Academic literature on the topic 'Stripe rust'
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Journal articles on the topic "Stripe rust"
Lan, C. X., R. P. Singh, J. Huerta-Espino, V. Calvo-Salazar, and S. A. Herrera-Foessel. "Genetic Analysis of Resistance to Leaf Rust and Stripe Rust in Wheat Cultivar Francolin#1." Plant Disease 98, no. 9 (September 2014): 1227–34. http://dx.doi.org/10.1094/pdis-07-13-0707-re.
Full textNavabi, A., J. P. Tewari, R. P. Singh, B. McCallum, A. Laroche, and K. G. Briggs. "Inheritance and QTL analysis of durable resistance to stripe and leaf rusts in an Australian cultivar, Triticum aestivum 'Cook'." Genome 48, no. 1 (February 1, 2005): 97–107. http://dx.doi.org/10.1139/g04-100.
Full textLiu, Weizhen, James Kolmer, Sheri Rynearson, Xianming Chen, Liangliang Gao, James A. Anderson, M. Kathryn Turner, and Michael Pumphrey. "Identifying Loci Conferring Resistance to Leaf and Stripe Rusts in a Spring Wheat Population (Triticum aestivum) via Genome-Wide Association Mapping." Phytopathology® 109, no. 11 (November 2019): 1932–40. http://dx.doi.org/10.1094/phyto-04-19-0143-r.
Full textKharouf, Shoula, Shadi Hamzeh, and Mohamad Fawaehz Azmeh. "Races Identification of Wheat Rusts in Syria during the 2019 Growing Season." Arab Journal for Plant Protection 39, no. 1 (March 2021): 1–13. http://dx.doi.org/10.22268/ajpp-39.1.001013.
Full textZhang, Peipei, Xing Li, Takele-Weldu Gebrewahid, Hexing Liu, Xianchun Xia, Zhonghu He, Zaifeng Li, and Daqun Liu. "QTL Mapping of Adult-Plant Resistance to Leaf and Stripe Rust in Wheat Cross SW 8588/Thatcher using the Wheat 55K SNP Array." Plant Disease 103, no. 12 (December 2019): 3041–49. http://dx.doi.org/10.1094/pdis-02-19-0380-re.
Full textWilliam, H. M., R. P. Singh, J. Huerta-Espino, G. Palacios, and K. Suenaga. "Characterization of genetic loci conferring adult plant resistance to leaf rust and stripe rust in spring wheat." Genome 49, no. 8 (August 1, 2006): 977–90. http://dx.doi.org/10.1139/g06-052.
Full textRioux, Sylvie, Benjamin Mimee, Annie-Ève Gagnon, and Sarah Hambleton. "First report of stripe rust (Puccinia striiformis f. sp. tritici) on wheat in Quebec, Canada." Communication brève 95, no. 1 (February 2, 2015): 7–9. http://dx.doi.org/10.7202/1028400ar.
Full textWilliam, M., R. P. Singh, J. Huerta-Espino, S. Ortiz Islas, and D. Hoisington. "Molecular Marker Mapping of Leaf Rust Resistance Gene Lr46 and Its Association with Stripe Rust Resistance Gene Yr29 in Wheat." Phytopathology® 93, no. 2 (February 2003): 153–59. http://dx.doi.org/10.1094/phyto.2003.93.2.153.
Full textSuenaga, K., R. P. Singh, J. Huerta-Espino, and H. M. William. "Microsatellite Markers for Genes Lr34/Yr18 and Other Quantitative Trait Loci for Leaf Rust and Stripe Rust Resistance in Bread Wheat." Phytopathology® 93, no. 7 (July 2003): 881–90. http://dx.doi.org/10.1094/phyto.2003.93.7.881.
Full textKHANFRI, Siham, Mohammed BOULIF, and Rachid LAHLALI. "Yellow Rust (Puccinia striiformis): a Serious Threat to Wheat Production Worldwide." Notulae Scientia Biologicae 10, no. 3 (September 27, 2018): 410–23. http://dx.doi.org/10.15835/nsb10310287.
