Yellow rust (Puccinia striiformis f. sp. tritici) on winter wheat (Triticum aestivum L.) has resulted in significant reductions in the yield losses and wheat grain quality. It is extremely important to quantitatively detect and assess such a serious disease rather than visual qualitative description. In comparison with traditional diagnosis method, remote sensing has proven to be a cost-effective tool to achieve such a goal. In this study, we used yellow rust in winter wheat to illustrate the capability of estimating the infection index in different leaf layers of the plant using hyperspectral measurements on individual wheat diseased leaves. The analysis results indicated that the severities showed a gradual increasing trend from F-1 (F=Flag leaf) to F-3, while the relative chlorophyll and nitrogen showed an inverse change. The spectral reflectance gradually increased from F-1 to F-3 in the visible and short-wave infrared (SWIR) regions, while it was the very reverse in the near-infrared (NIR) region. In addition, an integral spectral index -yellow rust spectral index (YRSI) was constructed to quantitatively estimate the disease using the most sensitive bands in the visible (704 nm), NIR (1423 nm) and SWIR (1926 nm) regions. The coefficient of determination (R 2 ) reaches 0.88 between the disease severity (DS%) and YRSI, which shows that the index can be suitable and effective to estimate the infection severity for a wheat plant.