Browsing by Author "Senyigit, Emre"

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    Correlation and path coefficient analysis of yield and yield components in hexaploid triticale (X Triticosecale Wittmack) genotypes under mediterranean conditions
    (Uludağ Üniversitesi, 2016-04-08) Dogan, Ramazan; Senyigit, Emre; Uludağ Üniversitesi/Ziraat Fakültesi/Tarla Bitkileri Bölümü.
    During the 2004-05 and 2005-06 vegetation periods, a study was conducted to determine the suitable selection criteria in triticale breeding for higher yields in Bursa ecological conditions. To this end, path and correlation coefficient analyses were applied to 22 triticale genotypes. Field trials were performed in a randomized block design, with three replications. According to the results, the relationships between the grain yield and all of its components were significant and positive. The results of the path coefficient analysis indicated that the grain number spike-1 , thousand kernel weight and test weight had the highest direct effects on the grain yield, whereas the plant height and spikelet number spike-1 were positive but less direct effects. In addition, the spike length had negative and low direct effects, whereas the grain weight spike-1 had negative and high direct effects on the grain yield. The results suggest that the grain number spike-1 , thousand kernel weight and test weight are primary selection criteria for higher grain yields in triticale.
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    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-1811-2021
    The 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.