Genotype-by-Trait Data Analysis and Decision-Making
This chapter discusses the analysis of genotype‐by‐trait (GT) two‐way tables. GT biplots can be generated for a single trial, across all trials, and across a group of homogeneous trials, that is within a mega‐environment. GT data analysis has three objectives: (i) to understand the relationships amo...
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description | This chapter discusses the analysis of genotype‐by‐trait (GT) two‐way tables. GT biplots can be generated for a single trial, across all trials, and across a group of homogeneous trials, that is within a mega‐environment. GT data analysis has three objectives: (i) to understand the relationships among traits; (ii) to understand the trait profiles of the genotypes; and (iii) to evaluate the genotypes based on multiple traits. The idea of index selection can also be used to formulate new crosses based on GT data to develop new hybrids or breeding populations. The Multi‐Trait Decision Maker module, which is illustrated in the chapter, allows specifying a level for each trait, in percentage of the selected check, for independent culling. The module also allows setting a weight for each trait, which can be used to calculate a selection index for each genotype. |
doi_str_mv | 10.1002/9781118688571.ch9 |
format | Book Chapter |
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GT biplots can be generated for a single trial, across all trials, and across a group of homogeneous trials, that is within a mega‐environment. GT data analysis has three objectives: (i) to understand the relationships among traits; (ii) to understand the trait profiles of the genotypes; and (iii) to evaluate the genotypes based on multiple traits. The idea of index selection can also be used to formulate new crosses based on GT data to develop new hybrids or breeding populations. The Multi‐Trait Decision Maker module, which is illustrated in the chapter, allows specifying a level for each trait, in percentage of the selected check, for independent culling. 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The module also allows setting a weight for each trait, which can be used to calculate a selection index for each genotype.</description><subject>AGRICULTURE & FARMING</subject><subject>BIOLOGY, LIFE SCIENCES</subject><subject>Crop husbandry</subject><subject>crop variety trials</subject><subject>cross trials</subject><subject>genotype‐by‐trait (GT) data analysis</subject><subject>mega‐environments</subject><subject>multiple traits</subject><subject>Multi‐Trait Decision Maker module</subject><subject>single trials</subject><isbn>1118688643</isbn><isbn>9781118688649</isbn><isbn>1118688554</isbn><isbn>9781118688557</isbn><isbn>1118688562</isbn><isbn>9781118688564</isbn><isbn>1118688570</isbn><isbn>9781118688571</isbn><fulltext>true</fulltext><rsrctype>book_chapter</rsrctype><creationdate>2014</creationdate><recordtype>book_chapter</recordtype><recordid>eNqN0M1OwzAMAOAgBGKMPQC3vkBGnP8cpw0G0hCXcY7SNGVlVVuaIlSefh0DJBAHDpEVy59lG6FLIFMghF4ZpQFAS62FgqnfmCN0_pUQ_Pj7Izk7RSMtDZFSUn2GJjE-E0IAGBihRogtQ1V3fRNw2uN164ouWbjOJbPKlX0sYuKqLFkEX8SirvC92xbV0wU6yV0Zw-QzjtHjzfV6fotXD8u7-WyFGyp4jjPtaeq9B8NSqXnqcyJ5YLkaJuRBGeGM98JTShnNMp4ZT7k0Qac-MGE4Y2OED33fijL0NqR1vY32x-r2vWjssL5tsnyohz_qgdj9yX65vRneYNjBNG398hpid2A-VF3rSr9xTRfaaDlhSgptJbEUxKD4fxRIQfQHkRYUYzvGDH8-</recordid><startdate>2014</startdate><enddate>2014</enddate><creator>Yan, Weikai</creator><general>John Wiley & Sons, Incorporated</general><general>Wiley</general><general>John Wiley & Sons, Inc</general><scope>FFUUA</scope></search><sort><creationdate>2014</creationdate><title>Genotype-by-Trait Data Analysis and Decision-Making</title><author>Yan, Weikai</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p254f-d8c2bccc193b684bcf064e3f75544e795a9cc5c22232dd4d9c2469e8bce359433</frbrgroupid><rsrctype>book_chapters</rsrctype><prefilter>book_chapters</prefilter><language>eng</language><creationdate>2014</creationdate><topic>AGRICULTURE & FARMING</topic><topic>BIOLOGY, LIFE SCIENCES</topic><topic>Crop husbandry</topic><topic>crop variety trials</topic><topic>cross trials</topic><topic>genotype‐by‐trait (GT) data analysis</topic><topic>mega‐environments</topic><topic>multiple traits</topic><topic>Multi‐Trait Decision Maker module</topic><topic>single trials</topic><toplevel>online_resources</toplevel><creatorcontrib>Yan, Weikai</creatorcontrib><collection>ProQuest Ebook Central - Book Chapters - Demo use only</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yan, Weikai</au><au>Yan, Weikai</au><format>book</format><genre>bookitem</genre><ristype>CHAP</ristype><atitle>Genotype-by-Trait Data Analysis and Decision-Making</atitle><btitle>Crop Variety Trials</btitle><date>2014</date><risdate>2014</risdate><spage>163</spage><epage>186</epage><pages>163-186</pages><isbn>1118688643</isbn><isbn>9781118688649</isbn><eisbn>1118688554</eisbn><eisbn>9781118688557</eisbn><eisbn>1118688562</eisbn><eisbn>9781118688564</eisbn><eisbn>1118688570</eisbn><eisbn>9781118688571</eisbn><abstract>This chapter discusses the analysis of genotype‐by‐trait (GT) two‐way tables. 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subjects | AGRICULTURE & FARMING BIOLOGY, LIFE SCIENCES Crop husbandry crop variety trials cross trials genotype‐by‐trait (GT) data analysis mega‐environments multiple traits Multi‐Trait Decision Maker module single trials |
title | Genotype-by-Trait Data Analysis and Decision-Making |
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