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Methods of analysis and number of replicates for trials with large numbers of soybean genotypes
The aim of this study was to evaluate the experimental precision of different methods of statistical analysis for trials with large numbers of soybean genotypes, and their relationship with the number of replicates. Soybean yield data (nine trials; 324 genotypes; 46 cultivars; 278 lines; agricultura...
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Published in: | Ciência rural 2017, Vol.47 (4) |
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description | The aim of this study was to evaluate the experimental precision of different methods of statistical analysis for trials with large numbers of soybean genotypes, and their relationship with the number of replicates. Soybean yield data (nine trials; 324 genotypes; 46 cultivars; 278 lines; agricultural harvest of 2014/15) were used. Two of these trials were performed at the same location, side by side, forming a trial with six replicates. Each trial was analyzed by the randomized complete block, triple lattice design, and use of the Papadakis method. The selective accuracy, least significant difference, and Fasoulas differentiation index were estimated, and model assumptions were tested. The resampling method was used to study the influence of the number of replicates, by varying the number of blocks and estimating the precision measurements. The experimental precision indicators of the Papadakis method are more favorable as compared to the randomized complete block design and triple lattice. To obtain selective accuracy above the high experimental precision range in trials with 324 soybean genotypes, two repetitions can be used, and data can be analyzed using the randomized complete block design or Papadakis method.
RESUMO: O objetivo deste estudo foi avaliar a precisão experimental de diferentes métodos de análise estatística para ensaios com grande número de genótipos de soja e sua relação com o número de repetições. Foram usados dados de produtividade de grãos de soja (nove ensaios, 324 genótipos, 46 cultivares, 278 linhagens, safra agrícola de 2014/15). Dois destes ensaios foram realizados no mesmo local, lado a lado, constituindo um ensaio com seis repetições. Cada ensaio foi analisado pelos delineamentos de blocos ao acaso, látice triplo e uso do método de Papadakis. Foram estimados a acurácia seletiva, diferença mínima significativa e índice de diferenciação de Fasoulas, e, ainda foram testados os pressupostos do modelo. O método de reamostragem foi usado para estudar a influência do número de repetições, variando o número de blocos e estimando as medidas de precisão. Os indicadores de precisão experimental do método de Papadakis são mais favoráveis, quando comparados com os delineamentos de blocos ao acaso e látice triplo. Para obter acurácia seletiva acima da faixa de alta precisão experimental em ensaios com 324 genótipos de soja, pode-se usar duas repetições e analisar os dados, usando o delineamento de blocos completos ao acaso ou método de Papa |
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RESUMO: O objetivo deste estudo foi avaliar a precisão experimental de diferentes métodos de análise estatística para ensaios com grande número de genótipos de soja e sua relação com o número de repetições. Foram usados dados de produtividade de grãos de soja (nove ensaios, 324 genótipos, 46 cultivares, 278 linhagens, safra agrícola de 2014/15). Dois destes ensaios foram realizados no mesmo local, lado a lado, constituindo um ensaio com seis repetições. Cada ensaio foi analisado pelos delineamentos de blocos ao acaso, látice triplo e uso do método de Papadakis. Foram estimados a acurácia seletiva, diferença mínima significativa e índice de diferenciação de Fasoulas, e, ainda foram testados os pressupostos do modelo. O método de reamostragem foi usado para estudar a influência do número de repetições, variando o número de blocos e estimando as medidas de precisão. Os indicadores de precisão experimental do método de Papadakis são mais favoráveis, quando comparados com os delineamentos de blocos ao acaso e látice triplo. Para obter acurácia seletiva acima da faixa de alta precisão experimental em ensaios com 324 genótipos de soja, pode-se usar duas repetições e analisar os dados, usando o delineamento de blocos completos ao acaso ou método de Papadakis.