,The disease known as Septoria nodorum blotch, or SNB, is caused by a fungal pathogen that infects wheat plants and can cause substantial losses in grain yield. When a specific protein known as Tox1 is produced by the fungus and it is recognized by the wheat gene named Snn1, there is a compatible interaction that leads to disease in the wheat plant. Here, researchers conducted genetic, genomic, and bioinformatic analyses to determine how the Snn1 gene evolved, characterize the level of genetic diversity among wheat lines that carry the Snn1 gene, determine how the Snn1 gene functions to recognize the fungal SnTox1 protein, and to develop molecular markers that can be used by wheat breeders to track the Snn1 gene. The researchers found that some wheat lines carry two copies of Snn1, and the second copy resulted from a relatively recent genetic duplication of the first copy. Specific features in the DNA of the Snn1 genes were identified that dictate whether Snn1 can recognize SnTox1 thereby making the wheat plant either resistant or susceptible to SNB. These features were targeted for the development of several molecular markers that can be used in efficient DNA assays to determine if the Snn1 gene is present, and therefore if a given wheat plant will be resistant or susceptible to SNB. These marker assays will serve as useful tools to wheat breeders for the efficient development of SNB-resistant wheat varieties.,

Advancing genetic solutions for crop protection in Australian wheat: identifying novel and optimal combinations of APR resistance genes to Septoria tritici blotch. Wheat is one of the most important crops in Australia, providing food, feed and export income. However, wheat production is threatened by various diseases, such as Septoria tritici blotch (STB), a foliar disease of wheat caused by the fungus Zymoseptoria tritici. This disease is prevalent in medium-high rainfall zones of Australia. If left unmanaged, STB can result in yield losses of up to 50% and traditional control by fungicides is estimated to cost the industry $121 million per year is less effective due to fungicide resistance evolving in Australia to some common triazoles and strobilurin. One way to manage this disease is to use wheat varieties resistant to STB. However, 10 out of 17 genes tested for adult plant resistance (APR) performance in field experiments over the past 8 years are no longer effective in Australia. These include; Stb2/11/WW, Stb3, Stb4, Stb6, Stb7/12, Stb9 and Stb18. Therefore, identifying new sources of APR genes is essential for developing wheat varieties with better agronomic performance. Adult plant resistance (APR) genes confer partial but durable resistance to the disease at later stages of plant development. They are preferred in breeding programs because of their flexibility in integrated disease management (IDM) systems and their durability of resistance. These projects aim to discover and transfer novel APR genes for STB resistance into adapted wheat varieties while also determining the optimal combinations of existing effective APR genes and remove the barriers to their adoption by Australian wheat breeding programs. The resources available on this site are developed through research partnerships between GRDC and NSW DPI. There are resources provided on this page which are available to download as well as metadata for resources which have restricted access and will be made available only on request.

,A panel of single nucleotide polymorphisms (SNPs) for 363 common bean accessions was generated. A genome-wide association study (GWAS) was applied to detect SNPs significantly associated with resistance to Heterodera glycines (HG) also known as the soybean cyst nematode (SCN) in the core collection of common bean, Phaseolus vulgaris. There were 84,416 SNPs identified in 363 common bean accessions.,,

