Background Genetic variation of regulatory alleles plays a key role in evolution and breeding. In polyploids, regulatory differences may preferentially affect genes on homoeologous chromosomes or sub-genomes. Selection in plant breeding may act upon total transcript dosage across homoeologous genes and on alleles that have strong effects on the transcriptome. Results To investigate these questions, we identified regulatory polymorphisms between an old and a recent hexaploid bread wheat cultivar ( Triticum aestivum , 2n=6x=42, AABBDD). The recent cultivar was the product of decades of selection for grain yield and quality. Regulatory allele polymorphisms preferentially affected genes on homoeologous chromosomes but rarely affected genes on specific sub-genomes. The chromosomal distributions of regulatory alleles indicated that past selection had acted upon them, and the effect of selection differed between alleles targeting environmental response genes and genes involved in other processes. Modern cultivar alleles that affected many genes’ transcripts corresponded to known selection targets and improved field crop performance. Modern cultivar alleles also had significant effects on homoeologous genes, and these alleles also improved crop performance. Conclusions Polyploid breeding across many species has been and will continue to be the key factor in plant improvement. By enhancing the favorability of strong regulatory alleles and by expanding the range of gene transcript abundances, genome duplications enable breeding progress. ### Competing Interest Statement The authors have declared no competing interest. * RNA-seq : RNA sequencing; SNP : Single Nucleotide Polymorphism cis-eQTL : cis-acting expression quantitative trait locus trans-eQTL : trans-acting expression quantitative trait locus UTR : Untranslated region DHLs : Doubled Haploid Lines TMM : trimmed mean of M-values FDR : false discovery rate GO : Gene Ontology BP : biological process SpikeL : spike length TKW : thousand kernel weight GA : gibberellin LASSO : Least Absolute Shrinkage and Selection Operator. Genome Canada, https://ror.org/029s29983 The Natural Sciences and Engineering Research Council of Canada

Ergot, caused by the fungus Claviceps purpurea, affects cereal crops such as wheat, barley, and rye. Producing ergot inoculum for research purposes and screening breeding materials for resistance has been a time-consuming and labor-intensive process. We aimed to modify the existing inoculum production process used by the wheat pathology and breeding programs at AAFCSwift Current. We developed a simpler and more efficient inoculum production method that yields consistent results. This paper presents this innovative approach to ergot inoculum production method.

Yield reliability under diverse environments is important to address climate stress consequences in wheat production systems. Breeding for reliability under a changing climate remains a challenge in wheat. We assessed the performance of 18 hexaploid (Triticum aestivum L.) genotypes in three field environments at a location within the semi-arid Canadian Prairies over four years with a primary aim to establish knowledge of the phenotypic plasticity and yield reliability in the parental lines as it relates to heat and drought stress tolerance. We collected data on various physiological traits along with some agronomic and morphological attributes, uncovering significant variation across early seeded rainfed, early seeded irrigated, and late seeded rainfed (hot and dry) environments. Eight high yielding hexaploid genotypes '01S0263-28', 'AC Foremost', AC Karma', 'Cutler', 'MN03358-4', 'Reeder', 'Stettler', and 'Superb' showed higher grain Δ13C. Six of these genotypes '01S0263-28', 'AC Foremost', 'MN03358-4', 'Reeder', 'Stettler', and 'Superb' showed higher water use efficiency under irrigated as well as hot and dry environment compared to the low yielding lines 'Red Fife','8021-V2' and 'BW278'. Only four genotypes '01S0263-28', 'MN03358-4', 'Reeder', and 'Stettler' were found with higher yield reliability index. The grain yield relationship with leaf rolling, glaucousness, and canopy temperature was found to be weak. The flag leaf stomatal numbers increased with water stress in high yielding lines which were otherwise low in stomatal numbers. Contrastingly, water stress significantly reduced the stomatal numbers in low yielding lines that were otherwise high in stomatal numbers. The results highlight the stomatal adaptability of different genotypes in response to drought. Taken together, these results provide baseline information that the genotypes with high grain Δ13C and WUE, and low stomata numbers are more yield reliable under variable field environments, and this information can guide the breeding of climate-resilient germplasm that expresses consistent and reliable grain yield production in the semi-arid Prairies.

