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Wheat stripe rust is one of the main wheat diseases worldwide, which has significantly adverse effects on wheat yield and quality, posing serious threats on food security. Disease severity grading plays a paramount role in stripe rust disease management including breeding disease-resistant wheat varieties. Manual inspection is time-consuming, labor-intensive and prone to human errors, therefore, there is a clearly urgent need to develop more effective and efficient disease grading strategy by using automated approaches. However, the differences between wheat leaves of different levels of stripe rust infection are usually tiny and subtle, and, as a result, ordinary deep learning networks fail to achieve satisfying performance. By formulating this challenge as a fine-grained image classification problem, this study proposes a novel deep learning network C-DenseNet which embeds Convolutional Block Attention Module (CBAM) in the densely connected convolutional network (DenseNet). The performance of C-DenseNet and its variants is demonstrated via a newly collected wheat stripe rust grading dataset (WSRgrading dataset) at Northwest A&F University, Shaanxi Province, China, which contains a total of 5,242 wheat leaf images with 6 levels of stripe rust infection. The dataset was collected by using various mobile devices in the natural field condition. Comparative experiments show that C-DenseNet with a test accuracy of 97.99% outperforms the classical DenseNet (92.53%) and ResNet (73.43%). GradCAM++ network visualization also shows that C-DenseNet is able to pay more attention to the key areas in making the decision. It is concluded that C-DenseNet with an attention mechanism is suitable for wheat stripe rust disease grading in field conditions. [ABSTRACT FROM AUTHOR]

The two most promising models for analyzing multi‐location trials (MLT) include the factor‐analytic (FA) and equal diagonal factor‐analytic (FA1) models. Here, we compare the two models by analyzing four datasets performed for the corn (Zea mays L.) performance trails in Northeastern and Northern China. The FA model contained more parameters for the variance–covariance of variety effects than the FA1 model. In data fitting, the effective (parameter value estimated >0) parameter number difference between the two models was not as large as in theory and was reduced with an increasing number of factors. In goodness‐of‐fit for trial data, the two models were competitive based on both the Akaike Information Criterion (AIC) and the likelihood‐ratio test (LRT). There were no notable differences between the two models in the estimates, rankings, standard errors of estimates, test efficiencies of contrasts for variety main (mean over all locations) effects, and discrimination power for varieties. The FA models were superior to FA1 models in the standard error of estimates and test efficiency of contrasts for variety simple effects. Therefore, the FA model was suggested for the analysis of MLTs. A general recommendation for the selection of either the FA or FA1 models using AIC or LRT cannot be made from this analysis. [ABSTRACT FROM AUTHOR]

Stripe rust caused by Puccinia striiformis f. sp. tritici (Pst) is one the most important diseases of wheat in Ethiopia and worldwide. To identify resistance genes, 90 bread wheat lines and 10 cultivars were tested at the seedling stage against one Pst race from Ethiopia and six races from China as well as evaluated for the stripe rust response in an inoculated field nursery at Yangling, Shaanxi province and in a naturally infected field in Jiangyou, Sichuan, China. Resistance genes were postulated using molecular assays for Yr9, Yr17, Yr18, Yr26, Yr29, Yr36, Yr44 and Yr62. Of the 100 entries tested, 16 had all stage resistance to all races. Molecular markers were positive for Yr9 in five genotypes, Yr17 in 21 genotypes, Yr18 in 27 genotypes, Yr26 in ten genotypes, Yr29 in 22 genotypes, Yr36 in 12 genotypes, Yr44 in 30 genotypes, and Yr62 in 51 genotypes. No line had Yr5, Yr8, Yr10 or Yr15. Complete or all stage resistance was observed in genotypes carrying gene combinations Yr9 + Yr18 + Yr44 + Yr62, Yr29 + Yr62 + Yr26 and Yr9 + Yr17 + Yr26 + Yr44 + Yr62. The results are helpful for developing wheat cultivars with effective and more durable resistance to stripe rust both in China and Ethiopia. [ABSTRACT FROM AUTHOR]

