A comparison between Joint Regression Analysis and the Additive Main and Multiplicative Interaction model: the robustness with increasing amounts of missing data

This paper joins the main properties of joint regression analysis (JRA), a model based on the Finlay-Wilkinson regression to analyse multi-environment trials, and of the additive main effects and multiplicative interaction (AMMI) model. The study compares JRA and AMMI with particular focus on robust...

Full description

Saved in:
Bibliographic Details
Published in:Scientia agricola 2011-12, Vol.68 (6), p.679-686
Main Authors: Rodrigues, Paulo Canas, Pereira, Dulce Gamito Santinhos, Mexia, João Tiago
Format: Article
Language:English
Subjects:
AGRICULTURE, MULTIDISCIPLINARY
AMMI models
durum wheat
genotype by environment interaction
joint regression analysis
missing values
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c411t-560909c98a7495380c82e389a173b532fd3b90e7d56b30e1e816add904a4c6b53
cites cdi_FETCH-LOGICAL-c411t-560909c98a7495380c82e389a173b532fd3b90e7d56b30e1e816add904a4c6b53
container_end_page 686
container_issue 6
container_start_page 679
container_title Scientia agricola
container_volume 68
creator Rodrigues, Paulo Canas
Pereira, Dulce Gamito Santinhos
Mexia, João Tiago
description This paper joins the main properties of joint regression analysis (JRA), a model based on the Finlay-Wilkinson regression to analyse multi-environment trials, and of the additive main effects and multiplicative interaction (AMMI) model. The study compares JRA and AMMI with particular focus on robustness with increasing amounts of randomly selected missing data. The application is made using a data set from a breeding program of durum wheat (Triticum turgidum L., Durum Group) conducted in Portugal. The results of the two models result in similar dominant cultivars (JRA) and winner of mega-environments (AMMI) for the same environments. However, JRA had more stable results with the increase in the incidence rates of missing values.
doi_str_mv 10.1590/S0103-90162011000600012
format article
fullrecord <record><control><sourceid>scielo_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_94728f73d9534b61aa7794a674d449e6</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><scielo_id>S0103_90162011000600012</scielo_id><doaj_id>oai_doaj_org_article_94728f73d9534b61aa7794a674d449e6</doaj_id><sourcerecordid>S0103_90162011000600012</sourcerecordid><originalsourceid>FETCH-LOGICAL-c411t-560909c98a7495380c82e389a173b532fd3b90e7d56b30e1e816add904a4c6b53</originalsourceid><addsrcrecordid>eNp1kdFq3DAQRU1poGnab6h-YNORLUtW35bQNhsSCm36LMbSeKPFlhZJ25DPyZ_G8ZZQKHkQI-7MuSN0q-oTh3Peavj8Czg0Kw1c1sA5AMj58PpNdfrSePvP_V31PucdQK05yNPqcc1snPaYfI6B9VTuiQK7ij4U9pO2iXL2c2MdcHzIPjMMjpU7YmvnfPF_iN2gD4t6cxiL34_e4qJvQqGEtjzTU3Q0flm4FPtDLmG2Zfe-3DEfbCLMPmwZTvEQSmZxYJPPi-Sw4IfqZMAx08e_9az6_e3r7cXl6vrH983F-nplBedl1UrQoK3uUAndNh3Yrqam08hV07dNPbim10DKtbJvgDh1XKJzGgQKK-eJs2pz9HURd2af_ITpwUT0ZhFi2hpMxduRjBaq7gbVuHmR6CVHVEoLlEo4ITTJ2ev86JWtpzGaXTyk-QezWcIy_4U1A-oI2BRzTjS8PICDeY75VfIJpC-Z8w</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>A comparison between Joint Regression Analysis and the Additive Main and Multiplicative Interaction model: the robustness with increasing amounts of missing data</title><source>SciELO Brazil</source><creator>Rodrigues, Paulo Canas ; Pereira, Dulce Gamito Santinhos ; Mexia, João Tiago</creator><creatorcontrib>Rodrigues, Paulo Canas ; Pereira, Dulce Gamito Santinhos ; Mexia, João Tiago</creatorcontrib><description>This paper joins the main properties of joint regression analysis (JRA), a model based on the Finlay-Wilkinson regression to analyse multi-environment trials, and of the additive main effects and multiplicative interaction (AMMI) model. The study compares JRA and AMMI with particular focus on robustness with increasing amounts of randomly selected missing data. The application is made using a data set from a breeding program of durum wheat (Triticum turgidum L., Durum Group) conducted in Portugal. The results of the two models result in similar dominant cultivars (JRA) and winner of mega-environments (AMMI) for the same environments. However, JRA had more stable results with the increase in the incidence rates of missing values.