET r 2 = 0.59 df = 21). Predictions of unobserved physiological traits using the CGM, akin to digital phenotyping, were stable. This understanding of germplasm response to ET enables predictive design of opportunities to close productivity gaps. We conclude that enabling physiology through digital methods can hasten genetic gain by improving predictive skill and defining breeding objectives bounded by physiological realities.

Radiation use efficiency increased over a century of maize (Zea mays L.) breeding in the US corn belt

Publisher: Oxford University Press (OUP)

Date: 30-05-2022

DOI: 10.1093/JXB/ERAC212

Abstract: In the absence of stress, crop growth depends on the amount of light intercepted by the canopy and the conversion efficiency [radiation use efficiency (RUE)]. This study tested the hypothesis that long-term genetic gain for grain yield was partly due to improved RUE. The hypothesis was tested using 30 elite maize hybrids commercialized in the US corn belt between 1930 and 2017. Crops grown under irrigation showed that pre-flowering crop growth increased at a rate of 0.11 g m–2 year–1, while light interception remained constant. Therefore, RUE increased at a rate of 0.0049 g MJ–1 year–1, translating into an average of 3 g m–2 year–1 of grain yield over 100 years of maize breeding. Considering that the harvest index has not changed for crops grown at optimal density for the hybrid, the cumulative RUE increase over the history of commercial maize breeding in the USA can account for ~32% of the documented yield trend for maize grown in the central US corn belt. The remaining RUE gap between this study and theoretical maximum values suggests that a yield improvement of a similar magnitude could be achieved by further increasing RUE.

Computer simulation of a selection strategy to accommodate genotype environment interactions in a wheat recurrent selection programme

Publisher: Wiley

Date: 03-1999

DOI: 10.1046/J.1439-0523.1999.118001017.X

Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction

Publisher: CSIRO Publishing

Date: 2014

DOI: 10.1071/CP14007

Abstract: For the foreseeable future, plant breeding methodology will continue to unfold as a practical application of the scaling of quantitative biology. These efforts to increase the effective scale of breeding programs will focus on the immediate and long-term needs of society. The foundations of the quantitative dimension will be integration of quantitative genetics, statistics, gene-to-phenotype knowledge of traits embedded within crop growth and development models. The integration will be enabled by advances in quantitative genetics methodology and computer simulation. The foundations of the biology dimension will be integrated experimental and functional gene-to-phenotype modelling approaches that advance our understanding of functional germplasm ersity, and gene-to-phenotype trait relationships for the native and transgenic variation utilised in agricultural crops. The trait genetic knowledge created will span scales of biology, extending from molecular genetics to multi-trait phenotypes embedded within evolving genotype–environment systems. The outcomes sought and successes achieved by plant breeding will be measured in terms of sustainable improvements in agricultural production of food, feed, fibre, biofuels and other desirable plant products that meet the needs of society. In this review, ex les will be drawn primarily from our experience gained through commercial maize breeding. Implications for other crops, in both the private and public sectors, will be discussed.

Relationships among analytical methods used to study genotypic variation and genotype-by-environment interaction in plant breeding multi-environment experiments

Publisher: Springer Science and Business Media LLC

Date: 07-1994

DOI: 10.1007/BF01240919

Investigations into the emergent properties of gene-to-phenotype networks across cycles of selection: a case study of shoot branching in plants

Publisher: Oxford University Press (OUP)

Date: 2022

DOI: 10.1093/INSILICOPLANTS/DIAC006

Abstract: Predictive breeding is now widely practised in crop improvement programmes and has accelerated selection response (i.e. the amount of genetic gain between breeding cycles) for complex traits. However, world food production needs to increase further to meet the demands of the growing human population. The prediction of complex traits with current methods can be inconsistent across different genetic, environmental and agronomic management contexts because the complex relationships between genomic and phenotypic variation are not well accounted for. Therefore, developing gene-to-phenotype network models for traits that integrate the knowledge of networks from systems biology, plant and crop physiology with population genomics has been proposed to close this gap in predictive modelling. Here, we develop a gene-to-phenotype network for shoot branching, a critical developmental pathway underpinning harvestable yield for many crop species, as a case study to explore the value of developing gene-to-phenotype networks to enhance understanding of selection responses. We observed that genetic canalization is an emergent property of the complex interactions among shoot branching gene-to-phenotype network components, leading to the accumulation of cryptic genetic variation, reduced selection responses and large variation in selection trajectories across populations. As genetic canalization is expected to be pervasive in traits, such as grain yield, that result from interactions among multiple genes, traits, environments and agronomic management practices, the need to model traits in crop improvement programmes as outcomes of gene-to-phenotype networks is highlighted as an emerging opportunity to advance our understanding of selection response and the efficiency of developing resilient crops for future climates.

Atomically Thin Ohmic Edge Contacts Between Two-Dimensional Materials

Publisher: American Chemical Society (ACS)

Date: 16-06-2016

DOI: 10.1021/ACSNANO.6B02879

Abstract: With the decrease of the dimensions of electronic devices, the role played by electrical contacts is ever increasing, eventually coming to dominate the overall device volume and total resistance. This is especially problematic for monolayers of semiconducting transition-metal dichalcogenides (TMDs), which are promising candidates for atomically thin electronics. Ideal electrical contacts to them would require the use of similarly thin electrode materials while maintaining low contact resistances. Here we report a scalable method to fabricate ohmic graphene edge contacts to two representative monolayer TMDs, MoS2 and WS2. The graphene and TMD layer are laterally connected with wafer-scale homogeneity, no observable overlap or gap, and a low average contact resistance of 30 kΩ·μm. The resulting graphene edge contacts show linear current-voltage (I-V) characteristics at room temperature, with ohmic behavior maintained down to liquid helium temperatures.

An investigation of the grain yield adaptation of advanced CIMMYT wheat lines to water stress environments in Queensland. II. Classification analysis

Publisher: CSIRO Publishing

Date: 1994

DOI: 10.1071/AR9940985

Abstract: The objective of this study was to use classification methodology to characterize the genotypic variation and line by environment (L x E) interaction for grain yield of a s le of advanced CIMMYT wheat lines and three local check cultivars tested over six Queensland environments. The environments were managed to differ in the magnitude of water stress they imposed on the lines at the critical developmental stage of anthesis. The grouping of lines was based on grain yield. The yield differences among the groups were investigated in terms of yield components and dry matter production and partitioning attributes. Groups of CIMMYT lines which outyielded the two groups which contained the three Queensland cultivars were identified. The yield advantage of the groups of CIMMYT lines decreased with increasing severity of water stress at anthesis and in the environment where the most severe stress was characterized there were no yield differences among the groups of lines. The yield advantage of the groups of CIMMYT lines was generally associated with a higher number of grains per unit area and in some cases a higher grain size. While phenology variation could account for some of the yield differences among the line groups there was considerable yield variation among line groups with similar phenology patterns across the environments. Additional measurements taken on the lines to characterize differences in dry matter production and the partitioning of the dry matter to yield components were not effective in explaining the yield variation among the groups of lines after the effects of phenology were taken into account. While the incidence of the large L x (water-stress) interactions encountered in this study would complicate selection for yield, the identification of groups of advanced CIMMYT lines which outyielded the Queensland cultivars in five of the six environments suggests that the L x (water stress) interactions do not preclude scope for further improvement of grain yield of wheat in Queensland.

Sustained improvement in tolerance to water deficit accompanies maize yield increase in temperate environments

Publisher: Wiley

Date: 10-09-2022

DOI: 10.1002/CSC2.20781

Abstract: Studies at a regional scale suggest that although maize ( Zea mays L.) yield increased substantially, sensitivity to water deficit also increased concurrently with crop improvement. This study assessed changes in yield and yield stability after two decades of breeding by evaluating two cohorts of hybrids released by the AQUAmax program and comparing them to a non‐AQUAmax control. Studies were conducted in 2019 and 2020 seasons at four sites under well‐watered, moderate and severe stress conditions. Plant densities varied from 2.5 to 12.5 pl m−2. AQUAmax hybrids yielded more than non‐AQUAmax hybrids under water deficit conditions with the magnitude of the difference dependent on plant density. The sensitivity in yield across environments with a wide range of total crop evapotranspiration (350–800 mm) was lower for AQUAmax than non‐AQUAmax, so both yield and yield under stress conditions (yield stability), were enhanced for AQUAmax hybrids. The median differences between observed yields and the 80% quantile yield–evapotranspiration front were 379 for AQUAmax and 427 g m −2 for non‐AQUAmax hybrids. We conclude that deliberate selection of hybrids for yield performance under water deficit underpinned the sustained improvement in yield stability after two decades of drought breeding. Future research should focus on understanding the root causes for the suboptimal utilization of drought tolerant maize for the ersity of environments at a regional scale.

Some vocabulary and grammar for the analysis of multi-environment trials, as applied to the analysis of FPB and PPB trials

Publisher: Springer Science and Business Media LLC

Date: 2001

DOI: 10.1023/A:1017591407285

The impact of genotype multiply environment interactions for sugar yield on the use of indirect selection in southern Queensland

Publisher: CSIRO Publishing

Date: 1993

DOI: 10.1071/EA9930629

Abstract: To develop a strategy to improve the efficiency of selection, indirect selection and pattern analysis were used to examine the magnitude and form of genotype x environment (GE) interactions for sugar yield in sugarcane clones in southern Queensland. Clone x location interactions were the predominant source of clone X environment interactions and were much larger than clone x crop-year and clone x location x crop-year interactions. Both the indirect selection study and the pattern analysis emphasised the relative magnitude of these sources of interactions. Pattern analysis strongly associated crop classes at each location, and indirect selection analysis emphasised an opportunity to exploit correlated genetic advance between crop classes within a location. These suggest that more emphasis should be placed on s ling a greater number of locations than on the testing of clonal ratooning ability within locations. This would improve the chances of obtaining both broadly and specifically adapted sugarcane varieties.

A Gene Regulatory Network Model for Floral Transition of the Shoot Apex in Maize and Its Dynamic Modeling

Publisher: Public Library of Science (PLoS)

Date: 17-08-2012

DOI: 10.1371/JOURNAL.PONE.0043450

Predicting grain yield in Australian environments using data from CIMMYT international wheat performance trials. 2. The application of classification to identify environmental relationships which expl

Publisher: Elsevier BV

Date: 03-1993

DOI: 10.1016/0378-4290(93)90040-T

Using clusters of computers for large QU-GENE simulation experiments

Publisher: Oxford University Press (OUP)

Date: 02-2001

DOI: 10.1093/BIOINFORMATICS/17.2.194

Abstract: Summary: The QU-GENE Computing Cluster (QCC) is a hardware and software solution to the automation and speedup of large QU-GENE (QUantitative GENEtics) simulation experiments that are designed to examine the properties of genetic models, particularly those that involve factorial combinations of treatment levels. QCC automates the management of the distribution of components of the simulation experiments among the networked single-processor computers to achieve the speedup. Contact: k.micallef@mailbox.uq.edu.au Supplementary information: pig.ag.uq.edu.au/qu-gene/cluster.htm * To whom correspondence should be addressed.