Full textDissertations / Theses on the topic "Stripe rust"
Kertho, Albert Okaba. "Evaluation of Winter Wheat Germplasm for Resistance to Stripe Rust and Leaf Rust." Thesis, North Dakota State University, 2014. https://hdl.handle.net/10365/27571.
Full textGrabow, Bethany. "Environmental conditions associated with stripe rust and leaf rust epidemics in Kansas winter wheat." Diss., Kansas State University, 2016. http://hdl.handle.net/2097/32835.
Full textDepartment of Plant Pathology
Erick D. DeWolf
Stripe rust (caused by Puccinia striiformis f. sp. tritici) and leaf rust (caused by Puccinia triticina) are the top two diseases of winter wheat (Triticum aestivum) with a 20-year average yield loss of 4.9% in Kansas. Due to the significant yield losses caused by these diseases, the overall objective of this research was to identify environmental variables that favor stripe and leaf rust epidemics. The first objective was to verify the environmental conditions that favor P. triticina infections in an outdoor field environment. Wheat was inoculated with P. triticina and exposed to ambient weather conditions for 16 hours. Number of hours with temperature between 5 to 25°C and relative humidity >87% were highly correlated and predicted leaf rust infections with 89% accuracy. The results of this outdoor assay were used to develop variables to evaluate the association of environment with regional leaf rust epidemics. Before regional disease models can be developed for a forecast system, suitable predictors need to be identified. Objectives two and three of this research were to identify environmental variables associated with leaf rust and stripe rust epidemics and to evaluate these predictors in models. Mean yield loss on susceptible varieties was estimated for nine Kansas crop reporting districts (CRD’s). Monthly environmental variables were evaluated for association with stripe rust epidemics (>1% yield loss), leaf rust epidemics (>1% yield loss), severe stripe rust epidemics (>14% yield loss) and severe leaf rust epidemics (>7% yield loss) at the CRD scale. Stripe rust and leaf rust epidemics were both strongly associated with soil moisture conditions; however, the timing differed between these diseases. Stripe rust epidemics were associated with soil moisture in fall and winter, and leaf rust epidemics during winter and spring. Severe stripe rust and leaf rust epidemics were associated with favorable temperature (7 to 12°C) and temperature (15 to 20°C) with relative humidity (>87%) or precipitation in May using tree-based methods of classification, respectively. The preliminary models developed in this research could be coupled with disease observations and varietal resistance information to advise growers about the need for foliar fungicides against these rusts in Kansas winter wheat.
Loladze, Alexander. "Identification of stripe rust resistance in wheat relatives and landraces." Online access for everyone, 2006. http://www.dissertations.wsu.edu/Thesis/Spring2006/A%5FLoladze%5F050306.pdf.
Full textCheng, Peng. "Molecular mapping of a gene for resistance to stripe rust in spring wheat cultivar IDO377s and identification of a new race of Puccinia striiformis f. sp. tritici virulent on IDO377s." [Pullman, Wash.] : Washington State University, 2008. http://www.dissertations.wsu.edu/Thesis/Fall2008/p_cheng_081808.pdf.
Full textTitle from PDF title page (viewed on Sept. 23, 2008). "Department of Plant Pathology." Includes bibliographical references.
Evin, Bryn Anndi. "Evaluation of Management Tools for Stripe Rust in Hard Red Spring Wheat and Assessment of Virulence Phenotypes and Aggressiveness in Puccinia striiformis Isolates." Diss., North Dakota State University, 2019. https://hdl.handle.net/10365/31562.
Full textNorth Dakota Wheat Commission
State Board of Agricultural Research and Education
Nyori, Peter Michael Bulli. "Genetics of resistance to leaf and stripe rust diseases in the spring wheat 'Amadina'." Diss., Kansas State University, 2010. http://hdl.handle.net/2097/4611.