Fusarium head blight (FHB) infection results in Fusarium damaged kernels (FDK) and deoxynivalenol (DON) contamination that are downgrading factors at the Canadian elevators. Durum wheat (Triticum turgidum L. var. durum Desf.) is particularly susceptible to FHB and most of the adapted Canadian durum wheat cultivars are susceptible to moderately susceptible to this disease. However, the durum line DT696 is less susceptible to FHB than commercially grown cultivars. Little is known about genetic variation for durum wheat ability to resist FDK infection and DON accumulation. This study was undertaken to map genetic loci conferring resistance to DON and FDK resistance using a SNP high-density genetic map of a DT707/DT696 DH population and to identify SNP markers useful in marker-assisted breeding. One hundred twenty lines were grown in corn spawn inoculated nurseries near Morden, MB in 2015, 2016 and 2017 and the harvested seeds were evaluated for DON. The genetic map of the population was used in quantitative trait locus analysis performed with MapQTL.6® software. Four DON accumulation resistance QTL detected in two of the three years were identified on chromosomes 1 A, 5 A (2 loci) and 7 A and two FDK resistance QTL were identified on chromosomes 5 and 7 A in single environments. Although not declared significant due to marginal LOD values, the QTL for FDK on the 5 and 7 A were showing in other years suggesting their effects were real. DT696 contributed the favourable alleles for low DON and FDK on all the chromosomes. Although no resistance loci contributed by DT707, transgressive segregant lines were identified resulting in greater resistance than DT696. Breeder-friendly KASP markers were developed for two of the DON and FDK QTL detected on chromosomes 5 and 7 A. Markers flanking each QTL were physically mapped against the durum wheat reference sequence and candidate genes which might be involved in FDK and DON resistance were identified within the QTL intervals. The DH lines harboring the desired resistance QTL will serve as useful resources in breeding for FDK and DON resistance in durum wheat. Furthermore, breeder-friendly KASP markers developed during this study will be useful for the selection of durum wheat varieties with low FDK and DON levels in durum wheat breeding programs.

Ambitious biodiversity goals to protect 30% or more of the Earth’s surface by 2030 (30x30) require strategic near-term targets. To define areas that must be protected to prevent the most likely and imminent extinctions, we propose Conservation Imperatives—16,825 unprotected sites spanning ~164 Mha of the terrestrial realm that harbor rare and threatened species. We estimate that protecting the Conservation Imperatives would cost approximately US$169 billion (90% probability: US$146—US$228 billion). Globally, 38% of the 16,825 sites are either adjacent to or within 2.5 km of an existing protected area, potentially reducing land acquisition and management costs. These sites should be prioritized for conservation action over the next 5 years as part of a broader strategy to expand the global protected area network. The expansion of global protected areas between 2018 and 2023 incorporated only 7% of sites harboring range-limited and threatened species, highlighting a renewed urgency to conserve these habitats. Permanently protecting only 0.74% of land found in the tropics, where Conservation Imperatives are concentrated, could prevent the majority of predicted near-term extinctions once adequately resourced. We estimate this cost to be from US$29 billion to US$46 billion per year over the next 5 years. Multiple approaches will be required to meet long-term protection goals: providing rights and titles to Indigenous Peoples and Local Communities (IPLCs) conserving traditional lands, government designation of new protected areas on federal and state lands, and land purchase or long-term leasing of privately held lands.

AAC McMurphy is a semi-leafless, yellow cotyledonary field pea (Pisum sativum L.) cultivar developed at Agriculture and Agri-Food Canada Lacombe Research and Development Centre, Lacombe, Alberta, Canada. It has a maturity of 90 days, onethousand-seed weight of 246 g, and a lodging score of 2.9 on the scale of 1-9. The seed crude protein content of AAC McMurphy is 24.2%. AAC McMurphy is resistant to powdery mildew (caused by Erysiphe pisi) and moderately susceptible to mycosphaerella blight (caused by Mycosphaerella pinodes) and fusarium root rot (caused by Fusarium avenaceum).

