AI Summary & Key Takeaways
AI InsightThe results show that the use of morphological characters alone for genetic diversity in populations is not sufficient to determine the difference between populations and their genetic structure.
📌 3 Key Takeaways
Abstract
The aim of this study is to investigate genetic diversity in 48 einkorn (Triticum monococcum L. ssp. monococcum) landraces grown in agricultural areas of Bolu and Kastamonu. Therefore, variation in seven agro-morphological traits was investigated. Agro-morphological traits such as leaf weight (mg), coleoptile length (cm), root number (n), root length (cm), fresh root weight (mg), and dry root weight (mg) were examined by the coefficient of variation, ANOVA, and principal components analysis. The highest coefficient of variation (%) was observed in fresh root weight (FRW = 52.09%), while the lowest was in leaf weight (LW = 8.9%). Principal Component Analysis (PCA) was calculated as 76.93% variation in two main components. For molecular characterization, data obtained with iSSR primers were analyzed with the population genetics analysis program PopGene (ver. 1.32). According to PopGene results, the mean number of alleles, the mean number of effective alleles, and average genetic diversity values were calculated as na = 2, nea = 1.33, and h = 0.13, respectively. Among the agro-morphological traits, germination power, root number, and coleoptile length appeared to be reliable traits. The results show that the use of morphological characters alone for genetic diversity in populations is not sufficient to determine the difference between populations and their genetic structure.
Özet
The aim of this study is to investigate genetic diversity in 48 einkorn (Triticum monococcum L. ssp. monococcum) landraces grown in agricultural areas of Bolu and Kastamonu. Therefore, variation in seven agro-morphological traits was investigated. Agro-morphological traits such as leaf weight (mg), coleoptile length (cm), root number (n), root length (cm), fresh root weight (mg), and dry root weight (mg) were examined by the coefficient of variation, ANOVA, and principal components analysis. The highest coefficient of variation (%) was observed in fresh root weight (FRW = 52.09%), while the lowest was in leaf weight (LW = 8.9%). Principal Component Analysis (PCA) was calculated as 76.93% variation in two main components. For molecular characterization, data obtained with iSSR primers were analyzed with the population genetics analysis program PopGene (ver. 1.32). According to PopGene results, the mean number of alleles, the mean number of effective alleles, and average genetic diversity values were calculated as na = 2, nea = 1.33, and h = 0.13, respectively. Among the agro-morphological traits, germination power, root number, and coleoptile length appeared to be reliable traits. The results show that the use of morphological characters alone for genetic diversity in populations is not sufficient to determine the difference between populations and their genetic structure.