近年来，随着恐怖活动的加剧，无损检测密闭容器或者密闭包装内液体是否含有爆炸液体对于安检部门是一个很大的挑战，这个问题也是市场销售环节食品质量检测的难点。本课题提出一种适用于瓶装复杂混合溶液（如红酒）无损测量的拉曼光谱检测方法。在修正的空间偏移拉曼光谱理论的基础上与复杂混合溶液的拉曼光谱信号处理方法相结合，实现透明、有色的玻璃密封瓶内红酒成分的测量。本课题首先根据双层物质拉曼散射方程及蒙特卡罗原理建立修正的空间偏移拉曼光谱模型，获得拉曼散射强度与空间位移的关系，为空间偏移拉曼光谱系统的搭建奠定理论基础。根据葡萄酒拉曼光谱的特点，通过滤波、平滑和扣除基线等数据处理，并在主流定量回归分析的基础上，进行光谱分离以及重建，实现红酒中酒精、总糖的浓度测量。在此基础上，开发空间偏移拉曼光谱检测系统，推动空间偏移拉曼光谱技术在食品药品安全领域中的应用。

The non-invasive detection of liquid explosives through containers or packaging represents a considerable analytical challenge of societal imporatance given the hieghtened terrorist threat in recent years，it is also the need of food security on the market. We present a Raman spectroscopic method for the noninvasive detection of liquid mixture (wine) within container. The approach used near infrared Fourier Transform Raman Signal processing based on a modification of the Spatially Offset Raman Spectroscopy (SORS) concept, which permits the interrogation of the transparent, colored containers. We present a Monte Carlo model, which we use to calculate the depth dependent sensitivity or sampling volume of different single fiber and multi-fiber Raman probes. A two-layer model is employed to investigate the dependency of the sampling volume on the absorption and reduced scattering coefficients in the near infrared (NIR) wavelength range. Followed by filtering, smoothing, subtracting baseline, other data processing and multivariate calibration method based on partial least squares regression (PLSR), the concentration of alcohol and sugar in wine can be measured. So the SORS system can be developed based on the Monte Carlo model and PLSR model. The aim of this research is to extend the application of SORS for investigation of liquid samples in container at food and drug safety.