Wheat photosystem II heat tolerance: evidence for genotype-by-environment interactions.

High temperature stress inhibits photosynthesis and threatens wheat production. One measure of photosynthetic heat tolerance is Tcrit - the critical temperature at which incipient damage to photosystem II (PSII) occurs. This trait could be improved in wheat by exploiting genetic variation and genotype-by-environment interactions (GEI). Flag leaf Tcrit of 54 wheat genotypes was evaluated in 12 thermal environments over 3 years in Australia, and analysed using linear mixed models to assess GEI effects. Nine of the 12 environments had significant genetic effects and highly variable broad-sense heritability (H2 ranged from 0.15 to 0.75). Tcrit GEI was variable, with 55.6% of the genetic variance across environments accounted for by the factor analytic model. Mean daily growth temperature in the month preceding anthesis was the most influential environmental driver of Tcrit GEI, suggesting biochemical, physiological and structural adjustments to temperature requiring different durations to manifest. These changes help protect or repair PSII upon exposure to heat stress, and may improve carbon assimilation under high temperature. To support breeding efforts to improve wheat performance under high temperature, we identified genotypes superior to commercial cultivars commonly grown by farmers, and demonstrated potential for developing genotypes with greater photosynthetic heat tolerance.

Wheat photosystem II heat tolerance responds dynamically to short- and long-term warming.

Wheat photosynthetic heat tolerance can be characterized using minimal chlorophyll fluorescence to quantify the critical temperature (Tcrit) above which incipient damage to the photosynthetic machinery occurs. We investigated intraspecies variation and plasticity of wheat Tcrit under elevated temperature in field and controlled-environment experiments, and assessed whether intraspecies variation mirrored interspecific patterns of global heat tolerance. In the field, wheat Tcrit varied diurnally-declining from noon through to sunrise-and increased with phenological development. Under controlled conditions, heat stress (36 °C) drove a rapid (within 2 h) rise in Tcrit that peaked after 3-4 d. The peak in Tcrit indicated an upper limit to PSII heat tolerance. A global dataset [comprising 183 Triticum and wild wheat (Aegilops) species] generated from the current study and a systematic literature review showed that wheat leaf Tcrit varied by up to 20 °C (roughly two-thirds of reported global plant interspecies variation). However, unlike global patterns of interspecies Tcrit variation that have been linked to latitude of genotype origin, intraspecific variation in wheat Tcrit was unrelated to that. Overall, the observed genotypic variation and plasticity of wheat Tcrit suggest that this trait could be useful in high-throughput phenotyping of wheat photosynthetic heat tolerance.

Wheat respiratory O2 consumption falls with night warming alongside greater respiratory CO2 loss and reduced biomass.

Warming nights are correlated with declining wheat growth and yield. As a key determinant of plant biomass, respiration consumes O2 as it produces ATP and releases CO2 and is typically reduced under warming to maintain metabolic efficiency. We compared the response of respiratory O2 and CO2 flux to multiple night and day warming treatments in wheat leaves and roots, using one commercial (Mace) and one breeding cultivar grown in controlled environments. We also examined the effect of night warming and a day heatwave on the capacity of the ATP-uncoupled alternative oxidase (AOX) pathway. Under warm nights, plant biomass fell, respiratory CO2 release measured at a common temperature was unchanged (indicating higher rates of CO2 release at prevailing growth temperature), respiratory O2 consumption at a common temperature declined, and AOX pathway capacity increased. The uncoupling of CO2 and O2 exchange and enhanced AOX pathway capacity suggest a reduction in plant energy demand under warm nights (lower O2 consumption), alongside higher rates of CO2 release under prevailing growth temperature (due to a lack of down-regulation of respiratory CO2 release). Less efficient ATP synthesis, teamed with sustained CO2 flux, could thus be driving observed biomass declines under warm nights.

Identification of genomic regions conferring rust resistance and enhanced mineral accumulation in a HarvestPlus Association Mapping Panel of wheat.

