عنوان مقاله [English]
Background and Objectives
Cumin (Cuminum cyminum L.) is one of the most important aromatic and medicinal plants in the world. It has a short life cycle (100-120 days) and needs little water for its growth cycle. Therefore, it is suitable for cultivation in arid and semi-arid regions of Iran. Different indices, including tolerance (TOL), mean productivity (MP), geometric mean productivity (GMP), stress tolerance index (STI), stress susceptibility index (SSI), harmonic mean (HM), yield index (YI), and yield stability index (YSI) have been employed for screening the stress tolerant genotypes. Due to the economic, medicinal, and aromatic importance of cumin, this study evaluated elite genotypes for drought tolerance in cumin in order to develop improved genetic population for farmers’ usage.
Materials and Methods
The experiment was carried out in the research field of Shahid Bahonar University of Kerman, during the growing season of 2016-2017. In this study, 15 elite genotypes in cumin were evaluated using a randomized complete block design with three replications in two different environments, including normal and stress conditions. Stress treatment was cutting-off irrigation at the early flowering stage. Seed yield (ton/ha) was measured. Tolerance indices were calculated for genotypes based on the seed yield. To find suitable indices in order to determine the tolerant genotypes, the correlation coefficient between the calculated indices YP and YS was performed. To evaluate the relationship between the tolerance indices and the studied genotypes, principal components analysis (PCA) was performed. In order to use all tolerance indices simultaneously, an equation was used for estimating the stress tolerance score (STS).
The results of the correlation analysis revealed that GMP, MP, and STI indices were positively correlated with seed yield under both stress and non-stress conditions. Therefore, they can be suitable indices for determining tolerant genotypes. Principal components analysis (PCA) showed that the first and second Principal component explained 61.89% and 37.52% of the total variation, respectively. According to the bi-plot graph, genotypes No. 7, 12, 8, and 13 with high MP, GMP, and STI scores and low TOL and SSI scores had the highest tolerance to drought stress. Based on the calculated STS (stress tolerance score), genotypes No. 7, 4, 12, 8, and 13 were the most tolerant genotypes and genotypes No. 14, 10, 6, 9, and 2 were the most sensitive genotypes, respectively. These results were identical with the results of bi-plot analysis. Moreover, this equation is much easier to be used than the multivariate analysis, such as principal components analysis (PCA).
The aim of this study was the evaluation and selection of tolerant genotypes with high seed yield, and based on the results obtained from all the applied methods, it can be concluded that genotypes No. 7, 4, 12, 8, and 13 are identified as tolerant genotypes and were recommended to develop improved genetic population after being-tested in other places.