本文通过时间相关单光子计数法，采用HORIBA Scientific时间分辨荧光光谱仪对食用植物油品种鉴别做了研究，结合DAS6和OriginPro 8.5数据处理软件，实现对山茶油、花生油和葵花籽油的种类鉴别。通过非线性最小二乘法对数据进行拟合，从拟合优度x2和残差分布两个角度确定最佳的拟合方法，从而得到3种食用植物油的荧光寿命，结果发现，山茶油的平均荧光寿命最长，花生油的荧光寿命最短，而葵花籽油的荧光寿命与花生油的荧光寿命相差0.11 ns，并通过山茶油-花生油-葵花籽油混合油样进行了掺杂对比试验，从而证明了荧光寿命分析法识别植物油种类的方案具有可行性。此方法的优点在于利用荧光寿命分析法可以避免光源波动、外界杂散光的影响，因此荧光寿命分析法对植物油的种类鉴别表现出更好的检测精度和准确度，检测结果准确可靠，为植物油品种鉴别提供了一种新思路。

The ability to identify types of vegetable oils by using a time-correlated single photon counting method and a HORIBA Scientific time-resolved spectrofluorometer was investigated. In combination with the data-processing software applications DAS6 and OriginPro8.5, camellia oil, peanut oil, and sunflower seed oil were successfully identified. Data fitting was performed using nonlinear least squares method, the optimal fitting method was determined by the goodness-of-fit (x2) and residual distribution, and the fluorescence lifetimes of three edible vegetable oils were obtained. The experimental results showed that the longest and shortest fluorescence lifetimes were presented by camellia oil and peanut oil, respectively, and the difference between sunflower oil and peanut oil was only 0.11 ns. Subsequently, a comparison test was performed with a mixture of camellia oil, peanut oil, and sunflower oil, to prove the feasibility of the fluorescence lifetime analysis method to identify types of vegetable oils. This method avoids the effects of light source fluctuation and external stray light, and can therefore provide better precision and accuracy in the identification of vegetable oils, with reliable results. This study provides a new approach for the identification of vegetable oils.

国家自然科学基金面上项目（31271874）；江苏高校优势学科建设工程资助项目