Sweet corn response to combined nitrogen and salinity environmental stresses
To define the nature of the combined response curve of sweet corn (Zea mays L.) plants to nitrogen and salinity, a lysimeter study was designed to follow water and solute budgets with combinations of the two variables over wide ranges of 0.5–7.5 dS m-1 and 0–150% of local N-fertilization recommendat...
Gespeichert in:
Veröffentlicht in: | Plant and soil 2003-09, Vol.256 (1), p.139-147 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 147 |
---|---|
container_issue | 1 |
container_start_page | 139 |
container_title | Plant and soil |
container_volume | 256 |
creator | Shenker, Moshe Ben-Gal, Alon Shani, Uri |
description | To define the nature of the combined response curve of sweet corn (Zea mays L.) plants to nitrogen and salinity, a lysimeter study was designed to follow water and solute budgets with combinations of the two variables over wide ranges of 0.5–7.5 dS m-1 and 0–150% of local N-fertilization recommendations. Patterns of water-use efficiency, N content, N uptake, and shoot dry-matter yield indicated the predominance of environmental interactions over Cl-nitrate physiological antagonism. At low salinities, the leaf N content, N uptake, and yield increased with increased N fertilization up to 45% of local N-fertilization recommendations, nitrogen was efficiently stripped from the percolating water and practically no nitrate was leached. At higher N fertilization the amount of leached N increased linearly with increased N input, and N uptake and yield were independent of N rates, levelling off at increased values for decreased salinities. The Liebig–Sprengel and Mitscherlich–Baule models were evaluated against measured data; both achieved similar values for the system's inherent N, the salinity level corresponding with zero-yield, and the predicted yields, which were highly correlated with the experimental data (R2 > 0.9). It is suggested that both models can be used successfully in mechanistic-based plant–soil solution models to predict yield, water and nutrient needs, and the resulted N leaching. |
doi_str_mv | 10.1023/a:1026274015858 |
format | Article |
fullrecord | <record><control><sourceid>jstor_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_17678222</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>24123364</jstor_id><sourcerecordid>24123364</sourcerecordid><originalsourceid>FETCH-LOGICAL-c448t-26ac8461a95acfabaeec4ef694cd304dedd60f098a1b0340c3f9734763cb0a113</originalsourceid><addsrcrecordid>eNp9kc1r3EAMxYfSQLebnHMqmEJKLk40H56xcwshX7CQQxrIzWjHcvHindmOvCn57zvLhpb00JOQ9HvvISTEsYQzCUqf40UuVjkDsqqr-oOYycrpsgJtP4oZgFYluOb5k_jMvIJdL-1MLB5_EU2FjykUiXgTA1MxxTxYL4dAXRGGKcUfFAoMXcE4DnnwWlB4GVIMawoTjgVPWcrEh-Kgx5Hp6K3OxdPN9feru3LxcHt_dbkovTH1VCqLvjZWYlOh73GJRN5QbxvjOw2mo66z0ENTo1yCNuB13zhtnNV-CSilnotve99Nij-3xFO7HtjTOGKguOVWOutqpVQGT_8PWmtV09RQZfTrP-gqblPIZ7SukqC1dLvg8z3kU2RO1LebNKwxvbYS2t0X2sv23Rey4uTNFtnj2CcMfuC_skrpHL_jvuy5FU8x_dkrI5XW1ujfNlqQnA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>751033171</pqid></control><display><type>article</type><title>Sweet corn response to combined nitrogen and salinity environmental stresses</title><source>Jstor Complete Legacy</source><source>Springer Nature - Complete Springer Journals</source><creator>Shenker, Moshe ; Ben-Gal, Alon ; Shani, Uri</creator><creatorcontrib>Shenker, Moshe ; Ben-Gal, Alon ; Shani, Uri</creatorcontrib><description>To define the nature of the combined response curve of sweet corn (Zea mays L.) plants to nitrogen and salinity, a lysimeter study was designed to follow water and solute budgets with combinations of the two variables over wide ranges of 0.5–7.5 dS m-1 and 0–150% of local N-fertilization recommendations. Patterns of water-use efficiency, N content, N uptake, and shoot dry-matter yield indicated the predominance of environmental interactions over Cl-nitrate physiological antagonism. At low salinities, the leaf N content, N uptake, and yield increased with increased N fertilization up to 45% of local N-fertilization recommendations, nitrogen was efficiently stripped from the percolating water and practically no nitrate was leached. At higher N fertilization the amount of leached N increased linearly with increased N input, and N uptake and yield were independent of N rates, levelling off at increased values for decreased salinities. The Liebig–Sprengel and Mitscherlich–Baule models were evaluated against measured data; both achieved similar values for the system's inherent N, the salinity level corresponding with zero-yield, and the predicted yields, which were highly correlated with the experimental data (R2 > 0.9). It is suggested that both models can be used successfully in mechanistic-based plant–soil solution models to predict yield, water and nutrient needs, and the resulted N leaching.