提出了一种基于近红外漫反射光谱技术的不同产地苹果货架期鉴别方法。从市场上购买山东和陕西的富士苹果各20 个，分别对购买当日和存放1 周(7d)后的样品进行光谱测试，分析表明一周后不同品种样品光谱在1 420nm 和1 630 nm 处吸光度值均有不同程度的增大。通过主成分分析研究了样品产地对不同货架期样品光谱的影响，将总贡献率为97.78%的前15 个特征变量作为输入，建立基于径向神经网络的有监督式近红外光谱不同产地苹果货架期的快速鉴别模型，从四类样品光谱中选择20 个作为预测集。实验结果表明，所建模型对校正集和预测集识别率均为100%，其中18 个预测样品准确率高于93%。本研究为实现不同产地苹果货架期的快速无损检测提供了新方法，具有很好的应用前景及使用价值。

The shelf-life identification method of different origin apples based on near infrared diffuse reflectance spectroscopy at normal atmospheric temperature was proposed. 20 each of the Fuji apple produced in Shandong and Shanxi were bought from the market respectively, and the spectrum of the samples were measured by the purchase date and after the storage of one week (7d). The spectrum of Shandong apple measured at two times were defined as class 1 and class 2, class 3 and class 4 of Shanxi, the absorbance of 1 420 nm and 1 630 nm increased at different degree after the storage of one week. A few preprocessing was compared, and there was litter difference between the sample spectrum analyze by the Principal Component Analysis (PCA) of two kinds. The top 15 variables of the total contribution rate of 97.78% extracted by PCA were input into the radial neural network, and shelf-life identification of different origin apples based on near infrared diffuse reflectance spectroscopy were built. 20 samples in the four classes were chosen as the predicated set. The recognition rates in the calibration set and prediction set were 100%, and the prediction accuracy of 18 samples was higher than 93%. The result shows that a new method proposed by study indicates the shelf-life of different origin apples rapidly.