Full textDepartment of Agronomy
Allan K. Fritz
In this research, a recombinant inbred line (RIL) population derived from cross between a leaf rust- and stripe rust-susceptible spring wheat ‘Avocet S’ and a slow leaf- and stripe-rusting resistant spring wheat ‘Amadina’ was used to postulate and map leaf rust seedling resistance genes, identify quantitative trait loci (QTL) for slow-rusting resistance against leaf and stripe rust, and study slow leaf-rusting components, latent period and infection frequency. Two known Lr genes (Lr23, and Lr26) were identified to be present in ‘Amadina’ through gene postulation, pedigree, cytogenetic, and polymerase chain reaction analyses. One unknown gene associated with seedling resistance was also mapped on chromosome 1BL. In greenhouse experiment, it was estimated that at least five genes conditioning final disease severity (FS) and latent period (LP), and four genes conditioning infection frequency (IF), segregated in the population. Correlations between LP and FS, and LP and IF were moderately negative, and that between IF and FS was moderately positive, indicating inter-dependence of the traits. Two QTL on chromosomes 1BL and 6BL were associated with LP and FS, and three QTL on chromosomes 1BL, 6BL and 2DS were associated with IF. Segregation of the RIL population in field experiment indicated that there were at least four and three adult plant resistance (APR) genes involved in resistance for leaf and stripe rust. Six QTL on chromosomes 3AL, 4AL, 1BL, 5BL, and 7BL were associated with APR for leaf rust, and seven QTL on chromosome 4AL, 5AL, 1BL, 2BL, 4BL, 5BL, 2DL, and 4D were associated with APR for stripe rust. Our results indicated that the major portion of genetic variability for slow-rusting resistance was additive gene action, and, to some extent, epistasis. In this research, we also explored the utility of remote sensing and geographic information systems (GIS) and analytical operations to discriminate leaf rust pustules from other parts of leaf and to accurately determine pustule size in ‘Amadina’ and ‘Avocet S’.
Ramburan, Viresh Premraj. "Genetic mapping of adult plant stripe rust resistance in the wheat cultivar Kariega." Thesis, Stellenbosch : Stellenbosch University, 2003. http://hdl.handle.net/10019.1/53438.
Full textENGLISH ABSTRACT: Stripe (yellow) rust of wheat, caused by Puccinia striiformis f.sp. tritici, was first detected as a single introduction into South Africa in 1996. Two additional pathotypes have since been identified. Control of the disease may be achieved by use of genetic adult plant resistance (APR) as is present in the local cultivar 'Kariega'. The aim of this project was to understand the genetic basis of the APR in 'Kariega' to facilitate breeding of new varieties with genetic resistance to stripe rust. A partial linkage map of a 'Kariega X Avocet S' doubled haploid population covering all 21 wheat chromosomes was generated using 208 DNA markers, viz, 62 SSR, 133 AFLP, 3 RGA and 10 SRAP markers, and 4 alternative loci. The different marker techniques detected varying polymorphism, viz, overall SSR: 46%, AFLP: 7%, SRAP: 6% and RGA: 9%, and the markers produced low levels of missing data (4%) and segregation distortion (5%). A significant feature of the linkage map was the low polymorphism found in the D genome, viz, 19% of all mapped DNA markers, 11% of all AFLP markers and 30% of the total genome map distance. A region exhibiting significant segregation distortion was mapped to chromosome 4A and a seedling resistance gene for stem rust (Puccinia graminis f.sp . tritici), Sr26, mapped to chromosome 6A close to three SSR markers. The leaf tip necrosis gene, Ltn, which was also segregating in the population, mapped to chromosome 7D. Protocols for SRAP and RGA were optimised, and SRAP marker use in wheat genetic linkage studies is reported for the first time. The linkage map was used together with growth chamber and replicated field disease scores for QTL mapping. Chromosomes showing statistically significant QTL effects were then targeted with supplementary SSR markers for higher resolution mapping. The quality of disease resistance phenotypic data was confirmed by correlation analysis between the different scorers for reaction type (0.799±0.023) and for transformed percentage leaf area infected (0.942±0.007). Major QTL were consistently identified on chromosome 7D (explaining some 25-48% of the variation) and on chromosome 2B (21-46%) using transformed percentage leaf area infected and transformed reaction type scores (early and final) with interval mapping and modified interval mapping techniques. Both chromosomal regions have previously been identified in other studies and the 7D QTL is thought likely to be the previously mapped APR gene Yr 18. Minor QTL were identified on chromosomes lA and 4A with the QTL on 4A being more prominent at the early field scoring for both score types. A QTL evidently originating from 'Avocet S' was detected under growth chamber conditions but was not detected in the field, suggesting genotype-environment interaction and highlighting the need for modifications of growth chamber conditions to better simulate conditions in the field. The genetic basis of the APR to stripe rust exhibited by 'Kariega' was established by mapping of QTL controlling this trait. The linkage map constructed will be a valuable resource for future genetic studies and provides a facility for mapping other polymorphic traits in the parents of this population with a considerable saving in costs.