KEY MESSAGE: New genomic regions for high accumulation of 10 minerals were identified. The 1B:1R and 2NS translocations enhanced concentrations of four and two minerals, respectively, in addition to disease resistance. Puccinia species, the causal agents of rust diseases of wheat, have the potential to cause total crop failures due their high evolutionary ability to acquire virulence for resistance genes deployed in commercial cultivars. Hence, the discovery of genetically diverse sources of rust resistance is essential. On the other hand, biofortification of wheat for essential nutrients, such as zinc (Zn) and iron (Fe), is also an objective in wheat improvement programs to tackle micronutrient deficiency. The development of rust-resistant and nutrient-concentrated wheat cultivars would be important for sustainable production and the fight against malnutrition. The HarvestPlus association mapping panel (HPAMP) that included nutrient-dense sources from diverse genetic backgrounds was genotyped using a 90 K Infinium SNP array and 13 markers linked with rust resistance genes. The HPAMP was used for genome-wide association mapping to identify genomic regions underpinning rust resistance and mineral accumulation. Twelve QTL for rust resistance and 53 for concentrations of 10 minerals were identified. Comparison of results from this study with the published QTL information revealed the detection of already known and some putatively new genes/QTL underpinning stripe rust and leaf rust resistance in this panel. Thirty-six new QTL for mineral concentration were identified on 17 chromosomes. Accessions carrying the 1B:1R translocation accumulated higher concentrations of Zn, Fe, Copper (Cu) and sulphur (S). The 2NS segment showed enhanced accumulation of grain Fe and Cu. Fifteen rust-resistant and biofortified accessions were identified for use as donor sources in breeding programs.

Genetic networks underlying salinity tolerance in wheat uncovered with genome-wide analyses and selective sweeps.

KEY MESSAGE: A genetic framework underpinning salinity tolerance at reproductive stage was revealed by genome-wide SNP markers and major adaptability genes in synthetic-derived wheats, and trait-associated loci were used to predict phenotypes. Using wild relatives of crops to identify genes related to improved productivity and resilience to climate extremes is a prioritized area of crop genetic improvement. High salinity is a widespread crop production constraint, and development of salt-tolerant cultivars is a sustainable solution. We evaluated a panel of 294 wheat accessions comprising synthetic-derived wheat lines (SYN-DERs) and modern bread wheat advanced lines under control and high salinity conditions at two locations. The GWAS analysis revealed a quantitative genetic framework of more than 200 loci with minor effect underlying salinity tolerance at reproductive stage. The significant trait-associated SNPs were used to predict phenotypes using a GBLUP model, and the prediction accuracy (r2) ranged between 0.57 and 0.74. The r2 values for flag leaf weight, days to flowering, biomass, and number of spikes per plant were all above 0.70, validating the phenotypic effects of the loci discovered in this study. Furthermore, the germplasm sets were compared to identify selection sweeps associated with salt tolerance loci in SYN-DERs. Six loci associated with salinity tolerance were found to be differentially selected in the SYN-DERs (12.4 Mb on chromosome (chr)1B, 7.1 Mb on chr2A, 11.2 Mb on chr2D, 200 Mb on chr3D, 600 Mb on chr6B, and 700.9 Mb on chr7B). A total of 228 reported markers and genes, including 17 well-characterized genes, were uncovered using GWAS and EigenGWAS. A linkage disequilibrium (LD) block on chr5A, including the Vrn-A1 gene at 575 Mb and its homeologs on chr5D, were strongly associated with multiple yield-related traits and flowering time under salinity stress conditions. The diversity panel was screened with more than 68 kompetitive allele-specific PCR (KASP) markers of functional genes in wheat, and the pleiotropic effects of superior alleles of Rht-1, TaGASR-A1, and TaCwi-A1 were revealed under salinity stress. To effectively utilize the extensive genetic information obtained from the GWAS analysis, a genetic interaction network was constructed to reveal correlations among the investigated traits. The genetic network data combined with GWAS, selective sweeps, and the functional gene survey provided a quantitative genetic framework for identifying differentially retained loci associated with salinity tolerance in wheat.

Leaf prickle hairs and longitudinal grooves help wheat plants capture air moisture as a water-smart strategy for a changing climate.