</description><identifier>ISSN: 0032-079X</identifier><identifier>EISSN: 1573-5036</identifier><identifier>DOI: 10.1023/a:1026274015858</identifier><identifier>CODEN: PLSOA2</identifier><language>eng</language><publisher>Dordrecht: Kluwer Academic Publishers</publisher><subject>Agronomy. Soil science and plant productions ; Allelopathy ; Animal, plant and microbial ecology ; Biological and medical sciences ; Corn ; Environmental stress ; Fertilization ; Fundamental and applied biological sciences. Psychology ; Irrigation water ; Leaching ; Lysimeters ; Modeling ; Nitrogen ; Percolating water ; Plant growth ; Plants ; Salinity ; Soil salinity ; Soil solution ; Water use</subject><ispartof>Plant and soil, 2003-09, Vol.256 (1), p.139-147</ispartof><rights>2003 Kluwer Academic Publishers</rights><rights>2004 INIST-CNRS</rights><rights>Kluwer Academic Publishers 2003</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c448t-26ac8461a95acfabaeec4ef694cd304dedd60f098a1b0340c3f9734763cb0a113</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/24123364$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/24123364$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,776,780,799,27901,27902,57992,58225</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=15239808$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Shenker, Moshe</creatorcontrib><creatorcontrib>Ben-Gal, Alon</creatorcontrib><creatorcontrib>Shani, Uri</creatorcontrib><title>Sweet corn response to combined nitrogen and salinity environmental stresses</title><title>Plant and soil</title><description>To define the nature of the combined response curve of sweet corn (Zea mays L.) plants to nitrogen and salinity, a lysimeter study was designed to follow water and solute budgets with combinations of the two variables over wide ranges of 0.5–7.5 dS m-1 and 0–150% of local N-fertilization recommendations. Patterns of water-use efficiency, N content, N uptake, and shoot dry-matter yield indicated the predominance of environmental interactions over Cl-nitrate physiological antagonism. At low salinities, the leaf N content, N uptake, and yield increased with increased N fertilization up to 45% of local N-fertilization recommendations, nitrogen was efficiently stripped from the percolating water and practically no nitrate was leached. At higher N fertilization the amount of leached N increased linearly with increased N input, and N uptake and yield were independent of N rates, levelling off at increased values for decreased salinities. The Liebig–Sprengel and Mitscherlich–Baule models were evaluated against measured data; both achieved similar values for the system's inherent N, the salinity level corresponding with zero-yield, and the predicted yields, which were highly correlated with the experimental data (R2 > 0.9). It is suggested that both models can be used successfully in mechanistic-based plant–soil solution models to predict yield, water and nutrient needs, and the resulted N leaching.</description><subject>Agronomy. Soil science and plant productions</subject><subject>Allelopathy</subject><subject>Animal, plant and microbial ecology</subject><subject>Biological and medical sciences</subject><subject>Corn</subject><subject>Environmental stress</subject><subject>Fertilization</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Irrigation water</subject><subject>Leaching</subject><subject>Lysimeters</subject><subject>Modeling</subject><subject>Nitrogen</subject><subject>Percolating water</subject><subject>Plant growth</subject><subject>Plants</subject><subject>Salinity</subject><subject>Soil salinity</subject><subject>Soil solution</subject><subject>Water use</subject><issn>0032-079X</issn><issn>1573-5036</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9kc1r3EAMxYfSQLebnHMqmEJKLk40H56xcwshX7CQQxrIzWjHcvHindmOvCn57zvLhpb00JOQ9HvvISTEsYQzCUqf40UuVjkDsqqr-oOYycrpsgJtP4oZgFYluOb5k_jMvIJdL-1MLB5_EU2FjykUiXgTA1MxxTxYL4dAXRGGKcUfFAoMXcE4DnnwWlB4GVIMawoTjgVPWcrEh-Kgx5Hp6K3OxdPN9feru3LxcHt_dbkovTH1VCqLvjZWYlOh73GJRN5QbxvjOw2mo66z0ENTo1yCNuB13zhtnNV-CSilnotve99Nij-3xFO7HtjTOGKguOVWOutqpVQGT_8PWmtV09RQZfTrP-gqblPIZ7SukqC1dLvg8z3kU2RO1LebNKwxvbYS2t0X2sv23Rey4uTNFtnj2CcMfuC_skrpHL_jvuy5FU8x_dkrI5XW1ujfNlqQnA</recordid><startdate>20030901</startdate><enddate>20030901</enddate><creator>Shenker, Moshe</creator><creator>Ben-Gal, Alon</creator><creator>Shani, Uri</creator><general>Kluwer Academic Publishers</general><general>Springer</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>AEUYN</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>PHGZM</scope><scope>PHGZT</scope><scope>PKEHL</scope><scope>PQEST</scope><scope>PQGLB</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>RC3</scope><scope>SOI</scope><scope>7UA</scope></search><sort><creationdate>20030901</creationdate><title>Sweet corn response to combined nitrogen and