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ABSTRACT
Flax is cultured for fiber and oil production around the world. The demand for flax is increasing in industries each year. In order to screening and selection of 86 accessions from five subspecies along with 19 unknown accessions, the seeds of the accessions were cultured in a randomized complete block design with three replications. The experiment took two years in Karaj, Iran. ANOVA results showed that the accessions and their interaction with year had significant effects on the measured traits (P < .05 or 0.01). Our results showed a substantial level of diversity among the accessions with respect to the measured traits. Based on correlation analysis, there were positive and significant relationships between seed yield (SY) and number of basal branches (NBB), capsules per main branch (CMB), number of capsules and seeds per plant (CP and NSP). Multiple linear regression analysis indicated that the predicting model explained 99% of flax yield variation in which the CP, NSP, and TSW were effective traits in describing the variation. Cluster analysis categorized the 100 accessions into seven clusters. Our results suggested that accessions ‘19ʹ and ‘35ʹ from the first and the third clusters could be cultivated as promising genotypes for SY and fiber production, respectively.
摘要
世界各地都种植亚麻以生产纤维和油. 工业对亚麻的需求每年都在增加. 为了筛选5个亚种的86份材料和19份未知材料, 采用3个重复的随机完全区组设计对这些材料的种子进行了培养. 这项实验在伊朗的卡拉吉进行了两年. ANOVA结果表明, 材料及其与年份的互作对所测性状有显著影响 (P<.05或0.01) . 我们的结果表明, 在所测性状方面, 各材料之间存在着相当程度的多样性. 相关分析表明, 种子产量 (SY) 与基枝数 (NBB), 主枝荚数 (CMB), 单株荚数和种子数 (CP和NSP) 呈显著正相关. 多元线性回归分析表明, 预测模型能解释99%的亚麻产量变异, 其中CP, NSP和TSW是描述变异的有效性状. 聚类分析将100份材料分为7类。我们的结果表明, 来自第一和第三簇的材料‘19ʹ和‘35ʹ可以分别作为SY和纤维生产的有希望的基因型.