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农学学报 ›› 2025, Vol. 15 ›› Issue (10): 83-91.doi: 10.11923/j.issn.2095-4050.cjas2025-0024

• 农业信息农业气象 • 上一篇    下一篇

黔南地区辣椒气象产量变化特征及预测模型

龙宇芸1(), 姜欢2, 姜雨函3, 高红梅1(), 杨仁翠4   

  1. 1 黔南州气象局, 贵州都匀 558000
    2 都匀市气象局, 贵州都匀 558000
    3 黑龙江省生态气象中心, 哈尔滨 150030
    4 黔南州农业农村局, 贵州都匀 558000
  • 收稿日期:2025-02-08 修回日期:2025-05-28 出版日期:2025-10-17 发布日期:2025-10-17
  • 通讯作者:
    高红梅,女,1985年出生,贵州都匀人,高级工程师,本科,主要从事应用气象研究。通信地址:55800 贵州省都匀市文峰街道文化路25号黔南州气象局,E-mail:
  • 作者简介:

    龙宇芸,女,1997年出生,贵州施秉人,助理工程师,硕士,研究方向:应用气象。通信地址:55800贵州省都匀市文化路文峰街道25号黔南州气象局,E-mail:

  • 基金资助:
    2023—2025贵州省气象局省市联合科研基金项目(黔气科合SS[2023]37号)

Characteristics of Pepper Meteorological Yield Variation and Prediction Model in Qiannan Region

LONG Yuyun1(), JIANG Huan2, JIANG Yuhan3, GAO Hongmei1(), YANG Rencui4   

  1. 1 Qiannan Prefecture Meteorological Bureau, Duyun Guizhou 558000
    2 Duyun Meteorological Bureau, Duyun Guizhou 558000
    3 Heilongjiang Ecological Meteorological Center, Harbin 150030
    4 Qiannan Agricultural and Rural Affairs Bureau, Duyun Guizhou 558000
  • Received:2025-02-08 Revised:2025-05-28 Online:2025-10-17 Published:2025-10-17

摘要:

本研究旨在深入剖析黔南地区辣椒气象产量的时间序列动态关系,为黔南地区辣椒种植业的生产规划、气候适应性分析及未来产量预估等工作提供坚实的理论依据。采用一次指数平滑法、二次指数平滑法、三年滑动平均法与HP滤波法,对黔南地区2013—2022年的辣椒单位产量数据进行分解,将其分离为辣椒趋势产量和气象产量。通过相关分析,筛选影响辣椒产量的主要气象因子,进而利用逐步回归模型构建辣椒气象产量预测模型。研究结果表明:(1)4种不同的产量分离方法均较好地反映气象产量序列与黔南气象灾害变化一致性特点,其中一次指数平滑法分离的趋势产量能够高效地捕捉到产量中较为剧烈的波动部分;(2)在辣椒气象产量预测模型中,除都匀和贵定外,其余县(市)的辣椒气象产量预测模型R2在0.728(龙里)~0.998(福泉),且均通过99%的信度检验。除平塘、三都、福泉和都匀外,其余县(市)基于气象因子构建的预测模型在模拟辣椒产量方面表现较好,且模型精度及预测准确率较高,可应用于辣椒产量估算。

关键词: 黔南地区, 辣椒趋势产量, 气象产量, 产量分离方法, 预测模型

Abstract:

The study aims to explorethe time series dynamic relationship between meteorological conditions and the yield of chili peppers in the Qiannan region,and lay a solid theoretical foundation for production planning, climate adaptability analysis, and future yield prediction of the chili pepper industry in this area. Four methods, namely the single exponential smoothing method, the quadratic exponential smoothing method, the 3-year moving mean method, and the HP filtering method, were adopted to separate the unit yield data of peppers in Qiannan region from 2013 to 2022 into the trend yield and meteorological yield of peppers. Through correlation analysis, the main meteorological factors affecting yield of pepper were screened out. Subsequently, a stepwise regression model was used to construct a prediction model for the meteorological yield of peppers. According to research findings, (1) four different methods for separating yield all effectivelyreflected the consistency characteristics of the meteorological yield sequence and the changes in meteorological disasters in Qiannan. Among them, the trend yield separated by the single exponential smoothing method could efficiently capture the more intense fluctuation parts in the yield; (2) in the meteorological yield prediction model of peppers, except for Duyun and Guiding, the R2 of the meteorological yield prediction model of peppers in the other counties ranged from 0.728 (Longli) to 0.998 (Fuquan), and all passed the 99% confidence test. Except for Pingtang, Sandu, Fuquan and Duyun, the prediction models based on meteorological factors constructed for the remaining counties performed well in simulating the yield of peppers, and the model accuracy and prediction accuracy were relatively high, which can be applied to the estimation of pepper yields.

Key words: Qiannan region, pepper trend yield, meteorological yield, yield separation method, prediction model