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农学学报 ›› 2025, Vol. 15 ›› Issue (2): 89-94.doi: 10.11923/j.issn.2095-4050.cjas2024-0074

• 农业信息 农业气象 • 上一篇    下一篇

高淳‘乌牛早’开采期预测

缪颖绮1(), 时冬头1, 任义方2()   

  1. 1 南京市高淳区气象局,南京 211300
    2 江苏省气候中心,南京 210009
  • 收稿日期:2024-04-23 修回日期:2024-12-17 出版日期:2025-02-20 发布日期:2025-02-18
  • 通讯作者:
    任义方,女,1986年出生,江苏苏州人,高级工程师,硕士,研究方向:农业气象服务技术、资源评价、风险区划与保险应用。通信地址:210009 江苏省南京市建邺区双闸街道雨顺路6号 江苏气象中心,E-mail:
  • 作者简介:

    缪颖绮,女,1992年出生,工程师,本科,研究方向:气象服务与应用气象。通信地址:211300 江苏省南京市高淳区淳溪街道宝塔路390号 南京市高淳区气象局,E-mail:

Picking Period Prediction of ‘Wuniuzao’ in Gaochun

MIAO Yingqi1(), SHI Dongtou1, REN Yifang2()   

  1. 1 Gaochun Meteorological Bureau, Nanjing 211300
    2 Jiangsu Climate Center, Nanjing 210009
  • Received:2024-04-23 Revised:2024-12-17 Online:2025-02-20 Published:2025-02-18

摘要:

为实现高淳春茶采摘的“早、新、优、价”,优化高淳地区茶叶采摘时间,助力茶农、茶企降本增效,基于高淳实际情况,建立最适宜有效的开采期预报模型开展高淳春茶开采期相关分析,以应用于实际生产。本研究基于2012—2023年高淳淳青茶园‘乌牛早’首次采摘日序值与同期气象资料,应用积温和逐步回归方法,分别构建积温预报模型和逐步回归预报模型。研究表明,积温预报模型存在较大不确定性,逐步回归预报模型的预报结果与实际相比更为理想,其中1月上旬的日平均气温、1月中旬平均相对湿度、1月中旬日照时数以及2月上旬平均温度小于4℃日数均是影响高淳‘乌牛早’开采期的关键气象因子,预报值与实际误差绝对值大部分在1 d以内,逐步回归预报模型具有实际生产指导作用,可为当地茶农茶企实际采摘提供合理精准建议。

关键词: 高淳, 春茶, 乌牛早, 开采期, 气象因子, 预报模型

Abstract:

In order to realize the best effects of spring tea picking in Gaochun, to optimize the tea picking time, and help tea farmers and tea enterprises to reduce costs and increase efficiency, based on the actual situation in Gaochun, the most suitable and effective forecast model of picking period was established to carry out the relevant analysis of spring tea picking period in Gaochun, so as to apply it into the actual production. Based on the first picking date of 'Wuniuzao' in Gaochun Chunqing Tea Garden from 2012 to 2023 and the meteorological data of the same period, the accumulated temperature and gradual regression methods were applied to construct the accumulated temperature forecast model and the stepwise regression forecast model. Research showed that the product temperature forecast model had great uncertainty, results of stepwise regression forecast model was more comparable with the actual result. The average temperature in the early January, the average relative humidity and sunshine duration in the middle of January, the days that average temperature less than 4℃ in the early February were the key meteorological factors affecting the picking period of 'Wuniuzao'. The absolute error value of forecast result and the actual error were mostly within 1d. Stepwise regression forecast model has actual production guidance, and can provide the local tea farmers and local tea enterprise picking advice.

Key words: Gaochun, spring tea, Wuniuzao, picking period, meteorological factor, forecast model