Wheat breeding enhances wheat crops for better environmental resistance and higher yield potential. Experimental breeding lines are evaluated based on their yield potential, where quantifying spikes per unit area and kernels per spike is crucial for assessment. This study introduces SPINEL (SPIke and kerNEL), a framework that combines unmanned aerial vehicle (UAV)-captured multispectral imaging and field-captured RGB camera imaging for spike and kernel quantification. This approach utilizes YOLOv8 models, each tailored for a specific detection task. The first model detects plots in UAV-captured multispectral images with a mean average precision (mAP) score of 95%, while the second model, trained to detect spikes in the same dataset, demonstrates an mAP score of 86%. The third model detects spikes and kernels in field-captured RGB images with an 85% mAP score. The first two models aid in estimating the spike density in each field plot. The third model provides the estimated number of kernels in spikes of each unique breeding line. Spikes per field plot and kernels per spike serve as key quantification metrics. The SPINEL framework utilizes the geolocation information of the multispectral images and associates these metrics with breeding lines at the field level. This integration provides a clear visual representation of spike count and average kernels per spike for each field plot. SPINEL offers a precise, automated solution for phenotyping in wheat breeding, promising significant advancements in crop improvement strategies.

Durum wheat (Triticum turgidum) is threatened by the appearance of new virulent races of leaf rust, caused by Puccinia triticina, in recent years. This study was conducted to determine the leaf rust resistance in a modern Canadian durum cultivar, Strongfield. Six populations derived from crosses of Strongfield with six tetraploid wheat lines, respectively, were tested at the seedling plant stage with different P. triticina races. Two of the populations were evaluated for adult plant leaf rust infection in Canada and Mexico. A stepwise regression joint linkage quantitative trait locus (QTL) mapping and analysis by MapQTL were performed. Strongfield contributed the majority of QTLs detected, contributing seven QTLs detected in field tests and eight QTLs conditioning seedling resistance. A 1B QTL, QLr-Spa-1B.1, from Strongfield had a significant effect in both Canadian and Mexican field tests and corresponded with Lr46/Yr29. The remaining field QTLs were found in only the Canadian or the Mexican environment, not both. The QTL from Strongfield on 3A, QLr-Spa-3A, conferred seedling resistance to all races tested and had a significant effect in the field in Canada. This is the first report of QLr-Spa-3A and Lr46/Yr29 as key components of genetic resistance in Canadian durum wheat. KASP markers were developed to detect QLr-Spa-3A for use in marker-assisted leaf rust resistance breeding. The susceptible parental lines contributed QTLs on 1A, 2B, and 5B that were effective in Mexican field tests and may be good targets to integrate into modern durum varieties to improve resistance to new durum virulent races.

Abstract Background Optimum moisture in straw and grain at maturity is important for timely harvesting of wheat. Grain harvested at the right time has reduced chance of being affected by adverse weather conditions which is important to maintain grain quality and end use functionality. Wheat varieties with a short dry down period could help in timely harvest of the crop. However, measuring single kernel moisture in wheat and other small grain crops is a phenotyping bottleneck which requires characterising moisture content of the developing kernel at physiological maturity. Results Here we report developing a pin-based probe to detect moisture in a developing wheat kernel required for determining physiological maturity. An in-house designed pin-based probe was used with different commercially available electronic moisture meters to assess the moisture content of the individual kernels in spikes with high accuracy (R2 = 0.73 to 0.94, P < 0.001) compared with a reference method of oven drying. The average moisture values varied among different electronic moisture meters and the oven-dry method and differences in values were minimized at low kernel moisture content (< 50%). The single kernel moisture probe was evaluated in the field to predict the physiological maturity in wheat using 38% moisture content as the reference and visible notes on kernel stage. Conclusion The pin-based moisture probe is a reliable tool for wheat physiologists and breeders to conveniently and accurately measure moisture content in developing grain that will aid in identifying wheat germplasm with fast dry-down characteristics.

Aim: Competition is often proposed to drive niche segregation along multiple axes in speciose communities. Understanding spatial partitioning of foraging areas is particularly important in species that are constrained to a central place. We present a natural experiment examining variation in habitat preferences of congeneric Southern Ocean predators in sympatry and allopatry. Our aim was to ascertain consistency of habitat preferences within species, and to test whether preferences changed in the presence of the congener. Location: Southern Hemisphere. Taxon: Multiple colonies of both species within the genus Phoebetria (sooty albatrosses). Methods: The two Phoebetria albatrosses breed on islands located from similar to 37-55 degrees S - sooty albatrosses (P. fusca) in the north and light-mantled albatrosses (P. palpebrata) in the south - with sympatric overlap at locations similar to 46-49 degrees S. We analysed GPS and PTT tracks from 87 individuals and multiple remotely sensed environmental variables using GAMs, to determine and compare the key factors influencing habitat preference for each species at each breeding colony. Results: While foraging habitat preferences are consistent in light-mantled albatrosses, there is divergence of preferences in sooty albatrosses depending on whether they are in sympatry with their congener or in allopatry. Main Conclusions: This study represents the most comprehensive work on this genus to date and highlights how habitat preferences and behavioural plasticity may influence species distributions under different competitive conditions.