,Wheat streak mosaic virus (WSMV) can cause significant yield loss in wheat (Triticum aestivum L.) in the Great Plains of North America. A recently identified WSMV resistance gene, Wsm2, was mapped to chromosome 3BS in germplasm line 'CO960293–2'. Effective genetic markers tightly linked to the gene will enhance the selection of WSMV-resistant lines through marker-assisted selection. We have mapped Wsm2 using a high-density map developed from the wheat 90K Infinium iSelect single-nucleotide polymorphism (SNP) array with recombinant inbred lines from the cross between CO960293–2 and susceptible cultivar 'TAM 111'. Array-based SNPs that mapped within 4 cM of Wsm2 on chromosome 3BS were converted to Kompetitive Allele Specific Polymerase Chain Reaction (KASP) assays in this study. Six KASP SNPs were validated in two doubled haploid populations developed from crosses of 'RonL' × 'Ripper' and 'Snowmass' × 'Antero'. RonL and Snowmass possess the Wsm2 gene from CO960293–2. Three closely linked KASP SNPs, converted from IAAV6442, BS00018764_51, and wsnp_Ra_c16264_24873670, showed high sensitivity and specificity (0.83 ≤ sensitivity ≤ 0.97, 0.89 ≤ specificity ≤ 0.99). The latter two were also validated in six F2 breeding populations. These three KASP SNPs were effective in differentiating resistant and susceptible genotypes. Comparative mapping was performed using sequences of SNPs flanking Wsm2 and identified candidate genes and regions in Brachypodium and rice (Oryza sativa L. ssp. japonica). The KASP SNPs developed in this study should be useful for marker-assisted selection of Wsm2 in wheat breeding programs, and the newly constructed map will also facilitate map based cloning of Wsm2.,,

,This dataset was generated from soybean (Glycine max) field trials conducted at the West Tennessee Research and Education Center in Jackson, TN and at the Research and Education Center at Milan in Milan, TN as well as from molecular marker screening conducted at the West Tennessee Research and Education Center in Jackson, TN.,Table 3 includes measured data for height, yield, and seed size, and rating data for lodging and seed quality for JTN-5110, 5601T, and select other released germplasm lines and cultivars tested in replicated breeder yield trials in Jackson and Milan, TN from 2010-2016, excluding 2014. This data may be useful in measuring yield gain in future releases of soybean germplasm or cultivars with broad resistance to soybean cyst nematode (SCN; Heterodera glycines). This data should not be used to measure yield gain for elite high-yielding cultivars that do not have broad cyst nematode resistance.,Table 5 includes rating data for JTN-5110 and soybeans with established SCN resistance from simple sequence repeat (SSR) markers: Satt309 and Sat_168, associated with rhg1 on chromosome 18; Sat_162, associated with Rhg4 on chromosome 8; and Satt574, associated with cqSCN-005 on chromosome 17. This data may be useful in understanding the role of these molecular regions in SCN resistance for JTN-5110 and parent line Anand. This data should not be used to draw broad conclusions about cyst nematode resistance, in general.,Table 7 includes rating data for JTN-5110 and check cultivars from frogeye leafspot (caused by Cercospora sojina) field disease screenings conducted in Milan, TN from 2010-2012. This data may be useful in measuring changes in frogeye leafspot incidence and severity in West Tennessee. This data should not be used to draw broad conclusions or represent different geographic areas.,,