</description><identifier>ISSN: 0103-8478</identifier><identifier>ISSN: 1678-4596</identifier><identifier>EISSN: 0103-8478</identifier><identifier>EISSN: 1678-4596</identifier><identifier>DOI: 10.1590/0103-8478cr20160629</identifier><language>eng</language><publisher>Santa Maria: Universidade Federal de Santa Maria Centro de Ciencias Rurais</publisher><subject>Accuracy ; acurácia seletiva ; AGRONOMY ; Crop yield ; Cultivars ; delineamento experimental ; Efficiency ; Genotype & phenotype ; Genotypes ; Glycine max ; Lattice design ; Methods ; Model testing ; precisão experimental ; reamostragem ; Resampling ; Software ; Soybeans ; Spatial analysis ; Statistical analysis ; Statistical methods</subject><ispartof>Ciência rural, 2017, Vol.47 (4)</ispartof><rights>2017. This work is published under http://creativecommons.org/licenses/by/4.0/deed.en (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>This work is licensed under a Creative Commons Attribution 4.0 International License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c427t-93b6398ac7d5c9878efc4f7d9f48fe6e0cb3b187d436b2c4cb11ed9e1012406b3</citedby><cites>FETCH-LOGICAL-c427t-93b6398ac7d5c9878efc4f7d9f48fe6e0cb3b187d436b2c4cb11ed9e1012406b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2492292455/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2492292455?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,4024,24150,25753,27923,27924,27925,37012,44590,75126</link.rule.ids></links><search><creatorcontrib>Matei, Gilvani</creatorcontrib><creatorcontrib>Benin, Giovani</creatorcontrib><creatorcontrib>Storck, Lindolfo</creatorcontrib><creatorcontrib>Milioli, Anderson Simionato</creatorcontrib><creatorcontrib>Bozi, Antonio Henrique</creatorcontrib><creatorcontrib>Dalló, Samuel Cristian</creatorcontrib><creatorcontrib>Lucion, Ricardo Antonio</creatorcontrib><creatorcontrib>Universidade Federal de Santa Maria (UFSM), Brazil</creatorcontrib><creatorcontrib>Universidade Tecnológica Federal do Paraná (UTFPR), Brazil</creatorcontrib><title>Methods of analysis and number of replicates for trials with large numbers of soybean genotypes</title><title>Ciência rural</title><addtitle>Cienc. Rural</addtitle><description>The aim of this study was to evaluate the experimental precision of different methods of statistical analysis for trials with large numbers of soybean genotypes, and their relationship with the number of replicates. Soybean yield data (nine trials; 324 genotypes; 46 cultivars; 278 lines; agricultural harvest of 2014/15) were used. Two of these trials were performed at the same location, side by side, forming a trial with six replicates. Each trial was analyzed by the randomized complete block, triple lattice design, and use of the Papadakis method. The selective accuracy, least significant difference, and Fasoulas differentiation index were estimated, and model assumptions were tested. The resampling method was used to study the influence of the number of replicates, by varying the number of blocks and estimating the precision measurements. The experimental precision indicators of the Papadakis method are more favorable as compared to the randomized complete block design and triple lattice. To obtain selective accuracy above the high experimental precision range in trials with 324 soybean genotypes, two repetitions can be used, and data can be analyzed using the randomized complete block design or Papadakis method.
