An improved imputation method for incomplete G×E trial data for asparagus

M. A. Nichols, A. J R Godfrey*, G. R. Wood, C. G. Qiao, S. Ganesalingam

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

    1 Citation (Scopus)

    Abstract

    Improving the analysis of incomplete genotype × environment (G×E) information has the potential to improve the efficiency of breeding programmes. This is particularly relevant in large-scale international cultivar trials. A two-stage imputation method is proposed which uses results from a cluster analysis; it provides more accurate estimates of missing values under random removal of data from five complete data sets in the literature. These imputed values are superior to those obtained using other clustering based methods. The two stage method is also considered to be superior to model based imputation as it does not rely on model selection or model fitting constraints.

    Original languageEnglish
    Title of host publication10th International Asparagus Symposium
    Place of PublicationLeuven, Belgium
    PublisherInternational Society for Horticultural Science
    Pages111-116
    Number of pages6
    Volume589
    ISBN (Print)9789066057968
    DOIs
    Publication statusPublished - 2002
    Event10th International Asparagus Symposium - Niigata, Japan
    Duration: 30 Aug 20012 Sept 2001

    Publication series

    NameActa Horticulturae
    Volume589
    ISSN (Print)05677572

    Conference

    Conference10th International Asparagus Symposium
    Country/TerritoryJapan
    CityNiigata
    Period30/08/012/09/01

    Keywords

    • Cluster analysis
    • G X E interaction
    • Imputation
    • Incomplete data
    • Two-stage method

    Fingerprint

    Dive into the research topics of 'An improved imputation method for incomplete G×E trial data for asparagus'. Together they form a unique fingerprint.

    Cite this