MAIN CONCLUSION: The leaf features like trichome density, gradient grooves, and leaf wettability determine the efficiency to capture air moisture for self-irrigation in the wheat plant. Plants in water-scarce environments evolved to capture air moisture for their water needs either directly or indirectly. Structural features like cones, hairs, and grooves assist water capture. The morphology of crops such as wheat can promote self-irrigation under drought. To examine this further, 34 wheat genotypes were characterized for leaf traits in near optimal conditions in the field using a randomized complete block design with 3 replications. An association was found between morphological and physiological traits and yield using simple correlation plots. A core set of nine genotypes was subsequently evaluated for moisture harvesting ability and leaf wettability. Results showed that variation among genotypes exists for fog harvesting ability attributed to structural leaf features. Physiological traits, especially photosynthesis and water use efficiency, were positively associated with yield, negatively correlated with soil moisture at booting, and positively correlated with soil moisture at anthesis. The genotypes with deep to medium leaf grooves and dense hairs on the edges and adaxial surfaces (genotypes 7 and 18) captured the most moisture. This was a function of higher water drop rolling efficiency resulting from lower contact angle hysteresis. These results can be exploited to develop more heat and drought-tolerant crops.

Acclimation of leaf photosynthesis and respiration to warming in field-grown wheat.

Climate change and future warming will significantly affect crop yield. The capacity of crops to dynamically adjust physiological processes (i.e., acclimate) to warming might improve overall performance. Understanding and quantifying the degree of acclimation in field crops could ensure better parameterization of crop and Earth System models and predictions of crop performance. We hypothesized that for field-grown wheat, when measured at a common temperature (25°C), crops grown under warmer conditions would exhibit acclimation, leading to enhanced crop performance and yield. Acclimation was defined as (a) decreased rates of net photosynthesis at 25°C (A25 ) coupled with lower maximum carboxylation capacity (Vcmax25 ), (b) reduced leaf dark respiration at 25°C (both in terms of O2 consumption Rdark _O225 and CO2 efflux Rdark _CO225 ) and (c) lower Rdark _CO225 to Vcmax25 ratio. Field experiments were conducted over two seasons with 20 wheat genotypes, sown at three different planting dates, to test these hypotheses. Leaf-level CO2 -based traits (A25 , Rdark _CO225 and Vcmax25 ) did not show the classic acclimation responses that we hypothesized; by contrast, the hypothesized changes in Rdark_ O2 were observed. These findings have implications for predictive crop models that assume similar temperature response among these physiological processes and for predictions of crop performance in a future warmer world.

Meta-analysis of genome-wide association studies reveal common loci controlling agronomic and quality traits in a wide range of normal and heat stressed environments.

KEY MESSAGE: Several stable QTL were detected using metaGWAS analysis for different agronomic and quality traits under 26 normal and heat stressed environments. Heat stress, exacerbated by global warming, has a negative influence on wheat production worldwide and climate resilient cultivars can help mitigate these impacts. Selection decisions should therefore depend on multi-environment experiments representing a range of temperatures at critical stages of development. Here, we applied a meta-genome wide association analysis (metaGWAS) approach to detect stable QTL with significant effects across multiple environments. The metaGWAS was applied to 11 traits scored in 26 trials that were sown at optimal or late times of sowing (TOS1 and TOS2, respectively) at five locations. A total of 2571 unique wheat genotypes (13,959 genotypes across all environments) were included and the analysis conducted on TOS1, TOS2 and both times of sowing combined (TOS1&2). The germplasm was genotyped using a 90 k Infinium chip and imputed to exome sequence level, resulting in 341,195 single nucleotide polymorphisms (SNPs). The average accuracy across all imputed SNPs was high (92.4%). The three metaGWAS analyses revealed 107 QTL for the 11 traits, of which 16 were detected in all three analyses and 23 were detected in TOS1&2 only. The remaining QTL were detected in either TOS1 or TOS2 with or without TOS1&2, reflecting the complex interactions between the environments and the detected QTL. Eight QTL were associated with grain yield and seven with multiple traits. The identified QTL provide an important resource for gene enrichment and fine mapping to further understand the mechanisms of gene × environment interaction under both heat stressed and unstressed conditions.

Genomic selection can accelerate the biofortification of spring wheat.