AFRIKAANSE OPSOMMING: Streep of geelroes van koring word veroorsaak deur Puccinia striiformis f. sp tritici, en is die eerste keer in 1996 in Suid-Afrika na introduksie van 'n enkele patotipe waargeneem. Twee verdere patotipes is sedertdien in Suid-Afrika gei"dentifiseer. Beheer van die siekte word veral moontlik gemaak deur die gebruik van genetiese volwasseplantweerstand soos gei"dentifiseer in die plaaslike kultivar 'Kariega'. Die doel van hierdie studie was om die genetiese grondslag van die streeproesweerstand te ontrafel ten einde die teling van nuwe bestande kultivars moontlik te maak. 'n Verdubbelde haplo1ede populasie uit die kruising 'Kariega X Avocet S' is aangewend om 'n gedeeltelike koppelingskaart vir die volle stel van 21 koring chromosome saam te stel. Die kaart het uit 208 DNA merkers, nl., 62 SSR, 133 AFLP, 3 RGA, 10 SRAP merkers en 4 ander lokusse bestaan. Totale polimorfisme wat deur die verskillende merkersisteme opgespoor is, was as volg: SSR: 46%, RGA: 9%, AFLP: 7% en SRAP: 6%. Die mate van ontbrekende data was gering (4%) asook die mate van segregasie distorsie (5%) van 'n enkele geval wat op chromosoom 4A gekarteer is. 'n Prominente kenmerk van die koppelingskaart is die relatiewe gebrek aan polimorfiese merkers op die D-genoom, nl., slegs 19% van alle DNA merkers en 11% van alle AFLP merkers wat slegs 30% van die totale genoom kaartafstand bestaan het. Die stamroes (Puccinia graminis f. sp. tritici) saailingweerstandsgeen, Sr26, karteer op chromosoom 6A naby drie SSR merkers. Die geen vir blaartipnekrose, Ltn, karteer op chromosoom 7D. Protokolle vir SRAP en RGA merkers is ge-optimiseer en gebruik van SRAP merkers in koppelings-analise word vir die eerste keer in koring gerapporteer. Die koppelingskaart is in kombinasie met groeikamerdata en gerepliseerde veldproefdata gebruik om die gene (QTL) vir volwasseplant streeproesweerstand te karteer. Chromosome met statisties betekenisvolle QTL is met aanvullende SSR merkers geteiken om die resolusie van kartering verder te verhoog. Die kwaliteit van fenotipiese data, soos in die proewe aangeteken, is bevestig deur korrelasies te bereken tussen lesings geneem deur onafhanklike plantpataloe (0.799 ± 0.023 vir reaksietipe en 0.942 ± 0.007 vir getransformeerde persentasie blaaroppervlakte besmet). Hoofeffek QTL vir die twee maatstawwe van weerstand is deur middel van die metodes van interval QTL kartering en gemodifiseerde interval QTL kartering konsekwent op chromosome 7D (25-48% van variasie verklaar) en 2B (21-46% van variasie verklaar) ge"identifiseer. In vorige studies is aangetoon dat beide chromosome 7D en 2B QTL vir volwasseplant streeproesweerstand dra. Die 7D QTL is waarskynlik die weerstandsgeen, Yr 18. QTL met klein effekte op weerstand is op chromosome lA en 4A ge"identifiseer. Die effek van laasgenoemde geen was meer prominent in die velddata in die vroee datum van weerstandsbeoordeling. Een QTL, afkomstig van 'Avocet S', is slegs onder groeikamertoestande identifiseerbaar. Dit dui op moontlike genotipe-omgewing wisselwerking en beklemtoon die noodsaaklikheid om aanpassings te maak in groeikamertoestande vir beter simulasie van veldproeftoestande. Die genetiese grondslag van volwasseplantweerstand teen streeproes in die kultivar 'Kariega' is deur QTL kartering bepaal. Die 'Kariega X Avocet S' koppelingskaart kan as 'n waardevolle basis dien vir toekomstige genetiese ontledings van ander polimorfiese kenmerke in die populasie.