Interpretation of randomly amplified polymorphic DNA marker data for fingerprinting sweet potato (Ipomoea batatas L.) genotypes

Publisher: Springer Science and Business Media LLC

Date: 06-1994

DOI: 10.1007/BF00223641

Addressing Research Bottlenecks to Crop Productivity

Publisher: Elsevier BV

Date: 06-2021

DOI: 10.1016/J.TPLANTS.2021.03.011

Influence of rate of development of water deficit on the expression of maximum osmotic adjustment and desiccation tolerance in three grain sorghum lines

Publisher: Elsevier BV

Date: 11-1996

DOI: 10.1016/S0378-4290(96)01032-5

Rainfed lowland rice breeding strategies for Northeast Thailand II. Comparison of intrastation and interstation selection

Publisher: Elsevier BV

Date: 11-1999

DOI: 10.1016/S0378-4290(99)00057-X

Reproductive resilience but not root architecture underpins yield improvement under drought in maize

Publisher: Oxford University Press (OUP)

Date: 25-05-2021

DOI: 10.1093/JXB/ERAB231

Abstract: Because plants capture water and nutrients through roots, it was proposed that changes in root systems architecture (RSA) might underpin the 3-fold increase in maize (Zea mays L.) grain yield over the last century. Here we show that both RSA and yield have changed with decades of maize breeding, but not the crop water uptake. Results from X-ray phenotyping in controlled environments showed that single cross (SX) hybrids have smaller root systems than double cross (DX) hybrids for root diameters between 2465 µm and 181µm (P& .05). Soil water extraction measured under field conditions ranged between 2.6 mm d–1 and 2.9 mm d–1 but were not significantly different between SX and DX hybrids. Yield and yield components were higher for SX than DX hybrids across densities and irrigation (P& .001). Taken together, the results suggest that changes in RSA were not the cause of increased water uptake but an adaptation to high-density stands used in modern agriculture. This adaptation may have contributed to shift in resource allocation to the ear and indirectly improved reproductive resilience. Advances in root physiology and phenotyping can create opportunities to maintain long-term genetic gain in maize, but a shift from ideotype to crop and production system thinking will be required.

A methodology for analysis of sugarcane productivity trends. 2. Comparing variety trials with commercial productivity

Publisher: CSIRO Publishing

Date: 2004

DOI: 10.1071/AR03074

Abstract: Previous research has reported both agreements and serious anomalies in relationships between production attributes of sugarcane varieties in variety trials (VTs) and commercial production (CP). This paper examines VT and CP data for tonnes of cane per hectare (TCH) and sugar content (CCS). Data, analysed by REML, included 107 VTs and 54 CP mill years for 9 varieties from the mill districts of Mulgrave, Babinda, and Tully for harvest years 1982–99. Important consistencies included high TCH of Q152, high CCS of Q117 and Q120, and low CCS of H56-752. Significant anomalies existed with respect to TCH for Q113, Q117, Q120, Q122, Q138, and H56-752 and to CCS for Q113 and Q124. Investigation of these anomalies was assisted by access to independent REML analyses of CP data for 65 692 in idual Tully cane blocks from 1988 to 1999 and by the knowledge of persons familiar with the preferential uses of varieties by farmers. Minor anomalies were due to limited year or mill area data. Q124 TCH was deemed to be decreased and its CCS increased by severe disease in Babinda CP in the extremely wet 1998 and 1999 seasons. Other serious anomalies have credible but unsubstantiated explanations. The most convincing, for Q113, Q117, Q138, and H56-752, are that these varieties were deployed unevenly with regard to late season harvesting, predominant use or avoidance on high fertility soils, or use confined to low fertility sandy soils, respectively. Uneven deployment results in confounding of these effects in the varietal CP statistics at mill area level. It is concluded that VTs cannot be enhanced to anticipate or evaluate most effects of uneven deployment. They give adequate predictions of relative CP performance for varieties deployed evenly across confounding influences. Routine analyses of in idual block CP data would be useful and enhanced by addition of relevant information to the block records.

Genotypic variation for drought stress response traits in soybean. I. Variation in soybean and wild Glycine spp. for epidermal conductance, osmotic potential, and relative water content

Publisher: CSIRO Publishing

Date: 2008

DOI: 10.1071/AR07159

Abstract: Studies were undertaken to assess genotypic variation in soybean and related wild species for traits with putative effects on leaf turgor maintenance in droughted plants. Traits of interest were (i) epidermal conductance (ge) which influences the rate of water loss from stressed leaves after stomatal closure (ii) osmotic adjustment (OA) as indicated by tissue osmotic potential (π), which potentially affects the capacity to withdraw water at low soil water potential and (iii) relative water content (RWC) at incipient leaf death (critical relative water content, RWCC), which is a measure of the dehydration tolerance of leaf tissue. The germplasm comprised a erse set of 58 soybean genotypes, 2 genotypes of the annual wild species G. soja and 9 genotypes representing 6 perennial wild Glycine spp. indigenous/endemic to Australia. Seedling plants were grown in soil-filled beds in the glasshouse and exposed to terminal water deficit stress from the second trifoliolate leaflet stage (21 days after sowing). Measurements were made on well watered plants, moderately stressed plants, and at incipient plant death, in 2 separate studies. In both studies, there were significant genotypic differences in all 3 traits in the stressed plants. However, across the 3 s le times, ge decreased and the absolute magnitude of π increased, indicating that the expression of these traits changed as the plants acclimated to the stress. RWC was therefore used as a covariate to adjust the genotypic values of π and ge in order to facilitate comparison at a consistent plant water status of 70% RWC. There was statistically significant genotypic variation for the adjusted values, ge70 and π70, in both studies, and genotypic correlations between the 2 studies were significant (P 0.05) and positive for all 3 traits: ge70 (r = 0.48), π70 (r = 0.50), and RWCC (r = 0.53). Among the soybean genotypes, there was at least a 2-fold range in ge70, a 0.7 MPa range in π70, and a 12 percentage point range in RWCC. Some of the perennial wild genotypes exhibited lower values of ge and RWCC and greater OA than soybean and G. soja, consistent with adaptation to drier environments. While the repeatability of measurement between experiments was variable among genotypes, the studies confirmed the existence of genotypic differences for ge, OA, and RWCC in cultivated soybean, with a wider range among the wild germplasm.

Improving drought tolerance in maize: a view from industry

Publisher: Elsevier BV

Date: 11-2004

DOI: 10.1016/J.FCR.2004.07.003

A rapid PCR protocol for marker assisted detection of heterozygotes in segregating generations involving 1BL/1RS translocation and normal wheat lines

Publisher: CSIRO Publishing

Date: 2002

DOI: 10.1071/AR00088

Abstract: A rapid and reliable polymerase chain reaction (PCR)-based protocol was developed for detecting zygosity of the 1BL/1RS translocation in hexaploid wheat. The protocol involved a multiplex PCR with 2 pairs of oligonucleotide primers, rye-specific Ris-1 primers, and consensus 5S intergenic spacer (IGS) primers, and digestion of the PCR products with the restriction enzyme, MseI. A small piece of alkali-treated intact leaf tissue is used as a template for the PCR, thereby eliminating the necessity for DNA extraction. The test is simple, highly sensitive, and rapid compared with the other detection systems of 1BS1RS heterozygotes in hexaploid wheat. PCR results were confirmed with AFLP analyses. Diagnostic tests for 1BL/1RS translocation based on Sec-1-specific ELISA, screening for chromosome arm 1RS controlled rust resistance locus Yr9, and the PCR test differed in their ability to detect heterozygotes. The PCR test and rust test detected more heterozygotes than the ELISA test. The PCR test is being used to facilitate S1 family recurrent selection in the Germplasm Enhancement Program of the Australian Northern Wheat Improvement Program. A combination of the PCR zygosity test with other markers currently being implemented in the breeding program makes this test economical for 1BL/1RS characterisation of S1 families.

The 1BL/1RS translocation decreases grain yield of spring wheat germplasm in low yield environments of north-eastern Australia

Publisher: CSIRO Publishing

Date: 2011

DOI: 10.1071/CP10219

Abstract: Wheat (Triticum aestivum L.) lines containing the 1BL/1RS chromosome translocation yield up to 20% more than established wheat cultivars in some Queensland environments. However, 1BL/1RS germplasm possesses a quality defect known as ‘sticky dough’, which is incompatible with the high-speed dough-mixing processes used for bread production in Australia. Therefore, we investigated whether the 1BL/1RS translocation conveyed a yield advantage to locally adapted germplasm across a wide range of environments that was sufficient to justify attempting to overcome the ‘sticky dough’ defect either through plant breeding or by altering the mixing processes. Three sets of recombinant inbred lines (RILs) that segregated for the presence or absence of the 1BL/1RS translocation were developed from crosses between 1BL/1RS germplasm (Seri and Genaro) and established local cultivars (Hartog and Banks), and grown in 11 environments representing six sites across southern Queensland and northern New South Wales and two years. The effect of the 1BL/1RS translocation on grain yield depended on environment and genetic background. In semi-dwarf genotypes of the Hartog/Seri and Hartog/Genaro crosses, the 1BL/1RS RILs had lower grain yield than the 1B RILs in the three lowest yielding environments. This effect was associated with changes in grain number per unit area, suggesting that the negative yield effect of the translocation is expressed before, or at, anthesis. In the higher yielding environments, the 1BL/1RS translocation conveyed a yield advantage in semi-dwarf genotypes of the Banks/Seri cross, but had no consistent effect on yield in semi-dwarf genotypes of the Hartog/Seri and Hartog/Genaro crosses. The 1BL/1RS translocation was also associated with decreased yield in the double-dwarf genotypes of the Hartog/Seri cross across all environments. We conclude that the 1BL/1RS translocation is not useful for local breeding programs, as it decreased yield among the more advanced, semi-dwarf germplasm in low-yielding environments that potentially represent up to 85% of the target population of environments, and had no consistent positive effect on yield in this germplasm in higher yielding environments.

Soil water capture trends over 50 years of single-cross maize (Zea maysL.) breeding in the US corn-belt

Publisher: Oxford University Press (OUP)

Date: 10-2015

DOI: 10.1093/JXB/ERV430

Breeding drought-tolerant maize hybrids for the US corn-belt: discovery to product

Publisher: Oxford University Press (OUP)

Date: 04-03-2014

DOI: 10.1093/JXB/ERU064

Abstract: Germplasm, genetics, phenotyping, and selection, combined with a clear definition of product targets, are the foundation of successful hybrid maize breeding. Breeding maize hybrids with superior yield for the drought-prone regions of the US corn-belt involves integration of multiple drought-specific technologies together with all of the other technology components that comprise a successful maize hybrid breeding programme. Managed-environment technologies are used to enable scaling of precision phenotyping in appropriate drought environmental conditions to breeding programme level. Genomics and other molecular technologies are used to study trait genetic architecture. Genetic prediction methodology was used to breed for improved yield performance for drought-prone environments. This was enabled by combining precision phenotyping for drought performance with genetic understanding of the traits contributing to successful hybrids in the target drought-prone environments and the availability of molecular markers distributed across the maize genome. Advances in crop growth modelling methodology are being used to evaluate the integrated effects of multiple traits for their combined effects and evaluate drought hybrid product concepts and guide their development and evaluation. Results to date, lessons learned, and future opportunities for further improving the drought tolerance of maize for the US corn-belt are discussed.

