Noninvasive glucose detection is highly required for more convenient and less pain glycaemic monitoring. Most of currently used methods are invasive. In this paper, a near-infrared reflectance spectroscopy (NIRS) is proposed to detect blood glucose to protect patient absent of pain. NIRS is a safe, simple and efficient technology applied in many fields. Experiments, based on Oral Glucose Tolerance Test (OGTT), were conducted to collect data modeling with partial least squares (PLS) regression. 42 samples of fingertip blood and palm were measured by commercially available blood glucose meter and NIRS separately at the same time. The glucose concentration range is between 5 and 12 mmol·L-1. With leave-one-out cross-validation, we obtained a result of root mean square error of cross-validation (RMSECV) of 1.16 mmol·L-1 for all the data. With the pre-processing methods of normalization and un-informative variables elimination reducing noise and eliminating some additional effects, we get a better result of 0.79 mmol·L-1. A RMSECV of 0.41 mmol·L-1 for individual modeling is much less than the total modeling. It has a broad application prospect in individual customization.