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中国农学通报

中国农学通报 ›› 2023, Vol. 39 ›› Issue (23): 55-61.doi: 10.11924/j.issn.1000-6850.casb2022-1043

所属专题： 资源与环境

• 资源·环境·生态·土壤·气象 • 上一篇    下一篇

基于关键气象因子的柴达木枸杞产量预报模型研究

雷玉红1(), 李春晖1, 妥淑贞1, 张英德1, 马秀兰1, 高成忠1, 钟存2, 颜亮东3   

  1. 1青海省格尔木市气象局，青海格尔木 816099
    2青海省贵德县气象局，青海贵德 811799
    3青海省气象科学研究所，西宁 810001
  • 收稿日期:2022-12-09 修回日期:2023-02-05 出版日期:2023-08-15 发布日期:2023-08-10
  • 作者简介:

    雷玉红，女，1976年出生，青海湟源人，副高级工程师，大专，主要从事农业气象与生态环境方向研究。通信地址：816099 青海省格尔木市气象局，Tel：0979-8492569，E-mail：。

  • 基金资助:
    青海省防灾减灾重点实验室开放基金重点攻关项目“柴达木盆地温棚作物观测试验与气象服务指标研究”(QFZ-2021-G05); 国家自然基金项目“高寒枸杞花蕾期低温冷害指标研究”(41765008)

Study on the Yield Forecast Model of Qaidam Lycium Barbarum based on Key Meteorological Factors

LEI Yuhong1(), LI Chunhui1, TUO Shuzhen1, ZHANG Yingde1, MA Xiulan1, GAO Chengzhong1, ZHONG Cun2, YAN Liangdong3   

  1. 1Qinghai Golmud Meteorological Bureau, Golmud, Qinghai 816099
    2Qinghai Guide Meteorological Bureau, Guide, Qinghai 811799
    3Qinghai Academy of Meteorological Sciences, Xining 810001
  • Received:2022-12-09 Revised:2023-02-05 Published:2023-08-15 Online:2023-08-10

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摘要：

选取柴杞主产区内各台站2011—2020年枸杞生育期观测数据及1991—2019年枸杞生育期气温、降水、日照等气象要素及枸杞产量数据，应用逐步回归、概率统计、图表分析法等统计方法进行基于关键气象因子的柴达木枸杞产量预报模型研究，结果表明：（1）影响枸杞产量的发育时段分别为展叶、老眼枝开花、春梢开花、老眼枝果成熟、秋梢开花、夏果成熟及秋果成熟期。（2）根据田间土壤墒情及早灌溉头遍水，促进展叶；日最高气温超过25℃时开花授粉将受到不利影响，落花率增高；日照强、日照时间长有利于果实成熟，风力大、大风日数多容易造成落果；连阴雨天气容易诱发黑果病，降低枸杞产量和品质；晴天有利于采收和晾晒。（3）通过0.01显著检验的气象因子与产量建立的枸杞产量预报模型，检验2019年的产量，准确率达到了91.8%，相对误差为8.2%，充分说明，选取的气象要素，能够较准确的预报该地区的枸杞产量，预报精度较好，可以在实际预报业务中应用。（4）在进行枸杞产量预报服务时，若出现气象要素以外其他影响因子出现较大变化时，应考虑趋势产量的显著变化，结合实地调研调整模型的预报结果，以进一步提高预测准确度。

关键词: 枸杞发育时段, 关键气象因子, 枸杞产量, 预报模型研究

Abstract:

This paper used the meteorological data of lycium barbarum growing period from 2011 to 2020, and meteorological factors such as temperature, precipitation, sunshine and lycium barbarum production data from 1991 to 2019 in the main production area, and applied statistical methods such as stepwise regression, probability statistics, and chart analysis to study the forecasting model of lycium barbarum production based on key meteorological factors. The results showed that: (1) the growing periods which affected lycium barbarum production were leaf expansion, old eye branch flowering, spring branch flowering, old eye branch fruit ripening, autumn branch flowering, summer fruit ripening and autumn fruit ripening. (2) According to the soil moisture in the field, the first layer of water should be irrigated as early as possible to promote leaf expansion; when the daily maximum temperature exceeded 25℃, flowering and pollination would be adversely affected, and the rate of falling flowers increased; strong sunshine and long sunshine were conducive to fruit ripening, while strong wind and many windy days were easy to cause fruit falling; continuous overcast and rainy weather could easily induce black fruit disease and reduce the yield and quality of wolfberry; sunny day was good for harvesting and drying. (3) The prediction model of lycium barbarum established by 0.01 significant tests of meteorological factors and yield was used to test the yield in 2019, the accuracy rate reached 91.8%, and the relative error was 8.2%. It fully showed that the selected meteorological factors could accurately predict the yield of lycium barbarum in the region, with good forecasting accuracy, and could be applied in actual forecasting operations. (4) During the forecasting service of lycium barbarum yield, if there were significant changes in other influencing factors other than meteorological factors, the significant changes in trend yield should be considered, and the forecast results of the model should be adjusted in combination with the field survey to further improve the forecast accuracy.

Key words: growing period of Lycium barbarum, key meteorological factors, lycium barbarum production, prediction model research