Investigation of Correlation between Traits and Path Analysis of Confectionary Sunflower Genotypes

The Heterosis and Combining Ability of Diallel Crosses of Rapeseed Inbred Lines

He GxE interaction (GEI) provides essential information for selecting and recommending cultivars in multi-environment trials. This study aimed to evaluate genotype (G) and environment (E) main effects and GxE interaction of 15 canola genotypes (10 canola lines and 5 check varieties) over 8 environments and to examine the existence of different mega environments. Canola yield performances were evaluated during 2015/16 and 2016/17 production season in three different locations (Southern Marmara, Thrace side of Marmara, and Black Sea regions) of Turkey. The trial in each location was arranged in a randomized complete block design with four replications. The seed yield data were analyzed using GGE biplot and the yield components data were analyzed using ANOVA. The agronomical traits revealed that environments, genotypes, and GEI were significant at 1 % probability for all of the characters. The variance analysis exhibited that genotypes, environments, and GEI explained 21.6, 21.7, and 25.7 % of the total sum of squares for seed yield, respectively. The GGE biplot analysis showed that the first and second principal components explained 57.3 and 18.3 % of the total variation in the data matrix, respectively. GGE biplot analysis showed that the polygon view of a biplot is an excellent way to visualize the interactions between genotypes and environments.

Seed yields of 14 soybean genotypes were evaluated in four locations i.e. Adana, Şanlıurfa, Antalya and İzmir under second crop conditions through summer seasons from 2014 to 2016. The aims of research are to estimate the stability parameters in terms of seed yield of 14 soybean genotypes by used different stability analysis methods across eleven environmental conditions and to study interrelationship among these stability methods. The analysis of variance for seed yield revealed that the genotypes and the environments as well as the genotype x environment interactions (GEI) were statistically significant at P<0.01. Environmental effects were contributed of 51.04% to the total sum of squares whereas GEI and genotype effects were 20.8% and 2.59%, respectively. According to most of stability methods, BATEM 223, BATEM 306, BATEM 317 and KASM 02 were determined to be stable genotypes. These genotypes demonstrated superior adaptability with high yield performances in many environments. Results of correlation analysis indicated that seed yield was positively and significantly correlated with Di2 (P<0.01), Si(6) (P<0.05) and TOP (P<0.01) and showed a negative and significant correlation with Pi (P<0.01) and RS (P<0.01). In addition, the coefficient of regression (bi) had positively significant associated with CVi, αi (P<0.01) and Ri2 (P<0.05).