Powdery mildew (Blumeria graminis f. sp. tritici) results in serious economic loss in wheat production. Exploration of plant resistance to wheat powdery mildew over several decades has led to the discovery of a wealth of resistance genes and quantitative trait loci (QTLs). We have provided a comprehensive summary of over 200 powdery mildew genes (permanently and temporarily designated genes) and QTLs reported in common bread wheat. This highlights the diverse and rich resistance sources that exist across all 21 chromosomes. To manage different data for breeders, here we also present a bridged mapping result from previously reported powdery mildew resistance genes and QTLs with the application of a published integrated wheat map. This will provide important insights to empower further breeding of powdery mildew resistant wheat via marker‐assisted selection (MAS).

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Durum wheat (Triticum turgidum L. ssp. durum) production can experience significant yield losses due to crown rot (CR) disease. Losses are usually exacerbated when disease infection coincides with terminal drought. Durum wheat is very susceptible to CR, and resistant germplasm is not currently available in elite breeding pools. We hypothesize that deploying physiological traits for drought adaptation, such as optimal root system architecture to reduce water stress, might minimize losses due to CR infection. This study evaluated a subset of lines from a nested association mapping population for stay-green traits, CR incidence and yield in field experiments as well as root traits under controlled conditions. Weekly measurements of normalized difference vegetative index (NDVI) in the field were used to model canopy senescence and to determine stay-green traits for each genotype. Genome-wide association studies using DArTseq molecular markers identified quantitative trait loci (QTLs) on chromosome 6B (qCR-6B) associated with CR tolerance and stay-green. We explored the value of qCR-6B and a major QTL for root angle QTL qSRA-6A using yield datasets from six rainfed environments, including two environments with high CR disease pressure. In the absence of CR, the favorable allele for qSRA-6A provided an average yield advantage of 0.57 t·ha−1, whereas in the presence of CR, the combination of favorable alleles for both qSRA-6A and qCR-6B resulted in a yield advantage of 0.90 t·ha−1. Results of this study highlight the value of combining above- and belowground physiological traits to enhance yield potential. We anticipate that these insights will assist breeders to design improved durum varieties that mitigate production losses due to water deficit and CR.

Mungbean (Vigna radiata (L.) R. Wilczek var. radiata) is a significant food and cash crop grown in tropical and subtropical regions. Mungbean production and consumer demand have increased substantially over the last two decades, owing to its agronomic, nutritional and economic benefits. Despite increased breeding efforts and the expansion of mungbean production in various agro‐climatic regions, further production is hindered by low yield and variability, which is partly attributed to the impacts of abiotic stress. Abiotic stress impacts on the physiology, morphology and reproductive ability of mungbean which influences yield. Exposure to abiotic stresses at the reproductive stage is considered the most critical for yield production. In this review, we evaluate how abiotic stress impacts mungbean growth and productivity when occurring during the reproductive stage and traits that may confer adaptation. We present the limitations of current research including limited number of genotypes, lack of field experiments and detailed experimental information. We highlight the opportunities to exploit new tools and technologies, such as high‐throughput phenotyping platforms, gene editing, and genomic selection, to accelerate breeding efforts to develop more resilient mungbean cultivars for today and tomorrow.

Durum wheat (Triticum turgidum L. ssp. Durum) is largely grown in rainfed production systems around the world. New cultivars with improved adaptation to water-limited environments are required to sustain productivity in the face of climate change. Physiological traits related to canopy development underpin the production of biomass and yield, as they interact with solar radiation and affect the timing of water use throughout the growing season. Despite their importance, there is limited research on the relationship between canopy development and yield in durum wheat, in particular studies exploring temporal canopy dynamics under field conditions. This study reports the genetic dissection of canopy development in a durum wheat nested-association mapping population evaluated for longitudinal normalized difference vegetation index (NDVI) measurements. Association mapping was performed to identify quantitative trait loci (QTL) for time-point NDVI and spline-smoothed NDVI trajectory traits. Yield effects associated with QTL for canopy development were explored using data from four rainfed field trials. Four QTL were associated with yield in specific environments, and notably, were not associated with a yield penalty in any environment. Alleles associated with slow canopy closure increased yield. This was likely due to a combined effect of optimised timing of water-use and pleiotropic effects on yield component traits, including spike number and spike length. Overall, this study suggests that slower canopy closure is beneficial for durum wheat production in rainfed environments. Selection for traits or loci associated with canopy development may indirectly improve yield and support selection for more resilient and productive cultivars in water limited environments.