RESUMO: O objetivo deste estudo foi avaliar a precisão experimental de diferentes métodos de análise estatística para ensaios com grande número de genótipos de soja e sua relação com o número de repetições. Foram usados dados de produtividade de grãos de soja (nove ensaios, 324 genótipos, 46 cultivares, 278 linhagens, safra agrícola de 2014/15). Dois destes ensaios foram realizados no mesmo local, lado a lado, constituindo um ensaio com seis repetições. Cada ensaio foi analisado pelos delineamentos de blocos ao acaso, látice triplo e uso do método de Papadakis. Foram estimados a acurácia seletiva, diferença mínima significativa e índice de diferenciação de Fasoulas, e, ainda foram testados os pressupostos do modelo. O método de reamostragem foi usado para estudar a influência do número de repetições, variando o número de blocos e estimando as medidas de precisão. Os indicadores de precisão experimental do método de Papadakis são mais favoráveis, quando comparados com os delineamentos de blocos ao acaso e látice triplo. Para obter acurácia seletiva acima da faixa de alta precisão experimental em ensaios com 324 genótipos de soja, pode-se usar duas repetições e analisar os dados, usando o delineamento de blocos completos ao acaso ou método de Papadakis.</description><subject>Accuracy</subject><subject>acurácia seletiva</subject><subject>AGRONOMY</subject><subject>Crop yield</subject><subject>Cultivars</subject><subject>delineamento experimental</subject><subject>Efficiency</subject><subject>Genotype & phenotype</subject><subject>Genotypes</subject><subject>Glycine max</subject><subject>Lattice design</subject><subject>Methods</subject><subject>Model testing</subject><subject>precisão experimental</subject><subject>reamostragem</subject><subject>Resampling</subject><subject>Software</subject><subject>Soybeans</subject><subject>Spatial analysis</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><issn>0103-8478</issn><issn>1678-4596</issn><issn>0103-8478</issn><issn>1678-4596</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpNkUtPwzAQhCMEEqXwC7hE4tyyfiSxj6jiUamIA3C2bGfdpkrjYqdC-fckbdVy2tVoZrT6NknuCUxJJuERCLCJ4IWwgQLJIafyIhmd1Mt_-3VyE-MagBaM81Gi3rFd-TKm3qW60XUXq9gvZdrsNgbDIAfc1pXVLcbU-ZC2odJ1TH-rdpXWOizxaN1XRN8Z1E26xMa33RbjbXLlejveHec4-X55_pq9TRYfr_PZ02JiOS3aiWQmZ1JoW5SZlaIQ6Cx3RSkdFw5zBGuYIaIoOcsNtdwaQrCUSIBQDrlh42R-6C29XqttqDY6dMrrSu0FH5ZKh7ayNSqbQc6MkWhAc5o7Y4TjxGojBNVEsL5reuiKtsLaq7XfhR5NVJ8DRTVQ7CkXAMB7jkD7wMMhsA3-Z4exPUcol5RKyrOsd7GDywYfY0B3OpOAGt6oTvXnN7I_nTuOfQ</recordid><startdate>2017</startdate><enddate>2017</enddate><creator>Matei, Gilvani</creator><creator>Benin, Giovani</creator><creator>Storck, Lindolfo</creator><creator>Milioli, Anderson Simionato</creator><creator>Bozi, Antonio Henrique</creator><creator>Dalló, Samuel Cristian</creator><creator>Lucion, Ricardo Antonio</creator><general>Universidade Federal de Santa Maria Centro de Ciencias Rurais</general><general>Universidade Federal de Santa Maria</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X2</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>M0K</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>GPN</scope><scope>DOA</scope></search><sort><creationdate>2017</creationdate><title>Methods of analysis and number of replicates for trials with large numbers of soybean genotypes</title><author>Matei, Gilvani ; Benin, Giovani ; Storck, Lindolfo ; Milioli, Anderson Simionato ; Bozi, Antonio Henrique ; Dalló, Samuel Cristian ; Lucion, Ricardo Antonio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c427t-93b6398ac7d5c9878efc4f7d9f48fe6e0cb3b187d436b2c4cb11ed9e1012406b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Accuracy</topic><topic>acurácia seletiva</topic><topic>AGRONOMY</topic><topic>Crop yield</topic><topic>Cultivars</topic><topic>delineamento experimental</topic><topic>Efficiency</topic><topic>Genotype & phenotype</topic><topic>Genotypes</topic><topic>Glycine max</topic><topic>Lattice design</topic><topic>Methods</topic><topic>Model testing</topic><topic>precisão experimental</topic><topic>reamostragem</topic><topic>Resampling</topic><topic>Software</topic><topic>Soybeans</topic><topic>Spatial analysis</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Matei, Gilvani</creatorcontrib><creatorcontrib>Benin, Giovani</creatorcontrib><creatorcontrib>Storck, Lindolfo</creatorcontrib><creatorcontrib>Milioli, Anderson Simionato</creatorcontrib><creatorcontrib>Bozi, Antonio Henrique</creatorcontrib><creatorcontrib>Dalló, Samuel Cristian</creatorcontrib><creatorcontrib>Lucion, Ricardo