This study explored how to use UAV-based multispectral imaging, a plot detection model, and machine learning (ML) algorithms to predict wheat grain yield at the field scale. Multispectral data were collected over several weeks using the MicaSense RedEdge-P camera. Ground truth data on vegetation indices were collected utilizing portable phenotyping instruments, and agronomic data were collected manually. The YOLOv8 detection model was utilized for field-scale wheat plot detection. Four ML algorithms—decision tree (DT), random forest (RF), gradient boosting (GB), and extreme GB (XGBoost were used to evaluate wheat grain yield prediction using normalized difference vegetation index (NDVI), normalized difference red edge index (NDRE), and green NDVI (G-NDVI) data. The results demonstrated the RF algorithm's predicting ability across all growth stages, with a root-mean-square error (RMSE) of 43 grams per plot (g/p) and a coefficient of determination ($R^{2}$) value of 0.90 for NDVI data. For NDRE data, DT outperformed other models, with an RMSE of 43 g/p and an $R^{2}$ of 0.88. GB exhibited the highest predictive accuracy for G-NDVI data, with an RMSE of 42 g/p and an $R^{2}$ value of 0.89. The study integrated isogenic bread wheat sister lines and checked cultivars differing in grain yield, grain protein, and other agronomic traits to facilitate the identification of high-yield performers. The results show the potential use of UAV-based multispectral imaging combined with a detection model and ML in various precision agriculture applications, including wheat breeding, agronomy research, and broader agricultural practices.

Wheat lodging is a serious problem affecting grain yield, plant health, and grain quality. Addressing the lodging issue in wheat is a desirable task in breeding programs. Precise detection of lodging levels during wheat screening can aid in selecting lines with resistance to lodging. Traditional approaches to phenotype lodging rely on manual data collection from field plots, which are slow and laborious, and can introduce errors and bias. This paper presents a framework called ‘LodgeNet,’ that facilitates wheat lodging detection. Using Unmanned Aerial Vehicles (UAVs) and Deep Learning (DL), LodgeNet improves traditional methods of detecting lodging with more precision and efficiency. Using a dataset of 2000 multi-spectral images of wheat plots, we have developed a novel image registration technique that aligns the different bands of multi-spectral images. This approach allows the creation of comprehensive RGB images, enhancing the detection and classification of wheat lodging. We have employed advanced image enhancement techniques to improve image quality, highlighting the important features of wheat lodging detection. We combined three color enhancement transformations into two presets for image refinement. The first preset, ‘Haze & Gamma Adjustment,’ minimize atmospheric haze and adjusts the gamma, while the second, ‘Stretching Contrast Limits,’ extends the contrast of the RGB image by calculating and applying the upper and lower limits of each band. LodgeNet, which relies on the state-of-the-art YOLOv8 deep learning algorithm, could detect and classify wheat lodging severity levels ranging from no lodging (Class 1) to severe lodging (Class 9). The results show the mean Average Precision (mAP) of 0.952% @0.5 and 0.641% @0.50-0.95 in classifying wheat lodging severity levels. LodgeNet promises an efficient and automated high-throughput solution for real-time crop monitoring of wheat lodging severity levels in the field.