salinity environmental stresses</title><author>Shenker, Moshe ; Ben-Gal, Alon ; Shani, Uri</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c448t-26ac8461a95acfabaeec4ef694cd304dedd60f098a1b0340c3f9734763cb0a113</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Agronomy. Soil science and plant productions</topic><topic>Allelopathy</topic><topic>Animal, plant and microbial ecology</topic><topic>Biological and medical sciences</topic><topic>Corn</topic><topic>Environmental stress</topic><topic>Fertilization</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Irrigation water</topic><topic>Leaching</topic><topic>Lysimeters</topic><topic>Modeling</topic><topic>Nitrogen</topic><topic>Percolating water</topic><topic>Plant growth</topic><topic>Plants</topic><topic>Salinity</topic><topic>Soil salinity</topic><topic>Soil solution</topic><topic>Water use</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Shenker, Moshe</creatorcontrib><creatorcontrib>Ben-Gal, Alon</creatorcontrib><creatorcontrib>Shani, Uri</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 One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & 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 Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Applied & Life Sciences</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Genetics Abstracts</collection><collection>Environment Abstracts</collection><collection>Water Resources Abstracts</collection><jtitle>Plant and soil</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Shenker, Moshe</au><au>Ben-Gal, Alon</au><au>Shani, Uri</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Sweet corn response to combined nitrogen and salinity environmental stresses</atitle><jtitle>Plant and soil</jtitle><date>2003-09-01</date><risdate>2003</risdate><volume>256</volume><issue>1</issue><spage>139</spage><epage>147</epage><pages>139-147</pages><issn>0032-079X</issn><eissn>1573-5036</eissn><coden>PLSOA2</coden><abstract>To define the nature of the combined response curve of sweet corn (Zea mays L.) plants to nitrogen and salinity, a lysimeter study was designed to follow water and solute budgets with combinations of the two variables over wide ranges of 0.5–7.5 dS m-1 and 0–150% of local N-fertilization recommendations. Patterns of water-use efficiency, N content, N uptake, and shoot dry-matter yield indicated the predominance of environmental interactions over Cl-nitrate physiological antagonism. At low salinities, the leaf N content, N uptake, and yield increased with increased N fertilization up to 45% of local N-fertilization recommendations, nitrogen was efficiently stripped from the percolating water and practically no nitrate was leached. At higher N fertilization the amount of leached N increased linearly with increased N input, and N uptake and yield were independent of N rates, levelling off at increased values for decreased salinities. The Liebig–Sprengel and Mitscherlich–Baule models were evaluated against measured data; both achieved similar values for the system's inherent N, the salinity level corresponding with zero-yield, and the predicted yields, which were highly correlated with the experimental data (R2 > 0.9). It is suggested that both models can be used successfully in mechanistic-based plant–soil solution models to predict yield, water and nutrient needs, and the resulted N leaching.</abstract><cop>Dordrecht</cop><pub>Kluwer Academic Publishers</pub><doi>10.1023/a:1026274015858</doi><tpages>9</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0032-079X |
ispartof | Plant and soil, 2003-09, Vol.256 (1), p.139-147 |
issn | 0032-079X 1573-5036 |
language | eng |
recordid | cdi_proquest_miscellaneous_17678222 |
source | Jstor Complete Legacy; Springer Nature - Complete Springer Journals |
subjects | Agronomy. Soil science and plant productions Allelopathy Animal, plant and microbial ecology Biological and medical sciences Corn Environmental stress Fertilization Fundamental and applied biological sciences. Psychology Irrigation water Leaching Lysimeters Modeling Nitrogen Percolating water Plant growth Plants Salinity Soil salinity Soil solution Water use |
title | Sweet corn response to combined nitrogen and salinity environmental stresses |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-20T20%3A58%3A19IST&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=Sweet%20corn%20response%20to%20combined%20nitrogen%20and%20salinity%20environmental%20stresses&rft.jtitle=Plant%20and%20soil&rft.au=Shenker,%20Moshe&rft.date=2003-09-01&rft.volume=256&rft.issue=1&rft.spage=139&rft.epage=147&rft.pages=139-147&rft.issn=0032-079X&rft.eissn=1573-5036&rft.coden=PLSOA2&rft_id=info:doi/10.1023/a:1026274015858&rft_dat=%3Cjstor_proqu%3E24123364%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=751033171&rft_id=info:pmid/&rft_jstor_id=24123364&rfr_iscdi=true |