Mixed model approaches for the identification of QTLs within a maize hybrid breeding program

Publisher: Springer Science and Business Media LLC

Date: 17-11-2009

DOI: 10.1007/S00122-009-1205-0

Genotype-by-environment interactions for grain yield associated with water availability at flowering in rainfed lowland rice

Publisher: Elsevier BV

Date: 03-2007

DOI: 10.1016/J.FCR.2006.10.003

A comparison of formal and participatory breeding approaches using selection theory

Publisher: Springer Science and Business Media LLC

Date: 2001

DOI: 10.1023/A:1017557307800

Classification of Maize Environments Using Crop Simulation and Geographic Information Systems

Publisher: Wiley

Date: 09-2005

DOI: 10.2135/CROPSCI2004.0370

Predicting trait phenotypes from knowledge of the topology of gene networks

Publisher: Cold Spring Harbor Laboratory

Date: 07-2021

DOI: 10.1101/2021.06.29.450449

Abstract: In many fields there is interest in manipulating genes and gene networks to realize improved trait phenotypes. The practicality of doing so, however, requires accepted theory on the properties of gene networks that is well-tested by empirical results. The extension of quantitative genetics to include models that incorporate properties of gene networks expands the long tradition of studying epistasis resulting from gene-gene interactions. Here we consider NK models of gene networks by applying concepts from graph theory and Boolean logic theory, motivated by a desire to model the parameters that influence predictive skill for trait phenotypes under the control of gene networks N defines the number of graph nodes, the number of genes in the network, and K defines the number of edges per node in the graph, representing the gene-gene interactions. We define and consider the attractor period of an NK network as an emergent trait phenotype for our purposes. A long-standing theoretical treatment of the dynamical properties of random Boolean networks suggests a transition from long to short attractor periods as a function of the average node degree K and the bias probability P in the applied Boolean rules. In this paper we investigate the appropriateness of this theory for predicting trait phenotypes on random and real microorganism networks through numerical simulation. We show that: (i) the transition zone between long and short attractor periods depends on the number of network nodes for random networks (ii) networks derived from metabolic reaction data on microorganisms also show a transition from long to short attractor periods, but at higher values of the bias probability than in random networks with similar numbers of network nodes and average node degree (iii) the distribution of phenotypes measured on microorganism networks shows more variation than random networks when the bias probability in the Boolean rules is above 0.75 and (iv) the topological structure of networks built from metabolic reaction data is not random, being best approximated, in a statistical sense, by a lognormal distribution. The implications of these results for predicting trait phenotypes where the genetic architecture of a trait is a gene network are discussed.

Crop improvement can accelerate agriculture adaptation to societal demands and climate change

Publisher: Cold Spring Harbor Laboratory

Date: 21-09-2023

DOI: 10.1101/2023.09.19.558447

Maize ARGOS1 (ZAR1) transgenic alleles increase hybrid maize yield

Publisher: Oxford University Press (OUP)

Date: 11-11-2013

DOI: 10.1093/JXB/ERT370

Accelerating crop genetic gains with genomic selection

Publisher: Springer Science and Business Media LLC

Date: 19-12-2019

DOI: 10.1007/S00122-018-3270-8

Abstract: Genomic prediction based on additive genetic effects can accelerate genetic gain. There are opportunities for further improvement by including non-additive effects that access untapped sources of genetic ersity. Several studies have reported a worrying gap between the projected global future demand for plant-based products and the current annual rates of production increase, indicating that enhancing the rate of genetic gain might be critical for future food security. Therefore, new breeding technologies and strategies are required to significantly boost genetic improvement of future crop cultivars. Genomic selection (GS) has delivered considerable genetic gain in animal breeding and is becoming an essential component of many modern plant breeding programmes as well. In this paper, we review the lessons learned from implementing GS in livestock and the impact of GS on crop breeding, and discuss important features for the success of GS under different breeding scenarios. We highlight major challenges associated with GS including rapid genotyping, phenotyping, genotype-by-environment interaction and non-additivity and give ex les for opportunities to overcome these issues. Finally, the potential of combining GS with other modern technologies in order to maximise the rate of crop genetic improvement is discussed, including the potential of increasing prediction accuracy by integration of crop growth models in GS frameworks.

Retrospective study in US commercial sorghum breeding: I. Genetic gain in relation to relative maturity

Publisher: Wiley

Date: 13-02-2023

DOI: 10.1002/CSC2.20897

Abstract: Sorghum [ Sorghum bicolor (L.) Moench] is an important staple food for human consumption and a source of animal feed in the semiarid regions of the world. Sustained positive rates of crop improvement are necessary to supply food and feed to a growing population. However, land allocated to sorghum and its inclusion in production systems has been in constant decline. Here we report the rate of sorghum genetic gain in a commercial breeding program in the United States and provide evidence that a modest yield improvement is an important factor limiting land allocation to this crop. A 6‐year study that evaluated 50 sorghum genotypes commercialized between the decades of 1960 and 2010 was conducted in 19 environments within the US Sorghum Belt region. Yield varied between 500 and 850 g m −2 . Here we show a positive rate of genetic gain of 2.63 g m −2 y −1 on average across three different maturity groups grown in the United States. Rates ranged from 2.1 to 4.3 g m −2 y −1 across maturity groups. This result contrasts with a stagnant rate of crop improvement for many regions of the world, yet the rates are insufficient to reverse the negative trend in planted area. Breeding technologies are proposed to hasten genetic gain in sorghum to reverse the loss of on‐farm agricultural bio ersity.

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

Publisher: Oxford University Press (OUP)

Date: 11-2007

DOI: 10.1534/GENETICS.107.071068

Abstract: Complex quantitative traits of plants as measured on collections of genotypes across multiple environments are the outcome of processes that depend in intricate ways on genotype and environment simultaneously. For a better understanding of the genetic architecture of such traits as observed across environments, genotype-by-environment interaction should be modeled with statistical models that use explicit information on genotypes and environments. The modeling approach we propose explains genotype-by-environment interaction by differential quantitative trait locus (QTL) expression in relation to environmental variables. We analyzed grain yield and grain moisture for an experimental data set composed of 976 F5 maize testcross progenies evaluated across 12 environments in the U.S. corn belt during 1994 and 1995. The strategy we used was based on mixed models and started with a phenotypic analysis of multi-environment data, modeling genotype-by-environment interactions and associated genetic correlations between environments, while taking into account intraenvironmental error structures. The phenotypic mixed models were then extended to QTL models via the incorporation of marker information as genotypic covariables. A majority of the detected QTL showed significant QTL-by-environment interactions (QEI). The QEI were further analyzed by including environmental covariates into the mixed model. Most QEI could be understood as differential QTL expression conditional on longitude or year, both consequences of temperature differences during critical stages of the growth.

Genotype by environment interactions affecting grain sorghum. III. Temporal sequences and spatial patterns in the target population of environments

Publisher: CSIRO Publishing

Date: 2000

DOI: 10.1071/AR99022

Abstract: The variable nature of rainfall in north-eastern Australia confounds the process of selecting sorghum hybrids that are broadly adapted. This paper uses a crop simulation model to characterise the drought environment types (ET) that occur in the target population of environments (TPE) for dryland sorghum. Seventy seasons (1921–1990) of simulations of the yield of a sorghum genotype and the associated within-season sequence of a stress index were conducted for a small TPE of 6 locations and also for a large TPE of 211 locations that attempted to represent the entire sorghum region. Previously, using the small dataset of 6 locations, pattern analysis enabled us to group seasonal stress indices from each trial into major ETs: ‘low terminal stress’ (ET1), severe terminal stress (ET2), and intermediate mid-season/terminal stress (ET3) in the ratio 33 : 38 : 29. When the dataset was broken into a sequence of 16 multi-environment trials (METs), each of 3 years and 6 locations, the ratios of ET1 : ET2 : ET3 differed greatly among METs, i.e. any single MET was not randomly s ling the TPE. Hence, for any MET, the average yield (GVu) was not the same as the overall mean of the entire 70-year dataset. If the trial yields were weighted according to the ratio of ET1 : ET2 : ET3 in the overall TPE, then GVw (s.d. = 0.13) for a single MET was much closer to the overall mean than was GVu (0.38). For different METs, the values of GVw were up to 30% higher or 15% lower than GVu. Across METs, the difference between GVu and GVw was positively correlated (r = 0.88, n = 16, P 0.05) with the frequency of ET1 (‘low terminal stress’) encountered within the MET and negatively correlated (r = −0.82) with the frequency of ET2. The value of weighting was confirmed by its ability to verify that two simulated genotypes had the same mean yield over many trials, even though they differed in their specific adaptation to the different ETs. The large TPE consisted of more than 15 000 simulations and was classified in 2 stages (within/among locations), repeated for each of 3 soil types. In years in which the simulation sowing criteria were met, the ratios of ET1 : ET2 : ET3 were about 4:2:4, 4:5:1, and 6:3:1 in the shallow, intermediate, and deep soils, respectively. Hence, over all soil types and locations, the sorghum TPE for northern Australia consists of at least 30% each of low terminal stress (ET1) or severe terminal stress (ET2) and these environment types need to be s led. The incidence and nature of the ‘intermediate midseason/terminal stress’ environment type (ET3) varies with soil type and location. Weighting genotype performance should improve the precision of the estimate of its broadly adapted value, and be of practical use in breeding programs in these variable environments. Although the ‘boundary conditions’ of the TPE are not yet resolved, this paper also shows that simulation and pattern analyses can be used to determine the structure of the abiotic TPE. Taking other factors into account (e.g. soil type distribution, shire production levels, and farm profit), selection trials could be weighted to improve selection for narrow or broad adaptation, depending on the purpose of the breeding program.

Determining appropriate group number and composition for data sets containing repeated check cultivars

Publisher: Elsevier BV

Date: 1993

DOI: 10.1016/0378-4290(93)90074-W

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

Publisher: Elsevier BV

Date: 10-2018

DOI: 10.1016/J.EJA.2018.01.007

Rainfed lowland rice breeding strategies for Northeast Thailand.

Publisher: Elsevier BV

Date: 11-1999

DOI: 10.1016/S0378-4290(99)00056-8

Genetic inference on quantitative traits through linkage and association studies

Publisher: CRC Press

Date: 05-08-2014

DOI: 10.1201/B17274

Genotype by environment interactions affecting grain sorghum. I. Characteristics that confound interpretation of hybrid yield

Publisher: CSIRO Publishing

Date: 2000

DOI: 10.1071/AR99020

Abstract: Past sorghum hybrid trials in north-eastern Australia have detected substantial genotype by environment (G×E) interactions for yield in s ling a variable target population of environments (TPE) that is affected by spatial and seasonal differences in crop water supply. Three datasets, comprising yields of commercial and final stage experimental hybrids and covering 9–17 years (Y) and up to 30 locations (L), were analysed to quantify variance components for trial error, genotypic (σ2g), and G×E (σ2gl, σ gy, and σ2gly) interaction effects. Whereas trial means varied 2–3-fold across seasons, a greater range was estimated for variance components of trial error (range of 0.05–0.5), G (0– .3), and G×L interaction (0.05– .0). There was substantial seasonal variation in the ratio of σ2g to (σ2g +σ2gl), and in two datasets, 73% of the seasonal σ2gl was due to poor genetic correlations among locations. This implies that any given set of hybrids in a random set of locations would be ranked differently from season to season. Analysis of locations over years detected 90% of the total G×E interaction as G×L×Y, rather than G×L or G×Y, although this was reduced by accounting for genotype maturity. To achieve repeatabilities of %, trials would need to be conducted over at least 5 years and 20 locations per year. The variable and unpredictable nature of much of the G×E interaction in the region implies that broad adaptation to different water regimes is required, unless prior knowledge of the seasonal weather can be used to choose ‘narrowly adapted’ cultivars. With current approaches, a large s le of environments is needed to identify such hybrids, and testing across locations and years is equally important. Alternative breeding strategies based on classifying environment types are discussed.

