Person: GÖKSOY, ABDURRAHİM TANJU
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GÖKSOY
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ABDURRAHİM TANJU
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Publication Response and yield stability of canola (brassica napus l.) genotypes to multi-environments using gge biplot analysis(Univ Centroccidential Lisandro Alvarado, 2021-01-01) Acar, Mustafa; Gizlenci, Sahin; Atagun, Gulhan; Suzer, Sami; Ulusoy, Yahya; ULUSOY, YAHYA; Sincik, Mehmet; SİNCİK, MEHMET; Senyigit, Emre; ŞENYİĞİT, EMRE; Goksoy, Abdurrahim T.; GÖKSOY, ABDURRAHİM TANJU; Bursa Uludağ Üniversitesi/Ziraat Fakültesi/Tarla Bitkileri Anabilim Dalı.; Bursa Uludağ Üniversitesi/Mustafakemal Paşa Yüksekokulu.; 0000-0002-0012-4412; 0000-0001-8641-6995; 0000-0003-2658-3905; AAH-1811-2021The 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.Publication Stability analysis of some soybean genotypes using parametric and non parametric methods in multi-environments(Soc Field Crop Sci, 2021-01-01) Cubukco, Pinar; Kocaturk, Mehmet; Ilker, Emre; Kadiroglu, Abdullah; Vurarak, Yasemin; Sahin, Yesim; Karakus, Mehmet; Yildirim, Umran Akgun; Sincik, Mehmet; Goksoy, Abdurrahim Tanju; GÖKSOY, ABDURRAHİM TANJU; Bursa Uludağ Üniversitesi/Ziraat Fakültesi.; 0000-0002-0012-4412; AAH-1811-2021; JCO-4159-2023; A-3491-2012Seed yields of 14 soybean genotypes were evaluated in four locations i.e. Adana, Sanhurfa, Antalya and Izmir under second crop conditions through summer seasons from 2014 to 2016. The study aims to estimate the stability parameters in terms of seed yield of 14 soybean genotypes by using different stability analysis methods across eleven environmental conditions and to study interrelationships 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 51.04% to the total sum of squares whereas GEI and genotype effects were 20.8% and 2.59%, respectively. According to most 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 Di(2) (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) was positively significant associated with CVi, alpha i (P<0.01) and Ri(2) (P<0.05).