How Well Does Zone Sampling Based on Soil Electrical Conductivity Maps Represent Soil Variability
In zone soil sampling a field is divided into homogenous areas using an easy to measure ancillary attribute (e.g., apparent soil electrical conductivity [ECa]) and a few samples are taken from each zone to estimate the soil characteristics in each zone. This study determined if ECa-directed zone sam...
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| Veröffentlicht in: | Agronomy journal 2008-09, Vol.100 (5), p.1472-1480 |
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| creator | Shaner, D.L Khosla, R Brodahl, M.K Buchleiter, G.W Faraham, H.J |
| description | In zone soil sampling a field is divided into homogenous areas using an easy to measure ancillary attribute (e.g., apparent soil electrical conductivity [ECa]) and a few samples are taken from each zone to estimate the soil characteristics in each zone. This study determined if ECa-directed zone sampling in two fields in northeastern Colorado could correctly predict soil texture and soil organic matter (SOM) patterns of samples taken by a more intensive grid sample method. Each field, which were predominantly Bijou loamy sand (coarse-loamy, mixed, superactive, mesic Ustic Haplargids), and Valentine sand (mixed, mesic Typic Ustipsamments), was divided into three ECa zones and soil texture and OM content in the top 30 cm of soil were measured. There was a significant difference in the soil texture and SOM in both fields between ECa Zone 1 and Zone 3. Logistic regression showed that in both fields, approximately 80% of the grid sample sites in ECa Zone 1 were correctly predicted. Only 50% of the grid sample sites in ECa Zone 3 were correctly predicted as Zone 3 in one field whereas 77% of the grid sites in ECa Zone 3 were correctly predicted in the other field. However, approximately 80% of the samples in the grid sites 10 m from the zone boundaries were classified correctly as compared to the samples that were |
| doi_str_mv | 10.2134/agronj2008.0060 |
| format | Article |
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This study determined if ECa-directed zone sampling in two fields in northeastern Colorado could correctly predict soil texture and soil organic matter (SOM) patterns of samples taken by a more intensive grid sample method. Each field, which were predominantly Bijou loamy sand (coarse-loamy, mixed, superactive, mesic Ustic Haplargids), and Valentine sand (mixed, mesic Typic Ustipsamments), was divided into three ECa zones and soil texture and OM content in the top 30 cm of soil were measured. There was a significant difference in the soil texture and SOM in both fields between ECa Zone 1 and Zone 3. Logistic regression showed that in both fields, approximately 80% of the grid sample sites in ECa Zone 1 were correctly predicted. Only 50% of the grid sample sites in ECa Zone 3 were correctly predicted as Zone 3 in one field whereas 77% of the grid sites in ECa Zone 3 were correctly predicted in the other field. However, approximately 80% of the samples in the grid sites 10 m from the zone boundaries were classified correctly as compared to the samples that were <10 m from the boundary in which only 50 to 54% were classified correctly. These results support the utilization of ECa-directed zone sampling as an alternative to grid soil sampling if the transition zones are avoided.</description><identifier>ISSN: 0002-1962</identifier><identifier>EISSN: 1435-0645</identifier><identifier>DOI: 10.2134/agronj2008.0060</identifier><identifier>CODEN: AGJOAT</identifier><language>eng</language><publisher>Madison: American Society of Agronomy</publisher><subject>Agronomy. Soil science and plant productions ; Biological and medical sciences ; electrical conductivity ; experimental design ; Fundamental and applied biological sciences. Psychology ; methodology ; sandy loam soils ; sandy soils ; soil analysis ; Soil conductivity ; soil organic matter ; soil sampling ; soil texture ; spatial variation</subject><ispartof>Agronomy journal, 2008-09, Vol.100 (5), p.1472-1480</ispartof><rights>Copyright © 2008 by the American Society of Agronomy</rights><rights>2008 