Antonio</creatorcontrib><creatorcontrib>Universidade Federal de Santa Maria (UFSM), Brazil</creatorcontrib><creatorcontrib>Universidade Tecnológica Federal do Paraná (UTFPR), Brazil</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Agricultural Science Collection</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)</collection><collection>ProQuest Central</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>SciTech Premium Collection</collection><collection>Agriculture Science Database</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>SciELO</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Ciência rural</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Matei, Gilvani</au><au>Benin, Giovani</au><au>Storck, Lindolfo</au><au>Milioli, Anderson Simionato</au><au>Bozi, Antonio Henrique</au><au>Dalló, Samuel Cristian</au><au>Lucion, Ricardo Antonio</au><aucorp>Universidade Federal de Santa Maria (UFSM), Brazil</aucorp><aucorp>Universidade Tecnológica Federal do Paraná (UTFPR), Brazil</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Methods of analysis and number of replicates for trials with large numbers of soybean genotypes</atitle><jtitle>Ciência rural</jtitle><addtitle>Cienc. Rural</addtitle><date>2017</date><risdate>2017</risdate><volume>47</volume><issue>4</issue><issn>0103-8478</issn><issn>1678-4596</issn><eissn>0103-8478</eissn><eissn>1678-4596</eissn><abstract>The aim of this study was to evaluate the experimental precision of different methods of statistical analysis for trials with large numbers of soybean genotypes, and their relationship with the number of replicates. Soybean yield data (nine trials; 324 genotypes; 46 cultivars; 278 lines; agricultural harvest of 2014/15) were used. Two of these trials were performed at the same location, side by side, forming a trial with six replicates. Each trial was analyzed by the randomized complete block, triple lattice design, and use of the Papadakis method. The selective accuracy, least significant difference, and Fasoulas differentiation index were estimated, and model assumptions were tested. The resampling method was used to study the influence of the number of replicates, by varying the number of blocks and estimating the precision measurements. The experimental precision indicators of the Papadakis method are more favorable as compared to the randomized complete block design and triple lattice. To obtain selective accuracy above the high experimental precision range in trials with 324 soybean genotypes, two repetitions can be used, and data can be analyzed using the randomized complete block design or Papadakis method.
RESUMO: O objetivo deste estudo foi avaliar a precisão experimental de diferentes métodos de análise estatística para ensaios com grande número de genótipos de soja e sua relação com o número de repetições. Foram usados dados de produtividade de grãos de soja (nove ensaios, 324 genótipos, 46 cultivares, 278 linhagens, safra agrícola de 2014/15). Dois destes ensaios foram realizados no mesmo local, lado a lado, constituindo um ensaio com seis repetições. Cada ensaio foi analisado pelos delineamentos de blocos ao acaso, látice triplo e uso do método de Papadakis. Foram estimados a acurácia seletiva, diferença mínima significativa e índice de diferenciação de Fasoulas, e, ainda foram testados os pressupostos do modelo. O método de reamostragem foi usado para estudar a influência do número de repetições, variando o número de blocos e estimando as medidas de precisão. Os indicadores de precisão experimental do método de Papadakis são mais favoráveis, quando comparados com os delineamentos de blocos ao acaso e látice triplo. Para obter acurácia seletiva acima da faixa de alta precisão experimental em ensaios com 324 genótipos de soja, pode-se usar duas repetições e analisar os dados, usando o delineamento de blocos completos ao acaso ou método de Papadakis.</abstract><cop>Santa Maria</cop><pub>Universidade Federal de Santa Maria Centro de Ciencias Rurais</pub><doi>10.1590/0103-8478cr20160629</doi><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy acurácia seletiva AGRONOMY Crop yield Cultivars delineamento experimental Efficiency Genotype & phenotype Genotypes Glycine max Lattice design Methods Model testing precisão experimental reamostragem Resampling Software Soybeans Spatial analysis Statistical analysis Statistical methods |
title | Methods of analysis and number of replicates for trials with large numbers of soybean genotypes |
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