For effective use of the factor‐analytic (FA) model in analyzing data from multi‐environmental trials (METs), we undertook an empirical study of data sets from the corn (Zea mays L.) performance trails in China to compare all FA models with possible number of factors. We found that for the variety main effects, the estimate, ranking, and test efficiency of contrast were compatible among the FA models with various numbers of factors. For the variety simple effects, the effect estimate, and hence the ranking, changed; the test efficiency of contrast and discrimination power increased with increasing number of factors as the number of factors was smaller than a specific number. With consideration of both test efficiency of contrast and discrimination power of varieties for the trials analyzed, about 10 could be chosen as the optimal number of factors of the FA model approach. [ABSTRACT FROM AUTHOR]

Stripe rust, caused by Puccinia striiformis f. sp. tritici , is one of the most damaging diseases of wheat in the world. China is one of the most important regions of wheat production and stripe rust epidemics. The spread of Yr26 -virulent races V26 has threatened wheat production in China. It is urgent to identify new resistance sources for use in breeding programs. A total of 60 accessions from different wheat regions in the world, showing excellent field resistance in previous study were examined in more details at Yangling under artificially inoculation conditions and Tianshui under naturally infection from 2015 to 2017. Seedling tests were also conducted using two Yr26 -virulent races and eight Yr26 -avirulent races. The combined field and seedling response data and pedigrees of the 60 entries were used to postulate the resistance genes involved. Molecular markers that are linked to some previously reported stripe rust resistance genes were used to validate the postulated genes. Resistance genes in 4 accessions that were resistant in all race tests in the seedling stage and field tests could not be predicted. These 4 accessions with all stage resistance should combine with other Yr genes to obtain durable resistance. Resistance in 24 accessions was attributed, at least in part, to combinations of known genes. Fifty accessions were susceptible to the Yr26 -virulent races in the seedling stage, but resistant in the fields of both locations. With at least partial assurance, the genes for effective resistance in the 50 accessions are different from those already widely used in Chinese wheat varieties. Therefore, these 50 accessions should be used in breeding programs to developing new cultivars with effective resistance to the new emerging races and other predominant races. • Resistance genes in 4 accessions that were resistant in all Pst race tests in the seedling stage and field tests could not be predicted. • Resistance in 24 accessions was attributed, at least in part, to combinations of known genes. • Resistance genes in the 50 accessions with adult plant resistance are different from those already widely used in Chinese wheat varieties. [ABSTRACT FROM AUTHOR]

The Yr26 gene, conferring resistance to all currently important races of Puccinia striiformis f. sp. tritici (Pst) in China, was previously mapped to wheat chromosome deletion bin C-1BL-6-0.32 with low-density markers. In this study, collinearity of wheat to Brachypodium distachyon and rice was used to develop markers to saturate the chromosomal region containing the Yr26 locus, and a total of 2,341 F2 plants and 551 F2∶3 progenies derived from Avocet S×92R137 were used to develop a fine map of Yr26. Wheat expressed sequence tags (ESTs) located in deletion bin C-1BL-6-0.32 were used to develop sequence tagged site (STS) markers. The EST-STS markers flanking Yr26 were used to identify collinear regions of the rice and B. distachyon genomes. Wheat ESTs with significant similarities in the two collinear regions were selected to develop conserved markers for fine mapping of Yr26. Thirty-one markers were mapped to the Yr26 region, and six of them cosegregated with the resistance gene. Marker orders were highly conserved between rice and B. distachyon, but some rearrangements were observed between rice and wheat. Two flanking markers (CON-4 and CON-12) further narrowed the genomic region containing Yr26 to a 1.92 Mb region in B. distachyon chromosome 3 and a 1.17 Mb region in rice chromosome 10, and two putative resistance gene analogs were identified in the collinear region of B. distachyon. The markers developed in this study provide a potential target site for further map-based cloning of Yr26 and should be useful in marker assisted selection for pyramiding the gene with other resistance genes. [ABSTRACT FROM AUTHOR]

