U.S. flagAn official website of the United States government
                    Here's how you know **Official websites use .gov**
                            
                            A **.gov** website belongs to an official government organization in the United States.
 **Secure .gov websites use HTTPS**
                            
                            A **lock** (                            
                              A locked padlock                                                      
                            
                            ) or **https://** means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.


Menu Agricultural Research Service
						
                    U.S. DEPARTMENT OF AGRICULTURE
 Genetics and Sustainable Agriculture Research: Mississippi State, MS
 close



    Research

                    Research Projects
                                    Publications
                                    Collaborations
                                    News
                                    Software
                People

                    Staff Listing
                                    CareersSearch small
                    Search
            
            ARS Home
                                About ARS
                                Contact Us




ARS Home Southeast Area Mississippi State, Mississippi Crop Science Research Laboratory Genetics and Sustainable Agriculture Research Research Publications at this Location





- ARS National Programs
- Search for a scientific manuscript
- Search for a research project
- ARS Software
- Programs and Projects
- Collaborations
- Subjects of Investigation
- Publications

Title:   Author  item
                                            WU, JIXIANG - MISSISSIPPI STATE UNIVitem
                                            WU, DONGFENG - MISSISSIPPI STATE UNIVitem
                                            Jenkins, Johnieitem
                                            McCarty, Jack
  Submitted to: Computational Statistics and Data Analysis
                                    Publication Type: Peer Reviewed Journal
                                    Publication Acceptance Date: 8/12/2005
                                    Publication  Date: 1/1/2006
                                    Citation: Wu, J., Wu, D., Jenkins, J.N., McCarty Jr., J.C. 2006. A recursive approach to detect multivariable conditional variance components and conditional random effects. Computational Statistics and Data Analysis. 50:285-300.Interpretive Summary: Complex traits in plants and animals are determined by several component traits.  Multivariable conditional analysis in a general mixed linear model is helpful in dissecting the gene expression for the complex trait that result from different effects such as environment, genotype, and genotype x environment interaction.  We present a recursive approach for constructing a new random variable that can be used to analyze multivariable conditional components and conditional effects.  We used end of season plant maps of cotton to illustrate the use of the new analysis.  The model determined the contribution of boll size, boll number, and lint percent individually, and in various combinations, to lint yield.  The computer program to run the new model can be downloaded at our website http://msa.ars.usda.gov/ms/msstate/jenkins.htm.  Results from this model should provide a better understanding of gene expression for complex traits.  It can be applied to data from either plant or animal genetics.
                                Technical Abstract: A complex trait like crop yield is determined by its several component traits. Multivariable conditional analysis in a general mixed linear model is helpful in dissecting the gene expression for the complex trait from different effects, such as environment, genotype, and genotype  environment interaction. In this paper, a recursive approach is presented for constructing a new random vector that can be equivalently used to analyze multivariable conditional variance components and conditional effects. End of season plant mapping data including lint yield and three yield components for nine cultivars of upland cotton (Gossypium hirsutum L.) were used to detect the conditional variance components and conditional effects using this new approach. This approach can help identify genotypes to be used in selection studies.


Return to top


Connect with ARS Sign up


ARS Home
                            USDA.gov
                            Plain Writing
                            Policies & Links
                            Civil Rights Statements
                            FOIA
                            Accessibility Statement
                            Privacy Policy
                            Non-Discrimination Statement
                            Quality of Information
                            USA.gov
                            WhiteHouse.gov