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| 咸阳市冬小麦病虫害气象风险预报技术研究 |
| Techniques for Meteorological Risk Forecasting of Diseases and Pests in Winter Wheat in Xianyang |
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| DOI： |
| 中文关键词: 冬小麦 病虫害 气象因子 相关性 风险预报 |
| 英文关键词:Winter Wheat Diseases and pests Meteorological factors Correlation Risk forecasting |
| 基金项目: |
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| 摘要点击次数: 648 |
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| 中文摘要: |
| 条锈病、赤霉病、蚜虫和红蜘蛛是冬小麦常见病虫害，本研究利用2014-2024年咸阳市12个气象站气温、降水量、日照时数、相对湿度作为自变量，对咸阳地区冬小麦条锈病、赤霉病、蚜虫和红蜘蛛发生发展趋势进行预测分析，探究冬小麦病虫害气象风险预报技术。利用Pearson相关性分析，计算气象因子与四种病虫害发生面积的相关性，选取通过相关性分析验证的气象因子，通过多元线性回归方程建模并进行检验。验证结果表明：模型预测的发生面积与实际差值在0至1.07万hm2之间，预测准确率为93.2%，预测等级与实际等级差的绝对值最大为1，无极端错误现象，可以满足农业部门对冬小麦病虫害精细化气象预测的需求。 |
| 英文摘要: |
| The major diseases and pests affecting winter wheat include stripe rust, Fusarium head blight, aphids, and red spider mites. This study utilized data on temperature, precipitation, sunshine duration, and relative humidity from 12 meteorological stations in Xianyang , covering the period from 2014 to 2024, as independent variables to analyze and predict the development trends of these diseases and pests. The objective is to develop meteorological risk forecasting techniques for winter wheat pests and diseases. Pearson correlation analysis was conducted to examine the relationships between meteorological factors and the affected areas of the two major diseases and two key pests. Significant meteorological variables identified through the correlation analysis were used to construct multiple linear regression models, which were subsequently validated. The validation results indicated that the predicted affected areas deviated from the actual values by 0 to 10.7 thousand hectares, with an accuracy rate of 93.2%. The maximum absolute difference between the predicted and observed severity levels was 1 (on a standardized scale), with no extreme errors, thereby satisfying the demand of the agricultural sector for accurate meteorological forecasts concerning winter wheat diseases and pests. |
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