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most important diseases of wheat (Triticum aestivum) in China and is responsible for major production losses worldwide. Wheat cultivar Centrum was resistant at seedling stage to Chinese Pst isolate V26-10. To map the gene(s) conferring resistance, Centrum was crossed with the susceptible cultivar MX169. Genetic analysis of F1, F2, F2:3, and F2:6 populations showed that resistance was conferred by a single recessive gene, tentatively named Yrcen. The F2:6 population was genotyped using Illumina 35 K SNP (single nucleotide polymorphism) assays. Gene Yrcen was located on chromosome 1DS. To saturate the genetic map, the Affymetrix Wheat 660 K SNP array was used to screen bulked extreme phenotype DNA pools. Eight SNPs were located around the resistance gene. After combining SNP data from both the 35 K and 660 K assays, Yrcen was mapped to an interval of 1.7 cM flanked by markers AX-94530296 and AX-94434109. These two markers were validated for marker assisted selection of Yrcen using a panel of 96 wheat cultivars and breeding lines. These tightly linked markers will be useful in developing cultivars for resistance to stripe rust. [ABSTRACT FROM AUTHOR]

Iron (Fe) deficiency affects over two billion people worldwide. Developing high-yielding wheat (Triticum aestivum L.) cultivars with high grain Fe concentration (GFeC) is a key step toward alleviating malnutrition in humans. In this study, we used a diversity panel of 388 wheat accessions to examine the GFeC in four field environments. We found that the mean GFeC of the four environments decreased with the release year. And GFeC showed poor correlation with grain yield or the three yield factors in the four environments. Importantly, wheat cultivars in the major wheat-producing region of China showed the lowest GFeC. The GFeC phenotype was used for a genome-wide association study (GWAS) using a 660 K single-nucleotide polymorphism (SNP) chip, and 17 quantitative trait loci (QTLs) were identified on chromosomes 3B, 4 A, 5 A, 6B, 6D, 7 A, 7B, and 7D. However, no universal QTLs were detected among the 17 identified QTLs and 2280 yield-related QTLs. Through allelic analysis, two homologous genes, TraesCS7A01G197400 and TraesCS7D01G198900 , were identified as potential candidate genes for GFeC, while the favourable alleles for GFeC were lost during the selection breeding process in China. The insights gained from this study showed that the yield dilution effect was not applied to the decrease in GFeC, which should be mainly caused by the loss of favourable alleles during the wheat breeding process in China. Therefore, wheat breeders should pay more attention to other traits to improve GFeC rather than the yield dilution effect. • GFeC of 388 wheat accessions was determined in four environments. • Wheat accessions for major wheat-producing region of China contain the lowest GFeC. • GFeC decreased with release year during the wheat breeding process in China. • Seventeen QTLs and two important candidate genes for wheat GFeC were identified. • Yield dilution effect was not applied to the decrease in GFeC. [ABSTRACT FROM AUTHOR]

Low Gain Avalanche Detectors (LGAD) are silicon particle sensors with intrinsic gain through a thin p-type multiplication layer inserted between n-type implant and p-type bulk. The first prototype of LGAD sensors in China have been developed at the Institute of High Energy Physics (IHEP) of Chinese Academic Sciences and the Novel Device Laboratory (NDL) of Beijing Normal University. With an active thickness of 33 μ m, good breakdown performance, gain > 10, these sensors have reached jitter contribution of 10 ps to timing resolution with laser tests. [ABSTRACT FROM AUTHOR]