Christopher, Mark David. "Identification and Mapping of Adult Plant Stripe Rust Resistance in Soft Red Winter Wheat." Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/39690.
Full textPh. D.
Dawson, Andrew. "Elucidating the molecular genetics of host and nonhost resistance in barley to stripe rust." Thesis, University of East Anglia, 2015. https://ueaeprints.uea.ac.uk/58560/.
Full textShao, Mingqin. "QTL mapping of pre-harvest sprouting and stripe rust resistance in wheat cultivars Danby and Tiger." Diss., Kansas State University, 2017. http://hdl.handle.net/2097/38205.
Full textDepartment of Agronomy
Guihua Bai
Guorong Zhang
Wheat yield and quality is influenced by many abiotic and biotic environmental factors. Pre-harvest sprouting (PHS) occurs when physiologically matured spikes are exposed to wet field conditions before harvest, which results in seed germination and causes significant losses in yield and end-use quality. Wheat stripe rust is one of the most important biotic factors reducing grain yield and quality. To investigate the genetic basis of the resistance to PHS and stripe rust in hard white winter wheat cultivars Danby and Tiger and develop molecular markers for marker- assisted breeding, a double haploid (DH) population, derived from those two cultivars, was genotyped with simple sequence repeats (SSR) markers and simple nucleotide polymorphism (SNP) markers. This DH population was assessed for resistance to PHS and stripe rust in both greenhouse and field experiments. For PHS, one major resistant quantitative trait locus (QTL) was consistently detected on the short arm of chromosome 3A in all three experiments conducted and explained 21.6% to 41.0% of the phenotypic variation (PVE). This QTL is corresponding to a previously cloned gene, TaPHS1. A SNP in the promoter of TaPHS1 co- segregated with PHS resistance in this mapping population. Meanwhile, two other QTLs, Qphs.hwwg-3B.1 and Qphs.hwwg-5A.1, were consistently detected on the chromosome arms 3BS and 5AL in two experiments. These two QTLs showed significant additive effects with TaPHS1 in improving PHS resistance. For stripe rust, three major QTLs were consistently detected in four out of six environments for infection type (IT) or disease severity (DS). Two of them, QYr.hwwg-2AS1 and QYr.hwwg-4BL1, contributed by the Danby allele explained up to 28.4% of PVE for IT and 60.5% of PVE for DS. The third QTL, QYr.hwwg-3BS1, contributed by the Tiger allele, had PVE values up to 14.7% for IT and 22.9% for DS. QYr.hwwg-2AS1 and QYr.hwwg- 4BL1 are likely the same resistance genes reported previously on chromosome arms 2AS and 4BL. However, QYr.hwwg-3BS1 might be different from the reported gene cluster near the distal end of 3BS where Yr57, Yr4, Yr30 and Sr2 were located. Significant additive effects on reducing IT and DS were observed among these three major QTLs. In order to pyramid multiple QTLs in breeding, user-friendly Kompetitive allele specific PCR (KASP) markers were successfully developed for several QTLs identified in this study. The QTLs and their interactions found in this study together with those novel flanking KASP markers developed will be useful not only for understanding genetic mechanisms of PHS and stripe rust resistance but also for marker- assisted breeding to improve wheat resistance to PHS and stripe rust by gene pyramiding.
