Quantitative trait loci analysis of zinc efficiency and grain zinc concentration in wheat using whole genome average interval mapping

Zinc (Zn) deficiency is a widespread problem which reduces yield and grain nutritive value in many cereal growing regions of the world. While there is considerable genetic variation in tolerance to Zn deficiency (also known as Zn efficiency), phenotypic selection is difficult and would benefit from...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Plant and soil 2009-01, Vol.314 (1/2), p.49-66
Hauptverfasser: Genc, Y., Verbyla, A. P., Torun, A. A., Cakmak, I., Willsmore, K., Wallwork, H., McDonald, G. K.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 66
container_issue 1/2
container_start_page 49
container_title Plant and soil
container_volume 314
creator Genc, Y.
Verbyla, A. P.
Torun, A. A.
Cakmak, I.
Willsmore, K.
Wallwork, H.
McDonald, G. K.
description Zinc (Zn) deficiency is a widespread problem which reduces yield and grain nutritive value in many cereal growing regions of the world. While there is considerable genetic variation in tolerance to Zn deficiency (also known as Zn efficiency), phenotypic selection is difficult and would benefit from the development of molecular markers. A doubled haploid population derived from a cross between the Zn inefficient genotype RAC875-2 and the moderately efficient genotype Cascades was screened in three experiments to identify QTL linked to growth under low Zn and with the concentrations of Zn and iron (Fe) in leaf tissue and in the grain. Two experiments were conducted under controlled conditions while the third examined the response to Zn in the field. QTL were identified using an improved method of analysis, whole genome average interval mapping. Shoot biomass and shoot Zn and Fe concentrations showed significant negative correlations, while there were significant genetic correlations between grain Zn and Fe concentrations. Shoot biomass, tissue and grain Zn concentrations were controlled by a number of genes, many with a minor effect. Depending on the traits and the site, the QTL accounted for 12–81% of the genetic variation. Most of the QTL linked to seedling growth under Zn deficiency and to Zn and Fe concentrations were associated with height genes with greater seedling biomass associated with lower Zn and Fe concentrations. Four QTL for grain Zn concentration and a single QTL for grain Fe concentration were also identified. A cluster of adjacent QTL related to the severity of symptoms of Zn deficiency, shoot Zn concentration and kernel weight was found on chromosome 4A and a cluster of QTL associated with shoot and grain Fe concentrations and kernel weight was found on chromosome 3D. These two regions appear promising areas for further work to develop markers for enhanced growth under low Zn and for Zn and Fe uptake. Although there was no significant difference between the parents, the grain Zn concentration ranged from 29 to 43 mg kg-1 within the population and four QTL associated with grain Zn concentration were identified. These were located on chromosomes 3D, 4B, 6B and 7A and they described 92% of the genetic variation. Each QTL had a relatively small effect on grain Zn concentration but combining the four high Zn alleles increased the grain Zn by 23%. While this illustrates the potential for pyramiding genes to improve grain Zn, breeding for increas
doi_str_mv 10.1007/s11104-008-9704-3
format Article
fullrecord <record><control><sourceid>jstor_proqu</sourceid><recordid>TN_cdi_proquest_journals_200540218</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>24124068</jstor_id><sourcerecordid>24124068</sourcerecordid><originalsourceid>FETCH-LOGICAL-c433t-3df47868d4b3dde3e7e6ae759e9471ba4d720ae85bfe903ecebee71eba1f51b3</originalsourceid><addsrcrecordid>eNp9kEFr3DAQhUVpodukP6CHgij06HZk2ZZ9LKFNCoFQyKE3MZZHrhavtJW0Wzb3_u9qcUhuPWmk973H6DH2TsAnAaA-JyEENBVAXw2qDPIF24hWyaoF2b1kGwBZV6CGn6_Zm5S2cL6LbsP-_jigzy5jdkfiOaLLfAnGcfS4nJJLPFj-4LzhZK0zjrw5FW3ic0H9qpjgDfnizS54Xl7__CLM_JCcn8scFuIz-bAjjkeKOFNhMsUjLnyH-32hLtkri0uit4_nBbv_9vX-6qa6vbv-fvXltjKNlLmSk21U3_VTM8ppIkmKOiTVDjQ0SozYTKoGpL4dLQ0gydBIpASNKGwrRnnBPqyx-xh-HyhlvQ2HWD6adA3QNlCLvkBihUwMKUWyeh_dDuNJC9DnrvXatS5d63PXWhbPx8dgTAYXG9Ebl56MdbHVQ3vOrlcuFcnPFJ8X-F_4-9W0TTnE59BG1A10vfwHxWGb-w</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>200540218</pqid></control><display><type>article</type><title>Quantitative trait loci analysis of zinc efficiency and grain zinc concentration in wheat using whole genome average interval mapping</title><source>SpringerNature Journals</source><source>JSTOR Archive Collection A-Z Listing</source><creator>Genc, Y. ; Verbyla, A. P. ; Torun, A. A. ; Cakmak, I. ; Willsmore, K. ; Wallwork, H. ; McDonald, G. K.