We study the radiation effects of the Low Gain Avalanche Detector (LGAD) sensors developed by the Institute of High Energy Physics (IHEP) and the Novel Device Laboratory (NDL) of Beijing Normal University in China. These sensors have been irradiated at the China Institute of Atomic Energy (CIAE) using 100 MeV proton beam with five different fluences from 7 × 1 0 14 n eq /cm 2 up to 4.5 × 1 0 15 n eq /cm 2. The result indicates that the effective doping concentration in the gain layer decreases with the increase of irradiation fluence, as expected by the acceptor removal mechanism. By comparing data and model gives the acceptor removal coefficient c A =(5.52±0.58)×10 − 16 cm 2 , which shows the NDL sensor has fairly good radiation resistance. The time resolution of the sensors after irradiation was measured at (−30 ± 2) °C. [ABSTRACT FROM AUTHOR]

Key Message: Four stable QTL for adult plant resistance were identified in wheat line Changwu 357-9, including a new QTL on 2AL showing significant interaction with Yr29 to reduce stripe rust severity. Stripe rust (yellow rust) is a serious disease of bread wheat (Triticum aestivum L.) worldwide. Genetic resistance is considered the most economical, effective and environmentally friendly method to control the disease and to minimize the use of fungicides. The current study focused on characterizing the components of stripe rust resistance and understanding the interactions in Changwu 357-9 (CW357-9)/Avocet S RIL population. A genetic linkage map constructed using a new GenoBaits Wheat 16K Panel and the 660K SNP array had 5104 polymorphic SNP markers spanning 3533.11 cM. Four stable QTL, consistently identified across five environments, were detected on chromosome arms 1BL, 2AL, 3DS, and 6BS in Changwu357-9. The most effective QTL QYrCW357-1BL was Yr29. The 6BS QTL was identified as Yr78, which has been combined with the 1BL QTL in many wheat cultivars and breeding lines. The novel QTL on 2AL with moderate effect showed a stable and significant epistatic interaction with Yr29. The QTL on 3DL should be same as QYrsn.nwafu-3DL and enriches the overall stripe rust resistance gene pool for breeding. Polymorphisms of flanking AQP markers AX-110020417 (for QYrCW357-1BL), AX-110974948 (for QYrCW357-2AL), AX-109466386 (for QYrCW357-3DL), and AX-109995005 (for QYrCW357-6BS) were evaluated in a diversity panel including 225 wheat cultivars and breeding lines. These results suggested that these high-throughput markers could be used to introduce QYrCW357-1BL, QYrCW357-2AL, QYrCW357-3DL, and QYrCW357-6BS into commercial wheat cultivars. Combinations of these genes with other APR QTL should lead to higher levels of stripe rust resistance along with the beneficial effects of multi-disease resistance gene Yr29 on improving resistance to other diseases., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Wheat cultivar Shaannong 33 (SN33) has remained highly resistant to stripe rust in the field since its release in 2009. To unravel the genetic architecture of stripe rust resistance, seedlings of 161 recombinant inbred lines (RILs) from the cross Avocet S × SN33 were evaluated with two isolates (PST-Lab.1 and PST-Lab.2) of the stripe rust pathogen ( Puccinia striiformis f. sp. tritici ) in the greenhouse, and the RILs were evaluated in naturally or artificially inoculated field sites during two cropping seasons. The RILs and parents were genotyped with the wheat 55K single-nucleotide polymorphism array. Three genomic regions conferring seedling resistance were mapped on chromosomes 1DS, 2AS, and 3DS, and four consistent quantitative trait loci (QTL) for adult-plant resistance (APR) were detected on 1BL, 2AS, 3DL, and 6BS. The 2AS locus conferring all-stage resistance was identified as the resistant gene Yr17 located on 2NS translocation. The QTL identified on 1BL and 6BS likely correspond to Yr29 and Yr78 , respectively. An APR QTL on 3DL explaining 5.8 to 12.2% of the phenotypic variation is likely to be new. Molecular marker detection assays with the 2NS segment ( Yr17 ), Yr29 , Yr78 , and QYrsn.nwafu-3DL on a panel of 420 current Chinese wheat cultivars and breeding lines indicated that these genes were present in 11.4, 7.6, 14.8, and 7.4% of entries, respectively. The interactions among these genes and QTL were additive, suggesting their potential value in enhancing stripe rust resistance breeding materials as observed in the resistant parent. In addition, we also identified two leaf necrosis genes, Ne1 and Ne2 ; however, the F 1 plants from cross Avocet S × SN33 survived, indicating that SN33 probably has another allele of Ne1 which allows seed to be harvested.