,Data reported in research published in Crop Science, “Mapping the quantitative field resistance to stripe rust in a hard winter wheat population ‘Overley’ × ‘Overland.’” Authors are Wardah Mustahsan, Mary J. Guttieri, Robert L. Bowden, Kimberley Garland-Campbell, Katherine Jordan, Guihua Bai, Guorong Zhang from USDA Agricultural Research Service and Kansas State University. This study was conducted to identify quantitative trait loci (QTL) associated with field resistance to stripe rust, also known as yellow rust (YR), in hard winter wheat. Stripe rust infection type and severity were rated in recombinant inbred lines (RILs, n=204) derived from a cross between hard red winter wheat cultivars ‘Overley’ and ‘Overland’ in replicated field trials in the Great Plains and Pacific Northwest. RILs (n=184) were genotyped with reduced representation sequencing to produce SNP markers from alignment to the ‘Chinese Spring’ reference sequence, IWGSC v2.1, and from alignment to the reference sequence for ‘Jagger’, which is a parent of Overley. Genetic linkage maps were developed independently from each set of SNP markers. QTL analysis identified genomic regions on chromosome arms 2AS, 2BS, 2BL, and 2DL that were associated with stripe rust resistance using multi-environment best linear unbiased predictors for stripe rust infection type and severity. Results for the two linkage maps were very similar. PCR-based SNP marker assays associated with the QTL regions were developed to efficiently identify these genomic regions in breeding populations.,Field response to YR was evaluated in seven trials: Rossville, KS (2018 and 2019), Hays, KS (2019), Pullman, WA (2019 and 2020) and Central Ferry, WA (2019 and 2020). An augmented experimental design was used at Rossville, KS with highly replicated checks and two full replications of RILs (n=187 in 2018; n=204 in 2019). The field experiment at Hays was arranged in a partially replicated augmented design with one or two replications of each RIL (n=194). The parental checks (Overley and Overland) were represented in three blocks for each of the two field replications at Hays, and RILs were distributed among blocks; not all RILs were present in each replication. RILs were arranged in an augmented design with two replications at Pullman (n=204 RILs) and Central Ferry (n=155 RILs in 2019; n=204 in 2020). At Pullman and Central Ferry.,The trials at Rossville, KS were inoculated using an inoculum consisting of equal parts of four isolates that were all virulent to Yr9. Two isolates were collected in Kansas in 2010 and had virulence to Yr17 but not QYr.tamu-2B. The other two isolates were from Kansas in 2012 and had virulence to QYr.tamu-2B, but not Yr17. Susceptible spreader rows (KS89180B, carrying Yr9) were inoculated several times during the tillering stage in the evenings with an ultra-low volume sprayer using a suspension of 2 mL of fresh urediniospores in 1 L of Soltrol 170 isoparaffin oil. Trials at Pullman, WA and Central Ferry, WA were evaluated under natural inoculum supplemented by a mixture of isolates collected in the previous field season. The trial at Hays, KS was evaluated under natural infection.,Data collection at Rossville, KS began once the susceptible check (KS89180B) had an infection severity coverage of ~10% and continued until senescence. In Rossville, disease ratings (IT and SEV) were collected on 16, 22, and 28th of May 2019. Most ratings in Rossville were taken some time after heading from Zadoks stages 55 to 70. In Pullman, disease ratings were collected on July 1 and 12. In Central Ferry, disease ratings were taken on 12th and 18th of June 2019. The second rating date was used for subsequent statistical analysis. In Hays, disease ratings were taken on June 1, 2019, when the plants were in early booting or heading stages (Zadoks 31-41). Stripe rust evaluations were measured using two disease rating scales: IT (0-9; from no infection to highly susceptible, Line and Qayoum, 1992)

This dataset originates from a comprehensive field trial conducted in Birchip, Victoria, during the 2024 winter cropping season. The trial, identified as 24_Nulla_0124_Long Coleoptile, involved 108 plots across six ranges and 26 rows, with GPS-referenced layout and border plots included. Treatments combined three factors: wheat genotype (including Mace18, Magenta13, Scepter, Calibre), sowing depth (shallow or deep), and presswheel pressure (light, standard, heavy). The dataset comprises multiple Excel sheets detailing agronomic measurements, environmental conditions, and sensor data. Soil water content was assessed gravimetrically and via matric potential across 12 plots at six depth increments (0–12 cm), both pre- and post-sowing. Soil strength was measured using a penetrometer, with readings taken in 2 cm increments and converted to kg/cm². Soil temperature was monitored using sensors placed at the surface, 3–4 cm, and 8–10 cm depths in two plots, with high-frequency time-series data recorded over several days. Emergence was tracked biweekly and then weekly from sowing through six weeks, with counts taken from 1 m sections of seeding rows. Coleoptile length and sowing depth were measured from 20 seedlings per tyne per plot, with values ranging from approximately 1.3 to 8.6 cm and 2.8 to 10.8 cm respectively. NDVI readings were collected using a handheld Greenseeker across 10 dates, showing progressive canopy development with values ranging from 0.09 to 0.79 and CV% from 0.5 to 29.5. Zadoks scores were recorded weekly from early September to October, capturing phenological stages from stem elongation to anthesis (Z43–Z71). Rabbit damage was assessed on 06/07/2024, with severity scores (1–5) and percent chewed recorded per plot. Final harvest data includes grain yield (raw and corrected), moisture content, protein percentage, test weight, screenings, and emergence rates. The dataset is structured for analytical modeling, enabling genotype, depth, pressure comparisons and supporting time-series analysis of emergence, growth, and yield. It includes both raw and processed data, with consistent formatting and minimal missing values. Some metadata corruption is present but does not affect core data usability.

