| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
Programa de Estadística del Instituto de Socioeconomía, Estadística e Informáitica (ISEI), Colegio de Postgraduados, CP 56230, Montecillo, Mexico, and International Maize ad Wheat Improvement Center (CIMMYT), Lisboa 27, Apdo. Postal 6-641, 06600 Mexico, D.F., Mexico;
Biometrics and Statistics Unit, CIMMY, Lisboa 27, Apdo. Postal 6-641, 06600 Mexico, D.F., Mexico;
Dep. of Agricultural, Environmental and Systems Technology, Wageningen Agricultural Univ., Dreijenlaan 4, 6703 HA Wageningen, the Netherlands;
Programa de Estadística del Instituto de Socioeconomía, Estadistica e Informática (ISEI), Colegio de Postgraduados, CP 56230, Montecillo, Mexico;
Wheat Program, CIMMYT, Lisboa 27, Apdo. Postal 6-641, 06600 Mexico, D.F., Mexico.
* Corresponding author (JCROSSA{at}CIMMYT.MX).
Partial least squares (PLS) and factorial regression (FR) are statistical models that incorporate external environmental and/or cultivar variables for studying and interpreting genotype x environment interaction (GEl). The Additive Main effect and Multiplicative Interaction (AMMI) model uses only the phenotypic response variable of interest; however, if information on external environmental (or genotypic) variables is available, this can be regressed on the environmental (or genotypic) scores estimated from AMMI and superimposed on the AMMI biplot. The objectives of this study with two wheat [Triticum turgidum (L.) var. durum] field trials were (i) to compare the results of PLS, FR, and AMMI on the basis of external environmental (and cultivar) variables, (ii) to examine whether procedures based PLS, FR, and AMMI identify the same or a different subset of cultivar and/or environmental covariables that influence GEI for grain yield, and (iii) to find multiple FR models that include environmental and cultivar covariables and their cross products that explain a large proportion of GEI with relatively few degrees of freedom. Results for the first trial showed that AMMI, PLS, and FR identified similar cultivar and environmental variables that explained a large proportion of the cultivar x year interaction. Results for the second wheat trial showed good correspondence between PLS and FR for 23 environmental covariables. For both trials, PLS and FR complement each other and the AMMI and PLS biplots offered similar interpretations of the GEl. The FR analysis can be used to confirm these results and to obtain even more parsimonious descriptions of the GEL
Received for publication July 2, 1998.
This article has been cited by other articles:
|
|
 |
|
  J. Rane, R. K. Pannu, V. S. Sohu, R. S. Saini, B. Mishra, J. Shoran, J. Crossa, M. Vargas, and A. K. Joshi Performance of Yield and Stability of Advanced Wheat Genotypes under Heat Stress Environments of the Indo-Gangetic Plains Crop Sci., July 30, 2007; 47(4): 1561 - 1573. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
P. Dhungana, K. M. Eskridge, P. S. Baenziger, B. T. Campbell, K. S. Gill, and I. Dweikat Analysis of Genotype-by-Environment Interaction in Wheat Using a Structural Equation Model and Chromosome Substitution Lines Crop Sci., March 1, 2007; 47(2): 477 - 484. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
W. Yan and N. A. Tinker An Integrated Biplot Analysis System for Displaying, Interpreting, and Exploring Genotype x Environment Interaction Crop Sci., May 6, 2005; 45(3): 1004 - 1016. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
B. T. Campbell, P. S. Baenziger, K. M. Eskridge, H. Budak, N. A. Streck, A. Weiss, K. S. Gill, and M. Erayman Using Environmental Covariates to Explain Genotype x Environment and QTL x Environment Interactions for Agronomic Traits on Chromosome 3A of Wheat Crop Sci., March 1, 2004; 44(2): 620 - 627. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Brancourt-Hulmel and C. Lecomte Effect of Environmental Variates on Genotype x Environment Interaction of Winter Wheat: A Comparison of Biadditive Factorial Regression to AMMI Crop Sci., March 1, 2003; 43(2): 608 - 617. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. S. Ebdon and H. G. Gauch Jr. Additive Main Effect and Multiplicative Interaction Analysis of National Turfgrass Performance Trials: I. Interpretation of Genotype x Environment Interaction Crop Sci., March 1, 2002; 42(2): 489 - 496. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. Vargas, J. Crossa, F. van Eeuwijk, K. D. Sayre, and M. P. Reynolds Interpreting Treatment Environment Interaction in Agronomy Trials Agron. J., July 1, 2001; 93(4): 949 - 960. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C.E.-L. Signor, S. Dousse, J. Lorgeou, J.-B. Denis, R. Bonhomme, P. Carolo, and A. Charcosset Interpretation of Genotype Environment Interactions for Early Maize Hybrids over 12 Years Crop Sci., May 1, 2001; 41(3): 663 - 669. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
W. Yan and L.A. Hunt Interpretation of Genotype Environment Interaction for Winter Wheat Yield in Ontario Crop Sci., January 1, 2001; 41(1): 19 - 25. [Abstract] [Full Text] [PDF]
|
|
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| The SCI Journals | Agronomy Journal | Vadose Zone Journal | |||
| Journal of Natural Resources and Life Sciences Education |
Soil Science Society of America Journal | ||||
| Journal of Plant Registrations | Journal of Environmental Quality |
The Plant Genome | |||
