Abstract: The growth environment data of autumn tomato in solar greenhouse were collected by sensor technology of agricultural Internet of Things. Through practical research, the early-warning model of stem-based rot of autumn tomato in solar greenhouse was initially established by SPSS Statistics Subscription. The model test effect was good, and the experiment proved that the operation effect of the early-warning model was better in actual production. The establishment of the early warning model fully explored the relationship between soil humidity, air temperature and the occurrence probability of tomato stem base rot, laid a foundation for the establishment of early warning system for tomato diseases and insect pests, and made an exploration for the realization of accurate management of modern agriculture.

Key words: tomato stem base rot, early warning model： agricultural internet of things, solar greenhouse