Books on the topic "Stripe rust"
Chen, Xianming, and Zhensheng Kang, eds. Stripe Rust. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-1111-9.
Full textLine, Roland F. Virulence, aggressiveness, evolution, and distribution of races of Puccinia striiformis (the cause of stripe rust of wheat) in North America, 1968-87 / [Line, Roland F., and Abdul Qayoum]. [Washington, D.C.?]: U.S. Dept. of Agriculture, Agricultural Research Service, 1992.
Find full text1969-, Price Jay M., ed. Cherokee Strip land rush. Charleston, SC: Arcadia Pub., 2006.
Find full textBook chapters on the topic "Stripe rust"
Chen, Xianming. "Stripe Rust Epidemiology." In Stripe Rust, 283–352. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-1111-9_4.
Full textWang, Meinan, and Xianming Chen. "Stripe Rust Resistance." In Stripe Rust, 353–558. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-1111-9_5.
Full textChen, Xianming, and Zhensheng Kang. "Introduction: History of Research, Symptoms, Taxonomy of the Pathogen, Host Range, Distribution, and Impact of Stripe Rust." In Stripe Rust, 1–33. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-1111-9_1.
Full textWan, Anmin, Xiaojie Wang, Zhensheng Kang, and Xianming Chen. "Variability of the Stripe Rust Pathogen." In Stripe Rust, 35–154. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-1111-9_2.
Full textKang, Zhensheng, Chunlei Tang, Jie Zhao, Yulin Cheng, Jie Liu, Jun Guo, Xiaojie Wang, and Xianming Chen. "Wheat-Puccinia striiformis Interactions." In Stripe Rust, 155–282. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-1111-9_3.
Full textChen, Xianming, and Zhensheng Kang. "Integrated Control of Stripe Rust." In Stripe Rust, 559–99. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-1111-9_6.
Full textChen, Xianming, and Zhensheng Kang. "Stripe Rust Research and Control: Conclusions and Perspectives." In Stripe Rust, 601–30. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-1111-9_7.
Full textVan Silfhout, C. H. "Durable Resistance in the Pathosystem: Wheat — Stripe Rust." In Durability of Disease Resistance, 135–45. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-2004-3_11.
Full textBakshi, Suman, Johar Singh, and Sanjay J. Jambhulkar. "Isolation and characterization of yellow rust resistant mutants in wheat." In Mutation breeding, genetic diversity and crop adaptation to climate change, 103–10. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789249095.0010.
Full textBroers, L. H. M. "Breeding for Partial Resistance in Wheat to Stripe Rust." In Durability of Disease Resistance, 179–83. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-2004-3_14.
Full textConference papers on the topic "Stripe rust"
Lihong Mo. "Prediction of wheat stripe rust using neural network." In 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2010). IEEE, 2010. http://dx.doi.org/10.1109/icicisys.2010.5658476.
Full textWang, Haiguang, and Zhanhong Ma. "Prediction of wheat stripe rust based on support vector machine." In 2011 Seventh International Conference on Natural Computation (ICNC). IEEE, 2011. http://dx.doi.org/10.1109/icnc.2011.6022095.
Full textJing, Xia, Teng Zhang, and Weina Duan. "Hyperspectral monitoring of wheat stripe rust based on PSO-KELM model." In Seventh Symposium on Novel Photoelectronic Detection Technology and Application 2020, edited by Junhao Chu, Qifeng Yu, Huilin Jiang, and Junhong Su. SPIE, 2021. http://dx.doi.org/10.1117/12.2587021.
Full textJiang, Jinbao, Yunhao Chen, Jianxiong Zhang, and Jing Li. "Using Hyperspectral Indices to Diagnose Severity of Winter Wheat Stripe Rust." In 2006 8th international Conference on Signal Processing. IEEE, 2006. http://dx.doi.org/10.1109/icosp.2006.344504.
Full textHe, Jia, Laigang WANG, Yan GUO, Yan ZHANG, Hongli ZHANG, and Shaobo XU. "Wheat stripe rust remote sensing monitoring based on a new vegetation index." In International Conference on Agri-Photonics and Smart Agricultural Sensing Technologies (ICASAST 2022), edited by Jiandong Hu. SPIE, 2022. http://dx.doi.org/10.1117/12.2657093.