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

Publisher: CSIRO Publishing

Date: 2000

DOI: 10.1071/AR99021

Abstract: Genotype × environment (G×E) interactions due to variation in soil moisture and rainfall complicate the interpretation of sorghum hybrid performance trials over locations (L) and years (Y). This paper aims to use pattern analysis to explain measures of the G×L interaction for yield, and whether these can, in turn, be explained using simulation models to determine the occurrence of environment types (within-season patterns of drought). The aim of this work is to simplify the analysis of G×E by explaining it in terms of interactions of genotypes with environment types (ET) that are not ‘fixed’ to locations and years. In a sequential analysis of 17 seasons, 18 locations were separated into groups that tended to represent either the northern (i.e. central Queensland, CQ) or southern Queensland (SQ) regions. For a subset of 6 locations, ordination partially explained differences among locations as being related to latitude (r = 0.88) and rainfall (r = −0.46), but they were better related (r 0.9) to the frequencies of 3 stress ETs as determined by long-term crop simulations. These 3 environment types were: (1) low stress (occurring in 33% of seasons) (2) severe terminal stress with an early-season (9%) or midseason time (29%) of onset and (3) intermediate terminal stress with a midseason (9%) or late-season (20%) time of onset. Low stress ETs were more common in two SQ locations than in CQ. Stress ETs as defined by simulation models and pattern analysis had more consistent relationships with simulated yields than did the fixed descriptors of locations and years. Sorghum hybrid trials for broad adaptation in Queensland should include locations at least from each of the 2 regions and the results should be interpreted in the context of the season in which they are conducted. To match the long-term patterns in the 6 locations of the analysis, trial yields would need to s le from at least 3 yield ranges: t/ha, 1–3.5 t/ha, and .5 t/ha. Additional seasons of testing are likely to be required when the locations used during a season do not adequately represent the target population of environments over all locations and years.

How can breeding contribute to more productive and sustainable rainfed lowland rice systems?

Publisher: Elsevier BV

Date: 11-1999

DOI: 10.1016/S0378-4290(99)00060-X

Grain Yield and Nitrogen Accumulation in Maize Hybrids Released during 1934 to 2013 in the US Midwest

Publisher: Wiley

Date: 05-2017

DOI: 10.2135/CROPSCI2016.08.0704

Prediction of hybrid performance in grain sorghum using RFLP markers

Publisher: Springer Science and Business Media LLC

Date: 02-2003

DOI: 10.1007/S00122-002-1144-5

Abstract: Heterosis is an important component of hybrid yield performance. Identifying high yielding hybrids is expensive and involves testing large numbers of hybrid combinations in multi-environment trials. Molecular marker ersity has been proposed as a more efficient method of selecting superior combinations. The aim of this study was to investigate the value of molecular marker-based distance information to identify high yielding grain sorghum hybrids in Australia. Data from 48 trials were used to produce hybrid performance-estimates for four traits (yield, height, maturity and stay green) for 162 hybrid combinations derived from 70 inbred parent lines. Each line was screened with 113 mapped RFLP markers. The Rogers distances between the parents of each hybrid were calculated from the marker information on a genome basis and in idually for each of the ten linkage groups of sorghum. Some of the inbred parents were related so the hybrids were classified into 75 groups with each group containing in idual hybrids that showed similar patterns of Rogers distances across linkage groups. Correlations between hybrid-group performance and hybrid-group Rogers distances were calculated. A significant correlation was observed between whole genome-based Rogers distance and yield ( r = 0.42). This association is too weak to be of value for identifying superior hybrid combinations. One reason for the generally poor association between parental genetic ersity and yield may be that important QTLs influencing heterosis are located in particular chromosome regions and not distributed evenly over the genome. Variation in the sign and magnitude of correlations between Rogers distance and hybrid-group performance for particular linkage groups observed in this study support this hypothesis. The concept of using ersity on in idual linkage groups to predict performance was explored. Using data from just two linkage groups 38% of the variation in hybrid performance for grain yield could be explained. A model combining phenotypic trait data and parental ersity on particular linkage groups explained 71% of the variation in grain yield and has potential for use in the selection of heterotic hybrids.

Genotypic variation for grain and stover yield of dryland (rabi) sorghum in India: 1. Magnitude of genotype×environment interactions

Publisher: Elsevier BV

Date: 09-2010

DOI: 10.1016/J.FCR.2010.05.013

Morphological and architectural development of root systems in sorghum and maize

Publisher: Springer Science and Business Media LLC

Date: 23-03-2010

DOI: 10.1007/S11104-010-0343-0

Use of Crop Growth Models with Whole‐Genome Prediction: Application to a Maize Multienvironment Trial

Publisher: Wiley

Date: 09-2016

DOI: 10.2135/CROPSCI2015.08.0512

Genotypic variation for grain and stover yield of dryland (rabi) sorghum in India 2. A characterisation of genotype×environment interactions

Publisher: Elsevier BV

Date: 09-2010

DOI: 10.1016/J.FCR.2010.05.014

Models for navigating biological complexity in breeding improved crop plants

Publisher: Elsevier BV

Date: 12-2006

DOI: 10.1016/J.TPLANTS.2006.10.006

Abstract: Progress in breeding higher-yielding crop plants would be greatly accelerated if the phenotypic consequences of making changes to the genetic makeup of an organism could be reliably predicted. Developing a predictive capacity that scales from genotype to phenotype is impeded by biological complexities associated with genetic controls, environmental effects and interactions among plant growth and development processes. Plant modelling can help navigate a path through this complexity. Here we profile modelling approaches for complex traits at gene network, organ and whole plant levels. Each provides a means to link phenotypic consequence to changes in genomic regions via stable associations with model coefficients. A unifying feature of the models is the relatively coarse level of granularity they use to capture system dynamics. Much of the fine detail is not directly required. Robust coarse-grained models might be the tool needed to integrate phenotypic and molecular approaches to plant breeding.

Loss of genetic diversity associated with selection for resistance to sorghum midge in Australian sorghum

Publisher: Springer Science and Business Media LLC

Date: 1998

DOI: 10.1023/A:1018311908636

Inhibitor screen for limited-transpiration trait among maize hybrids

Publisher: Elsevier BV

Date: 2015

DOI: 10.1016/J.ENVEXPBOT.2014.07.015

Yield response of rice (Oryza sativa L.) genotypes to drought under rainfed lowland

Publisher: Elsevier BV

Date: 2002

DOI: 10.1016/S0378-4290(01)00194-0

Hybrid variation for root system efficiency in maize: potential links to drought adaptation

Publisher: CSIRO Publishing

Date: 2016

DOI: 10.1071/FP15308

Abstract: Water availability can limit maize (Zea mays L.) yields, and root traits may enhance drought adaptation if they can moderate temporal patterns of soil water extraction to favour grain filling. Root system efficiency (RSE), defined as transpiration per unit leaf area per unit of root mass, represents the functional mass allocation to roots to support water capture relative to the allocation to aerial mass that determines water demand. The aims of this study were to identify the presence of hybrid variation for RSE in maize, determine plant attributes that drive these differences and illustrate possible links of RSE to drought adaptation via associations with water extraction patterns. In idual plants for a range of maize hybrids were grown in large containers in shadehouses in Queensland, Australia. Leaf area, shoot and root mass, transpiration, root distribution and soil water were measured in all or selected experiments. Significant hybrid differences in RSE existed. High RSE was associated with reduced dry mass allocation to roots and more efficient water capture per unit of root mass. It was also weakly negatively associated with total plant dry mass, reducing preanthesis water use. This could increase grain yield under drought. RSE provides a conceptual physiological framework to identify traits for high-throughput phenotyping in breeding programs.

Strategies and considerations for implementing genomic selection to improve traits with additive and non-additive genetic architectures in sugarcane breeding

Publisher: Springer Science and Business Media LLC

Date: 15-02-2021

DOI: 10.1007/S00122-021-03785-3

Genotypic variation for grain yield and grain nitrogen concentration among sorghum hybrids under different levels of nitrogen fertiliser and water supply

Publisher: CSIRO Publishing

Date: 1998

DOI: 10.1071/A97130

Abstract: Sorghum [Sorghum bicolor (L.) Moench] is often grown under nitrogen- or water-limited conditions, but there is little information on genotypic variation for grain yield and grain nitrogen (N) concentration under these conditions. This study examined the expression of specific adaptation of hybrids to these stress conditions and, secondly, the effect of N fertiliser application on yield and grain N concentration of the hybrids. Two experiments, one irrigated and the other under rainfed conditions, were conducted in 2 seasons to examine 14 hybrids grown under 3 levels of fertiliser N supply (0, 60, and 240 kg/ha). Genotypic variation for yield and grain N concentration was generally larger than the in˚uence of genotype environment (predominantly N and water) interactions. Genotypic variation for phenology was important in determining variation for yield and grain N concentration in high-input and rainfed conditions when N was not the limiting factor, but not under N-limiting conditions. Under high-input conditions (240 kg/ha of N fertiliser and irrigated), maturity date accounted for about 50% of the genotypic variation for grain yield (798-1049 g/m2), with later maturing hybrids having a higher yield. Maturity date had little effect on plant N content at maturity or N harvest index, and hence grain N concentration (1·67-2·01%) was negatively correlated with grain yield. Under N-limiting conditions, N fertiliser application had large effects on yield and/or grain N concentration in both well-watered and pre-anthesis water stress conditions. In the irrigated experiment, when N was limiting (0 and 60 kg/ha of N fertiliser), genotypic variation for grain yield (225-729 g/m2) was not related to that for maturity date. It was, however, related to the variation in N uptake and dry matter growth by anthesis in the non-fertilised treatment. There was significant genotypic variation for grain N concentration (0·94-1·26%), which was not explained by variation for grain yield. Under rainfed conditions, where severe pre-anthesis water stress occurred, phenology was important in determining about 40% of the genotypic variation for yield (69-286 g/m2). The late-flowering hybrids escaped the major impact of the pre-anthesis water stress, had reduced damage to panicle development, and had higher N utilisation, consequently producing higher grain yield. Grain N concentration (1·09-2·85%) was again negatively related with grain yield. Genetic improvement of N uptake is identified as a possible breeding strategy for raising productivity and quality of grain sorghum under N-limiting conditions.