</creator><creatorcontrib>Genc, Y. ; Verbyla, A. P. ; Torun, A. A. ; Cakmak, I. ; Willsmore, K. ; Wallwork, H. ; McDonald, G. K.</creatorcontrib><description>Zinc (Zn) deficiency is a widespread problem which reduces yield and grain nutritive value in many cereal growing regions of the world. While there is considerable genetic variation in tolerance to Zn deficiency (also known as Zn efficiency), phenotypic selection is difficult and would benefit from the development of molecular markers. A doubled haploid population derived from a cross between the Zn inefficient genotype RAC875-2 and the moderately efficient genotype Cascades was screened in three experiments to identify QTL linked to growth under low Zn and with the concentrations of Zn and iron (Fe) in leaf tissue and in the grain. Two experiments were conducted under controlled conditions while the third examined the response to Zn in the field. QTL were identified using an improved method of analysis, whole genome average interval mapping. Shoot biomass and shoot Zn and Fe concentrations showed significant negative correlations, while there were significant genetic correlations between grain Zn and Fe concentrations. Shoot biomass, tissue and grain Zn concentrations were controlled by a number of genes, many with a minor effect. Depending on the traits and the site, the QTL accounted for 12–81% of the genetic variation. Most of the QTL linked to seedling growth under Zn deficiency and to Zn and Fe concentrations were associated with height genes with greater seedling biomass associated with lower Zn and Fe concentrations. Four QTL for grain Zn concentration and a single QTL for grain Fe concentration were also identified. A cluster of adjacent QTL related to the severity of symptoms of Zn deficiency, shoot Zn concentration and kernel weight was found on chromosome 4A and a cluster of QTL associated with shoot and grain Fe concentrations and kernel weight was found on chromosome 3D. These two regions appear promising areas for further work to develop markers for enhanced growth under low Zn and for Zn and Fe uptake. Although there was no significant difference between the parents, the grain Zn concentration ranged from 29 to 43 mg kg-1 within the population and four QTL associated with grain Zn concentration were identified. These were located on chromosomes 3D, 4B, 6B and 7A and they described 92% of the genetic variation. Each QTL had a relatively small effect on grain Zn concentration but combining the four high Zn alleles increased the grain Zn by 23%. While this illustrates the potential for pyramiding genes to improve grain Zn, breeding for increased grain Zn concentration requires identification of individual QTL with large effects, which in turn requires construction and testing of new mapping populations in the future.</description><identifier>ISSN: 0032-079X</identifier><identifier>EISSN: 1573-5036</identifier><identifier>DOI: 10.1007/s11104-008-9704-3</identifier><identifier>CODEN: PLSOA2</identifier><language>eng</language><publisher>Dordrecht: Springer</publisher><subject>Agronomy. Soil science and plant productions ; Alleles ; Animal, plant and microbial ecology ; Biological and medical sciences ; Biomass ; Biomedical and Life Sciences ; Chromosomes ; Ecology ; Fundamental and applied biological sciences. Psychology ; Gene mapping ; Genes ; Genetic diversity ; Genetic variation ; Genotype &amp; phenotype ; Grain ; Grains ; Life Sciences ; Nutritive value ; Phenotypic traits ; Plant Physiology ; Plant Sciences ; Plant tissues ; Plants ; Quantitative trait loci ; Regular Article ; Seedlings ; Soil Science &amp; Conservation ; Studies ; Wheat ; Zinc</subject><ispartof>Plant and soil, 2009-01, Vol.314 (1/2), p.49-66</ispartof><rights>Springer Science+Business Media B.V. 2008</rights><rights>2009 INIST-CNRS</rights><rights>Springer Science+Business Media B.V. 2009</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c433t-3df47868d4b3dde3e7e6ae759e9471ba4d720ae85bfe903ecebee71eba1f51b3</citedby><cites>FETCH-LOGICAL-c433t-3df47868d4b3dde3e7e6ae759e9471ba4d720ae85bfe903ecebee71eba1f51b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/24124068$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/24124068$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>315,781,785,804,27929,27930,41493,42562,51324,58022,58255</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=21002958$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Genc, Y.