中国农业科学

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最新录用:棉花出苗期耐冷综合评价体系的构建及耐冷指标的筛选

沈倩1, 2,张思平1,刘瑞华1,刘绍东1,陈静1,葛常伟1,马慧娟1,赵新华1,杨国正2,宋美珍1*,庞朝友1*
  

  1. 1中国农业科学院棉花研究所/棉花生物学国家重点实验室,河南安阳 4550002华中农业大学植物科学与技术学院,武汉 430070
  • 发布日期:2022-09-29

Construction of A Comprehensive Evaluation System and Screening of Cold Tolerance Indicators for Cold Tolerance of Cotton during Seeding Stage #br#

SHEN Qian1,2, ZHANG SiPing1, LIU RuiHua1, LIU ShaoDong1, CHEN Jing1, GE ChangWei1, MA HuiJuan1, ZHAO XinHua1, YANG GuoZheng2, SONG MeiZhen1*, PANG ChaoYou1*   

  1. 1Institute of Cotton, Chinese Academy of Agricultural Sciences/State Key Laboratory of Cotton Biology, Anyang 455000, Henan; 2College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070
  • Online:2022-09-29

摘要: 【目的】综合评价棉花品种(系)在出苗期的耐冷性,建立可靠评价模型,筛选鉴定指标,为耐冷品种选育鉴定提供简便有效评价方法。【方法】以200份陆地棉品种(系)为试验材料,设恒定低温昼夜变温和适宜温度3个处理,测定其出苗率、下胚轴长根长、百粒重指标,采用耐冷系数差异分析、频次分析降幅分析、主成分分析、聚类分析和多元回归分析等方法,对群体进行耐冷型划分,并建立耐冷性评价模型和鉴定指标。【结果】各指标适温温度变异幅度较小,变异系数3.12%18.89%,各品种(系)出苗率在85.00%以上具有较高的生活可用于后续耐冷性分析。在低温胁迫下群体内各指标变异幅度增7.14%108.33%,在恒定低温昼夜变温变幅最大的指标依次为根长和萌发指数。主成分分析将14个低温相关指标和百粒重转换为6个相互独立的综合指标,代表了全部数据74.98%的信息量。利用隶属函数法计算综合耐冷评价值(D),并对其进行聚类分析,按照耐冷性强弱将200份陆地棉品种(系)划分为5类,第Ⅰ类群属于强耐冷型共2份,第Ⅱ类群属于耐冷型42份,第Ⅲ类群属于中耐冷型69份,Ⅳ类属于较敏感型83份,第Ⅴ类群属于敏感4份,其中新陆中16为耐冷性最强的品种采用多元回归分析方法,建立棉花出苗期耐冷性预测模型为Y=-4.10+0.58X4+0.40X14+0.32X1+0.22X5(R2=0.92),筛选出4个耐冷性鉴定指标,分别为恒定低温下的总长、出苗率、干物重和昼夜变温下的萌发率。田间早播试验中各品种(系)的出苗率,室内试验结果基本一致。【结论】采用恒定低温和昼夜变温处理结合多元统计分析方法对棉花出苗期的耐冷性评价是可行的,恒定低温下的总长、出苗率、干物重和昼夜变温下的萌发率,可作鉴定指标。


关键词: 棉花, 出苗期, 耐冷性, 综合评价, 指标筛选

Abstract: 【Objective】In this study, the purpose was to comprehensively evaluate the cold tolerance of cotton varieties (lines) at the seeding stage, establish a reliable evaluation model, screen and identify indicators, and provide a simple and effective evaluation method for the selection and identification of cold-tolerant varieties in cotton.【Method】200 upland cotton varieties (lines) were used to test hypocotyl length, root length and 100-grain weight, etc. under three treatments of constant chilling (CC), diurnal variation of chilling (DVC) and normal conditions. A combination of integrated cold tolerance coefficient difference analysis, frequency analysis, drop analysis, principal component analysis, cluster analysis, and multiple regression analysis were used to classify their cold tolerance types, establish cold tolerance prediction models, and screen evaluation parameters. 【Result】The variation of each parameters at normal conditions were minor fluctuations ranging from 3.12% to 18.89%. The seedling emergence rate was above 85.00%, which had high viability and could be used for subsequent cold tolerance analysis. The variability of each parameters within the accessions increased under chilling stress, ranging from 7.14%-108.33%, and the most variable parameter were root length under CC condition and germination index under DVC condition. Principal component analysis converted the 14 parameters under chilling stress and 100-grain weight measured into six mutually independent composite indicators, representing 74.98% of the total data information. The comprehensive cold tolerance evaluation value (D) was calculated by the affiliation function method and then clustering analysis was performed. 200 cotton varieties (lines) were divided into five categories according to their cold tolerance, with 2 of the group Ⅰ being strongly cold tolerant, 42 of the group Ⅱ being cold tolerant, 69 of the group Ⅲ being medium cold tolerant, 83 of the group Ⅳ being more sensitive, and 4 of the group Ⅴ being sensitive, of which Xinluzhong 16 was the most cold-tolerant material. A multiple regression analysis was applied to establish a prediction model for cold tolerance of cotton at seedling emergence as Y=-4.10+0.58X4+0.40X14+0.32X1+0.22X5 (R2=0.92), and four parameters for cold resistance evaluation were confirmed, namely total length, emergence rate, and dry matter weight under CC stress, germination rate under DVC stress. The cold-tolerant varieties (lines) had higher seedling emergence rates of early sowing experiment in the field, which were basically consistent with the results of the indoor results. 【Conclusion】It is feasible to use CC and DVC stress combined with multivariate statistical analysis to evaluate the cold tolerance of cotton at seeding stage, and total length, emergence rate, and dry matter weight under CC stress, germination rate under DVC stress can be used as evaluation parameters.


Key words: Gossypium hirsutum , L., seeding stage, cold tolerance, comprehensive evaluation, parameters screening