Yield–trait performance landscapes: from theory to application in breeding maize for drought tolerance

Publisher: Oxford University Press (OUP)

Date: 11-2010

DOI: 10.1093/JXB/ERQ329

Abstract: The effectiveness of breeding strategies to increase drought resistance in crops could be increased further if some of the complexities in gene-to-phenotype (G → P) relations associated with epistasis, pleiotropy, and genotype-by-environment interactions could be captured in realistic G → P models, and represented in a quantitative manner useful for selection. This paper outlines a promising methodology. First, the concept of landscapes was extended from the study of fitness landscapes used in evolutionary genetics to the characterization of yield-trait-performance landscapes for agricultural environments and applications in plant breeding. Second, the E(NK) model of trait genetic architecture was extended to incorporate biophysical, physiological, and statistical components. Third, a graphical representation is proposed to visualize the yield-trait performance landscape concept for use in selection decisions. The methodology was demonstrated at a particular stage of a maize breeding programme with the objective of improving the drought tolerance of maize hybrids for the US Western Corn-Belt. The application of the framework to the genetic improvement of drought tolerance in maize supported selection of Doubled Haploid (DH) lines with improved levels of drought tolerance based on physiological genetic knowledge, prediction of test-cross yield within the target population of environments, and their predicted potential to sustain further genetic progress with additional cycles of selection. The existence of rugged yield-performance landscapes with multiple peaks and intervening valleys of lower performance, as shown in this study, supports the proposition that phenotyping strategies, and the directions emphasized in genomic selection can be improved by creating knowledge of the topology of yield-trait performance landscapes.

Inheritance of osmotic adjustment to water stress in three grain sorghum crosses

Publisher: Springer Science and Business Media LLC

Date: 04-1995

DOI: 10.1007/BF00222133

Use of drought response index for identification of drought tolerant genotypes in rainfed lowland rice

Publisher: Elsevier BV

Date: 10-2006

DOI: 10.1016/J.FCR.2006.03.003

Concepts and strategies for plant adaptation research in rainfed lowland rice

Publisher: Elsevier BV

Date: 11-1999

DOI: 10.1016/S0378-4290(99)00048-9

Back to the future: implications of genetic complexity for the structure of hybrid breeding programs

Publisher: Oxford University Press (OUP)

Date: 05-05-2021

DOI: 10.1093/G3JOURNAL/JKAB153

Abstract: Commercial hybrid breeding operations can be described as decentralized networks of smaller, more or less isolated breeding programs. There is further a tendency for the disproportionate use of successful inbred lines for generating the next generation of recombinants, which has led to a series of significant bottlenecks, particularly in the history of the North American and European maize germplasm. Both the decentralization and the disproportionate contribution of inbred lines reduce effective population size and constrain the accessible genetic space. Under these conditions, long-term response to selection is not expected to be optimal under the classical infinitesimal model of quantitative genetics. In this study, we therefore aim to propose a rationale for the success of large breeding operations in the context of genetic complexity arising from the structure and properties of interactive genetic networks. For this, we use simulations based on the NK model of genetic architecture. We indeed found that constraining genetic space through program decentralization and disproportionate contribution of parental inbred lines, is required to expose additive genetic variation and thus facilitate heritable genetic gains under high levels of genetic complexity. These results introduce new insights into why the historically grown structure of hybrid breeding programs was successful in improving the yield potential of hybrid crops over the last century. We also hope that a renewed appreciation for “why things worked” in the past can guide the adoption of novel technologies and the design of future breeding strategies for navigating biological complexity.

Predicting grain yield in Australian environments using data from CIMMYT international wheat performance trials 3. Testing predicted correlated response to selection

Publisher: Elsevier BV

Date: 12-1993

DOI: 10.1016/0378-4290(93)90153-E

Pattern analysis of the diversity of morphological plant attributes and herbage yield in a world collection of white clover (Trifolium repens L.) germplasm characterised in a summer moisture stress environment of Australia

Publisher: Springer Science and Business Media LLC

Date: 1997

DOI: 10.1023/A:1008692629734

Power of the joint segregation analysis method for testing mixed major-gene and polygene inheritance models of quantitative traits

Publisher: Springer Science and Business Media LLC

Date: 10-2001

DOI: 10.1007/S001220100628

Indirect selection using reference and probe genotype performance in multi-environment trials

Publisher: CSIRO Publishing

Date: 2011

DOI: 10.1071/CP10318

Abstract: There is a substantial challenge in identifying appropriate cultivars from databases for introduction into a breeding program. We propose an indirect selection procedure that illustrates how strategically designed multi-environment trials, linked to historical performance databases, can identify germplasm to meet objectives of plant breeding programs. Two strategies for indirect selection of germplasm from the International Wheat and Maize Improvement Center’s (CIMMYT) trial database were developed based on reference and probe genotype sets included in the International Adaptation Trial (IAT). The IAT was designed to improve the understanding of relationships among global spring wheat (Triticum spp.) locations. Grain yield (t/ha) data were collated from 183 IAT trials grown in 40 countries (including Australia) between 2001 and 2004. The reference genotype set strategy used the genetic correlations among locations in the IAT to identify locations similar to a target environment. For a key southern Australian breeding location, Roseworthy, the number of cultivars targeted for selection was reduced to 35% of the original 1252. The Irrigated Winter Cereals Trials (2008–09) aimed to identify high yield potential lines in south-eastern Australian irrigated environments. Thirty-five CIMMYT cultivars identified using the reference genotype selection strategy were grown in this trial series. In all trials, the proportion of CIMMYT cultivars in the top 20% yielding lines exceeded the expected proportion, 0.20. The probe genotype strategy utilised contrasting line yield responses to assess the occurrence of soil-borne stresses such as root lesion nematode (Pratylenchus thorneii) and boron toxicity. For these stresses, the number of targeted cultivars was reduced to 25% and 83% of the original 1252, respectively.

Can we harness digital technologies and physiology to hasten genetic gain in US maize breeding?

Publisher: Oxford University Press (OUP)

Date: 15-11-2021

DOI: 10.1093/PLPHYS/KIAB527

Abstract: Plant physiology can offer invaluable insights to accelerate genetic gain. However, translating physiological understanding into breeding decisions has been an ongoing and complex endeavor. Here we demonstrate an approach to leverage physiology and genomics to hasten crop improvement. A half-diallel maize (Zea mays) experiment resulting from crossing 9 elite inbreds was conducted at 17 locations in the USA corn belt and 6 locations at managed stress environments between 2017 and 2019 covering a range of water environments from 377 to 760 mm of evapotranspiration and family mean yields from 542 to 1,874 g m−2. Results from analyses of 35 families and 2,367 hybrids using crop growth models linked to whole-genome prediction (CGM–WGP) demonstrated that CGM–WGP offered a predictive accuracy advantage compared to BayesA for untested genotypes evaluated in untested environments (r = 0.43 versus r = 0.27). In contrast to WGP, CGMs can deal effectively with time-dependent interactions between a physiological process and the environment. To facilitate the selection/identification of traits for modeling yield, an algorithmic approach was introduced. The method was able to identify 4 out of 12 candidate traits known to explain yield variation in maize. The estimation of allelic and physiological values for each genotype using the CGM created in silico phenotypes (e.g. root elongation) and physiological hypotheses that could be tested within the breeding program in an iterative manner. Overall, the approach and results suggest a promising future to fully harness digital technologies, gap analysis, and physiological knowledge to hasten genetic gain by improving predictive skill and definition of breeding goals.

Plant Breeding in the face of climate change

Publisher: Cold Spring Harbor Laboratory

Date: 08-10-2022

DOI: 10.1101/2022.10.07.511293

Abstract: Climate change will have a net negative and inequitable impact on agriculture. Genetics for crop improvement ranks in the top set of technologies that can contribute to human adaptation to climate change. However, a framework for how to breed crops for climate change adaptation is lacking. Here we propose a framework to develop new genotype (G) x management (M) technologies (G x M) to adapt to climate change, and to transition from current to future G x M technologies in a way that future food security does not come at the expense of current food security. The framework integrate genomic, agronomic, and environmental (E) predictors to accomplish two critical goals: 1-predict emergent phenotypes that stems from the dynamic interplay between G, E and M, and thus enable the breeder to consider the behavior of new genetic and trait combinations in environments that plants have not been exposed or tested before, and 2-identify G x M technologies that could increase food and nutritional security while regenerating natural and production resources. We highlight the need to invest in artificial intelligence and information technologies for breeders to harness multiple sources of information to create G x M technologies to address the erse cultural and geographically granular societal needs.

Modeling biomass accumulation in maize kernels

Publisher: Elsevier BV

Date: 09-2013

DOI: 10.1016/J.FCR.2013.07.014

Molecular Breeding for Complex Adaptive Traits: How Integrating Crop Ecophysiology and Modelling Can Enhance Efficiency

Publisher: Springer International Publishing

Date: 2020

DOI: 10.1007/978-3-319-20562-5_7

Comparison of identity by descent and identity by state for detecting genetic regions under selection in a sorghum pedigree breeding program

Publisher: Springer Science and Business Media LLC

Date: 2005

DOI: 10.1007/S11032-005-0901-Y

Global adaptation patterns of Australian and CIMMYT spring bread wheat

Publisher: Springer Science and Business Media LLC

Date: 09-2007

DOI: 10.1007/S00122-007-0611-4

Abstract: The International Adaptation Trial (IAT) is a special purpose nursery designed to investigate the genotype-by-environment interactions and worldwide adaptation for grain yield of Australian and CIMMYT spring bread wheat (Triticum aestivum L.) and durum wheat (T. turgidum L. var. durum). The IAT contains lines representing Australian and CIMMYT wheat breeding programs and was distributed to 91 countries between 2000 and 2004. Yield data of 41 reference lines from 106 trials were analysed. A multiplicative mixed model accounted for trial variance heterogeneity and inter-trial correlations characteristic of multi-environment trials. A factor analytic model explained 48% of the genetic variance for the reference lines. Pedigree information was then incorporated to partition the genetic line effects into additive and non-additive components. This model explained 67 and 56% of the additive by environment and non-additive by environment genetic variances, respectively. Australian and CIMMYT germplasm showed good adaptation to their respective target production environments. In general, Australian lines performed well in south and west Australia, South America, southern Africa, Iran and high latitude European and Canadian locations. CIMMYT lines performed well at CIMMYT's key yield testing location in Mexico (CIANO), north-eastern Australia, the Indo-Gangetic plains, West Asia North Africa and locations in Europe and Canada. Maturity explained some of the global adaptation patterns. In general, southern Australian germplasm were later maturing than CIMMYT material. While CIANO continues to provide adapted lines to northern Australia, selecting for yield among later maturing CIMMYT material in CIANO may identify lines adapted to southern and western Australian environments.