,Hessian fly (HF, Mayetiola destructor Say) is a major pest on wheat and can cause significant yield losses. Currently there are some HF resistance genes deployed, but mostly in hexaploid winter wheat (Triticum aestivum), with fewer resistance genes identified in durum wheat (Triticum turgidum ssp. durum L.) and other wheat wild relatives. Mapping of additional resistance genes, along with developing markers for these is needed to develop resistant germplasm. ARS researchers in Fargo, ND evaluated the BP025 population under greenhouse and growth chamber conditions to the Great Plains (GP) biotype of Hessian fly (HF, Mayetiola destructor Say). The BP025 population was developed by crossing Ben (PI 596557), a North Dakota hard amber durum variety, with PI 41025, a cultivated emmer (T. turgidum ssp. dicoccum) accession collected near Samara, Russia. The BP025 population consists of 200 RILs developed by single seed-descent and was advanced to the F7:8 generation. The BP025 population was evaluated for stunting score, larval mortality, and the percentage of resistant plants under growth chamber and greenhouse conditions in Fargo, ND (46.893273, -96.807319). Experimental plants were maintained in a greenhouse at 20 ± 2° C with an ambient relative humidity of between 40 and 70% and a 16:8 (L:D) photoperiod. Natural lighting was enhanced with the use of 430-watt high pressure sodium lamps. Individual seeds of the mapping population entries were planted in Ray Leach cone-tainer (4 cm diameter × 21 cm deep, Stuewe & Sons, Inc., Tangent, OR), held in racks (RL98). Plants were grown in potting media (SB100 Professional Growing Mix, Sungro Horticulture, Bellevue, WA), and fertilized at planting with Osmocote Plus 15-9-12 (N-P-K) standard release fertilizer. Each cone was considered an experimental unit. The BP025 population and the parental lines Ben and PI 41025 were screened for HF larval resistance over two greenhouse seasons. All plants were evaluated using a completely randomized design. For the infestations, seedling plants were exposed to egg-laying HF adult females (~ 1 female for each plant) for 24 h. Infestations were timed to occur when seedlings were at the two-leaf growth stage. Three days after exposure to adult females, plants were moved to a high humidity (50-75% RH) growth chamber. High humidity facilitates egg hatching and promotes the successful migration of neonate larvae down the leaf blade to feeding sites at the base of the plant. Following egg hatch, plants were returned to the greenhouse for 10 to 14 days. This provided time for virulent larvae to grow and be differentiated from the small presumably dead avirulent larvae. Detailed observations of plant quality and larval success provided each plant with a score of “resistant” or “susceptible.” Specifically, plants were scored for their growth, with information on the number of leaves and tillers being recorded. Plant health and appearance (i.e., severity of larval-induced stunting), was also scored for each plant. Normal healthy plants were given a score of 0, lightly stunted plants were scored as a 1, moderately stunted plants were given a 2, and severely stunted planted were given the score of 3. Each plant was also dissected using a stereo microscope. At the time of plant dissection, virulent (i.e., successful) larvae were expected to be large and white in color. The number of dead larvae (eg. large, medium, small, and neonate) and live larvae (eg. large, medium, and small) were recorded for each plant. Averages for the plant and insect measurements were derived from the mean score of the 12 to 14 plants evaluated for each entry in the population. Phenotypic data was analyzed using JMP version 15 (SAS Institute, 2015). Prior to analysis, homogeneity of variance was tested using an O-Brien test at p < 0.05 (O’Brien, 1979). The genotypic data used for further QTL analysis is available Peters Haugrud, Amanda; Saini Sharma, Jyoti; Zhang, Qijun; Green, Andrew J.;