</creatorcontrib><creatorcontrib>Verbyla, A. P.</creatorcontrib><creatorcontrib>Torun, A. A.</creatorcontrib><creatorcontrib>Cakmak, I.</creatorcontrib><creatorcontrib>Willsmore, K.</creatorcontrib><creatorcontrib>Wallwork, H.</creatorcontrib><creatorcontrib>McDonald, G. K.</creatorcontrib><title>Quantitative trait loci analysis of zinc efficiency and grain zinc concentration in wheat using whole genome average interval mapping</title><title>Plant and soil</title><addtitle>Plant Soil</addtitle><description>Zinc (Zn) deficiency is a widespread problem which reduces yield and grain nutritive value in many cereal growing regions of the world. While there is considerable genetic variation in tolerance to Zn deficiency (also known as Zn efficiency), phenotypic selection is difficult and would benefit from the development of molecular markers. A doubled haploid population derived from a cross between the Zn inefficient genotype RAC875-2 and the moderately efficient genotype Cascades was screened in three experiments to identify QTL linked to growth under low Zn and with the concentrations of Zn and iron (Fe) in leaf tissue and in the grain. Two experiments were conducted under controlled conditions while the third examined the response to Zn in the field. QTL were identified using an improved method of analysis, whole genome average interval mapping. Shoot biomass and shoot Zn and Fe concentrations showed significant negative correlations, while there were significant genetic correlations between grain Zn and Fe concentrations. Shoot biomass, tissue and grain Zn concentrations were controlled by a number of genes, many with a minor effect. Depending on the traits and the site, the QTL accounted for 12–81% of the genetic variation. Most of the QTL linked to seedling growth under Zn deficiency and to Zn and Fe concentrations were associated with height genes with greater seedling biomass associated with lower Zn and Fe concentrations. Four QTL for grain Zn concentration and a single QTL for grain Fe concentration were also identified. A cluster of adjacent QTL related to the severity of symptoms of Zn deficiency, shoot Zn concentration and kernel weight was found on chromosome 4A and a cluster of QTL associated with shoot and grain Fe concentrations and kernel weight was found on chromosome 3D. These two regions appear promising areas for further work to develop markers for enhanced growth under low Zn and for Zn and Fe uptake. Although there was no significant difference between the parents, the grain Zn concentration ranged from 29 to 43 mg kg-1 within the population and four QTL associated with grain Zn concentration were identified. These were located on chromosomes 3D, 4B, 6B and 7A and they described 92% of the genetic variation. Each QTL had a relatively small effect on grain Zn concentration but combining the four high Zn alleles increased the grain Zn by 23%. While this illustrates the potential for pyramiding genes to improve grain Zn, breeding for increased grain Zn concentration requires identification of individual QTL with large effects, which in turn requires construction and testing of new mapping populations in the future.</description><subject>Agronomy. Soil science and plant productions</subject><subject>Alleles</subject><subject>Animal, plant and microbial ecology</subject><subject>Biological and medical sciences</subject><subject>Biomass</subject><subject>Biomedical and Life Sciences</subject><subject>Chromosomes</subject><subject>Ecology</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Gene mapping</subject><subject>Genes</subject><subject>Genetic diversity</subject><subject>Genetic variation</subject><subject>Genotype &amp; phenotype</subject><subject>Grain</subject><subject>Grains</subject><subject>Life Sciences</subject><subject>Nutritive value</subject><subject>Phenotypic