Developing genetically resistant soybean cultivars is key in controlling the most damaging soybean disease worldwide; soybean cyst nematode (SCN) is critical for soybean production. Development and spread of new HG types of SCN that break down current resistance genes warrant continuous efforts to identify novel resistance sources. Here, a GWAS study in a diversity panel consisting of modern Canadian and Chinese soybean cultivars was used to identify novel marker–trait associations in the soybean genome derived from Chinese germplasm. Soybean cyst nematode (SCN), caused by Heterodera glycines Ichinohe, is the most destructive pathogen affecting soybean production in North America. Overreliance on plant introduction (PI) 88788 as a resistance source in commercial soybean cultivars has led to SCN field populations shifting toward virulence against this resistance source. Modern Chinese soybean cultivars have emerged as potential sources of both known and novel SCN resistance genes. This study aimed to investigate the genetics underlying HG-type 2.5.7 SCN resistance in a genomic diversity panel (n = 201) comprised of modern Canadian (CD), Chinese (CH), and combined CD-CH soybean genotypes through a genome-wide association study (GWAS). Genotyping-by-sequencing (GBS) detected 15,932 single nucleotide polymorphisms (SNPs). Phenotypic SCN resistance was assessed by infesting genotypes in the GWAS panel using a greenhouse bioassay with HG-type 2.5.7 to calculate the female index (FI). FarmCPU detected one SNP on chromosome 9, explaining 7.26
This study determined the relationship between gluten network dynamics, water migration, and surface viscosity during dough resting based on the specific experimental conditions for the five flours examined. LF-NMR relaxation curves and ATR-FTIR hydroxyl stretching vibrational spectroscopy indicated that water migrated from the dough interior to the surface, leading to an increase in dough surface viscosity. Dynamic rheological testing, SEM, and CLSM analyses tracked the evolution of the gluten network structure during the dough resting period. The results showed that the gluten network transformed from an aggregated structure (0-30 min) to a continuous and uniform network (45-60 min), followed by a gradual structural disintegration (90-135 min). Molecular structure analysis shows that non-covalent interactions (hydrogen bonds and hydrophobic interactions) and covalent bonds (disulfide bonds) jointly regulate the polymerization and depolymerization of the gluten network. An appropriate resting time promotes the orderly formation of the gluten structure. Correlation analysis revealed that the gluten index and farinograph quality are key factors in regulating water migration, gluten reorganization, and relaxation. Doughs with poorer gluten quality tend to relax more easily, resulting in faster water release and further accelerated protein chain breakage at the dough surface, this is the fundamental reason for the increased adhesion of the dough surface. Furthermore, the optimal resting time for dough (45-60 min) was consistent throughout this study. Excessive resting times (>90 min) can lead to severe network damage, thereby reducing dough quality. In summary, this study elucidates the mechanisms of water migration and changes in dough surface viscosity during resting, providing a theoretical basis for improving processing techniques and precisely controlling dough quality.
To exploit allelic variation in Hordeum vulgare subsp. spontaneum, the Wild Barley Diversity Collection was subjected to paired-end Illumina sequencing at ∼9 × depth and evaluated for several agronomic traits. We discovered 240.2 million single nucleotide polymorphisms (SNPs) after alignment to the Morex V3 assembly and 24.4 million short (1 to 50 bp) insertions and deletions. A genome-wide association study of lemma color identified one marker-trait association (MTA) on chromosome 1H close to HvBlp, the cloned gene controlling black lemma. Four MTAs were identified for seedling stem rust resistance, including 2 novel loci on chromosomes 1H and 6H and one co-locating to the complex RMRL1-RMRL2 locus on 5H. The whole-genome sequence data described herein will facilitate the identification and utilization of new alleles for barley improvement.