INIST-CNRS</rights><rights>Copyright American Society of Agronomy Sep/Oct 2008</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4800-e0064e8dbeac3be159453a7a6316abaa4263b128c2766a744995616c708360433</citedby><cites>FETCH-LOGICAL-c4800-e0064e8dbeac3be159453a7a6316abaa4263b128c2766a744995616c708360433</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.2134%2Fagronj2008.0060$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.2134%2Fagronj2008.0060$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=20682806$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Shaner, D.L</creatorcontrib><creatorcontrib>Khosla, R</creatorcontrib><creatorcontrib>Brodahl, M.K</creatorcontrib><creatorcontrib>Buchleiter, G.W</creatorcontrib><creatorcontrib>Faraham, H.J</creatorcontrib><title>How Well Does Zone Sampling Based on Soil Electrical Conductivity Maps Represent Soil Variability</title><title>Agronomy journal</title><description>In zone soil sampling a field is divided into homogenous areas using an easy to measure ancillary attribute (e.g., apparent soil electrical conductivity [ECa]) and a few samples are taken from each zone to estimate the soil characteristics in each zone. This study determined if ECa-directed zone sampling in two fields in northeastern Colorado could correctly predict soil texture and soil organic matter (SOM) patterns of samples taken by a more intensive grid sample method. Each field, which were predominantly Bijou loamy sand (coarse-loamy, mixed, superactive, mesic Ustic Haplargids), and Valentine sand (mixed, mesic Typic Ustipsamments), was divided into three ECa zones and soil texture and OM content in the top 30 cm of soil were measured. There was a significant difference in the soil texture and SOM in both fields between ECa Zone 1 and Zone 3. Logistic regression showed that in both fields, approximately 80% of the grid sample sites in ECa Zone 1 were correctly predicted. Only 50% of the grid sample sites in ECa Zone 3 were correctly predicted as Zone 3 in one field whereas 77% of the grid sites in ECa Zone 3 were correctly predicted in the other field. However, approximately 80% of the samples in the grid sites 10 m from the zone boundaries were classified correctly as compared to the samples that were <10 m from the boundary in which only 50 to 54% were classified correctly. These results support the utilization of ECa-directed zone sampling as an alternative to grid soil sampling if the transition zones are avoided.</description><subject>Agronomy. Soil science and plant productions</subject><subject>Biological and medical sciences</subject><subject>electrical conductivity</subject><subject>experimental design</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>methodology</subject><subject>sandy loam soils</subject><subject>sandy soils</subject><subject>soil analysis</subject><subject>Soil conductivity</subject><subject>soil organic matter</subject><subject>soil sampling</subject><subject>soil texture</subject><subject>spatial variation</subject><issn>0002-1962</issn><issn>1435-0645</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqFkEtPGzEURq2KSgTKmiVWpS6HXD_GM7NCaQqBiIdEoJW6Gd1xHOTIjKf2BJR_j6OJ2mVXluxzz3f9EXLK4JwzIcf4Eny75gDlOYCCT2TEpMgzUDI_ICMA4BmrFD8kRzGuARirJBsRvPbv9Jdxjv7wJtLfvjV0ga-ds-0L_Y7RLKlv6cJbRy-d0X2wGh2d-na50b19s_2W3mEX6aPpgomm7Qf2JwaLjXXp_Qv5vEIXzcn-PCbPV5dP0-vs9mF2M53cZlqWAJlJS0tTLhuDWjSG5ZXMBRaoBFPYIEquRMN4qXmhFBZSVlWumNIFlEKBFOKYfB28XfB_Nib29dpvQpsiawFS8RJEkaDxAOngYwxmVXfBvmLY1gzqXY31vxrrXY1p4tteizF9fRWw1Tb-HeOgyqRWibsYuHfrzPZ_2noym_PJ7PHhfr672yedDYYV-h2fUp4XHJgAlstKiFx8AH_6jlo</recordid><startdate>200809</startdate><enddate>200809</enddate><creator>Shaner, D.L</creator><creator>Khosla, R</creator><creator>Brodahl, M.K</creator><creator>Buchleiter, G.W</creator><creator>Faraham, H.J</creator><general>American Society of Agronomy</general><scope>FBQ</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X2</scope><scope>7XB</scope><scope>88I</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M0K</scope><scope>M2O</scope><scope>M2P</scope><scope>M7S</scope><scope>MBDVC</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>S0X</scope></search><sort><creationdate>200809</creationdate><title>How