KEY MESSAGE: Genomic selection enabled accurate prediction for the concentration of 13 nutritional element traits in wheat. Wheat biofortification is one of the most sustainable strategies to alleviate mineral deficiency in human diets. Here, we investigated the potential of genomic selection using BayesR and Bayesian ridge regression (BRR) models to predict grain yield (YLD) and the concentration of 13 nutritional elements in grains (B, Ca, Co, Cu, Fe, K, Mg, Mn, Mo, Na, Ni, P and Zn) using a population of 1470 spring wheat lines. The lines were grown in replicated field trials with two times of sowing (TOS) at 3 locations (Narrabri-NSW, all lines; Merredin-WA and Horsham-VIC, 200 core lines). Narrow-sense heritability across environments (locations/TOS) ranged from 0.09 to 0.45. Co, K, Na and Ca showed low to negative genetic correlations with other traits including YLD, while the remaining traits were negatively correlated with YLD. When all environments were included in the reference population, medium to high prediction accuracy was observed for the different traits across environments. BayesR had higher average prediction accuracy for mineral concentrations (r = 0.55) compared to BRR (r = 0.48) across all traits and environments but both methods had comparable accuracies for YLD. We also investigated the utility of one or two locations (reference locations) to predict the remaining location(s), as well as the ability of one TOS to predict the other. Under these scenarios, BayesR and BRR showed comparable performance but with lower prediction accuracy compared to the scenario of predicting reference environments for new lines. Our study demonstrates the potential of genomic selection for enriching wheat grain with nutritional elements in biofortification breeding.

Lr80: A new and widely effective source of leaf rust resistance of wheat for enhancing diversity of resistance among modern cultivars.

KEY MESSAGE: A new leaf rust resistance gene Lr80 was identified and closely linked markers were developed for its successful pyramiding with other marker-tagged genes to achieve durable control of leaf rust. Common wheat landrace Hango-2, collected in 2006 from the Himalayan area of Hango, District Kinnaur, in Himachal Pradesh, exhibited a very low infection type (IT;) at the seedling stage to all Indian Puccinia triticina (Pt) pathotypes, except the pathotype 5R9-7 which produced IT 3+. Genetic analysis based on Agra Local/Hango-2-derived F3 families indicated monogenic control of leaf rust resistance, and the underlying locus was temporarily named LrH2. Bulked segregant analysis using 303 simple sequence repeat (SSR) markers located LrH2 in the short arm of chromosome 2D. An additional set of 10 chromosome 2DS-specific markers showed polymorphism between the parents and these were mapped on the entire Agra Local/Hango-2 F3 population. LrH2 was flanked by markers cau96 (distally) and barc124 (proximally). The 90 K Infinium SNP array was used to identify SNP markers linked with LrH2. Markers KASP_17425 and KASP_17148 showed association with LrH2. Comparison of seedling leaf rust response data and marker locations across different maps demonstrated the uniqueness of LrH2 and it was formally named Lr80. The Lr80-linked markers KASP_17425, KASP_17148 and barc124 amplified alleles/products different to Hango-2 in 82 Australian cultivars indicating their robustness for marker-assisted selection of this gene in wheat breeding programs.

Generation and molecular marker and cytological characterization of wheat - Secale strictum subsp. anatolicum derivatives.

Cereal rye and its wild forms are important sources of genetic diversity for wheat breeding due to their resistances to biotic and abiotic stresses. Secale strictum subsp. anatolicum (Boiss.) K. Hammer (SSA) is a weedy relative of cultivated rye, S. cereale. Meiotic chromosome pairing in F1 hybrids of SSA and S. cereale reveals strong genomic affinity between the two genomes. A study of the transferability of S. cereale sequence-based markers to SSA and hexaploid triticale demonstrated their applicability for tracing SSA chromatin in wheat. The transferability of the markers was over 80% from homoeologous groups 1, 2, and 3, and greater than 70% from groups 4 to 7. This study focused on the generation and molecular and cytogenetic characterization of wheat-SSA alien derivatives. Twelve were identified using combinations of non-denaturing fluorescence in situ hybridization (ND-FISH), genomic in situ hybridization (GISH), and molecular marker analysis. All SSA chromosomes, except 3Ra and 6Ra, were transferred to wheat either in the form of monosomic additions (MA), mono-telosomic additions (MtA), double-mono-telosomic additions (dMtA), or double-monosomic additions (dMA). The germplasm developed in this study will help to enhance the genetic base of wheat and facilitate molecular breeding of wheat and triticale.