The Canada Western Red Spring wheat (Triticum aestivum L.) cultivars AAC Concord, AAC Prevail, CDC Hughes, Lillian, Glenlea, and elite line BW961 express a spectrum of resistance to leaf rust caused by Puccinia triticina Eriks. This study aimed to identify and map the leaf rust resistance of the cultivars using three doubled haploid populations, AAC Prevail/BW961 (PB), CDC Hughes/AAC Concord (HC), and Lillian/Glenlea (LG). The populations were evaluated for seedling resistance in the greenhouse and adult plant disease response in the field at Morden, MB for 3 years and genotyped with the 90K wheat Infinium iSelect SNP array. Genetic maps were constructed to perform QTL analysis on the seedling and field leaf rust data. A total of three field leaf rust resistance QTL segregated in the PB population, five in the HC, and six in the LG population. In the PB population, BW961 contributed two QTL on chromosomes 2DS and 7DS, and AAC Prevail contributed a QTL on 4AL consistent across trials. Of the five QTL in HC, AAC Concord contributed two QTL on 4AL and 7AL consistent across trials and a QTL on 3DL.1 that provided seedling resistance only. CDC Hughes contributed two QTL on 1DS and 3DL.2. Lillian contributed four QTL significant in at least two of the three trials on 2BS, 4AL, 5AL, and 7AL, and Glenlea two QTL on 4BL and 7BL. The 1DS QTL from CDC Hughes, the 2DS from BW961, the 4AL from the AAC Prevail, AAC Concord, and Lillian, and the 7AL from AAC Concord and Lillian conferred seedling leaf rust resistance. The QTL on 4AL corresponded with Lr30 and was the same across cultivars AAC Prevail, AAC Concord, and Lillian, whereas the 7AL corresponding with LrCen was coincident between AAC Concord and Lillian. The 7DS and 2DS QTL in BW961 corresponded with Lr34 and Lr2a, respectively, and the 1DS QTL in CDC Hughes with Lr21. The QTL identified on 5AL could represent a novel gene. The results of this study will widen our knowledge of leaf rust resistance genes in Canadian wheat and their utilization in resistance breeding.

Fusarium head blight (FHB) is a highly destructive fungal disease of wheat to which host resistance is quantitatively inherited and largely influenced by the environment. Resistance to FHB has been associated with taller height and later maturity; however, a further understanding of these relationships is needed. An association mapping panel (AMP) of 192 predominantly Canadian spring wheat was genotyped with the wheat 90K single-nucleotide polymorphism (SNP) array. The AMP was assessed for FHB incidence (INC), severity (SEV) and index (IND), days to anthesis (DTA), and plant height (PLHT) between 2015 and 2017 at three Canadian FHB-inoculated nurseries. Seven multi-environment trial (MET) datasets were deployed in a genome-wide association study (GWAS) using a single-locus mixed linear model (MLM) and a multi-locus random SNP-effect mixed linear model (mrMLM). MLM detected four quantitative trait nucleotides (QTNs) for INC on chromosomes 2D and 3D and for SEV and IND on chromosome 3B. Further, mrMLM identified 291 QTNs: 50 (INC), 72 (SEV), 90 (IND), 41 (DTA), and 38 (PLHT). At two or more environments, 17 QTNs for FHB, DTA, and PLHT were detected. Of these 17, 12 QTNs were pleiotropic for FHB traits, DTA, and PLHT on chromosomes 1A, 1D, 2D, 3B, 5A, 6B, 7A, and 7B; two QTNs for DTA were detected on chromosomes 1B and 7A; and three PLHT QTNs were located on chromosomes 4B and 6B. The 1B DTA QTN and the three pleiotropic QTNs on chromosomes 1A, 3B, and 6B are potentially identical to corresponding quantitative trait loci (QTLs) in durum wheat. Further, the 3B pleiotropic QTN for FHB INC, SEV, and IND co-locates with TraesCS3B02G024900 within the Fhb1 region on chromosome 3B and is ~3 Mb from a cloned Fhb1 candidate gene TaHRC. While the PLHT QTN on chromosome 6B is putatively novel, the 1B DTA QTN co-locates with a disease resistance protein located ~10 Mb from a Flowering Locus T1-like gene TaFT3-B1, and the 7A DTA QTN is ~5 Mb away from a maturity QTL QMat.dms-7A.3 of another study. GWAS and QTN candidate genes enabled the characterization of FHB resistance in relation to DTA and PLHT. This approach should eventually generate additional and reliable trait-specific markers for breeding selection, in addition to providing useful information for FHB trait discovery.

