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生态学杂志 ›› 2005, Vol. ›› Issue (4): 398-401.

• 研究报告 • 上一篇    下一篇

高温胁迫下不同茄子品种幼苗耐热性研究

贾开志1,2, 陈贵林1   

  1. 1. 内蒙古大学生命科学学院, 呼和浩特, 010021;
    2. 河北农业大学园艺学院, 保定, 071001
  • 收稿日期:2003-06-07 修回日期:2003-06-16 出版日期:2005-04-10
  • 通讯作者: 陈贵林
  • 基金资助:
    河北省自然科学基金资助项目(399125)

Tolerance of different eggplant varieties at seedling stage to high temperature stress

JIA Kaizhi1,2, CHEN Guilin 1   

  1. 1. College of Life Sciences, Nei Mongol University, Huhhot 010021, China;
    2. College of Horticulture, Hebei Agricultural University, Baoding 071001, China
  • Received:2003-06-07 Revised:2003-06-16 Online:2005-04-10

摘要: 以14个茄子品种为材料,研究了高温对茄子幼苗的热害指数、恢复指数、电解质渗透率、脯氨酸、可溶性糖含量的影响。结果表明,43/38℃(昼/夜)高温处理下,茄子幼苗热害指数升高,电解质渗透率和脯氨酸含量增加,可溶性糖含量下降。其中,热害指数、恢复指数、电解质渗透率、脯氨酸含量可作为不同茄子品种耐热性的筛选指标,而可溶性糖含量不宜作为耐热筛选指标。高温胁迫条件下,N1(农友茄)表现出极强的耐热性,C2(刺红茄)、F3(丰研二号)、F4(伏龙茄)、Y5(圆杂二号)、X6(西安绿茄)、B7(北京六叶)、Y8(野茄2号)、N9(粘毛茄)、B11(北京五叶)耐热性中等,K11(快圆茄)、R12(二苠茄)、C13(赤茄)、G14(刚果红茄)耐热性极差.

关键词: 水稻, 直链淀粉, 生态环境, 预测模型

Abstract: The effects of high temperature stress on heat injury index,recovery index,electrolytic leakage,proline and soluble sugar content in eggplant ( Solanum melongena ) seedling of 14 varieties were investigated.The result showed that high temperature stress at eggplant seedling stage led to the increase of electrolytic leakage and proline and soluble sugar content,the aggravation of heat injury index,but the decrease of soluble sugar content.It was proposed that heat injury index,recovery index,electrolytic leakage and proline content might be suitable for selecting heat-tolerant eggplant genotype in breeding programe except soluble sugar content.In this research,It also indicated that N1(Nongyouqie) was the most heat-tolerant to heat stress,K11(Kuaiyuanqie),R12 (Erminqie),C13(Chiqie),G14(Gangguohongqie)were the most sensitive to heat stress,while C2(Cihongqie),F3(Fengyan No.2),F4(Fulongqie),Y5(Yuanza No.2),X6(Xianluqie),B7(Beijignliuyeqie),Y8(Yeqie No.2),N9(Nianmoqie),and B11(Beijingwuyeqie) were the intermediate.

Key words: Rice, Amylose, Ecological environment, Prediction model

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