Genome-wide association study of multiple traits linked to heat tolerance in emmer-derived hexaploid wheat genotypes.

Heat stress tolerance in plants is a complex trait controlled by multiple genes of minor effect which are influenced by the environment and this makes breeding and selection complicated. Emmer wheat (Triticum dicoccon Schrank) carries valuable diversity that can be used to improve the heat tolerance of modern bread wheat. A diverse set of emmer-based genotypes was developed by crossing emmer wheat with hexaploid wheat. These materials, along with their hexaploid recurrent parents and commercial cultivars, were evaluated at optimum (E1) and heat stressed (E2) sowing times in the field for three consecutive years (2014-2016). The material was genotyped using the Infinium iSelect SNP 90K SNP Assay. The phenotypic data were combined across years within each sowing time and best linear unbiased estimators calculated for each genotype in each environment. These estimates were used for GWAS analysis. Significant phenotypic and genotypic variation was observed for all traits. A total of 125 and 142 marker-trait associations (MTAs) were identified in E1 and E2, respectively. The highest number of MTAs were observed on the A genome (106), followed by the B (105) and D (56) genomes. MTAs with pleiotropic effects within and across the environments were observed. Many of the MTAs found were reported previously for various traits, and a few significant MTAs under heat stress were new and linked to emmer genome. Genomic regions identified on chromosomes 2B and 3A had a significant positive impact on grain yield under stress with a 7% allelic effect. Genomic regions on chromosomes 1A and 4B contributed 11% and 9% of the variation for thousand kernel weight (TKW) under heat stress respectively. Following fine mapping, these regions could be used for marker-assisted selection to improve heat tolerance in wheat. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01222-3.

Pathogenic Specialization in Uromyces viciae-fabae in Australia and Rust Resistance in Faba Bean.

The pathogen Uromyces viciae-fabae causes rust (a fungal disease) on faba bean (Vicia faba). This disease limits faba bean production in Africa, Asia, Europe, and Australia. The development of resistant cultivars to U. viciae-fabae is the optimal solution for sustainable disease management. However, unknown virulence in Australian U. viciae-fabae populations has confounded resistance breeding. This study examined differences in virulence among Australian U. viciae-fabae isolates collected from various locations and established a differential set of faba bean genotypes. Ten rust isolates were collected from the major faba bean growing regions in Australia and single spore cultures produced. These cultures were subsequently used for assessing virulence on 40 diverse faba bean genotypes. Based on the host-pathogen interactions, 12 putative host genotypes were identified as a differential set. A nomenclature system was subsequently developed using the binary pathotype naming system. Based upon host-pathogen interactions, nine virulence patterns were detected, and the isolates were named using the new nomenclature. We report characterization and naming of U. viciae-fabae pathotypes using differential genotypes in Australia. This differential set will help identify and track the evolution of new virulence in pathogen population and will assist pyramiding of rust resistance genes.

Identification and characterization of a new stripe rust resistance gene Yr83 on rye chromosome 6R in wheat.

KEY MESSAGE: A physical map of Secale cereale chromosome 6R was constructed using deletion mapping, and a new stripe rust resistance gene Yr83 was mapped to the deletion bin of FL 0.73-1.00 of 6RL. Rye (Secale cereale L., RR) possesses valuable genes for wheat improvement. In the current study, we report a resistance gene conferring stripe rust resistance effective from seedling to adult plant stages located on chromosome 6R. This chromosome was derived from triticale line T-701 and also carries highly effective resistance to the cereal cyst nematode species Heterodera avenae Woll. A wheat-rye 6R(6D) disomic substitution line exhibited high levels of seedling resistance to Australian pathotypes of the stripe rust (Puccinia striiformis f. sp. tritici; Pst) pathogen and showed an even greater resistance to the Chinese Pst pathotypes in the field. Ten chromosome 6R deletion lines and five wheat-rye 6R translocation lines were developed earlier in the attempt to transfer the nematode resistance gene to wheat and used herein to map the stripe rust resistance gene. These lines were subsequently characterized by sequential multicolor fluorescence in situ hybridization (mc-FISH), genomic in situ hybridization (GISH), mc-GISH, PCR-based landmark unique gene (PLUG), and chromosome 6R-specific length amplified fragment sequencing (SLAF-Seq) marker analyses to physically map the stripe rust resistance gene. The new stripe rust resistance locus was located in a chromosomal bin with fraction length (FL) 0.73-1.00 on 6RL and was named Yr83. A wheat-rye translocation line T6RL (#5) carrying the stripe rust resistance gene will be useful as a new germplasm in breeding for resistance.

