大蒜主要农艺性状变异特征及其与产量相关构成分析

doi:10.3864/j.issn.0578-1752.2015.06.19

摘要/Abstract

摘要： 【目的】大蒜为无性繁殖作物，难以采用常规方法创制新种质，新品种选育较为困难。因此，研究分析大蒜农艺性状的变异特征，探索决定大蒜产量形成的主要农艺性状，为合理评价与挖掘利用现有种质资源，以及优选大蒜高产品种提供参考。【方法】以78份国内外大蒜种质资源为材料，根据《大蒜种质资源描述规范和数据标准》，选取代表性植株，分别于大蒜抽薹期和鳞茎收获晾干后测试大蒜种质资源的16个农艺性状，采用相关分析、主成分分析、多元线性回归分析和通径分析等方法，探讨大蒜主要农艺性状之间的关系，明确大蒜鳞茎及蒜薹产量形成的主要决定因子。【结果】大蒜主要农艺性状变异丰富，变异系数达11.1%—64.0%，其中以蒜薹相关性状变异系数较大，鳞茎重、鳞芽数次之，株形等相关性状较小。除鳞芽宽外，其他农艺性状与鳞茎重的简单相关系数均达极显著水平，而除叶夹角及鳞芽数外，其他农艺性状与蒜薹重的简单相关系数亦达极显著水平。通过主成分分析，明确了影响大蒜鳞茎及蒜薹产量的主要性状包括株形因子、蒜薹因子和叶形鳞芽因子。采用逐步回归分析，分别建立了鳞茎产量和蒜薹产量与农艺性状之间的回归模型，经统计学检验，两个模型均达极显著水平，其决定系数分别为0.8516和0.9449。通过通径分析，确定影响大蒜鳞茎产量的关键农艺性状依次为鳞茎横径（0.5353）、鳞芽长（0.1652）、鳞芽数（0.147）、假茎粗（0.1136）及叶片数（0.1036），而影响大蒜蒜薹产量的关键农艺性状依次为蒜薹粗（0.8875）、株高（0.1585）和鳞芽数（-0.1382）。【结论】大蒜种质资源具有丰富的遗传多样性，且大蒜农艺性状之间多存在极显著相关关系，决定大蒜蒜薹和鳞茎产量形成的关键农艺性状显著不同，除蒜薹和鳞茎自身性状外，以较高株型大蒜的蒜薹产量较高，以较粗株型大蒜的鳞茎产量较高。

关键词: 大蒜, 农艺性状, 数学模型, 产量决定因子

Abstract: 【Objective】Garlic is a clonal propagation crop. This makes it difficult to breed new garlic varieties by conventional method. Accordingly, the purpose of this study was to analyze the variation of agronomic traits and to explore the traits controlling the yielding of garlic, wishing to provide important information for germplasm evaluation and innovation to select the high yielding garlic varieties.【Method】In this study, 16 agronomic traits of 78 garlic varieties were analyzed. The relationship of main agronomic traits, including garlic-scape, weight of bulbs and number of cloves were studied to identify the primary indexes of garlic-scapeand bulb yield using the methods of correlation analysis, principal component analysis, multiple linear regression analysis and path analysis.【Result】The results showed that variations in main agronomic traits of garlic varieties were abundant and its coefficient of variation was ranging from 11.1% to 64%. Among the main agronomic traits, the garlic-scape had the most variation in related traits, the weight of bulbs and number of cloves had less variation, taking the second place while the ideotype traits had the least variation ratio. The bulb weight was positively correlated with other agronomic traits significantly, in which clove-width was not included. A significant positive correlation was clearly established between other agronomic traits, except leaf-angle and clove-number. Principal component analysis showed that plant type factors, garlic-scape factors, leaf and clove factors were largely responsible for the yield of garlic-bulb and garlic-scape . Regression models, which successfully forecasted the relationships not only between agronomic traits but also between garlic yield bulb and scape were established by stepwise regression analysis. Statistical test was performed and the results showed that the correlation coefficient was significant, the coefficients of garlic bulb and scape were 0.8516 and 0.9449, respectively. Furthermore , path analysis indicated that the main factors that influenced bulb yield were cross diameter of bulb (0.5353), clove length (0.1652), number of cloves (0.147), diameter of pseudostem (0.1136) and number of leaves (0.1036). On the other hand, the main factors that influenced garlic-scape yield were diameter of garlic-scape (0.8875), plant height (0.1585) and number of cloves(-0.1382). 【Conclusion】Garlic germplasm had high-level genetic diversity. And the extremely significant correlation between agronomic traits was clearly indicated. The key agronomic traits which had influence on them were still significantly distinguished. The only exception was for the garlic-scape and bulb, the variety which grows higher had higher yield of garlic-scape, and the variety which had wider diameter of pseudostem had higher yield of bulb.

Key words: garlic, agronomic trait, mathematical model, yield determining factors

孔素萍，孙敬强，吴雄，杨妍妍，霍雨猛，徐坤. 大蒜主要农艺性状变异特征及其与产量相关构成分析[J]. 中国农业科学, 2015, 48(6): 1240-1248.

KONG Su-ping, SUN Jing-qiang, WU Xiong, YANG Yan-yan, HUO Yu-meng, XU Kun. Analysis of Relationship Between Variations of Main Agronomic Traits and Yield in Garlic[J]. Scientia Agricultura Sinica, 2015, 48(6): 1240-1248.

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