Antimicrobial resistance (AMR) is a growing global public health concern affecting animals, humans, and the environment. Given its ubiquity, Escherichia coli may play a key role in the dissemination of AMR across these domains. Peri-urban regions where urban and rural systems intersect present unique challenges for controlling AMR. Despite this, limited data are available on AMR dissemination across the One Health continuum in peri-urban settings such as the Fraser Valley region of Canada. This study adopted a One Health approach to assess associations in AMR traits between E. coli from dairy production systems, nearby natural environments, and peri-urban communities within the same geographic location and timeframe. Over 1,000 isolates were recovered, and 421 were whole-genome sequenced to determine the presence of antimicrobial resistance genes (ARGs), plasmids, and virulence genes and to assess genomic relatedness. Findings revealed that AMR was not widespread: 17.8% of isolates carried at least one ARG, 10.2% were classified as multidrug-resistant, and 9.5% carried beta-lactamase genes. Phylogenomic analysis revealed high genomic diversity, with isolates belonging to 174 different sequence types (STs), including clinically important ST131 and ST10. Pairwise single-nucleotide polymorphism (SNP) comparisons identified 207 isolate pairs differing by ≤100 SNPs, indicating early-stage cross-domain movement of AMR. Overall, the findings from this study show that the prevalence of AMR E. coli is low, but there is evidence of transmission between animals and the environment, highlighting the importance of proactive, integrated surveillance and mitigation strategies to reduce the risk of future AMR dissemination across the One Health continuum. IMPORTANCE:Antimicrobial resistance (AMR) is a global public health concern that spans all three One Health domains (humans, animals, and the environment). Escherichia coli is present in humans, animals, and environmental sources-its ubiquity makes it an ideal organism to study AMR hotspots and transmission pathways across the One Health continuum. While surveillance of AMR in agricultural settings is increasing globally, little is known about transmission pathways in peri-urban agriculture areas where there is a high density of livestock farming in close proximity to residential communities. To identify potential AMR hotspots and transmission routes, this study investigated the occurrence and genomic relatedness of generic E. coli in the Fraser Valley region of British Columbia, a highly diverse agricultural region in western Canada. Our findings expand current knowledge by suggesting that early-stage transmission of AMR is occurring between the human, animal, and environmental sectors of the One Health triad, highlighting areas for improved resistance mitigation to prevent widespread dissemination.
Predicting N2O emissions can help identify crop production practices and environmental conditions for mitigation. The objectives were to calibrate and validate the DeNitrification-DeComposition (DNDCv.CAN) model to simulate N2O emission in crop rotation (CR) systems in Brazil’s Cerrado biome, using different N fertilizer sources. Field data were obtained from a CR experiment with maize and common beans cultivated under no-till for 10 years. Treatments were: Zero-N, calcium ammonium nitrate (CAN), urea (UR), and ammonium sulfate (AS), with 5 replicates. Measured data including N2O fluxes, NH3 volatilization, soil NH4+ and NO3-, water-filled pore space (WFPS), and grain yields were used to calibrate and validate the DNDCv.CAN. The model acceptably captured the daily N2O emissions associated with different N sources, although episodic peaks were over or under-predicted. Correlation coefficient was 0.62 during calibration, with a mean absolute error of 17 g N2O-N ha-1 day-1, close to average measured (18 g ha-1 d-1), and simulated (17 g ha-1 day-1) emissions. Accumulated measured N2O-N emissions were 1.19, 4.38, 3.17, and 2.56 kg N2O-N ha-1 for Zero-N, CAN, UR, and AS, respectively, whereas the simulated were 1.13, 3.44, 2.24, and 3.32 kg N2O-N ha-1. The NH3, NH4+, NO3-, WFPS, and yields were also fairly simulated. Soil hydrologic parameters were adjusted in the model using a built in pedotransfer function to improve the simulations, which should be further investigated. The DNDCv.CAN effectively simulated cumulative N2O emissions from different N sources applied to CR under tropical conditions, making it valuable for evaluating potential emissions and mitigation strategies.
