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中国农学通报

中国农学通报 ›› 2026, Vol. 42 ›› Issue (11): 102-106.doi: 10.11924/j.issn.1000-6850.casb2025-0593

• 资源·环境·生态·土壤·气象 • 上一篇    下一篇

半干旱区春小麦条锈病发生发展与气象条件关系研究

薛潇1(), 刘小娟2, 张红兵3(), 杨维俊4, 雷俊3, 焦润安1, 武艳娟5   

  1. 1 甘肃省通渭县气象局， 甘肃通渭 743300
    2 定西市植保与植检站， 甘肃定西 743000
    3 甘肃省定西市气象局， 甘肃定西 743000
    4 定西市农业技术推广站， 甘肃定西 743000
    5 甘肃省平凉市气象局， 甘肃平凉 744000
  • 收稿日期:2025-07-15 修回日期:2026-03-24 出版日期:2026-06-12 发布日期:2026-06-12
  • 通讯作者:
    张红兵，女，1969年出生，甘肃定西人，高级工程师，本科，主要从事农业气象服务与试验研究。通信地址：743000 甘肃省定西市安定区气象新村50号，Tel：0932-8223247，E-mail：。
  • 作者简介:

    薛潇，女，1997年出生，甘肃定西人，助理工程师，本科，主要从事地面气象观测与农业气象服务工作。通信地址：743300 甘肃省定西市通渭县西街57号，Tel：0932-5552304，E-mail：。

Relationship Between Occurrence and Development of Spring Wheat Stripe Rust and Meteorological Conditions in Semi-arid Areas

XUE Xiao1(), LIU Xiaojuan2, ZHANG Hongbing3(), YANG Weijun4, LEI Jun3, JIAO Run’an1, WU Yanjuan5   

  1. 1 Tongwei Meteorological Bureau, Tongwei, Gansu 743300
    2 Dingxi Station of Plant Protection and Quarantine, Dingxi, Gansu 743000
    3 Meteorological Bureau of Dingxi of Gansu Province, Dingxi, Gansu 743000
    4 Agricultural Technology Extension Station of Dingxi City, Dingxi, Gansu 743000
    5 Meteorological Bureau of Pingliang of Gansu Province, Pingliang, Gansu 744000
  • Received:2025-07-15 Revised:2026-03-24 Published:2026-06-12 Online:2026-06-12

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摘要：

为保障小麦安全生产，本研究基于2008—2017年定西市安定区春小麦条锈病发病率资料，结合同期气象及小麦农业气象观测数据，利用数理统计方法，分析了条锈病的发生发展特征及其与气象因子的关系，并运用逐步回归方法建立了春小麦条锈病预测模型。结果表明：近年来，春小麦各典型发育期出现时间变化幅度较大，其中出苗期最早和最晚日期相差36 d，乳熟期次之，相差19 d；春小麦条锈病的发病时间与典型发育期无显著相关性；近10 a，春小麦条锈病发病率呈逐年下降趋势，线性变化速率为 -0.25/10 a(P>0.05)；春小麦条锈病发病率与夏、秋、冬季平均气温呈负相关，与春季气温呈正相关；与降水量总体呈正相关，其中与冬季降水的相关性最显著，相关系数为0.663(P<0.05)；发病率与日照时数主要表现为负相关，即日照时数增多，条锈病发病率降低，其中与5月日照时数的相关性最高，为-0.599，但未达显著水平；不同时段的空气湿度与条锈病发病率的相关性表现不一致。基于气温、降水、日照时数和湿度等数据建立的春小麦条锈病气候预测模型，在实际应用中效果较好。研究结果为条锈病发生发展气象风险预警、病害防治及科学决策提供重要依据。

关键词: 春小麦, 发育期, 条锈病, 气候要素, 预测模型, 生长季, 发病面积

Abstract:

To ensure safe wheat production, based on the incidence data of spring wheat stripe rust in Anding District, Dingxi City from 2008 to 2017, combined with concurrent meteorological and agro-meteorological observation data of spring wheat, the occurrence and development characteristics of stripe rust and its relationship with meteorological factors were analyzed by statistical methods. A prediction model of spring wheat stripe rust was established using stepwise regression analysis. The results showed that in recent years, the timing of typical growth stages of spring wheat varied considerably, with a difference of 36 days between the earliest and latest emergence dates, followed by a 19-day difference for the milk-ripening stage. The onset time of spring wheat stripe rust showed no significant correlation with the typical growth stages. Over the past decade, the incidence of spring wheat stripe rust exhibited a decreasing trend, with a linear change rate of -0.25/10 a (P > 0.05). The incidence was negatively correlated with the mean air temperature in summer, autumn, and winter, but positively correlated with spring temperature. A positive correlation was generally observed with precipitation, with the strongest correlation occurring in winter (r = 0.663, P < 0.05). The incidence was mainly negatively correlated with sunshine duration; increased sunshine was associated with lower disease incidence. The strongest correlation was with sunshine duration in May (r = -0.599), although it did not reach statistical significance. Correlations between air humidity and disease incidence varied across different periods. A climate prediction model for spring wheat stripe rust was established using temperature, precipitation, sunshine duration, and humidity data, and it performed well in practical applications. These findings provide an important basis for forecasting the occurrence and development of stripe rust, predicting meteorological risk levels, and supporting scientific decision-making in disease control.

Key words: spring wheat, growth stage, spring wheat stripe rust, climatic element, forecast model, growing season, stripe rust affected area

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