为向安徽砀山地区酥梨果农提供精准的气象预报服务，本文采用2017—2023年3—4月砀山县梨树集中种植区域的A、B、C、D、E共5个果园每日最低温度数据和砀山县国家基本气象观测站每日最低气温数据，通过一元一次线性回归方程建立酥梨花期果园最低温度气象预报模型，并利用该模型对2024年3—4月酥梨花期果园最低温度进行检验。结果表明，A、B、C、D、E共5个果园最低温度预报模型分别为y _A=0.917 6x _A-1.164 9，y _B=0.908 6x _B-0.342 6，y _C=0.984 1x _C-1.792 1，y _D=0.974 7x _D-0.314 6，y _E=0.928 4x _E-0.547 1，其中x为砀山每日最低气温预报值，y为果园每日最低温度预报值。模型检验R ²均大于0.8，表明模型预报效果较好；5个果园最低温度预报模型的平均绝对误差分别为1.6、1.2、1.4、0.6和1.2 ℃，均小于2 ℃，且比使用砀山县国家基本气象观测站最低气温作为果园最低温度预报的平均绝对误差更小，预测更精准。预报结果与实况的平均绝对误差分别为1.4、1.1、1.2、0.8和1.1 ℃，均小于2 ℃，且比使用砀山最低气温预报值作为果园最低温度预报值的平均绝对误差更小，预测更精准。说明该预报模型使用便捷，预报效果较好，可应用于实际气象预报业务。本文为提高区域日最低温度预报精准度提供参考。

To provide accurate meteorological forecasting services to crisp pear farmers in Dangshan County, Anhui Province, this article uses daily minimum temperature data from 5 orchards, A, B, C, D, and E, in the concentrated pear planting area of Dangshan County from March to April of 2017 to 2023, as well as daily minimum temperature data from the Dangshan National Basic Meteorological Observation Station. A simple linear regression equation was used to establish a meteorological forecasting model for the minimum temperature of crisp pear orchards during the flowering period, and this model was used to test and forecast the minimum temperature of crisp pear orchards during the flowering period in March to April 2024. The results showed that the 5 minimum temperature prediction models for orchards A, B, C, D, and E were as follows: y _A=0.917 6x _A-1.164 9，y _B=0.908 6x _B-0.342 6，y _C=0.984 1x _C-1.792 1，y _D=0.974 7x _D-0.314 6，y _E=0.928 4x _E-0.547 1, where x was the daily minimum temperature forecast value for Dangshan, and y was the daily minimum temperature forecast value for the orchard. The R ² values of the model tests were all greater than 0.8, indicating that the model had a good forecasting effect; the average absolute errors of the 5 minimum temperature prediction models for orchards were 1.6, 1.2, 1.4, 0.6, and 1.2 ℃, respectively, all of which were less than 2 ℃, and the average absolute error was smaller and more accurate than using the minimum temperature of Dangshan National Basic Meteorological Observatory as the minimum temperature prediction for orchards. The average absolute errors between the forecast results and the actual situation were 1.4, 1.1, 1.2, 0.8, and 1.1 ℃, respectively, all of which were less than 2 ℃, and were smaller than the average absolute error of using the lowest temperature forecast value of Dangshan as the lowest temperature forecast value for orchards, making the prediction more accurate. This indicates forecasting model for the orchard is convenient to use, has good forecasting effects, and can be applied to practical meteorological forecasting operations. This article provides a reference for improving the accuracy of regional daily minimum temperature forecasting.