Development and molecular cytogenetic characterization of Thinopyrum bessarabicum introgression lines in hexaploid and tetraploid wheats.

KEY MESSAGE: A variety of Thinopyrum bessarabicum introgressions in both hexaploid and tetraploid wheats were generated and characterized by molecular cytogenetic analysis. Six wheat-J genome recombinants were identified with ND-FISH and GISH. Diploid wheatgrass, Thinopyrum bessarabicum (2n = 2x = 14, EbEb or JbJb or JJ), is a well-known alien source of salinity tolerance and disease resistance for wheat improvement. The true genetic potential and effect of such introgressions into wheat can be best studied in chromosomal addition or substitution lines. Here, we report the generation and characterization of various categories of Th. bessarabicum derivatives in both hexaploid and tetraploid cultivated wheats. Sequential non-denaturing fluorescence in situ hybridization (ND-FISH) and genomic in situ hybridization (GISH) are robust techniques to visualize the size of alien introgressions and breakpoints. We identified a complete set of monosomic addition lines into both bread wheat and durum wheat, except for 7J in durum wheat, by sequential ND-FISH and GISH. We also characterized alien derivatives belonging to various classes including mono-telosomic additions, disomic additions, monosomic substitutions, double monosomic substitutions, monosomic substitution-monosomic additions, double monosomic additions, and multiple monosomic additions into both bread and durum wheats. In addition, various wheat-Th. bessarabicum recombinant chromosomes were also detected in six alien derivatives. These wheat-Th. bessarabicum derivatives will provide useful cytogenetic resources for improvement of both hexaploid and tetraploid wheats.

Phenology and related traits for wheat adaptation.

Wheat is a major food crop, with around 765 million tonnes produced globally. The largest wheat producers include the European Union, China, India, Russia, United States, Canada, Pakistan, Australia, Ukraine and Argentina. Cultivation of wheat across such diverse global environments with variation in climate, biotic and abiotic stresses, requires cultivars adapted to a range of growing conditions. One intrinsic way that wheat achieves adaptation is through variation in phenology (seasonal timing of the lifecycle) and related traits (e.g., those affecting plant architecture). It is important to understand the genes that underlie this variation, and how they interact with each other, other traits and the growing environment. This review summarises the current understanding of phenology and developmental traits that adapt wheat to different environments. Examples are provided to illustrate how different combinations of alleles can facilitate breeding of wheat varieties with optimal crop performance for different growing regions or farming systems.

Development of RNA-seq-based molecular markers for characterizing Thinopyrum bessarabicum and Secale introgressions in wheat.

Sequence-based markers have added a new dimension in the efficiency of identifying alien introgressions in wheat. Expressed sequence tag-sequence tagged sites (EST-STS) markers have proved useful in tracing alien chromatin. In this study, we report the development of Thinopyrum bessarabicum- and Secale anatolicum-specific EST-STS markers and their application in tracing respective alien chromatin introgressions in wheat. The parental lines, Chinese Spring (CS), ISR991.1 (CS/Th. bessarabicum amphidiploid), and ISR1049.2 (CS/Secale anatolicum amphidiploid), were used as core experimental materials. Using comparative analysis of RNA-Seq data, 10 903 and 10 660 candidate sequences specific to Th. bessarabicum and S. anatolicum, respectively, were assembled and identified. To validate the genome specificity of these candidate sequences, 68 and 64 EST-STS markers were developed from randomly selected candidate sequences of Th. bessarabicum and S. anatolicum, respectively, and tested on sets of alien addition lines. Fifty-five and 53 markers for Th. bessarabicum and S. anatolicum chromatin, respectively, were assigned to chromosomal location(s), covering all seven chromosomes. Approximately 83% of S. anatolicum-specific markers were transferable to S. cereale. The genome-specific candidate sequences identified and the EST-STS markers developed will be valuable resources for exploitation of Th. bessarabicum and Secale species diversity in wheat and triticale breeding.

