Abstract:

Maize is the most important crop in Heilongjiang Province, because of the limitation of heat resources, it is essential to sow early to achieve high yield. The study on the prediction method of maize ground temperature and the prediction of suitable maize sowing date could guide the early sowing of maize in field and guarantee maize safety production in the province. Based on the prediction data of temperature, ground temperature and wind speed of 80 weather stations in Heilongjiang from 2007 to 2017, we established a daily prediction model of 10 cm ground temperature in spring sowing period of maize by using multiple regression analysis method, and developed a 10 cm ground temperature prediction system. We used the observation data and forecast data from 2007 to 2012 to carry out the return test, and the observation data and forecast data from 2018 to 2020 to carry out the field application test. The results showed that the prediction of the ground temperature of the day, the next day and the next two days were relatively good. Although the prediction of the ground temperature of the next three days was slightly worse, the prediction of temperature rise and fall trend was accurate. The ground temperature prediction system developed according to the prediction model is easy to operate, and the prediction results could be stored in two ways of graph and table for easy application to business services.

Key words: Maize, Ground Temperature, Multiple Regression, Model, Prediction, System