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Askarinia P., Saeidi G., Rezaei A. (2008): Assessment of genotype × environment interaction in ten wheat cultivars with regression and path coefficient analysis. Electronic J. Crop Prod. , 1, 64
175 183 Annicchiarico, P. (2002): Genotype × environment interactions — Challenges and opportunities for plant breeding and cultivar recommendations. FAO Plant Production and Protection
Annicchiarico, P. (1997): Joint regression vs AMMI analysis of genotype-environment interactions for cereals in Italy. Euphytica , 94 , 53–62. Annicchiarico P. Joint regression vs
Nine bitter vetch selection lines were evaluated in three successive years to determine their yield and seed index (100-seed weight) stabilities, based on three parameters: phenotypic index (P), regression coefficient (bi), and least deviation from regression (S2 di). The line Sel. 2517 (L7) was identified as the most stable one for the growing seasons, while Sel. 2509 (L2) and Sel. 2511 (L4) were found to be stable for seed yield under favourable climatic conditions. For seed index Sel. 2515 (L6) was identified as the most stable line. Selection line 2513 (L5), which originated from Cyprus, had the highest degree of responsiveness to changing environments.
): Regression methods for studying genotype — environment interactions. Heredity , 28 , 209–222. Wood J. T. Regression methods for studying genotype — environment interactions
.J. , Pourdad , S.S. 2009 . Comparison of parametric and non-parametric methods for analyzing genotype × environment interactions in safflower ( Carthamus tinctorius L.) . J. Agric. Sci. 147 : 601 – 612
Terminal heat, which is referred as increase in temperature during grain filling, is one of the important stress factors for wheat production. Current estimates indicate that wheat crop grown on around 13.5mha in India is affected by heat stress. In order to meet the challenges of high temperature ahead of global warming, concerted efforts are needed to evaluate germplasm for heat tolerance and identify and develop genotypes suitable for such stressed environments. The advanced wheat genotypes developed for stress and normal environments by different research centers were evaluated across 7 locations representing varied agroclimatic zones during 2007–08 and 2008–09 to study their adaptability for heat stress and non-stress environments. The additive main effects and multiplicative interaction analysis for G × E interactions revealed differences amongst locations to phenology and grain yield. Genotype RAJ 4083 developed for cultivation under late sown conditions in peninsular zone was also found adaptable to timely sown conditions. Similarly, HD 2733 a cultivar of NEPZ timely sown conditions and PBW 574 an advanced breeding line of NWPZ late sown conditions was found adapted to Peninsular zone. The cultivar RAJ 3765 showed specific adaptability to Pantnagar in NWPZ. Genotype NW 3069 developed for NEPZ timely sown conditions have shown adaptability to number of locations; timely sown conditions at Karnal and Hisar in NWPZ and Niphad in PZ. Likewise, WH 1022 developed for NEPZ late sown conditions exhibited specific adaptability to all timely sown locations in NWPZ.
The genotype by environment (GE) interaction is a major problem in the study of quantitative traits because it complicates the interpretation of genetic experiments and makes predictions difficult. In order to quantify GE interaction effects on the grain yield of durum wheat and to determine stable genotypes, field experiments were conducted with ten genotypes for four consecutive years in two different conditions (irrigated and rainfed) in a completely randomized block design with three replications in each environment. Combined analysis of variance exhibited significant differences for the GE interaction, indicating the possibility of stable entries. The results of additive main effect and multiplicative interaction (AMMI) analysis revealed that 12% of total variability was justified by the GE interaction, which was six times more than that of genotype. Ordination techniques displayed high differences for the interaction principal components (IPC1, IPC2 and IPC3), indicating that 92.5% of the GE sum of squares was justified by AMMI1, AMMI2 and AMMI3, i.e. 4.5 times more than that explained by the linear regression model. The results of the AMMI model and biplot analysis showed two stable genotypes with high grain yield, due to general adaptability to both rainfed and irrigated conditions, and one with specific adaptation.
There is little information on interaction between productivity, stability and drought resistance of crop. This problem is very important in Kazakhstan, where the most of the agricultural area is located in arid and semiarid regions. In this context the genotype × environment interaction (GEI) is of major importance to the plant breeders in developing improved drought resistant cultivars. In this study GEI and stability parameters of recombinant inbred lines (RILs) has been determined by field testing at three contrasting environments. The comparison of the performance and stability of the lines L3, L10, L5, L1 indicated that this breeding material tended to display better performance for main of productivity traits and stability for plant grain yield as compared with other RILs and parental forms. There was positive association between high leaf Relative Water Content (RWC), low leaf Relative Water Loss (RWL) and yield stability. Both physiological parameters (RWC and RWL) are good indicators of drought adaptation by wheat genotypes. A comparison of glume pubescent and unpubescent lines has shown close negative correlation for spike RWL and spike RWC of all pubescent RILs (R2= -0.845). So the glume pubescence can be used as a morphological marker and indirect criterion for selection of drought resistant genotypes. As a result several promising lines combining high yield stability and drought resistance has been selected and used in breeding program.
. 1983 75 153 155 Mohammadi, M., Karimizadeh, R., Sabaghnia, N., Shefazadeh, M.K. 2012. Genotype × environment interaction