Well Does Zone Sampling Based on Soil Electrical Conductivity Maps Represent Soil Variability</title><author>Shaner, D.L ; Khosla, R ; Brodahl, M.K ; Buchleiter, G.W ; Faraham, H.J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4800-e0064e8dbeac3be159453a7a6316abaa4263b128c2766a744995616c708360433</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Agronomy. Soil science and plant productions</topic><topic>Biological and medical sciences</topic><topic>electrical conductivity</topic><topic>experimental design</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>methodology</topic><topic>sandy loam soils</topic><topic>sandy soils</topic><topic>soil analysis</topic><topic>Soil conductivity</topic><topic>soil organic matter</topic><topic>soil sampling</topic><topic>soil texture</topic><topic>spatial variation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Shaner, D.L</creatorcontrib><creatorcontrib>Khosla, R</creatorcontrib><creatorcontrib>Brodahl, M.K</creatorcontrib><creatorcontrib>Buchleiter, G.W</creatorcontrib><creatorcontrib>Faraham, H.J</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>eLibrary</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Agricultural Science Database</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>Environmental Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>SIRS Editorial</collection><jtitle>Agronomy journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Shaner, D.L</au><au>Khosla, R</au><au>Brodahl, M.K</au><au>Buchleiter, G.W</au><au>Faraham, H.J</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>How Well Does Zone Sampling Based on Soil Electrical Conductivity Maps Represent Soil Variability</atitle><jtitle>Agronomy journal</jtitle><date>2008-09</date><risdate>2008</risdate><volume>100</volume><issue>5</issue><spage>1472</spage><epage>1480</epage><pages>1472-1480</pages><issn>0002-1962</issn><eissn>1435-0645</eissn><coden>AGJOAT</coden><abstract>In zone soil sampling a field is divided into homogenous areas using an easy to measure ancillary attribute (e.g., apparent soil electrical conductivity [ECa]) and a few samples are taken from each zone to estimate the soil characteristics in each zone. This study determined if ECa-directed zone sampling in two fields in northeastern Colorado could correctly predict soil texture and soil organic matter (SOM) patterns of samples taken by a more intensive grid sample method. Each field, which were predominantly Bijou loamy sand (coarse-loamy, mixed, superactive, mesic Ustic Haplargids), and Valentine sand (mixed, mesic Typic Ustipsamments), was divided into three ECa zones and soil texture and OM content in the top 30 cm of soil were measured. There was a significant difference in the soil texture and SOM in both fields between ECa Zone 1 and Zone 3. Logistic regression showed that in both fields, approximately 80% of the grid sample sites in ECa Zone 1 were correctly predicted. Only 50% of the grid sample sites in ECa Zone 3 were correctly predicted as Zone 3 in one field whereas 77% of the grid sites in ECa Zone 3 were correctly predicted in the other field. However, approximately 80% of the samples in the grid sites 10 m from the zone boundaries were classified correctly as compared to the samples that were <10 m from the boundary in which only 50 to 54% were classified correctly. These results support the utilization of ECa-directed zone sampling as an alternative to grid soil sampling if the transition zones are avoided.</abstract><cop>Madison</cop><pub>American Society of Agronomy</pub><doi>10.2134/agronj2008.0060</doi><tpages>9</tpages></addata></record> |
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| subjects | Agronomy. Soil science and plant productions Biological and medical sciences electrical conductivity experimental design Fundamental and applied biological sciences. Psychology methodology sandy loam soils sandy soils soil analysis Soil conductivity soil organic matter soil sampling soil texture spatial variation |
| title | How Well Does Zone Sampling Based on Soil Electrical Conductivity Maps Represent Soil Variability |
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