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生态学杂志 ›› 2022, Vol. 41 ›› Issue (3): 618-624.doi: 10.13292/j.1000-4890.202202.024

• 技术与方法 • 上一篇    

苹果花期预报中的生物学机理及应用

冯建设,薛晓萍*,李曼华,李楠   

  1. (山东省气象防灾减灾重点实验室, 山东省气候中心, 济南 250031)
  • 出版日期:2022-03-10 发布日期:2022-03-11

Biological mechanism and its application in the prediction of apple flowering time.

FENG Jian-she, XUE Xiao-ping*, LI Man-hua, LI Nan   

  1. (Key Laboratory for Meteorological Disaster Prevention and Mitigation of Shandong, Shandong Climate Center, Jinan 250031, China).
  • Online:2022-03-10 Published:2022-03-11

摘要: 通过相关性分析,确定苹果开花进程中的“花芽萌动”、“高温加速”、“低温迟滞”和春季回暖气候趋势背景等生物学指标,以山东为例,采用逐步回归方法,建立具有生物学意义的预报模型。结果表明:综合考虑相关系数和苹果开花需要的大致时间,日平均气温稳定通过5 ℃初日更适合作为苹果“花芽萌动”的指标;通过相关性分析,确定“高温加速”和“低温迟滞”的气温临界值分别为“日最高气温≥20 ℃”和“日最低气温≤1 ℃”;以不同的积温累计起点和终点,建立动态预报模型,经检验,以3月1日和5 ℃初日为起点的模型预报效果较好,但预报时效并无明显优势;借助于数值预报产品,可以突破实况数据的制约,提高预报服务的主动性和灵活性。

关键词: 苹果, 花期预报, 生物学指标, 数值预报

Abstract: By the correlation analysis, we determined biological indices such as “bud initiation”, “high temperature acceleration”, “low temperature retardation”, and the climate trend background of spring warming. Taking Shandong Province as an example, we established forecast models with biological implications by stepwise regression. The results showed that the first day when daily average temperature steadily passed 5 ℃ is more suitable as the temperature index of “flower bud sprouting” by comprehensive considerations of the correlation coefficient and the number of days required for apple flowering. The critical temperature of “high temperature acceleration” and “low temperature hysteresis” was “daily highest temperature ≥20 ℃” and “daily lowest temperature ≤1 ℃”respectively as found by correlation analysis. Dynamic prediction models were established with different starting point and ending point of accumulated temperature. The prediction effect of the model with accumulated temperature starting point of March 1 and the daily average temperature steadily passed through 5 ℃ is fairly good, but without significant advantage in terms of real prediction effectiveness. With the help of numerical prediction products, the restriction of real data can be overcome, which would improve the initiative and flexibility of forecast services.

Key words: apple, flowering forecast, biological index, numerical prediction.