中国农业气象 ›› 2026, Vol. 47 ›› Issue (7): 1133-1145.doi: 10.3969/j.issn.1000-6362.2026.07.011

• 农业生物气象栏目 • 上一篇    下一篇

基于气候适宜度的贵州春茶品质评估和等级评价

张波,古书鸿,胡家敏,于飞,蒋梓烨,吴俨,孙思思   

  1. 1. 贵州省生态与农业气象中心,贵阳 550002;2. 贵州省山地气象科学研究所,贵阳 550081;3. 贵阳学院,贵阳 550005
  • 收稿日期:2025-05-28 出版日期:2026-07-22 发布日期:2026-07-21
  • 作者简介:张波,E-mail:zzbzhangbo@126.com
  • 基金资助:
    贵州省基础研究计划(自然科学类)项目(黔科合基础-ZK〔2023〕一般230);贵州省气象科技创新团队“农业气象服务关键技术研究”项目(黔气科合TD〔2024〕06号);贵州省第六批千层次人才贵阳市入选对象培养项目(筑科合同-GCC〔2022〕005)

Climate Quality Assessment and Grade Evaluation of Spring Tea in Guizhou Based on Climate Suitability Index

ZHANG Bo, GU Shu-hong, HU Jia-min, YU Fei, JIANG Zi-ye, WU Yan, SUN Si-si   

  1. 1. Guizhou Ecological and Agrometeorological Center, Guiyang 550002, China; 2.Guizhou Institute of Mountain Meteorology Science, Guiyang 550081; 3. Guiyang University, Guiyang 550005
  • Received:2025-05-28 Online:2026-07-22 Published:2026-07-21

摘要:

基于贵州省83个气象台站1961−2025年逐日气象数据,结合湄潭、花溪、凤冈、桐梓、道真、正安和都匀7春茶采样点,2013年、2016年、2018年、2021年和2023年的春茶酚氨比数据,运用模糊数学、逐步回归以及高斯混合模型等方法设置7个春茶采摘前置时段(采摘前3d、采摘前5d、采摘前7d、采摘前9d、采摘前11d、采摘前13d和采摘前15d),分别计算各时间段平均气候适宜度,通过相关分析筛选酚氨比关键影响因子,构建春茶逐日气候适宜度模型和酚氨比模拟模型,开展春茶品质模拟与气候品质评价结果表明1961−2024贵州春茶期气候适宜度数值范围在0.620.81,93%的站点呈递增趋势,其中37%站点呈显著递增(P<0.05);空间上呈自南向北、自东向西递减趋势春茶采摘前15d平均气候适宜度是影响酚氨比的关键因子。细化采摘前15d5个连续子时段,共同构建酚氨比模拟模型,模型训练集和测试集的模拟精度良好(P=0.009)。以采摘前15d综合平均气候适宜度及酚氨比模拟值为基础,通过高斯混合聚类确定春茶气候品质评价阈值与等级,采摘前15d综合平均气候适宜度>0.75或酚氨比模拟值≤4.98为特优,采摘前15d综合平均气候适宜度0.67~0.75或酚氨比模拟值4.98~5.78为优,采摘前15d综合平均气候适宜度在0.56~0.67或酚氨比模拟值5.78~6.40为良,采摘前15d综合平均气候适宜度≤0.56或酚氨比模拟值>6.40为一般。研究结果可为春茶气候品质评价以及采摘期调控提供参考。

关键词: 贵州春茶, 采摘期, 气候适宜度, 逐步回归, 气候品质评价

Abstract:

Based on the daily meteorological data from 83 weather stations in Guizhou province from 1961 to 2025 and the ratio of tea polyphenol content to amino acid content (TP/AA) of spring tea collected from seven sampling sites (Meitan, Huaxi, Fenggang, Tongzi, Daozhen, Zheng'an and Duyun) for the years 2013, 2016, 2018, 2021 and 2023, this study employed methodologies including fuzzy mathematics, stepwise regression and Gaussian mixture models. Seven pre−harvest periods (3d, 5d, 7d, 9d, 11d, 13d and 15d prior to harvesting) were established. The average climate suitability index for each period was calculated. Key factors affecting TP/AA were screened by correlation analysis, enabling the simulation of spring tea quality and climate quality assessment. The results showed that the climate suitability for the spring tea season in Guizhou province from 1961 to 2024 ranged from 0.62 to 0.81. Overall, there was an increasing trend over time, with 93% of stations showing an increasing trend and 37% of stations showing a significant increase (P<0.05). The spatial distribution showed a decreasing trend from south to north and from east to west in Guizhou. Average climate suitability 15d before harvesting was identified as the major factor affecting the phenol to amino acid ratio. By further dividing the 15-day pre-harvest period into five consecutive sub-periods, a TP/AA simulation model was jointly constructed, which demonstrated good simulation accuracy for both the training and test sets (P=0.009). Based on the comprehensive climate suitability index and simulated phenol to amino acid ratio, Gaussian mixture clustering was employed to establish thresholds and grades for evaluating the climatic quality of spring tea: comprehensive index>0.75 or simulated ratio≤4.98 as superior, 0.67<comprehensive index≤0.75 or 4.98<simulated ratio≤5.78 as excellent, 0.56<comprehensive index≤0.67 or 5.78<simulated ratio≤6.40 as good and comprehensive index≤0.56 or simulated ratio>6.40 as common. These results provide a scientific basis for climate−based quality evaluation and harvest timing regulation of spring tea.

Key words: Guizhou spring tea, Pre?harvest period, Climate suitability, Stepwise regression, Climate quality evaluation