Anthropogenic climate change is resulting in spatial redistributions of many species. We assessed the potential effects of climate change on an abundant and widely distributed group of diving birds, Eudyptes penguins, which are the main avian consumers in the Southern Ocean in terms of biomass consumption. Despite their abundance, several of these species have undergone population declines over the past century, potentially due to changing oceanography and prey availability over the important winter months. We used light-based geolocation tracking data for 485 individuals deployed between 2006 and 2020 across 10 of the major breeding locations for five taxa of Eudyptes penguins. We used boosted regression tree modelling to quantify post-moult habitat preference for southern rockhopper (E. chrysocome), eastern rockhopper (E. filholi), northern rockhopper (E. moseleyi) and macaroni/royal (E. chrysolophus and E. schlegeli) penguins. We then modelled their redistribution under two climate change scenarios, representative concentration pathways RCP4.5 and RCP8.5 (for the end of the century, 2071-2100). As climate forcings differ regionally, we quantified redistribution in the Atlantic, Central Indian, East Indian, West Pacific and East Pacific regions. We found sea surface temperature and sea surface height to be the most important predictors of current habitat for these penguins; physical features that are changing rapidly in the Southern Ocean. Our results indicated that the less severe RCP4.5 would lead to less habitat loss than the more severe RCP8.5. The five taxa of penguin may experience a general poleward redistribution of their preferred habitat, but with contrasting effects in the (i) change in total area of preferred habitat under climate change (ii) according to geographic region and (iii) the species (macaroni/royal vs. rockhopper populations). Our results provide further understanding on the regional impacts and vulnerability of species to climate change.

Fusarium head blight (FHB) has rapidly become a major challenge to successful wheat production and competitive end-use quality in western Canada. Continuous effort is required to develop germplasm with improved FHB resistance and understand how to incorporate the material into crossing schemes for marker-assisted selection and genomic selection. The aim of this study was to map quantitative trait loci (QTL) responsible for the expression of FHB resistance in two adapted cultivars and to evaluate their co-localization with plant height, days to maturity, days to heading, and awnedness. A large doubled haploid population of 775 lines developed from cultivars Carberry and AC Cadillac was assessed for FHB incidence and severity in nurseries near Portage la Prairie, Brandon, and Morden in different years, and for plant height, awnedness, days to heading, and days to maturity near Swift Current. An initial linkage map using a subset of 261 lines was constructed using 634 polymorphic DArT and SSR markers. QTL analysis revealed five resistance QTL on chromosomes 2A, 3B (two loci), 4B, and 5A. A second genetic map with increased marker density was constructed using the Infinium iSelect 90k SNP wheat array in addition to the previous DArT and SSR markers, which revealed two additional QTL on 6A and 6D. The complete population was genotyped, and a total of 6,806 Infinium iSelect 90k SNP polymorphic markers were used to identify 17 putative resistance QTL on 14 different chromosomes. As with the smaller population size and fewer markers, large-effect QTL were detected on 3B, 4B, and 5A that were consistently expressed across environments. FHB resistance QTL were co-localized with plant height QTL on chromosomes 4B, 6D, and 7D; days to heading on 2B, 3A, 4A, 4B, and 5A; and maturity on 3A, 4B, and 7D. A major QTL for awnedness was identified as being associated with FHB resistance on chromosome 5A. Nine small-effect QTL were not associated with any of the agronomic traits, whereas 13 QTL that were associated with agronomic traits did not co-localize with any of the FHB traits. There is an opportunity to select for improved FHB resistance within adapted cultivars by using markers associated with complementary QTL.

Fusarium head blight (FHB), caused by Fusarium spp., is a destructive disease of cereal grains. Apart from grain yield loss, a major quality concern is contamination with Fusarium-produced mycotoxins, specifically deoxynivalenol (DON). Mycotoxins accumulate in the grain, making it unfit for consumption by humans and animals. Breeding cultivars with high disease resistance and low mycotoxin contamination is a priority for wheat breeders. However, DON measurement in breeding programs is expensive and time consuming due to the lack of efficient quantification methods. In this study, we established a simple fast chromatography-tandem mass spectrometry method, which employed a one-step acetonitrile extraction protocol with a short guard column to reduce complexity, cost, and analysis time. To ensure robustness and reproducibility, the method was validated according to the U.S. Food and Drug Administration Guidance for Bioanalytical Method Validation. Furthermore, the method was applied for determination of DON in 102 wheat grain samples. Obtained results highly correlated with the conventional immunological method for all tested samples. With its ease of use, rapid sample analysis, and high sensitivity and accuracy, the method could be integrated into current FHB breeding programs to increase breeding efficiency and accelerate screening progress to identify germplasm with increased resistance to DON accumulation. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