traits</subject><subject>Plant Physiology</subject><subject>Plant Sciences</subject><subject>Plant tissues</subject><subject>Plants</subject><subject>Quantitative trait loci</subject><subject>Regular Article</subject><subject>Seedlings</subject><subject>Soil Science &amp; Conservation</subject><subject>Studies</subject><subject>Wheat</subject><subject>Zinc</subject><issn>0032-079X</issn><issn>1573-5036</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kEFr3DAQhUVpodukP6CHgij06HZk2ZZ9LKFNCoFQyKE3MZZHrhavtJW0Wzb3_u9qcUhuPWmk973H6DH2TsAnAaA-JyEENBVAXw2qDPIF24hWyaoF2b1kGwBZV6CGn6_Zm5S2cL6LbsP-_jigzy5jdkfiOaLLfAnGcfS4nJJLPFj-4LzhZK0zjrw5FW3ic0H9qpjgDfnizS54Xl7__CLM_JCcn8scFuIz-bAjjkeKOFNhMsUjLnyH-32hLtkri0uit4_nBbv_9vX-6qa6vbv-fvXltjKNlLmSk21U3_VTM8ppIkmKOiTVDjQ0SozYTKoGpL4dLQ0gydBIpASNKGwrRnnBPqyx-xh-HyhlvQ2HWD6adA3QNlCLvkBihUwMKUWyeh_dDuNJC9DnrvXatS5d63PXWhbPx8dgTAYXG9Ebl56MdbHVQ3vOrlcuFcnPFJ8X-F_4-9W0TTnE59BG1A10vfwHxWGb-w</recordid><startdate>20090101</startdate><enddate>20090101</enddate><creator>Genc, Y.</creator><creator>Verbyla, A. P.</creator><creator>Torun, A. A.</creator><creator>Cakmak, I.</creator><creator>Willsmore, K.</creator><creator>Wallwork, H.</creator><creator>McDonald, G. K.</creator><general>Springer</general><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SN</scope><scope>7ST</scope><scope>7T7</scope><scope>7X2</scope><scope>88A</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M0K</scope><scope>M7P</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>RC3</scope><scope>SOI</scope></search><sort><creationdate>20090101</creationdate><title>Quantitative trait loci analysis of zinc efficiency and grain zinc concentration in wheat using whole genome average interval mapping</title><author>Genc, Y. ; Verbyla, A. P. ; Torun, A. A. ; Cakmak, I. ; Willsmore, K. ; Wallwork, H. ; McDonald, G. K.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c433t-3df47868d4b3dde3e7e6ae759e9471ba4d720ae85bfe903ecebee71eba1f51b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Agronomy. Soil science and plant productions</topic><topic>Alleles</topic><topic>Animal, plant and microbial ecology</topic><topic>Biological and medical sciences</topic><topic>Biomass</topic><topic>Biomedical and Life Sciences</topic><topic>Chromosomes</topic><topic>Ecology</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Gene mapping</topic><topic>Genes</topic><topic>Genetic diversity</topic><topic>Genetic variation</topic><topic>Genotype &amp; phenotype</topic><topic>Grain</topic><topic>Grains</topic><topic>Life Sciences</topic><topic>Nutritive value</topic><topic>Phenotypic traits</topic><topic>Plant Physiology</topic><topic>Plant Sciences</topic><topic>Plant tissues</topic><topic>Plants</topic><topic>Quantitative trait loci</topic><topic>Regular Article</topic><topic>Seedlings</topic><topic>Soil Science &amp; Conservation</topic><topic>Studies</topic><topic>Wheat</topic><topic>Zinc</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Genc, Y.</creatorcontrib><creatorcontrib>Verbyla, A. P.</creatorcontrib><creatorcontrib>Torun, A. A.</creatorcontrib><creatorcontrib>Cakmak, I.</creatorcontrib><creatorcontrib>Willsmore, K.</creatorcontrib><creatorcontrib>Wallwork, H.</creatorcontrib><creatorcontrib>McDonald, G. K.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Ecology Abstracts</collection><collection>Environment Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Agricultural Science Collection</collection><collection>Biology Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural &amp; Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Genetics Abstracts</collection><collection>Environment Abstracts</collection><jtitle>Plant and soil</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Genc, Y.</au><au>Verbyla, A. P.</au><au>Torun, A. A.</au><au>Cakmak, I.</au><au>Willsmore, K.</au><au>Wallwork, H.</au><au>McDonald, G. K.