中国农业科学 ›› 2020, Vol. 53 ›› Issue (20): 4152-4163.doi: 10.3864/j.issn.0578-1752.2020.20.005

• 耕作栽培·生理生化·农业信息技术 • 上一篇    下一篇

化学封顶对棉花株型的调控及评价指标筛选

祝令晓1(),刘连涛1(),张永江1,孙红春1,张科1,白志英1,董合忠2,李存东1()   

  1. 1河北农业大学农学院/省部共建华北作物改良与调控国家重点实验室/河北省作物生长调控重点实验室,河北保定 071000
    2山东省农业科学院棉花研究中心,济南 250100
  • 收稿日期:2020-01-08 接受日期:2020-07-06 出版日期:2020-10-16 发布日期:2020-10-26
  • 通讯作者: 刘连涛,李存东
  • 作者简介:祝令晓,E-mail: zlxhbnydx@163.com
  • 基金资助:
    国家自然科学基金(31871569);国家自然科学基金(31900623);国家重点研发计划(2017YFD0201900);国家重点研发计划(2018YFD0100306);河北省农业技术现代体系(HBCT2018040201)

The Regulation and Evaluation Indexes Screening of Chemical Topping on Cotton’s Plant Architecture

ZHU LingXiao1(),LIU LianTao1(),ZHANG YongJiang1,SUN HongChun1,ZHANG Ke1,BAI ZhiYing1,DONG HeZhong2,LI CunDong1()   

  1. 1College of Agronomy, Hebei Agricultural University/State Key Laboratory of North China Crop Improvement and Regulation/Key Laboratory of Crop Growth Regulation of Hebei Province, Baoding 071000, Hebei
    2Cotton Research Center, Shandong Academy of Agricultural Sciences, Jinan 250100
  • Received:2020-01-08 Accepted:2020-07-06 Online:2020-10-16 Published:2020-10-26
  • Contact: LianTao LIU,CunDong LI

摘要:

【目的】株型是重要的农艺性状,对棉花的栽培适应性和产量等有着巨大影响。研究化学封顶对棉花株型相关性状的影响,并进行综合分析,为化学封顶的应用和推广提供理论支持。【方法】于2015—2016年在河北农业大学试验基地,以黄河流域大面积种植的冀棉863和农大棉601为试验材料,设置人工打顶、化学封顶和不打顶3个处理,测定产量构成及株高、茎粗、果枝数等株型相关指标,开展化学封顶对棉花株型性状影响的研究。【结果】人工打顶和化学封顶处理的籽棉产量无显著差异,且均显著高于不打顶处理,冀棉863和农大棉601在化学封顶处理下的籽棉产量比不打顶处理分别提高了7.19%和6.18%。与不打顶处理相比,化学封顶处理显著降低了棉花的株高、节间数、果枝数、果节数,显著增加了上部果枝的近远端直径比。与人工打顶处理相比,化学封顶处理显著降低了主茎的节间长度和上部果枝长度。通过皮尔逊相关性分析、主成分分析和灰色关联度分析认为可通过株高和上部果枝的近远端直径比来评价化学封顶对棉花株型的调控效果。【结论】化学封顶可显著调控棉花的营养生长,且与人工打顶相比对产量无显著影响,株高和上部果枝近远端直径可作为评价化学封顶对棉花株型调控效果的最佳评价指标。

关键词: 棉花, 株型, 人工打顶, 化学封顶, 产量, 主成分分析, 灰色关联度分析

Abstract:

【Objective】Plant architecture is of major agronomic importance because it strongly influences the suit-ability of a plant for cultivation, its overall yield and its economic coefficient. This study was aimed to explore the effects of chemical topping on the traits of cotton’s plant architecture and to make a comprehensive analysis, thus providing a theoretical basis for the application and popularization of chemical topping. 【Method】Three topping treatments, including manual topping, chemical topping and non-decapitation treatment, were established by using Jimian863 and Nongda601, which were widely grown in Yellow River Valley, in Hebei Agriculture University experimental base during 2015-2016, yield components, plant height, stem diameter, number of fruit branches and other plant architecture related indicators were measured, carry out research on the effect of chemical topping on plant architecture. 【Result】There was no significant difference in seed cotton yield between manual topping treatment and chemical topping treatment, and both treatments were significantly higher than that of non-decapitation treatment. Compared with non-decapitation treatment, chemical topping increased the seed cotton yield of Jiman863 and Nongda601 by 7.19% and 6.78%, respectively. Compared with non-decapitation treatment, chemical topping significantly decreased the cotton plant, internode number, fruiting branches number and fruiting node number, and significantly increased the diameter ratio of near and far branches. Chemical topping significantly decreased the internode length of stem and upper fruiting branches length. The effect of chemical topping on cotton’s plant architecture could be evaluated by the plant height and the diameter ratio of near and far branches according to Pearson correlation analysis, principal component analysis and grey correlation analysis. 【Conclusion】Chemical topping treatment had the same purpose on the regulation of cotton’s vegetative and regenerative growth as manual topping treatment, and had no significant effect on seed cotton yield. The plant height and the diameter ratio of near and far branches were taken as the main evaluation indexes for the regulation of chemical topping on cotton’s plant architecture.

Key words: cotton, plant architecture, manual topping, chemical topping, yield, principal component analysis, grey correlation analysis