CROP SCIENCE, VOL. 54, JULY– AUGUST 2014 WWW.CROPS.ORG 1
RESEARCH
W
heat is grown under diferent environmental conditions,
especially with regard to water availability, soil, and weather
conditions. Genotype by environment interaction is a measure of
the diferentiated response of genotypes to the varied environmen-
tal conditions. The GEI is the main cause of variability in wheat
yield performance of diferent environments in Brazil.
Brazilian Spring Wheat Homogeneous
Adaptation Regions can be Dissected
in Major Megaenvironments
Lucas Berger Munaro, Giovani Benin,* Volmir Sérgio Marchioro, Francisco de Assis Franco,
Raphael Rossi Silva, Cristiano Lemes da Silva, and Eduardo Beche.
ABSTRACT
The objectives of this study were to investigate
the pattern of genotype environment interaction
and identify megaenvironments (ME), essential
test locations, and suitable genotypes for each
ME. The genotype plus genotype by environ-
ment interaction (GGE) biplot and additive main
effects and multiplicative interaction analysis
(AMMI) were used to demonstrate the potential
of using a graphical biplot to analyze the geno-
type by environment interaction (GEI) in data
of multienvironment trials (MET). These trials of
the Central Cooperative Agricultural Research
(COODETEC) evaluated 36 advanced breeding
lines and 27 check cultivars for 3 years (2008–
2010) at 12 test locations. Yield data were ana-
lyzed using the genotype plus GGE and AMMI
biplot methods. The test environments were
classiied into two ME (i.e. ME1: Castro, Gua-
rapuava, Não-Me-Toque, Abelardo Luz, and
Cachoeira do Sul; and ME2: Campo Mourão,
Dourados, Palmital, Palotina, Ponta Porã ,and
Rolândia. In ME1, the locations Guarapuava,
Cachoeira do Sul, and Abelardo Luz were clas-
siied as ideal, while in ME2, Ponta Porã, Dou-
rados and Palotina were close to ideal. Guar-
apuava was the essential test location in ME1;
however the identiication of an essential test
location in ME2 was unclear. Superior cultivars
and advanced lines were identiied in both ME
that could be valuable for spring wheat (Triticum
aestivum L.) improvement or cultivars released.
L.B. Munaro, G. Benin, R.R. Silva, C.L. da Silva, and E. Beche,
Universidade Tecnológica Federal do Paraná (UTFPR), PR 469, km 01,
85501-970, Pato Branco, PR, Brazil; V.S. Marchioro and F.A. Franco,
Cooperativa Central de Pesquisa Agropecuária (COODETEC), BR
467, km 98, 85813-450, Cascavel, PR, Brazil. Received 4 June 2013.
*Corresponding author (benin@utfpr.edu.br).
Abbreviations: ABL, Abelardo Luz; AEC, average environment
coordinate; AMMI, additive main efects and multiplicative inter-
action analysis; CDS, Cachoeira do Sul; CMR, Campo Mourão;
COODETEC, Central Cooperative Agricultural Research; CSC,
Cascavel; CST, Castro; DRD, Dourados; E, environment main efect;
G, genotype main efect; GEI, genotype by environment interaction;
GGE, genotype plus genotype by environment interaction; GVA,
Guarapuava; IPCA, interaction principal component axis; ME, megae-
nvironment; ME1, Megaenvironment 1 (Castro, Guarapuava, Não-Me-
Toque, Abelardo Luz, and Cachoeira do Sul); ME2, Megaenvironment
2 (Campo Mourão, Dourados, Palmital, Palotina, Ponta Porã ,and
Rolândia); MET, multi-environment trials; NMT, Não-Me-Toque;
PC, principal component; PMT, Palmital; PTN, Palotina; PTP, Ponta
Porã; RLD, Rolândia; SVP, singular value partitioning; VCU, value
for cultivation and use; VCU1, VCU region 1 (cold, humid, and high
elevation); VCU2, VCU Region 2 (moderately hot, humid, and low
elevation); VCU3, VCU Region 3 (hot, moderately dry, and low eleva-
tion); VCU4, VCU Region 4 (hot and dry).
Published in Crop Sci. 54:1–10 (2014).
doi: 10.2135/cropsci2013.06.0365
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Published June 6, 2014