中国农业科学 ›› 2013, Vol. 46 ›› Issue (3): 476-485.doi: 10.3864/j.issn.0578-1752.2013.03.004

• 耕作栽培·生理生化·农业信息技术 • 上一篇    下一篇

油菜苗期抗旱性评价及抗旱相关指标变化分析

 谢小玉, 张霞, 张兵   

  1. 西南大学农学与生物科技学院/南方山地农业教育部工程研究中心,重庆 400716
  • 收稿日期:2012-09-10 出版日期:2013-02-01 发布日期:2012-10-24
  • 通讯作者: 谢小玉,E-mail:xiexy8009@163.com
  • 作者简介:谢小玉,E-mail:xiexy8009@163.com
  • 基金资助:

    中央高校基本科研业务费专项资金(XDJK2009B020)、重庆市自然科学基金(CSTC2010BB1012)

Evaluation of Drought Resistance and Analysis of Variation of Relevant Parameters at Seedling Stage of Rapeseed (Brassica napus L.)

 XIE  Xiao-Yu, ZHANG  Xia, ZHANG  Bing   

  1. College of Agronomy and Bio-technology, Southwest University/Engineering Research Center of South Upland Agriculture, Ministry of Education, Chongqing 400716
  • Received:2012-09-10 Online:2013-02-01 Published:2012-10-24

摘要: 【目的】探讨甘蓝型油菜苗期的抗旱性,为甘蓝型油菜抗旱种质的筛选提供可借鉴的指标、方法,同时为抗旱育种、栽培提供材料和理论依据。【方法】在遮雨网室对油菜苗期进行干旱胁迫,于胁迫的第0、5、10、15、20、25天分别取样测定叶片相对含水量、丙二醛(MDA)含量和保护性酶活性等的变化。采用综合抗旱系数、抗旱指数、聚类分析、灰色关联度分析相结合的方法,对其抗旱性进行综合评价,并对不同类型种质抗旱相关指标的变化进行分析。【结果】被考查的各指标对干旱胁迫的反应程度各异,其中脯氨酸含量、POD活性对干旱胁迫的反应迟钝,而叶片相对含水量反应敏感;根据抗旱性量度值(D值)的聚类结果,将10个油菜种质划分为抗旱性强、抗旱性中等和抗旱性差3个抗旱级别。抗旱相关指标的变化表现为,随干旱胁迫时间的延长和胁迫程度的增大,叶片的相对含水量和叶面积下降幅度变大,而丙二醛(MDA)、脯氨酸、可溶性糖、可溶性蛋白含量和SOD、POD活性相对值总体表现出上升趋势。MDA含量相对值与品种抗旱性呈负相关,而脯氨酸、可溶性糖、可溶性蛋白质含量和POD活性相对值与品种抗旱性呈正相关。10个参试油菜种质中,94005、中双11号和中双9号抗旱性强。【结论】采用综合抗旱系数、聚类分析、灰色关联度等相结合的方法对油菜苗期抗旱性进行评估,可以较好地揭示指标性状与抗旱性的关系。油菜在连续干旱胁迫下,其叶片相对含水量、丙二醛、叶面积可作为油菜抗旱种质筛选的依据。

关键词: 油菜 , 抗旱相关指标 , 隶属函数 , 聚类分析 , 关联度分析

Abstract: 【Objective】An experiment was conducted to investigate the ability of drought resistance at seedling stage of rapeseed (Brassica napus L.), to explore the parameters and methods for screening of drought-resistant germplasm, and to provide the materials and a theoretical basis for drought-resistant breeding and cultivation.【Method】 Leaf relative water content, malondialdehyde (MDA) and protective enzyme activity in rapeseed were measured under drought stress on 0, 5, 10, 15, 20 and 25 d; Comprehensive drought-resistance coefficient, drought-resistance index, fuzzy clustering and grey correlation analysis were used to evaluate the drought tolerance; And the variation trend of relevant drought-resistance index was analyzed for ten rapeseed varieties. 【Result】 Different examined indexes showed different responses to drought stress, in which, the content of proline and POD activity were retarded, but the relative water content of leaves was sensitive in response to drought stress. According to the clustering result of drought-resistance measuration value (D value), the 10 tested varieties were divided into 3 groups including high, moderate and low drought resistance, respectively. The variation trend of relevant drought-resistance index showed that the decrease rate of leaf relative water content and leaf area became larger with the increase of degree and time of drought stress, but the contents of MDA, proline, soluble sugar and soluble protein and the relative activities of SOD and POD were overall ascendant. The relative value of MDA content was negatively correlated with drought resistance, while the increase rate of relative content of proline, soluble sugar, soluble protein and the activity of POD were positively correlated with that of rapeseed varieties. 【Conclusion】 It is an effective way to evaluate the drought tolerance of rapeseed seedlings by using the combination method of comprehensive drought-resistance coefficient, drought-resistance index, fuzzy clustering and grey correlation analysis, which could reflect the relationship between different parameter traits and drought tolerance in rapeseed. Among the 10 tested varieties, the drought tolerance of 94005, Zhongshuang11 and Zhongshuang9 were better and more stable. The change of drought-resistance related parameters of rapeseed under continuous drought stress presented a certain regularity, which indicated the responses of rapeseed to drought stress and could lay a basis for the screening of rapeseed germplasm.

Key words: rapeseed (Brassica napus L.) , drought-resistance parameters , subordinate function coefficients , fuzzy clustering , grey correlative analysis