The U.S. drought of 2012 in perspective: A call to action

Publisher: Elsevier BV

Date: 09-2013

DOI: 10.1016/J.GFS.2013.08.002

Hydraulic Conductance of Maize Hybrids Differing in Transpiration Response to Vapor Pressure Deficit

Publisher: Wiley

Date: 05-2014

DOI: 10.2135/CROPSCI2013.05.0303

Abstract: Limited transpiration rate (TR) under high vapor pressure deficit (VPD) conditions has been proposed as a desirable trait for crop yield improvement. The limited‐TR trait has been identified in several single‐cross maize hybrids, and among these hybrids, a range in the VPD breakpoint for limited TR was identified. It was hypothesized that the variation in the VPD breakpoint was due to differences in hydraulic conductance in their roots or leaves, or both. Therefore, the objective of this study was to compare relative hydraulic conductance in the roots and leaves across the maize hybrids expressing the VPD breakpoint. It was found that the VPD of the breakpoint was correlated with each of three indices of hydraulic conductance. That is, low VPD breakpoint was associated with low hydraulic conductance in both leaves and roots indicating a common, underlying limiting mechanism in these two tissues. It was hypothesized that expression of similar aquaporin populations influencing hydraulic flow across membranes in the roots and leaves may account for the consistency in results across the indices of hydraulic conductance.

Yield response of rice (Oryza sativa L.) genotypes to different types of drought under rainfed lowlands

Publisher: Elsevier BV

Date: 2002

DOI: 10.1016/S0378-4290(01)00187-3

Crop science: A foundation for advancing predictive agriculture

Publisher: Wiley

Date: 03-2020

DOI: 10.1002/CSC2.20116

Quantitative analysis of the effect of selection history on sugar yield adaptation of sugarcane clones

Publisher: Springer Science and Business Media LLC

Date: 1994

DOI: 10.1007/BF00222887

Extending the breeder’s equation to take aim at the Target Population of Environments

Publisher: Cold Spring Harbor Laboratory

Date: 15-12-2022

DOI: 10.1101/2022.12.13.520360

Abstract: 1) A major focus for genomic prediction has been on improving trait prediction accuracy using combinations of algorithms and the training data sets available from plant breeding multi-environment trials (METs). Any improvements in prediction accuracy are viewed as pathways to improve traits in the reference population of genotypes and product performance in the target population of environments (TPE). To realise these breeding outcomes there must be a positive MET-TPE relationship that provides consistency between the trait variation expressed within the MET data sets that are used to train the genome-to-phenome ( G2P ) model for applications of genomic prediction and the realised trait and performance differences in the TPE for the genotypes that are the prediction targets. The strength of this MET-TPE relationship is usually assumed to be high, however it is rarely quantified. To date investigations of genomic prediction methods have not given adequate attention to quantifying the structure of the TPE and the MET-TPE relationship and its potential impact on training the G2P model for applications of genomic prediction to accelerate breeding outcomes for the on-farm TPE. We provide a perspective on the importance of the MET-TPE relationship as a key component for the design of genomic prediction methods to realize improved rates of genetic gain for the target yield, quality, stress tolerance and yield stability traits in the on-farm TPE.

Erratum to “Genotype-by-management interactions for grain yield and grain protein concentration of wheat”

Publisher: Elsevier BV

Date: 04-2001

DOI: 10.1016/S0378-4290(01)00134-4

Genetic analysis of preharvest sprouting tolerance in three wheat crosses

Publisher: CSIRO Publishing

Date: 1997

DOI: 10.1071/A96071

Abstract: Three recombinant inbred populations were assessed for tolerance to preharvest sprouting (PHS). Genetic analysis of the PHS scores, as assessed under artificial rain treatment, indicated that for 2 of the populations, tolerance to sprouting was simply inherited and was controlled by 2 independent genes, both of which are necessary for full tolerance. The data presented here show that in these 2 populations the trait is highly heritable under controlled environment situations. It was also demonstrated that the red seed colour gene, derived from Aus1490 and traditionally associated with tolerance, is not necessary for full tolerance to sprouting, although indirect selection for preharvest sprouting tolerance can be performed very effectively by selecting for red grain. The presence of white-seeded lines, recovered from this cross with a red-seeded donor of PHS tolerance, that are at least as tolerant as the most tolerant red-seeded in iduals demonstrates that red-seeded donors of PHS tolerance should not be discarded for improvement of this trait.

Sorghum hybrid differences in grain yield and nitrogen concentration under low soil nitrogen availability. I. Hybrids with similar phenology

Publisher: CSIRO Publishing

Date: 1998

DOI: 10.1071/A98018

Abstract: In Australia, grain sorghum [Sorghum bicolor (L.) Moench] hybrids are often grown under conditions of low soil nitrogen (N) availability with suboptimal levels of N fertiliser supplied. However, little is known about the traits that contribute to sorghum hybrid performance in environments with low available N. We examined plant traits that may contribute to adaptation of sorghum to low soil N conditions, and the influence of genotype × N environment interactions on yield and grain N concentration. Two experiments were conducted using 3–6 hybrids with similar phenology. Three N fertiliser application rates (0, 60, and 240 kg/ha) were used in Expt 1, and 2 application rates (0 and 60 kg/ha) were used in Expt 2. Hybrid yield was associated with plant N content at maturity. The ability of a hybrid to take up N continuously during grain filling, under N limiting conditions, was identified as an important component contributing to high yield. In the non-fertilised treatment of Expt 2, where plants suffered the most severe N limitation before anthesis (e.g. total plant N content at anthesis g/m2), hybrid yield was associated with biomass production and duration of effective grain filling. The dependence of the expression of the higher N uptake trait on N availability and other environmental factors resulted in genotype × environment interactions for yield. Differences among hybrids in leaf senescence and grain growth rate had little effect on yield. Genotypic variation for grain N concentration was consistent across experiments for hybrids with and without the staygreen attribute. In Expt 2 the magnitude of leaf senescence and amount of N mobilised from leaf to grain were greater at 60 kg N/ha than in the non-fertilised treatment. In addition, the staygreen hybrid 72389–1-1–3/QL36 had a slower rate of leaf senescence, took up larger amounts of N after anthesis, and had higher grain N concentration (1·07%) than the senescent hybrids ATx623/RTx430 (0·95%) and QL41/69264–2-2–2 (0·90%).

Predicting grain yield in Australian environments using data from CIMMYT international wheat performance trials. 1. Potential for exploiting correlated response to selection

Publisher: Elsevier BV

Date: 03-1993

DOI: 10.1016/0378-4290(93)90039-P

Sorghum hybrid differences in grain yield and nitrogen concentration under low soil nitrogen availability. II. Hybrids with contrasting phenology

Publisher: CSIRO Publishing

Date: 1998

DOI: 10.1071/A98019

Abstract: Genotypic variation for phenology is important when considering the adaptation of grain sorghum (Sorghum bicolor (L.) Moench) to adverse environments, but little is known about its role under environmental conditions that result in low soil nitrogen (N) availability. We examined the role of phenology in relation to other traits considered to contribute to the adaptation of sorghum to low soil N conditions. Four hybrids with contrasting maturity date were examined (2 early and 2 late) under conditions of full irrigation supply. The late-maturing hybrids had higher yield than one of the early hybrids only in optimum N conditions (960 v. 815 g/m2). The high yield of the late-maturing hybrids was a result of greater biomass production due to a longer period of radiation interception, rather than a greater fraction of radiation interception at any time. Longer growth duration had no positive effect on N capture, resulting in a lower grain N concentration at maturity relative to the early-maturing hybrid (1·42% v. 1·67%). The other early-maturing hybrids achieved a comparable amount of biomass production and grain yield (997 g/m2) to the late-maturing hybrids, and higher grain N concentration (1·55%). This was attributed to their higher plant N uptake by maturity, which contributed to higher grain N and maintained higher radiation use efficiency (RUE) relative to the other hybrids. Under N-limiting conditions, the advantage of the late-maturing hybrids was small in terms of radiation interception, and there was no advantage in terms of total plant N content. One of the early-maturing hybrids continued to absorb more N and accumulated larger amounts of N to grain for a longer period after anthesis than the other hybrids, resulting in higher grain N concentration (1·10% v. 0·92%). Genotypic variation for RUE, N utilisation, and harvest index was observed, but was confounded with the other components, resulting in a small difference in yield (392–454 g/m2).

Two decades of creating drought tolerant maize and underpinning prediction technologies in the US corn-belt: Review and perspectives on the future of crop design

Publisher: Cold Spring Harbor Laboratory

Date: 30-10-2020

DOI: 10.1101/2020.10.29.361337

Abstract: Over the last decade, society witnessed the largest expansion of agricultural land planted with drought tolerant (DT) maize ( Zea mays L.) Dedicated efforts to drought breeding led to development of DT maize. Here we show that after two decades of sustained breeding efforts the rate of crop improvement under drought is in the range 1.0-1.6% yr −1 , which is higher than rates (0.7% yr −1 ) reported prior to drought breeding. Prediction technologies that leverage biological understanding and statistical learning to improve upon the quantitative genetics framework will further accelerate genetic gain. A review of published and unpublished analyses conducted on data including 138 breeding populations and 93 environments between 2009 and 2019 demonstrated an average prediction skill ( r ) improvement around 0.2. These methods applied to pre-commercial stages showed accuracies higher that current statistical approaches (0.85 vs. 0.70). Improvement in hybrid and management choice can increase water productivity. Digital gap analyses are applicable at field scale suggesting the possibility of transition from evaluating hybrids to designing genotype x management (GxM) technologies for target cropping systems in drought prone areas. Due to the biocomplexity of drought, research and development efforts should be sustained to advance knowledge and iteratively improve models. Crop improvement rate in maize increased after implementation of drought breeding efforts. Harnessing crop, quantitative genetics and gap models will enable the transition from genetic evaluation to crop design.

Screening for drought resistance in rainfed lowland rice

Publisher: Elsevier BV

Date: 11-1999

DOI: 10.1016/S0378-4290(99)00051-9

Development of drought-resistant cultivars using physiomorphological traits in rice

Publisher: Elsevier BV

Date: 02-1995

DOI: 10.1016/0378-4290(94)00096-U

Environment characterization as an aid to wheat improvement: interpreting genotype–environment interactions by modelling water-deficit patterns in North-Eastern Australia

Publisher: Oxford University Press (OUP)

Date: 03-2011

DOI: 10.1093/JXB/ERQ459

Abstract: Genotype-environment interactions (GEI) limit genetic gain for complex traits such as tolerance to drought. Characterization of the crop environment is an important step in understanding GEI. A modelling approach is proposed here to characterize broadly (large geographic area, long-term period) and locally (field experiment) drought-related environmental stresses, which enables breeders to analyse their experimental trials with regard to the broad population of environments that they target. Water-deficit patterns experienced by wheat crops were determined for drought-prone north-eastern Australia, using the APSIM crop model to account for the interactions of crops with their environment (e.g. feedback of plant growth on water depletion). Simulations based on more than 100 years of historical climate data were conducted for representative locations, soils, and management systems, for a check cultivar, Hartog. The three main environment types identified differed in their patterns of simulated water stress around flowering and during grain-filling. Over the entire region, the terminal drought-stress pattern was most common (50% of production environments) followed by a flowering stress (24%), although the frequencies of occurrence of the three types varied greatly across regions, years, and management. This environment classification was applied to 16 trials relevant to late stages testing of a breeding programme. The incorporation of the independently-determined environment types in a statistical analysis assisted interpretation of the GEI for yield among the 18 representative genotypes by reducing the relative effect of GEI compared with genotypic variance, and helped to identify opportunities to improve breeding and germplasm-testing strategies for this region.

