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农学学报 ›› 2020, Vol. 10 ›› Issue (2): 1-6.doi: 10.11923/j.issn.2095-4050.cjas20190700133

所属专题: 水稻

• 农艺科学 生理生化 •    下一篇

广西典型地区水稻产量形成要素分析

陈飘1, 李家文2(), 黄彬香1, 胡莉婷1, 谭英3, 潘学标1   

  1. 1 中国农业大学资源与环境学院,北京 100193
    2 柳州市气象局,广西柳州 545001
    3 中国农业大学人文与发展学院,北京 100193
  • 收稿日期:2019-07-23 修回日期:2019-08-21 出版日期:2020-02-24 发布日期:2020-02-24
  • 通讯作者: 李家文 E-mail:lzlijiawen@126.com
  • 作者简介:陈飘,女,1995年出生,河北邢台人,在读硕士,研究方向:水稻灾害。通信地址:100193 北京市海淀区中国农业大学西校区,E-mail:chenpiao233@cau.edu.cn,897074988@qq.com。
  • 基金资助:
    国家重点研发计划课题(2017YFD0300401)

Rice Yield in Typical Areas of Guangxi: Components Analysis

Chen Piao1, Li Jiawen2(), Huang Binxiang1, Hu Liting1, Tan Ying3, Pan Xuebiao1   

  1. 1 College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
    2 Liuzhou Meteorological Bureau, Liuzhou 545001, Guangxi, China
    3 College of Humanities and Development Studies, China Agricultural University, Beijing 100193, China
  • Received:2019-07-23 Revised:2019-08-21 Online:2020-02-24 Published:2020-02-24
  • Contact: Jiawen Li E-mail:lzlijiawen@126.com

摘要:

为探究广西壮族自治区典型地区水稻产量与产量构成要素间的关系,利用2007—2016年4个典型试验点水稻区域试验的3个品种的产量相关数据,针对水稻5个产量构成要素,分析不同地点及不同品种的表现,并通过不同统计学分析方法,探讨各要素对产量的影响。灰色关联度分析结果表明,结实率对产量贡献最大,其次是穗数和穗粒数,各产量要素间差异不大;相关分析结果表明,对产量影响最大的是结实率,其次是每穗实粒数和千粒重;回归分析揭示了3个品种各自的培育优势;通径分析解析了产量构成要素对产量的直接影响与间接影响差异程度。根据分析结果,对广西水稻品种培育与栽培提出建议,在优先保障结实率的基础上,探索有效穗数与千粒重的平衡。

关键词: 广西水稻, 产量, 产量构成要素, 灰色关联度分析, 相关分析, 通径分析

Abstract:

To explore the relationship between rice yield and yield components in typical areas of Guangxi, based on the yield data of 3 varieties in 4 typical test sites from 2007 to 2016, we analyzed the performance of different locations and varieties, and studied the impact of various factors on yield by different statistical analysis methods. The results of grey correlation analysis showed that: the seed setting rate of the rice varieties in the study area contributed the most to the yield, followed by the number of panicles and the number of grains per panicle, but the differences among the yield factors were not significant; the correlation analysis showed that: the biggest impact on yield was the seed setting rate, followed by the number of grains per panicle and 1000-grain weight; the regression analysis revealed the breeding advantages of the 3 varieties; the path analysis analyzed the differences between the direct and indirect effects of components on yield. According to the results, we propose suggestions for breeding and cultivation of rice varieties in Guangxi as taking the priority of ensuring the seed setting rate, and exploring the balance between effective panicle number and 1000-grain weight.

Key words: Rice in Guangxi, Yield, Yield Components, Grey Correlation Analysis, Correlation Analysis, Path Analysis

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