GGE Biplot vs. AMMI Analysis of Genotype-by-Environment Data

The use of genotype main effect (G) plus genotype-by-environment (GE) interaction (G+GE) biplot analysis by plant breeders and other agricultural researchers has increased dramatically during the past 5 yr for analyzing multi-environment trial (MET) data. Recently, however, its legitimacy was questi...

Full description

Saved in:
Bibliographic Details
Published in:Crop science 2007-03, Vol.47 (2), p.643-653
Main Authors: Yan, W, Kang, M.S, Ma, B, Woods, S, Cornelius, P.L
Format: Article
Language:English
Subjects:
Agronomy. Soil science and plant productions
Biological and medical sciences
crops
cultivars
data analysis
environmental factors
Fundamental and applied biological sciences. Psychology
genetic variation
Genetics and breeding of economic plants
Genotype & phenotype
genotype-environment interaction
literature reviews
mathematical models
Matrix
plant breeding
Research methodology
statistical analysis
Statistical methods
Studies
variety trials
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!
Description
Summary:The use of genotype main effect (G) plus genotype-by-environment (GE) interaction (G+GE) biplot analysis by plant breeders and other agricultural researchers has increased dramatically during the past 5 yr for analyzing multi-environment trial (MET) data. Recently, however, its legitimacy was questioned by a proponent of Additive Main Effect and Multiplicative Interaction (AMMI) analysis. The objectives of this review are: (i) to compare GGE biplot analysis and AMMI analysis on three aspects of genotype-by-environment data (GED) analysis, namely mega-environment analysis, genotype evaluation, and test-environment evaluation; (ii) to discuss whether G and GE should be combined or separated in these three aspects of GED analysis; and (iii) to discuss the role and importance of model diagnosis in biplot analysis of GED. Our main conclusions are: (i) both GGE biplot analysis and AMMI analysis combine rather than separate G and GE in mega-environment analysis and genotype evaluation, (ii) the GGE biplot is superior to the AMMI1 graph in mega-environment analysis and genotype evaluation because it explains more G+GE and has the inner-product property of the biplot, (iii) the discriminating power vs. representativeness view of the GGE biplot is effective in evaluating test environments, which is not possible in AMMI analysis, and (iv) model diagnosis for each dataset is useful, but accuracy gain from model diagnosis should not be overstated.
ISSN:0011-183X
1435-0653
DOI:10.2135/cropsci2006.06.0374