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中国农学通报 ›› 2021, Vol. 37 ›› Issue (32): 120-126.doi: 10.11924/j.issn.1000-6850.casb2021-0099

所属专题: 园艺

• 资源·环境·生态·土壤·气象 • 上一篇    下一篇

油用牡丹花期预报

张翠英1(), 樊献政2, 李瑞英1()   

  1. 1山东省菏泽市气象局,山东菏泽 274000
    2山东省招远市气象局,山东招远 265400
  • 收稿日期:2021-01-27 修回日期:2021-04-28 出版日期:2021-11-15 发布日期:2022-01-07
  • 通讯作者: 李瑞英
  • 作者简介:张翠英,女,1972年出生,山东菏泽人,高级工程师,本科,主要从事农业气象服务方面的研究。通信地址:274000 山东省菏泽市气象局,Tel:0530-5622460,E-mail: hezezcy@126.com
  • 基金资助:
    山东省气象局项目“油用牡丹气象服务终端研究”(2016sdqxm22);十三五山东重大气象工程项目(鲁发改农经[2017]97号)

Oil Peony Flowering Season Forecast

Zhang Cuiying1(), Fan Xianzheng2, Li Ruiying1()   

  1. 1Heze Meteorological Service, Heze Shandong 274000
    2Zhaoyuan Meteorological Service, Zhaoyuan Shandong 265400
  • Received:2021-01-27 Revised:2021-04-28 Online:2021-11-15 Published:2022-01-07
  • Contact: Li Ruiying

摘要:

根据菏泽市2008—2019年油用牡丹花期观测资料及相应气象要素,利用滑动平均、相关分析及逐步回归等数理统计方法,分析了影响菏泽市油用牡丹始花期早晚的主要气象因子。结果表明:温度条件是影响油用牡丹始花期主要的气象因子之一,并与花期呈显著负相关;日照、降水及日较差等气象条件与油用牡丹始花期相关均不显著。选取2008—2018年对牡丹花期影响较大的气象因子,采用逐步回归方法,建立了油用牡丹始花期预报模型,可分别于3月21日、4月1日发布花期预报。模型历史回代(允许误差均在±1天),并对2019、2020年进行试报,准确率均为100%,拟合程度较为理想,试报效果较好,满足气象服务需求。

关键词: 油用牡丹, 始花期, 花期预报, 气象因子, 预报模型

Abstract:

According to the observation data of flowering period of oil peony in Heze City from 2008 to 2019 and the corresponding meteorological elements, the main meteorological factors affecting the flowering period of oil peony in Heze City were analyzed by using the mathematical statistical methods of moving average, correlation analysis and stepwise regression. The results showed that temperature was one of the main meteorological factors affecting the first flowering period of oil peony, and had a significant negative correlation with the flowering period; sunshine, precipitation and daily range had no significant correlation with the first flowering period of oil peony. Based on the meteorological factors that had great influence on the flowering period of peony from 2008 to 2018, a forecasting model for the first flowering period of oil peony was established by using the stepwise regression method, which could release the flowering forecast on March 21 and April 1 respectively. The accuracy of the model was 100% in 2019 and 2020, and the fitting degree was ideal. The model has a good forecasting effect and could meet the needs of meteorological services.

Key words: oil peony, initial flowering period, flowering forecast, meteorological factors, forecast model

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