Investigations into the emergent properties of gene-to-phenotype networks across cycles of selection: A case study of shoot branching in plants

Publisher: Cold Spring Harbor Laboratory

Date: 05-02-2022

DOI: 10.1101/2022.02.03.479064

Abstract: Predictive breeding is now widely practised in crop improvement programs and has accelerated selection response (i.e., the amount of genetic gain between breeding cycles) for complex traits. However, world food production needs to increase further to meet the demands of the growing human population. The prediction of complex traits with current methods can be inconsistent across different genetic, environmental, and agronomic management contexts because the complex relationships between genomic and phenotypic variation are not well accounted for. Therefore, developing gene-to-phenotype network models for traits that integrate the knowledge of networks from systems biology, plant and crop physiology with population genomics has been proposed to close this gap in predictive modelling. Here, we develop a gene-to-phenotype network for shoot branching, a critical developmental pathway underpinning harvestable yield for many crop species, as a case study to explore the value of developing gene-to-phenotype networks to enhance understanding of selection responses. We observed that genetic canalization is an emergent property of the complex interactions among shoot branching gene-to-phenotype network components, leading to the accumulation of cryptic genetic variation, reduced selection responses, and large variation in selection trajectories across populations. As genetic canalization is expected to be pervasive in traits, such as grain yield, that result from interactions among multiple genes, traits, environments, and agronomic management practices, the need to model traits in crop improvement programs as outcomes of gene-to-phenotype networks is highlighted as an emerging opportunity to advance our understanding of selection response and the efficiency of developing resilient crops for future climates.

Genotypic variation for stolon and other morphological attributes of white clover (Trifolium repens L.). Populations and their influence on herbage yield in the summer rainfall region of New South Wal

Publisher: CSIRO Publishing

Date: 1994

DOI: 10.1071/AR9940703

Abstract: A random s le of 60 germplasm accessions from the Australian white clover germplasm collection was characterized in the field at Glen Innes, N.S.W. Genotypic variation for stolon and other morphological attributes was measured in one season. Herbage yield was evaluated over seven seasons to quantify the magnitude of accession-by-season interaction. There were significant (P 0.01) differences among accessions, seasons, and accession-by-season interactions for herbage yield. Classification was used to group the accessions on their seasonal herbage yield. A summer active group, a winter active group and a group showing autumn activity for herbage yield were identified. There was significant (P 0.01) variation among accessions for all plant attributes measured and their accession mean repeatability was moderate to high. There were strong genotypic correlations among the morphological attributes. Five of the morphological attributes (stolon density, stolon branching, plant spread, plant height, stolon thickness and leaf length) expressed a strong genotypic correlation with average herbage yield over seven seasons. The genotypic variation estimated for herbage production and plant attributes signifies the potential of the collection to be used as a source of variation for the genetic improvement of productivity and perenniality of white clover for Australian environments.

Can Changes in Canopy and/or Root System Architecture Explain Historical Maize Yield Trends in the U.S. Corn Belt?

Publisher: Wiley

Date: 2009

DOI: 10.2135/CROPSCI2008.03.0152

The role of physiological understanding in plant breeding; from a breeding perspective

Publisher: Elsevier BV

Date: 11-1996

DOI: 10.1016/S0378-4290(96)01012-X

Influence of phenology on grain yield variation among barley cultivars grown under terminal drought

Publisher: CSIRO Publishing

Date: 1996

DOI: 10.1071/AR9960757

Abstract: We investigated the influence of sowing time and genotypic variation for phenology on grain yield of barley in south-eastern Queensland. Over 3 seasons, 8 trials with 10 cultivars and 1 trial with 4 cultivars were conducted under either irrigated or terminal drought conditions at 2 locations. Rainout shelters ensured the development of severe terminal water stress. Trials were either sown on a common date, as conducted in traditional multi-environment trials, or over 3 weeks to synchronise anthesis among cultivars of different phenologies. Within the common sowing date trials, variation (P 0.01) existed among cultivars for grain yield. From the 6 common sowing trials there was a negative correlation (P 0.05) between grain yield and days to anthesis that is, the shorter duration cultivars expressed the highest grain yield. Variation in days to anthesis accounted for 48-72% of the variation for grain yield. In the staggered sowing trials, where anthesis of all cultivars occurred within 4 or 2 days of the mean anthesis date, variation for grain yield was small or non-significant, and there was no association between grain yield and days to anthesis. The staggered sowing experiment with 10 cultivars indicated that duration of the vegetative phase was important in determining total dry matter production at maturity when cultivars were grown under terminal drought. Long-duration cultivars sown earlier had greater total dry matter at maturity than short-duration cultivars. This was associated with a greater water extraction by the long-duration cultivars, especially at depth, which remained inaccessible to later sown, short-duration cultivars. However, due to the low harvest index of the long-duration cultivars, grain yield of long- and short-duration cultivars was comparable when anthesis of cultivars was synchronised. When sown at the same time, a short-duration cultivar is advantageous because of a high chance of escaping water stress that develops during the critical development stage of anthesis. The results from the staggered sowing date experiments, however, indicated that the long-duration cultivars, when sown earlier in the season, had no yield disadvantage in comparison with the short-duration cultivars sown later in the season. Therefore, there is scope to develop barley cultivars of later phenology than is currently available to provide Queensland farmers with the option of utilising early rainfall events which are sometimes the only planting opportunity.

A procedure to assess the relative merit of classification strategies for grouping environments to assist selection in plant breeding regional evaluation trials

Publisher: Elsevier BV

Date: 10-1993

DOI: 10.1016/0378-4290(93)90137-C

Two decades of harnessing standing genetic variation for physiological traits to improve drought tolerance in maize

Publisher: Oxford University Press (OUP)

Date: 24-06-2023

DOI: 10.1093/JXB/ERAD231

Abstract: We review approaches to maize breeding for improved drought tolerance during flowering and grain filling in the central and western US corn belt and place our findings in the context of results from public breeding. Here we show that after two decades of dedicated breeding efforts, the rate of crop improvement under drought increased from 6.2 g m−2 year−1 to 7.5 g m−2 year−1, closing the genetic gain gap with respect to the 8.6 g m−2 year–1 observed under water-sufficient conditions. The improvement relative to the long-term genetic gain was possible by harnessing favourable alleles for physiological traits available in the reference population of genotypes. Experimentation in managed stress environments that maximized the genetic correlation with target environments was key for breeders to identify and select for these alleles. We also show that the embedding of physiological understanding within genomic selection methods via crop growth models can hasten genetic gain under drought. We estimate a prediction accuracy differential (Δr) above current prediction approaches of ~30% (Δr=0.11, r=0.38), which increases with increasing complexity of the trait environment system as estimated by Shannon information theory. We propose this framework to inform breeding strategies for drought stress across geographies and crops.

Yield response of rice (Oryza sativa L.) genotypes to drought under rainfed lowlands

Publisher: Elsevier BV

Date: 2002

DOI: 10.1016/S0378-4290(01)00195-2

Integrating genetic gain and gap analysis to predict improvements in crop productivity

Publisher: Wiley

Date: 03-2020

DOI: 10.1002/CSC2.20109

Abstract: A Crop Growth Model (CGM) is used to demonstrate a biophysical framework for predicting grain yield outcomes for Genotype by Environment by Management (G×E×M) scenarios. This required development of a CGM to encode contributions of genetic and environmental determinants of biophysical processes that influence key resource (radiation, water, nutrients) use and yield‐productivity within the context of the target agricultural system. Prediction of water‐driven yield‐productivity of maize for a wide range of G×E×M scenarios in the U.S. corn‐belt is used as a case study to demonstrate applications of the framework. Three experimental evaluations are conducted to test predictions of G×E×M yield expectations derived from the framework: (1) A maize hybrid genetic gain study, (2) A maize yield potential study, and (3) A maize drought study. Ex les of convergence between key G×E×M predictions from the CGM and the results of the empirical studies are demonstrated. Potential applications of the prediction framework for design of integrated crop improvement strategies are discussed. The prediction framework opens new opportunities for rapid design and testing of novel crop improvement strategies based on an integrated understanding of G×E×M interactions. Importantly the CGM ensures that the yield predictions for the G×E×M scenarios are grounded in the biophysical properties and limits of predictability for the crop system. The identification and delivery of novel pathways to improved crop productivity can be accelerated through use of the proposed framework to design crop improvement strategies that integrate genetic gains from breeding and crop management strategies that reduce yield gaps.

The effect of the accumulation of disease resistance genes on the long-term association of a global sample of environments for testing spring bread wheat

Publisher: Springer Science and Business Media LLC

Date: 11-2000

DOI: 10.1007/S001220051593

Temperature effect on transpiration response of maize plants to vapour pressure deficit

Publisher: Elsevier BV

Date: 05-2012

DOI: 10.1016/J.ENVEXPBOT.2011.12.034

Effect of Plot Size on Accuracy of Yield Estimation of Rainfed Lowland Rice Genotypes with Different Plant Heights and Grown under Different Soil Fertility Conditions

Publisher: Informa UK Limited

Date: 2003

DOI: 10.1626/PPS.6.95

High-mobility three-atom-thick semiconducting films with wafer-scale homogeneity

Publisher: Springer Science and Business Media LLC

Date: 04-2015

DOI: 10.1038/NATURE14417

Abstract: The large-scale growth of semiconducting thin films forms the basis of modern electronics and optoelectronics. A decrease in film thickness to the ultimate limit of the atomic, sub-nanometre length scale, a difficult limit for traditional semiconductors (such as Si and GaAs), would bring wide benefits for applications in ultrathin and flexible electronics, photovoltaics and display technology. For this, transition-metal dichalcogenides (TMDs), which can form stable three-atom-thick monolayers, provide ideal semiconducting materials with high electrical carrier mobility, and their large-scale growth on insulating substrates would enable the batch fabrication of atomically thin high-performance transistors and photodetectors on a technologically relevant scale without film transfer. In addition, their unique electronic band structures provide novel ways of enhancing the functionalities of such devices, including the large excitonic effect, bandgap modulation, indirect-to-direct bandgap transition, piezoelectricity and valleytronics. However, the large-scale growth of monolayer TMD films with spatial homogeneity and high electrical performance remains an unsolved challenge. Here we report the preparation of high-mobility 4-inch wafer-scale films of monolayer molybdenum disulphide (MoS2) and tungsten disulphide, grown directly on insulating SiO2 substrates, with excellent spatial homogeneity over the entire films. They are grown with a newly developed, metal-organic chemical vapour deposition technique, and show high electrical performance, including an electron mobility of 30 cm(2) V(-1) s(-1) at room temperature and 114 cm(2) V(-1) s(-1) at 90 K for MoS2, with little dependence on position or channel length. With the use of these films we successfully demonstrate the wafer-scale batch fabrication of high-performance monolayer MoS2 field-effect transistors with a 99% device yield and the multi-level fabrication of vertically stacked transistor devices for three-dimensional circuitry. Our work is a step towards the realization of atomically thin integrated circuitry.