Crown rot (CR) and Fusarium head blight (FHB) are two serious wheat diseases caused by Fusarium pathogens in China. To identify new resistant sources for CR and FHB, 205 Chinese wheat cultivars collected from Huang-Huai wheat-growing region in China were screened for resistance. Cunmai633, LS4607, Pubing01, and Hongyun2 showed seedling resistance to CR with disease index (DI) less than 0.25. Sixteen cultivars showed adult-plant resistance to CR with DI lower than 0.10. Twenty-six cultivars showed moderate resistance to CR at seedling stage with DI from 0.26 to 0.35, and 63 cultivars showed moderate adult-plant resistance with DI from 0.11 to 0.20. Among them, Cunmai633, LS4607, Pubing01, Xinong916, Zhengda161, Xumai14017, Zhengpinmai30, Bainong8822, Jimai216, Huacheng865, Fengyumai5, and Tianmin319 showed resistance or moderate resistance to CR at both seedling and adult plant stages, with Cunmai633 showing the best resistance. Most of the cultivars (>76%) were susceptible to FHB in both the 2017 and 2018 experiments with DI > 0.40. However, some cultivars demonstrated excellent FHB resistance. For example, Zhongyu1526, Tianminxiaoyan369, and Yangao168 were resistant (DI ≤ 0.25) in 2017 and moderately resistant (0.26 ≤ DI ≤ 0.40) in 2018; Zhongwo9 was moderately resistant in 2017 (DI = 0.38) and resistant in 2018 (DI = 0.25). Eight cultivars (Cunmai608, Zhengmai162, Minfeng266, Junda159, LS4607, Deyan1603, Pumai1165, and Fengmai12) showed moderate FHB resistance with DI lower than 0.40 in both experiments. LS4607 showed moderate resistance to both diseases. The resistant cultivars identified in this study can be used for mapping the resistance genes and improving resistance to CR and/or FHB.

Stripe rust caused by Puccinia striiformis f. sp. tritici ( Pst ) is one of the most destructive fungal diseases of wheat worldwide. The expanding Yr26 -virulent Pst race (V26) group overcomes almost all currently deployed resistance genes in China and has continued to accumulate new virulence. Investigating the genetic architecture of stripe rust resistance in common wheat is an important basis for a successful utilization of resistance in breeding programs. A panel of 410 exotic wheat germplasms was used for characterizing new stripe rust resistance loci. This panel was genotyped using high-density wheat 660K single-nucleotide polymorphism (SNP) array, and phenotypic evaluation of seedlings for stripe rust resistance was performed using multiple Pst races. Thirty-five loci conferring resistance were identified through genome-wide association mapping, and explained phenotypic variances ranged from 53 to 75%. Of these, 14 were colocated in the proximity of the known loci, including cataloged Yr genes Yr9 , Yr10 , Yr26 , Yr33 , Yr47 , Yr56 , Yr57 , Yr64 , Yr67 , Yr72 , and Yr81 and three temporarily designated as YrCen , YrNP63 , and YrRC detected in our quantitative trait locus (QTL) mapping studies. Seven of them ( Yr9 , Yr10 , Yr24/26 , Yr81 , YrCEN , YrNP63 , and YrRC ) were confirmed by molecular detection or genetic analysis. New loci that were identified to be different from reported Yr genes need further confirmation. Nine QTL with significantly large phenotypic effect on resistance to all tested races were considered as major loci for effective resistance. The identified loci enrich our stripe rust resistance gene pool, and the linked SNPs should be useful for marker-assisted selection in breeding programs.