RESPONSE AND YIELD STABILITY OF CANOLA (Brassica napus L.) GENOTYPES TO MULTI-ENVIRONMENTS USING GGE BIPLOT ANALYSIS

SİNCİK M., GÖKSOY A. T., ŞENYİĞİT E., ULUSOY Y., Acar M., Gizlenci S., ...Daha Fazla

BIOAGRO, cilt.33, sa.2, ss.105-114, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 33 Sayı: 2
  • Basım Tarihi: 2021
  • Doi Numarası: 10.51372/bioagro332.4
  • Dergi Adı: BIOAGRO
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Fuente Academica Plus, CAB Abstracts, Veterinary Science Database, DIALNET
  • Sayfa Sayıları: ss.105-114
  • Anahtar Kelimeler: Genotype x environment interaction, multi-environment trials, seed yield, yield components, CULTIVAR EVALUATION, TRIAL DATA
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

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.