</description><identifier>ISSN: 0103-9016</identifier><identifier>ISSN: 1678-992X</identifier><identifier>EISSN: 0103-9016</identifier><identifier>EISSN: 1678-992X</identifier><identifier>DOI: 10.1590/S0103-90162011000600012</identifier><language>eng</language><publisher>São Paulo - Escola Superior de Agricultura "Luiz de Queiroz"</publisher><subject>AGRICULTURE, MULTIDISCIPLINARY ; AMMI models ; durum wheat ; genotype by environment interaction ; joint regression analysis ; missing values</subject><ispartof>Scientia agricola, 2011-12, Vol.68 (6), p.679-686</ispartof><rights>This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c411t-560909c98a7495380c82e389a173b532fd3b90e7d56b30e1e816add904a4c6b53</citedby><cites>FETCH-LOGICAL-c411t-560909c98a7495380c82e389a173b532fd3b90e7d56b30e1e816add904a4c6b53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,24129,27901,27902</link.rule.ids></links><search><creatorcontrib>Rodrigues, Paulo Canas</creatorcontrib><creatorcontrib>Pereira, Dulce Gamito Santinhos</creatorcontrib><creatorcontrib>Mexia, João Tiago</creatorcontrib><title>A comparison between Joint Regression Analysis and the Additive Main and Multiplicative Interaction model: the robustness with increasing amounts of missing data</title><title>Scientia agricola</title><addtitle>Sci. agric. (Piracicaba, Braz.)</addtitle><description>This paper joins the main properties of joint regression analysis (JRA), a model based on the Finlay-Wilkinson regression to analyse multi-environment trials, and of the additive main effects and multiplicative interaction (AMMI) model. The study compares JRA and AMMI with particular focus on robustness with increasing amounts of randomly selected missing data. The application is made using a data set from a breeding program of durum wheat (Triticum turgidum L., Durum Group) conducted in Portugal. The results of the two models result in similar dominant cultivars (JRA) and winner of mega-environments (AMMI) for the same environments. However, JRA had more stable results with the increase in the incidence rates of missing values.</description><subject>AGRICULTURE, MULTIDISCIPLINARY</subject><subject>AMMI models</subject><subject>durum wheat</subject><subject>genotype by environment interaction</subject><subject>joint regression analysis</subject><subject>missing values</subject><issn>0103-9016</issn><issn>1678-992X</issn><issn>0103-9016</issn><issn>1678-992X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNp1kdFq3DAQRU1poGnab6h-YNORLUtW35bQNhsSCm36LMbSeKPFlhZJ25DPyZ_G8ZZQKHkQI-7MuSN0q-oTh3Peavj8Czg0Kw1c1sA5AMj58PpNdfrSePvP_V31PucdQK05yNPqcc1snPaYfI6B9VTuiQK7ij4U9pO2iXL2c2MdcHzIPjMMjpU7YmvnfPF_iN2gD4t6cxiL34_e4qJvQqGEtjzTU3Q0flm4FPtDLmG2Zfe-3DEfbCLMPmwZTvEQSmZxYJPPi-Sw4IfqZMAx08e_9az6_e3r7cXl6vrH983F-nplBedl1UrQoK3uUAndNh3Yrqam08hV07dNPbim10DKtbJvgDh1XKJzGgQKK-eJs2pz9HURd2af_ITpwUT0ZhFi2hpMxduRjBaq7gbVuHmR6CVHVEoLlEo4ITTJ2ev86JWtpzGaXTyk-QezWcIy_4U1A-oI2BRzTjS8PICDeY75VfIJpC-Z8w</recordid><startdate>20111201</startdate><enddate>20111201</enddate><creator>Rodrigues, Paulo Canas</creator><creator>Pereira, Dulce Gamito Santinhos</creator><creator>Mexia, João Tiago</creator><general>São Paulo - Escola Superior de Agricultura "Luiz de Queiroz"</general><general>Universidade de São Paulo</general><scope>AAYXX</scope><scope>CITATION</scope><scope>GPN</scope><scope>DOA</scope></search><sort><creationdate>20111201</creationdate><title>A comparison between Joint Regression Analysis and the Additive Main and Multiplicative Interaction model: the robustness