The hexaploid spring wheat cultivar, Carberry, was registered in Canada in 2009, and has since been grown over an extensive area on the Canadian Prairies. Carberry has maintained a very high level of leaf rust (Puccinia triticina Eriks.) resistance since its release. To understand the genetic basis of Carberry’s leaf rust resistance, Carberry was crossed with the susceptible cultivar, Thatcher, and a doubled haploid (DH) population of 297 lines was generated. The DH population was evaluated for leaf rust in seven field environments at the adult plant stage. Seedling and adult plant resistance (APR) to multiple virulence phenotypes of P. triticina was evaluated on the parents and the progeny population in controlled greenhouse studies. The population was genotyped with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, and quantitative trait loci (QTL) analysis was performed. The analysis using field leaf rust response indicated that Carberry contributed nine QTL located on chromosomes 1B, 2B (2 loci), 2D, 4A, 4B, 5A, 5B, and 7D. The QTL located on 1B, 2B, 5B, and 7D chromosomes were observed in two or more environments, whereas the remainder were detected in single environments. The resistance on 1B, detected in five environments, was attributed to Lr46 and on 7D, detected in seven environments to Lr34. The first 2B QTL corresponded with the adult plant gene, Lr13, while the second QTL corresponded with Lr16. The seedling analysis showed that Carberry carries Lr2a, Lr16, and Lr23. Five epistatic effects were identified in the population, with synergistic interactions being observed for Lr34 with Lr46, Lr16, and Lr2a. The durable rust resistance of Carberry is attributed to Lr34 and Lr46 in combination with these other resistance genes, because the resistance has remained effective even though the P. triticina population has evolved virulent to Lr2a, Lr13, Lr16, and Lr23.

Invasive species are one of the greatest drivers of biodiversity loss worldwide, and the eradication of invasive species from islands is a highly efficient management strategy. Because eradication operations require large financial investments, uncertainty over the magnitude of impacts of both invasive species and their removal can impede the willingness of decision makers to invest in eradication. Such uncertainty is prevalent for long-lived species that display an inherent lag between life stages affected by invasive species and those used for population status assessments. Albatrosses are amongst the longest-living bird species and are threatened on land by invasive species and at sea by industrial fisheries. As in many seabird species, usually only a segment of the population (breeding adults) is used for status assessments, making it difficult to assess albatross population trends and the potential benefit of conservation action, such as the management of predatory invasive species. We used population monitoring and mark-recapture data to estimate the past population trajectory of the critically endangered Tristan albatross Diomedea dabbenena by accounting for unobservable birds at sea in an integrated population model. We then projected the future population trajectory of Tristan albatrosses for scenarios with or without predation by invasive house mice Mus musculus on their main breeding site, Gough Island. The adult breeding population remained stable between 2004 and 2021, but breeding success was low (31%) and our model indicated that the total population (including unobservable immature birds) decreased from a median estimate of 9,795 to 7,752 birds. Eradicating invasive mice leading to a two-fold increase in breeding success would result in a 1.8-7.6 times higher albatross population by 2050 (median estimate 10,352 individuals) than without this intervention. Low reproductive output for long-lived species may lead to a cryptic population decrease, which can be obscured from readily available counts of breeding pairs by changes in the population structure. Mouse eradication is necessary to halt the ongoing population decrease of the Tristan albatross, even if this decrease is not yet apparent in the breeding population size.

AAC Julius is a semi-leafless, yellow cotyledonary field pea ( Pisum sativum L.) variety developed at Lacombe Research and Development Centre, Agriculture and Agri-Food Canada , Lacombe, AB, Canada. It has a maturity of 100 days, 1000-seed weight of 210 g, and a lodging score of 3.6 on the scale of 1–9. The seed crude protein content of AAC Julius is 24.8%. AAC Julius is resistant to powdery mildew (caused by Erysiphe pisi D.C.) and moderately susceptible to mycosphaerella blight (caused by Mycosphaerella pinodes) and Fusarium root rot (caused by Fusarium avenaceum (Fr.) Sacc. and F. solani).