A Simple Protocol for AMMI Analysis of Yield Trials

被引:287
作者
Gauch, Hugh G., Jr. [1 ]
机构
[1] Cornell Univ, Ithaca, NY 14853 USA
关键词
LINEAR UNBIASED PREDICTION; STATISTICAL-ANALYSIS; LOCATION INTERACTION; MODEL SELECTION; VALIDATION; VARIETY; WHEAT; GGE;
D O I
10.2135/cropsci2013.04.0241
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
The Additive Main effects and Multiplicative Interaction (AMMI) model has been used extensively for analysis of multi-environment yield trials for two main purposes: understanding complex genotype x environment interactions and increasing accuracy. Nevertheless, AMMI analyses implementing best practices have been rare. Accordingly, this paper presents a simple protocol with four steps: (i) analysis of variance, (ii) model diagnosis, (iii) mega-environment delineation, and (iv) agricultural recommendations. This protocol is illustrated with an international bread wheat trial. This paper concerns a basic and common application of AMMI: yield-trial analysis without consideration of special structure or additional data for either genotypes or environments. Best practices involve using both treatment and experimental designs to gain accuracy and exploiting both broad and narrow adaptations to increase yields.
引用
收藏
页码:1860 / 1869
页数:10
相关论文
共 25 条
[1]   Repeatable genotype X location interaction and its exploitation by conventional and GIS-based cultivar recommendation for durum wheat in Algeria [J].
Annicchiarico, P ;
Bellah, F ;
Chiari, T .
EUROPEAN JOURNAL OF AGRONOMY, 2006, 24 (01) :70-81
[2]   Additive main effects and multiplicative interaction (AMMI) analysis of genotype-location interaction in variety trials repeated over years [J].
Annicchiarico, P .
THEORETICAL AND APPLIED GENETICS, 1997, 94 (08) :1072-1077
[3]  
Annicchiarico P., 2002, Genotype * environment interaction: challenges and opportunities for plant breeding and cultivar recommendations: FAO Plant Production and Protection Paper
[4]  
[Anonymous], 2007, MATMODEL VERSION 3 0
[5]   Cross-validation of component models: A critical look at current methods [J].
Bro, R. ;
Kjeldahl, K. ;
Smilde, A. K. ;
Kiers, H. A. L. .
ANALYTICAL AND BIOANALYTICAL CHEMISTRY, 2008, 390 (05) :1241-1251
[6]   AMMI ADJUSTMENT FOR STATISTICAL-ANALYSIS OF AN INTERNATIONAL WHEAT YIELD TRIAL [J].
CROSSA, J ;
FOX, PN ;
PFEIFFER, WH ;
RAJARAM, S ;
GAUCH, HG .
THEORETICAL AND APPLIED GENETICS, 1991, 81 (01) :27-37
[7]   Direct Validation of AMMI Predictions in Turfgrass Trials [J].
Ebdon, J. S. ;
Gauch, H. G., Jr. .
CROP SCIENCE, 2011, 51 (02) :862-869
[8]   ANALYSIS OF ADAPTATION IN A PLANT-BREEDING PROGRAMME [J].
FINLAY, KW ;
WILKINSON, GN .
AUSTRALIAN JOURNAL OF AGRICULTURAL RESEARCH, 1963, 14 (06) :742-&
[9]   MODEL SELECTION AND VALIDATION FOR YIELD TRIALS WITH INTERACTION [J].
GAUCH, HG .
BIOMETRICS, 1988, 44 (03) :705-715
[10]   Optimal replication in selection experiments [J].
Gauch, HG ;
Zobel, RW .
CROP SCIENCE, 1996, 36 (04) :838-843