with increasing amounts of missing data</title><author>Rodrigues, Paulo Canas ; Pereira, Dulce Gamito Santinhos ; Mexia, João Tiago</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c411t-560909c98a7495380c82e389a173b532fd3b90e7d56b30e1e816add904a4c6b53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>AGRICULTURE, MULTIDISCIPLINARY</topic><topic>AMMI models</topic><topic>durum wheat</topic><topic>genotype by environment interaction</topic><topic>joint regression analysis</topic><topic>missing values</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rodrigues, Paulo Canas</creatorcontrib><creatorcontrib>Pereira, Dulce Gamito Santinhos</creatorcontrib><creatorcontrib>Mexia, João Tiago</creatorcontrib><collection>CrossRef</collection><collection>SciELO</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Scientia agricola</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rodrigues, Paulo Canas</au><au>Pereira, Dulce Gamito Santinhos</au><au>Mexia, João Tiago</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A comparison between Joint Regression Analysis and the Additive Main and Multiplicative Interaction model: the robustness with increasing amounts of missing data</atitle><jtitle>Scientia agricola</jtitle><addtitle>Sci. agric. (Piracicaba, Braz.)</addtitle><date>2011-12-01</date><risdate>2011</risdate><volume>68</volume><issue>6</issue><spage>679</spage><epage>686</epage><pages>679-686</pages><issn>0103-9016</issn><issn>1678-992X</issn><eissn>0103-9016</eissn><eissn>1678-992X</eissn><abstract>This paper joins the main properties of joint regression analysis (JRA), a model based on the Finlay-Wilkinson regression to analyse multi-environment trials, and of the additive main effects and multiplicative interaction (AMMI) model. The study compares JRA and AMMI with particular focus on robustness with increasing amounts of randomly selected missing data. The application is made using a data set from a breeding program of durum wheat (Triticum turgidum L., Durum Group) conducted in Portugal. The results of the two models result in similar dominant cultivars (JRA) and winner of mega-environments (AMMI) for the same environments. However, JRA had more stable results with the increase in the incidence rates of missing values.</abstract><pub>São Paulo - Escola Superior de Agricultura "Luiz de Queiroz"</pub><doi>10.1590/S0103-90162011000600012</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0103-9016
ispartof Scientia agricola, 2011-12, Vol.68 (6), p.679-686
issn 0103-9016
1678-992X
0103-9016
1678-992X
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_94728f73d9534b61aa7794a674d449e6
source SciELO Brazil
subjects AGRICULTURE, MULTIDISCIPLINARY
AMMI models
durum wheat
genotype by environment interaction
joint regression analysis
missing values
title A comparison between Joint Regression Analysis and the Additive Main and Multiplicative Interaction model: the robustness with increasing amounts of missing data
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-12T18%3A29%3A24IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-scielo_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20comparison%20between%20Joint%20Regression%20Analysis%20and%20the%20Additive%20Main%20and%20Multiplicative%20Interaction%20model:%20the%20robustness%20with%20increasing%20amounts%20of%20missing%20data&rft.jtitle=Scientia%20agricola&rft.au=Rodrigues,%20Paulo%20Canas&rft.date=2011-12-01&rft.volume=68&rft.issue=6&rft.spage=679&rft.epage=686&rft.pages=679-686&rft.issn=0103-9016&rft.eissn=0103-9016&rft_id=info:doi/10.1590/S0103-90162011000600012&rft_dat=%3Cscielo_doaj_%3ES0103_90162011000600012%3C/scielo_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c411t-560909c98a7495380c82e389a173b532fd3b90e7d56b30e1e816add904a4c6b53%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_scielo_id=S0103_90162011000600012&rfr_iscdi=true