Stripe rust is one of the main diseases that affects the production of winter wheat in China. The disease information was detected early in the winter wheat infection, and it is of great significance to prevent and control the disease and improve the yield and quality of winter wheat. The reflectance spectrum can reflect the change of concentration information of vegetation biochemical components, but it is greatly affected by the background noise, while the canopy solarinduced chlorophyll fluorescence (SIF) is less affected by the background noise and has certain photosynthetic physiological diagnosis capabilities. In order to study the feasibility of early detection of winter wheat stripe rust by SIF, the canopy SIF data was extracted based on two methods: 3band Fraunhofer line discrimination (3FLD) and reflectance fluorescence index. In order to explore the advantages of SIF in the early detection of wheat stripe rust, some SI sensitive to wheat stripe rust were obtained for comparison. The sensitivity of SIF and SI to wheat stripe rust early disease index (DI) was analyzed through correlation, and then the sensitive SIF and SI were used to construct the early wheat stripe rust spectrum detection model based on the partial least squares (PLS). The results showed that the fluorescence index SIF-A, ρ440/ρ690, ρ675ρ690/ρ2683, ρ690/ρ655, ρ690/ρ600, DλP/D744, D705/D722 extracted based on the radiance and reflectance method all had very significant correlation to the severity of wheat stripe rust, the correlation coefficients were -0.793, -0.523, -0.539, -0.497, 0.541, 0.446 and 0.490, respectively, which can be used as the chlorophyll fluorescence characteristic parameters for detection of winter wheat stripe rust. Based on the three sets of data, the determination coefficients of the PLS-SIF test model were 0.801, 0.772 and 0.807, respectively, and the root mean square errors were 3.3%, 3.1% and 3.2%, which were 27% at least higher than that of the SI-PLS model determination coefficients. The error was reduced by at least 24%. Therefore, canopy SIF data was more suitable for early detection of the severity of winter wheat stripe rust. The research results had important application value for timely prevention and control of winter wheat stripe rust, and provided a reference for the use of satellite fluorescence data for largearea, nondestructive detection of wheat stripe rust in the early stage.