Durum wheat (Triticum turgidum L.) breeding programs face many challenges surrounding the development of stable varieties with high quality and yield. Therefore, researchers and breeders are focused on deciphering the genetic architecture of biotic and abiotic traits with the aim of pyramiding desirable traits. These efforts require access to diverse genetic resources, including wild relatives, germplasm collections, and mapping populations. Advances in accelerated generation technologies have enabled the rapid development of mapping populations with signi cant genetic diversity. Here, we describe the development of a durum Nested Association Mapping (dNAM) population, which represents a valuable genetic resource for mapping the effects of different alleles on trait performance. We created this population to understand the quantitative nature of drought-adaptive traits in durum wheat. We developed 920 F 6 lines in only 18 months using speed breeding technology, including the F 4 generation in the eld. Large variation in above-and belowground traits was observed, which could be harnessed using genetic mapping and breeding approaches. We genotyped the population using 13,393 DArTseq markers. Quality control resulted in 6,785 high-quality polymorphic markers used for structure analysis, linkage disequilibrium decay, and marker-trait association analyses. To demonstrate the effectiveness of dNAM as a resource for elucidating the genetic control of quantitative traits, we took a genomewide mapping approach using the FarmCPU method for plant height and days to owering. These results highlight the power of using dNAM as a tool to dissect the genetics of durum wheat traits, supporting the development of varieties with improved adaptation and yield.

Aims Rhizoboxes allow non-invasive phenotyping of root systems and are often used as an alternative to evaluation in the field which typically requires excavation, a laborious endeavour. Semi-automated rhizobox methods can be used to screen large numbers of plants, but these platforms can be expensive due to the cost of customised components, assembly, and maintenance, which limits the accessibility for many root researchers. To widen access to the rhizobox method—for example for preliminary screening of germplasm for root system architecture traits—we present a method to build a simple, low-cost rhizobox method using widely available materials, which should allow any research group to conduct root experiments and phenotype root system architecture in their own laboratories and greenhouses. Methods The detailed construction of 80 wooden rhizoboxes is described (each 40 cm width x 90 cm height x 6 cm depth; total cost 1,786 AUD, or 22 AUD or [$15 USD] per rhizobox). Using a panel of 20 spring wheat lines, including parental lines and derived intro-selection lines selected for divergent seedling root traits (seminal root angle and root biomass), genotypic variation in root biomass distribution were examined in the upper (0–30 cm), middle (30–60 cm) and lower sections (60–90 cm) of the rhizobox. At the conclusion of the experiment, rhizobox covers were removed and the exposed roots were imaged prior to destructive root washing. Root morphological traits were extracted from the images using RhizoVision Explorer (Seethepalli and York 2020). Results There were significant genotypic differences in total root biomass in the upper and middle sections of the rhizobox, but differences were not detected in the deepest section. Compared with the recurrent elite parent Borlaug100, some of the intro-selection lines showed greater biomass (or less), depending on the status of the root biomass QTL on chromosome 5B. Genotypes also differed in shoot biomass and tiller number. The donor lines for high and low root biomass showed corresponding differences in shoot biomass. Additional root parameters such as total root length and branching frequency were obtained through image analysis and genotypic effects were detected at different depths. Conclusions The rhizobox set up is easy-to-build-and-implement for phenotyping the root distribution of wheat. This will support root research and breeding efforts to identify and utilise sources of genetic variation for target root traits that are needed to develop future wheat cultivars with improved resource use efficiency and yield stability.

Durum wheat (Triticum turgidum L.) breeding programs face many challenges surrounding the development of stable varieties with high quality and yield. Therefore, researchers and breeders are focused on deciphering the genetic architecture of biotic and abiotic traits with the aim of pyramiding desirable traits. These efforts require access to diverse genetic resources, including wild relatives, germplasm collections, and mapping populations. Advances in accelerated generation technologies have enabled the rapid development of mapping populations with significant genetic diversity. Here, we describe the development of a durum Nested Association Mapping (dNAM) population, which represents a valuable genetic resource for mapping the effects of different alleles on trait performance. We created this population to understand the quantitative nature of drought-adaptive traits in durum wheat. We developed 920 F6 lines in only 18 months using speed breeding technology, including the F4 generation in the field. Large variation in above- and belowground traits was observed, which could be harnessed using genetic mapping and breeding approaches. We genotyped the population using 13,393 DArTseq markers. Quality control resulted in 6,785 high-quality polymorphic markers used for structure analysis, linkage disequilibrium decay, and marker-trait association analyses. To demonstrate the effectiveness of dNAM as a resource for elucidating the genetic control of quantitative traits, we took a genome-wide mapping approach using the FarmCPU method for plant height and days to flowering. These results highlight the power of using dNAM as a tool to dissect the genetics of durum wheat traits, supporting the development of varieties with improved adaptation and yield.