,Intermediate wheatgrass [Thinopyrum intermedium (Host) Barkw. & D.R. Dewey subsp. intermedium] is a high-yielding cool-season grass with adaptable uses for grazing, haying, and soil restoration. Despite its adaptability, adoption of intermediate wheatgrass has been limited due to inadequate stand longevity under grazing stress. A study was conducted near Mandan, ND USA to investigate if stand longevity of intermediate wheatgrass was affected by changes in soil properties due to grazing. Soil data from this study included measurements of soil bulk density, soil pH, soil organic carbon, and total soil nitrogen on a Wilton silt loam soil (USDA: Fine-silty, mixed, superactive frigid Pachic Haplustoll). Measurements were made in May 1997 (baseline) and again in May 2004 following four years of grazing. Data may be used to understand soil property responses to grazed perennial forages. Data are generally applicable to rainfed conditions under a semiarid Continental climate for the following associated soil types: Temvik, Grassna, Linton, Mandan, and Williams.,Resources in this dataset:,Resource title: Intermediate Wheatgrass Grazing Study Data Dictionary File name: IWGS_Data Dictionary.xlsx Resource description: Data dictionary for associated dataset.,Resource title: Intermediate Wheatgrass Grazing Study_Soil Data for Aggregated Depths File name: IWGS_Soil Data_Aggregated Depths.xlsx Resource description: File includes data for 0-30 cm depth.,Resource title: Intermediate Wheatgrass Grazing Study_Soil Data for Separated Depths File name: IWGS_Soil Data_Separated Depths.xlsx Resource description: Soil data for 0-5, 5-10, 10-20, and 20-30 cm depths.,Resource title: Intermediate Wheatgrass Grazing Study_Soil Data_Aggregated Depths File name: IWGS_Soil Data_Aggregated Depths.csv Resource description: Data for aggregated depths in csv format.,Resource title: Intermediate Wheatgrass Grazing Study_Metadata_Aggregated Depths File name: IWGS_Soil Data_Aggregated Depths_Metadata.csv Resource description: Metadata for aggregated depths.,Resource title: Intermediate Wheatgrass Grazing Study_Soils Data_Separated Depths File name: IWGS_Soil Data_Separated Depths.csv Resource description: Soil data for 0-5, 5-10, 10-20, and 20-30 cm depths.,Resource title: Intermediate Wheatgrass Grazing Study_Metadata_Separated Depths File name: IWGS_Soil Data_Separated Depths_Metadata.csv Resource description: Metadata for soils data separated by depth increment.,

This dataset documents the results of a 2024 field trial conducted by CSIRO at Tabbita, NSW, to evaluate the performance of long coleoptile wheat genotypes under varying sowing depths and soil conditions. The Excel file (.xlsx) contains 12 sheets, each representing a specific data type or collection date. The trial compared wheat genotypes sown at 4 cm and 10 cm depths, with some entries extending to 15 cm, across multiple replicates and ranges. The genotypes included standard and long coleoptile lines such as Mace, Mace18, Magenta, Magenta13, Gregory, Yitpi, Calibre, and Scepter, with suffixes indicating seed size or treatment (e.g., _sml, _std, _L, _S). The dataset includes sowing layout maps, cone penetrometer readings taken on three dates (17th, 24th, and 30th May) to assess soil resistance at different depths, and multiple rounds of plant counts (28th May, 30th May, 5th June, 7th June, and 13th June) across different rows and depths. Elongation measurements were recorded on 28th and 30th May, with up to 10 readings per plot, providing data on early shoot growth. Final yield data is presented in the last sheet, including raw yield (kg) and adjusted yield per hectare (Ayld), calculated based on a 4 m plot length, 23 cm row spacing, and six harvested rows. The dataset includes over 30 variables, such as genotype, sowing depth, plant counts per row, elongation measurements (ER1–ER10), and yield metrics. Codes like “Mace18_sml” denote genotype and seed size, while “4cm SD” and “10cm SD” refer to sowing depths. The data were collected using standard field protocols, with consistent plot dimensions and measurement intervals. This dataset enables analysis of genotype × environment × management interactions, particularly the influence of sowing depth and soil strength on emergence, early growth, and yield performance in long coleoptile wheat.