A procedure for investigating the number of genotypes required to provide a stable classification of environments

Publisher: Elsevier BV

Date: 07-1994

DOI: 10.1016/0378-4290(94)90031-0

TheE(NK) model: Extending theNK model to incorporate gene-by-environment interactions and epistasis for diploid genomes

Publisher: Wiley

Date: 07-2002

DOI: 10.1002/CPLX.10044

QU-GENE: a simulation platform for quantitative analysis of genetic models.

Publisher: Oxford University Press (OUP)

Date: 1998

DOI: 10.1093/BIOINFORMATICS/14.7.632

Abstract: MOTIVATION: Classical quantitative genetics theory makes a number of simplifying assumptions in order to develop mathematical expressions that describe the mean and variation (genetic and phenotypic) within and among populations, and to predict how these are expected to change under the influence of external forces. These assumptions are often necessary to render the development of many aspects of the theory mathematically tractable. The availability of high-speed computers today provides opportunity for the use of computer simulation methodology to investigate the implications of relaxing many of the assumptions that are commonly made. RESULTS: QU-GENE (QUantitative-GENEtics) was developed as a flexible computer simulation platform for the quantitative analysis of genetic models. Three features of the QU-GENE software that contribute to its flexibility are (i) the core E(N:K) genetic model, where E is the number of types of environment, N is the number of genes, K indicates the level of epistasis and the parentheses indicate that different N:K genetic models can be nested within types of environments, (ii) the use of a two-stage architecture that separates the definition of the genetic model and genotype-environment system from the detail of the in idual simulation experiments and (iii) the use of a series of interactive graphical windows that monitor the progress of the simulation experiments. The E(N:K) framework enables the generation of families of genetic models that incorporate the effects of genotype-by-environment (G x E) interactions and epistasis. By the design of appropriate application modules, many different simulation experiments can be conducted for any genotype-environment system. The structure of the QU-GENE simulation software is explained and demonstrated by way of two ex les. The first concentrates on some aspects of the influence of G x E interactions on response to selection in plant breeding, and the second considers the influence of multiple-peak epistasis on the evolution of a four-gene epistatic network. AVAILABILITY: QU-GENE is available over the Internet at (pig.ag.uq.edu.au/qu-gene/) CONTACT: m.cooper@mailbox.uq.edu. au

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

Publisher: Oxford University Press (OUP)

Date: 28-12-2021

DOI: 10.1093/INSILICOPLANTS/DIAA016

Abstract: Plant-breeding programs are designed and operated over multiple cycles to systematically change the genetic makeup of plants to achieve improved trait performance for a Target Population of Environments (TPE). Within each cycle, selection applied to the standing genetic variation within a structured reference population of genotypes (RPG) is the primary mechanism by which breeding programs make the desired genetic changes. Selection operates to change the frequencies of the alleles of the genes controlling trait variation within the RPG. The structure of the RPG and the TPE has important implications for the design of optimal breeding strategies. The breeder’s equation, together with the quantitative genetic theory behind the equation, informs many of the principles for design of breeding programs. The breeder’s equation can take many forms depending on the details of the breeding strategy. Through the genetic changes achieved by selection, the cultivated varieties of crops (cultivars) are improved for use in agriculture. From a breeding perspective, selection for specific trait combinations requires a quantitative link between the effects of the alleles of the genes impacted by selection and the trait phenotypes of plants and their breeding value. This gene-to-phenotype link function provides the G2P map for one to many traits. For complex traits controlled by many genes, the infinitesimal model for trait genetic variation is the dominant G2P model of quantitative genetics. Here we consider motivations and potential benefits of using the hierarchical structure of crop models as CGM-G2P trait link functions in combination with the infinitesimal model for the design and optimization of selection in breeding programs.

Genotype×environment interactions and some considerations of their implications for wheat breeding in Australia This review is one of a series commissioned by the Advisory Committee of the Journal.

Publisher: CSIRO Publishing

Date: 1998

DOI: 10.1071/A97035

Abstract: Genotype×environment (G×E) interactions complicate selection forbroad adaptation, while their nature and causes need to be understood toutilise and exploit them in selection for specific adaptation. This invitedreview combines an assessment of the literature with the experience we havegained from involvement in wheat breeding and associated research programs toassess (1) the implications of G×E interactions for wheat breeding inAustralia, (2) the impact that research into G E interactions has had onbreeding strategy, and (3) the evidence for impact from this research efforton genetic improvement of crop adaptation. The role of analytical methodologyin this process is considered and some important issues are discussed.There are sufficient ex les drawn from wheat breeding in Australia tosuggest that progress in dealing with G×E interactions can be made andseveral of these are presented. They show that impact in plant breedingfollows from achieving an appropriate level of understanding of theenvironmental and genetic factors causing the interactions as well as anassessment of their importance in the target genotype-environment system. Anaccurate definition of the environmental factor(s) contributing to theG×E interactions has been particularly important in determining therelevance of observed differences in plant adaptation to the target populationof environments. From the combination of biological and statistical studies, amore comprehensive understanding of G×E interactions has emerged andcontributed to new concepts and procedures for dealing with them.Distinguishing between what are repeatable and non-repeatable interactions isa key step. Genuine cases of positive specific adaptation observed inmulti-environment trials (METs) can be exploited by appropriately targetedselection strategies, while non-repeatable interactions are accommodated byselection for broad adaptation.The investigation of G×E interactions for grain yield of wheat inAustralia has matured to the point where an understanding of some of theircauses has enabled wheat breeders to exploit positive components of specificadaptation. The experience that has been gained in achieving these advancesindicates the importance of establishing a MET system that is relevant to thetarget population of environments of the breeding program. The investment ofadequate resources into effective design, conduct, analysis, andinterpretation of METs remains critical to continued progress from selectionin complex genotype-environment systems that present large G× Einteractions. Wheat breeders who understand their genetic material and thetarget population of environments can then use the generated information baseto achieve impact from their breeding programs.

Towards a multiscale crop modelling framework for climate change adaptation assessment.

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.

Integrating Crop Growth Models with Whole Genome Prediction through Approximate Bayesian Computation

Publisher: Public Library of Science (PLoS)

Date: 29-06-2015

DOI: 10.1371/JOURNAL.PONE.0130855

Adaptation of rainfed lowland rice

Publisher: Elsevier BV

Date: 11-1999

DOI: 10.1016/S0378-4290(99)00062-3

Stacking Order Dependent Second Harmonic Generation and Topological Defects in h-BN Bilayers

Publisher: American Chemical Society (ACS)

Date: 16-10-2013

DOI: 10.1021/NL403328S

Abstract: The ability to control the stacking structure in layered materials could provide an exciting approach to tuning their optical and electronic properties. Because of the lower symmetry of each constituent monolayer, hexagonal boron nitride (h-BN) allows more structural variations in multiple layers than graphene however, the structure-property relationships in this system remain largely unexplored. Here, we report a strong correlation between the interlayer stacking structures and optical and topological properties in chemically grown h-BN bilayers, measured mainly by using dark-field transmission electron microscopy (DF-TEM) and optical second harmonic generation (SHG) mapping. Our data show that there exist two distinct h-BN bilayer structures with different interlayer symmetries that give rise to a distinct difference in their SHG intensities. In particular, the SHG signal in h-BN bilayers is observed only for structures with broken inversion symmetry, with an intensity much larger than that of single layer h-BN. In addition, our DF-TEM data identify the formation of interlayer topological defects in h-BN bilayers, likely induced by local strain, whose properties are determined by the interlayer symmetry and the different interlayer potential landscapes.

Root system growth and function response to soil temperature in maize (Zea maysL.)

Publisher: Cold Spring Harbor Laboratory

Date: 16-03-2023

DOI: 10.1101/2023.03.15.532822

Abstract: Crop adaptation to the mixture of environments that defines the target population of environments is the result from a balanced resource allocation between roots, shoots and reproductive organs. Root growth places a critical role in the determination of this balance. Root growth and function responses to temperature can determine the strength of roots as sinks but also influence the crop’s ability to uptake water and nutrients. Surprisingly, this behavior has not been studied in maize since the middle of the last century, and the genetic determinants are unknown. Low temperatures often recorded in deep soil layers limit root growth and soil exploration and may constitute a bottleneck towards increasing drought tolerance, nitrogen recovery, sequestration of carbon and productivity in maize. High throughput phenotyping (HTP) systems were developed to investigate these responses and to examine genetic variability therein across erse maize germplasm. Here we show that there is: 1) genetic variation of root growth under low temperature and below 10°C, and 2) genotypic variation in water transport under low temperature. Using simulation, we demonstrate that the measured variation for both traits contribute to drought tolerance and explain important components of yield variation in the US corn-belt. The trait set examined herein and HTP platform developed for its characterization reveal a unique opportunity to remove a major bottleneck for crop improvement, and adaptation to climate change.

Maize Hybrid Variability for Transpiration Decrease with Progressive Soil Drying

Publisher: Wiley

Date: 28-06-2012

DOI: 10.1111/J.1439-037X.2012.00530.X

Breeding crops for drought-affected environments and improved climate resilience

Publisher: Oxford University Press (OUP)

Date: 12-11-2022

DOI: 10.1093/PLCELL/KOAC321

Abstract: Breeding climate-resilient crops with improved levels of abiotic and biotic stress resistance as a response to climate change presents both opportunities and challenges. Applying the framework of the “breeder’s equation,” which is used to predict the response to selection for a breeding program cycle, we review methodologies and strategies that have been used to successfully breed crops with improved levels of drought resistance, where the target population of environments (TPEs) is a spatially and temporally heterogeneous mixture of drought-affected and favorable (water-sufficient) environments. Long-term improvement of temperate maize for the US corn belt is used as a case study and compared with progress for other crops and geographies. Integration of trait information across scales, from genomes to ecosystems, is needed to accurately predict yield outcomes for genotypes within the current and future TPEs. This will require transdisciplinary teams to explore, identify, and exploit novel opportunities to accelerate breeding program outcomes both improved germplasm resources and improved products (cultivars, hybrids, clones, and populations) that outperform and replace the products in use by farmers, in combination with modified agronomic management strategies suited to their local environments.

Integrating Breeding Tools to Generate Information for Efficient Breeding: Past, Present, and Future

Publisher: Wiley

Date: 10-05-2006

DOI: 10.1002/9780470752708.CH10

Modeling Qtl Effects and Mas in Plant Breeding

Publisher: Springer Netherlands

Date: 2007

DOI: 10.1007/978-1-4020-6295-7_4

Cornell University

Location: United States of America

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Pohang University Of Science And Technology

Location: Korea, Republic of

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DuPont Pioneer

Location: United States of America

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Zenrun42, Inc.

Location: United States of America

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University Of Queensland

Location: Australia

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Industrial Transformation Training Centres - Grant ID: IC230100016

Start Date: 2023

End Date: 12-2027

Amount: $5,000,000.00

Funder: Australian Research Council

Linkage Projects - Grant ID: LP210200723

Start Date: 05-2023

End Date: 05-2028

Amount: $1,062,378.00

Funder: Australian Research Council

ARC Centres Of Excellence - Grant ID: CE200100015

Start Date: 12-2020

End Date: 12-2027

Amount: $35,000,000.00

Funder: Australian Research Council