نوع مقاله : مقاله پژوهشی
نویسندگان
1 استادیار پژوهش موسسه تحقیقات کشاورزی دیم کشور، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی زنجان، سازمان تحقیقات، آموزش و ترویج
2 بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان لرستان، سازمان تحقیقات، آموزش و ترویج کشاورزی،
3 موسسه تحقیقات کشاورزی دیم کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، مراغه، ایران.
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Background and objectives: Lentils are one of the most important crop plants in rotation.Lentil seed yield is strongly influenced by environments and breeders often determine the stability of high yield genotypes across environments before recommending a stable cultivar for release. Genotypial adaptability to environmental fluctuations is important for the stabilization of crop production over regions and years.Identification of high- yield genotypes with adaptation to a wide range of environments is one of the major goals in crop breeding programs. The challenge of the interaction of genotype × environment is one of the main issues in plant breeding. Various statistical methods to estimate the interaction of genotype × environment and choice the stable and productive genotype(s) have been introduced. One of the applications of Non-Parametric methods is determination of genotypes rank in different environments, which is also used as a measuring stability. A stable genotype shows similar ranks across different environments and has minimum rank variance in different environments. Non-Parametric Stability Statistics require no statistical assumptions about the distribution of the phenotypic values and are easy to use.
Materials and methods: This study was conducted during two years (2019-2020 and 2020-2021) in two stations in the cold dry areas of the country (Qeydar Zanjan, Maragheh). The experiment consisted of 17 advanced lentil genotypes along with three control cultivars Kimia, Bilesvar and Senna (20 genotypes in total) which was performed in a randomized complete block design with 3 replications.
Results: The combined analysis of variance indicated that the main effects of genotype (G), environment (E) and their interactions genotype and environmen (G×E) were highly significant (p < . ). The principal component analysis (PCA) based on rank correlation matrix indicated that the first two PCAs explained . of the variance of original variables. Based on bi-plot analysis, the stability parameters were classified into four groups. Clustering of the genotypes according to the mean yield and nonparametric stability statistics showed that there were two main clusters. Overall, according to mean rank of nonparametric stability parameters, G17 , G3 , G9 and G2 had the lowest variations and were recognized as the most stable genotypes. Genotypes G7 , G11 and G13 had the highest values of mean rank of parameters and therefore, would be considered to be the most unstable. According to the present study, the stability measures Ysi, and TOP were associated with mean yield (MY) and the dynamic concept of stability. Therefore, these procedures were suitable for selecting stable and high yielding genotypes
Conclusion: Therefore, these procedures were suitable for selecting stable and high yielding genotypes. Based on these parameters, genotypes G13 (340 t/ha) and G11 (305 t/ha) were identified as high yield stable genotypes.
کلیدواژه‌ها [English]
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