Full textSTRAZDINA, Vija, Valentina FETERE, Liga FEODOROVA-FEDOTOVA, Janis JASKO, and Olga TREIKALE. "REACTION OF WINTER WHEAT GENOTYPES ON THE YELLOW (STRIPE) RUST PUCCINIA STRIIFORMIS, WES." In RURAL DEVELOPMENT. Aleksandras Stulginskis University, 2018. http://dx.doi.org/10.15544/rd.2017.124.
Full textWang, Liwen, Fangmin Dong, Qing Guo, Chenwei Nie, and Shuifa Sun. "Improved rotation kernel transformation directional feature for recognition of wheat stripe rust and powdery mildew." In 2014 7th International Congress on Image and Signal Processing (CISP). IEEE, 2014. http://dx.doi.org/10.1109/cisp.2014.7003793.
Full textJiang, Jinbao, Yunhao Chen, Adu Gong, and Jing Li. "Study on inversion models for the severity of winter wheat stripe rust using hyperspectral remote sensing." In 2007 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2007. http://dx.doi.org/10.1109/igarss.2007.4423522.
Full textZhao, Jinling, Lin Yuan, Juhua Luo, Shizhou Du, Linsheng Huang, and Wenjiang Huang. "Spectral differences of opposite sides of stripe rust infested winter wheat leaves using ASD's Leaf Clip." In IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2012. http://dx.doi.org/10.1109/igarss.2012.6352090.
Full textYao, Zhifeng, Dongjian He, and Yu Lei. "<i>Thermal imaging for early nondestructive detection of wheat stripe rust </i>." In 2018 Detroit, Michigan July 29 - August 1, 2018. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2018. http://dx.doi.org/10.13031/aim.201801728.
Full textReports on the topic "Stripe rust"
Kleczewski, Nathan, Carl Bradley, Martin Chilvers, Alyssa Collins, Erick DeWolf, Andrew Friskop, Alyssa Koehler, et al. Stripe Rust of Wheat. United States: Crop Protection Netework, September 2020. http://dx.doi.org/10.31274/cpn-20200922-3.
Full textBreiman, Adina, Jan Dvorak, Abraham Korol, and Eduard Akhunov. Population Genomics and Association Mapping of Disease Resistance Genes in Israeli Populations of Wild Relatives of Wheat, Triticum dicoccoides and Aegilops speltoides. United States Department of Agriculture, December 2011. http://dx.doi.org/10.32747/2011.7697121.bard.
Full textDubcovsky, Jorge, Tzion Fahima, and Ann Blechl. Molecular characterization and deployment of the high-temperature adult plant stripe rust resistance gene Yr36 from wheat. United States Department of Agriculture, November 2013. http://dx.doi.org/10.32747/2013.7699860.bard.
Full textDistelfeld, Assaf, Jan Dvorak, and Hanan Sela. Introgression of stripe rust resistance genes from Aegilops speltodies into wheat with a novel introgression methodology. United States Department of Agriculture, 2015. http://dx.doi.org/10.32747/2015.7600026.bard.
Full textSela, Hanan, Eduard Akhunov, and Brian J. Steffenson. Population genomics, linkage disequilibrium and association mapping of stripe rust resistance genes in wild emmer wheat, Triticum turgidum ssp. dicoccoides. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7598170.bard.
Full textFahima, Tzion, and Jorge Dubcovsky. Map-based cloning of the novel stripe rust resistance gene YrG303 and its use to engineer 1B chromosome with multiple beneficial traits. United States Department of Agriculture, January 2013. http://dx.doi.org/10.32747/2013.7598147.bard.
Full textJacobsen, Nils. Linjebussens vekst og fall i den voksende byen: en studie av bybussenes geografiske kvalitet Stavanger – Sandnes 1920 – 2010. University of Stavanger, November 2019. http://dx.doi.org/10.31265/usps.244.
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