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中国农学通报 ›› 2019, Vol. 35 ›› Issue (13): 95-99.doi: 10.11924/j.issn.1000-6850.casb18110088

所属专题: 油料作物 园艺 农业气象

• 资源 环境 生态 土壤 气象 • 上一篇    下一篇

高寒地区油菜花期与气象条件的关系及预测模型

张晓云 孔祥萍 曾聪彩 杨东, 孔祥萍   

  1. 青海省海南州气象局
  • 收稿日期:2018-11-21 修回日期:2019-03-11 接受日期:2019-03-20 出版日期:2019-05-05 发布日期:2019-05-05
  • 通讯作者: 孔祥萍
  • 基金资助:
    无基金

Rape Florescence in Alpine Region: The Relationship with Meteorological Conditions and Prediction Model

  • Received:2018-11-21 Revised:2019-03-11 Accepted:2019-03-20 Online:2019-05-05 Published:2019-05-05

摘要: 为准确预测高寒地区油菜始花期提供方法支持。笔者利用1991—2017年青海省贵南县气象局观测的油菜始花期资料和地面气象观测资料,应用气候倾向率和Mann-Kendall突变法等统计分析法探讨了油菜始花期与气象条件的关系,利用多元回归分析方法对油菜始花期进行了预测。结果表明:随着气候变暖,高寒贵南地区油菜始花期以3d/10a的趋势逐年延迟,始花期在1998年前后发生了一次突变。油菜始花期与5月份的平均气温和≥0℃积温呈显著正相关,与5月份平均最高气温和平均风速的正相关极显著,与5月降水量和相对湿度之间的负相关极显著。利用多元回归分析法建立了油菜始花期预测模型。用所建立的预测模型对历年油菜始花期进行回测,回代效果总体较好。

关键词: 酸模叶蓼, 酸模叶蓼, 大豆, 产量性状, 经济阈值

Abstract: To provide a methodological support for accurately predicting the initial flowering period of rape in alpine regions. The initial flowering data of the rape and ground meteorological observation data were adopted in this paper over the Guinan County Meteorological Bureau of Qinghai Province from 1991 to 2017, and applied climate propensity rate and statistical analysis such as Mann-Kendall mutation method, studied the relationship between the initial flowering period of rape and meteorological conditions, and predicted it with multiple regression analysis. The results showed that the initial flowering period of rape in the high-cold southern Guinan region was delayed by 3d/10a, and it occurred a mutation in the initial flowering period of rape around 1998 with the warming of the climate. The initial flowering period of rape was significantly positively correlated with the average temperature and ≥0°C of the accumulated temperature in May, and with the average maximum temperature and average wind speed significantly extremely. However, it was significant negative correlation with the precipitation and relative humidity extremely in May. It established a prediction model for the initial flowering period of rape by multivariate regression analysis method. The established prediction model was used to measure the initial flowering period of rape, and the retro-generation effects was good.