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantitative trait loci analysis of zinc efficiency and grain zinc concentration in wheat using whole genome average interval mapping</atitle><jtitle>Plant and soil</jtitle><stitle>Plant Soil</stitle><date>2009-01-01</date><risdate>2009</risdate><volume>314</volume><issue>1/2</issue><spage>49</spage><epage>66</epage><pages>49-66</pages><issn>0032-079X</issn><eissn>1573-5036</eissn><coden>PLSOA2</coden><abstract>Zinc (Zn) deficiency is a widespread problem which reduces yield and grain nutritive value in many cereal growing regions of the world. While there is considerable genetic variation in tolerance to Zn deficiency (also known as Zn efficiency), phenotypic selection is difficult and would benefit from the development of molecular markers. A doubled haploid population derived from a cross between the Zn inefficient genotype RAC875-2 and the moderately efficient genotype Cascades was screened in three experiments to identify QTL linked to growth under low Zn and with the concentrations of Zn and iron (Fe) in leaf tissue and in the grain. Two experiments were conducted under controlled conditions while the third examined the response to Zn in the field. QTL were identified using an improved method of analysis, whole genome average interval mapping. Shoot biomass and shoot Zn and Fe concentrations showed significant negative correlations, while there were significant genetic correlations between grain Zn and Fe concentrations. Shoot biomass, tissue and grain Zn concentrations were controlled by a number of genes, many with a minor effect. Depending on the traits and the site, the QTL accounted for 12–81% of the genetic variation. Most of the QTL linked to seedling growth under Zn deficiency and to Zn and Fe concentrations were associated with height genes with greater seedling biomass associated with lower Zn and Fe concentrations. Four QTL for grain Zn concentration and a single QTL for grain Fe concentration were also identified. A cluster of adjacent QTL related to the severity of symptoms of Zn deficiency, shoot Zn concentration and kernel weight was found on chromosome 4A and a cluster of QTL associated with shoot and grain Fe concentrations and kernel weight was found on chromosome 3D. These two regions appear promising areas for further work to develop markers for enhanced growth under low Zn and for Zn and Fe uptake. Although there was no significant difference between the parents, the grain Zn concentration ranged from 29 to 43 mg kg-1 within the population and four QTL associated with grain Zn concentration were identified. These were located on chromosomes 3D, 4B, 6B and 7A and they described 92% of the genetic variation. Each QTL had a relatively small effect on grain Zn concentration but combining the four high Zn alleles increased the grain Zn by 23%. While this illustrates the potential for pyramiding genes to improve grain Zn, breeding for increased grain Zn concentration requires identification of individual QTL with large effects, which in turn requires construction and testing of new mapping populations in the future.</abstract><cop>Dordrecht</cop><pub>Springer</pub><doi>10.1007/s11104-008-9704-3</doi><tpages>18</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0032-079X
ispartof Plant and soil, 2009-01, Vol.314 (1/2), p.49-66
issn 0032-079X
1573-5036
language eng
recordid cdi_proquest_journals_200540218
source SpringerNature Journals; JSTOR Archive Collection A-Z Listing
subjects Agronomy. Soil science and plant productions
Alleles
Animal, plant and microbial ecology
Biological and medical sciences
Biomass
Biomedical and Life Sciences
Chromosomes
Ecology
Fundamental and applied biological sciences. Psychology
Gene mapping
Genes
Genetic diversity
Genetic variation
Genotype & phenotype
Grain
Grains
Life Sciences
Nutritive value
Phenotypic traits
Plant Physiology
Plant Sciences
Plant tissues
Plants
Quantitative trait loci
Regular Article
Seedlings
Soil Science & Conservation
Studies
Wheat
Zinc
title Quantitative trait loci analysis of zinc efficiency and grain zinc concentration in wheat using whole genome average interval mapping
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-14T13%3A10%3A58IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Quantitative%20trait%20loci%20analysis%20of%20zinc%20efficiency%20and%20grain%20zinc%20concentration%20in%20wheat%20using%20whole%20genome%20average%20interval%20mapping&rft.jtitle=Plant%20and%20soil&rft.au=Genc,%20Y.&rft.date=2009-01-01&rft.volume=314&rft.issue=1/2&rft.spage=49&rft.epage=66&rft.pages=49-66&rft.issn=0032-079X&rft.eissn=1573-5036&rft.coden=PLSOA2&rft_id=info:doi/10.1007/s11104-008-9704-3&rft_dat=%3Cjstor_proqu%3E24124068%3C/jstor_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=200540218&rft_id=info:pmid/&rft_jstor_id=24124068&rfr_iscdi=true