Rate of photosynthetic induction in fluctuating light varies widely among genotypes of wheat.

Crop photosynthesis and yield are limited by slow photosynthetic induction in sunflecks. We quantified variation in induction kinetics across diverse genotypes of wheat for the first time. Following a preliminary study that hinted at wide variation in induction kinetics across 58 genotypes, we grew 10 genotypes with contrasting responses in a controlled environment and quantified induction kinetics of carboxylation capacity (Vcmax) from dynamic A versus ci curves after a shift from low to high light (from 50 µmol m-2 s-1 to 1500 µmol m-2 s-1), in five flag leaves per genotype. Within-genotype median time for 95% induction (t95) of Vcmax varied 1.8-fold, from 5.2 min to 9.5 min. Our simulations suggest that non-instantaneous induction reduces daily net carbon gain by up to 15%, and that breeding to speed up Vcmax induction in the slowest of our 10 genotypes to match that in the fastest genotype could increase daily net carbon gain by up to 3.4%, particularly for leaves in mid-canopy positions (cumulative leaf area index ≤1.5 m2 m-2), those that experience predominantly short-duration sunflecks, and those with high photosynthetic capacities.

Exploring high temperature responses of photosynthesis and respiration to improve heat tolerance in wheat.

High temperatures account for major wheat yield losses annually and, as the climate continues to warm, these losses will probably increase. Both photosynthesis and respiration are the main determinants of carbon balance and growth in wheat, and both are sensitive to high temperature. Wheat is able to acclimate photosynthesis and respiration to high temperature, and thus reduce the negative affects on growth. The capacity to adjust these processes to better suit warmer conditions stands as a potential avenue toward reducing heat-induced yield losses in the future. However, much remains to be learnt about such phenomena. Here, we review what is known of high temperature tolerance in wheat, focusing predominantly on the high temperature responses of photosynthesis and respiration. We also identify the many unknowns that surround this area, particularly with respect to the high temperature response of wheat respiration and the consequences of this for growth and yield. It is concluded that further investigation into the response of photosynthesis and respiration to high temperature could present several methods of improving wheat high temperature tolerance. Extending our knowledge in this area could also lead to more immediate benefits, such as the enhancement of current crop models.

Extension of a haplotype-based genomic prediction model to manage multi-environment wheat data using environmental covariates.

KEY MESSAGE: A multi-environment genomic prediction model incorporating environmental covariates increased the prediction accuracy of wheat grain protein content. The advantage of the haplotype-based model was dependent upon the trait of interest. The inclusion of environment covariates (EC) in genomic prediction models has the potential to precisely model environmental effects and genotype-by-environment interactions. Together with EC, a haplotype-based genomic prediction approach, which is capable of accommodating the interaction between local epistasis and environment, may increase the prediction accuracy. The main objectives of our study were to evaluate the potential of EC to portray the relationship between environments and the relevance of local epistasis modelled by haplotype-based approaches in multi-environment prediction. The results showed that among five traits: grain yield (GY), plant height, protein content, screenings percentage (SP) and thousand kernel weight, protein content exhibited a 2.1% increase in prediction accuracy when EC was used to model the environmental relationship compared to treatment of the environment as a regular random effect without a variance-covariance structure. The approach used a Gaussian kernel to characterise the relationship among environments that displayed no advantage in contrast to the use of a genomic relationship matrix. The prediction accuracies of haplotype-based approaches for SP were consistently higher than the genotype-based model when the numbers of single-nucleotide polymorphisms (SNP) in a haplotype were from three to ten. In contrast, for GY, haplotype-based models outperformed genotype-based methods when two to four SNPs were used to construct the haplotype.