从玉米籽粒胚的朝向, 中长波漫反射分析和短波透射分析, 进样方式三个方面进行了研究, 通过比较不同的测量方法对品种识别模型性能的影响来选择最佳的玉米单籽粒光谱测量方式, 进而鉴定玉米单籽粒品种真实性。 原始光谱经过预处理后, 使用判别式偏最小二乘法(PLS-DA)对数据进行特征提取和降维, 选取前9个因子建立8个玉米品种的仿生模式识别模型。 结果表明, 玉米籽粒胚正对光源优于胚背对光源, 中长波漫反射分析优于短波透射分析, 小样品池效果好于小光阑。 采用最优测量方法(籽粒胚正对光源, 使用小样品池和中长波漫反射分析)获取玉米单籽粒的近红外光谱, 建立的品种识别模型对本品种样品的平均正确识别率达到94.6%, 对其他品种样品的平均正确拒识率达到96.5%。

In order to establish the better maize variety identification models based on single kernel samples, the near-infrared spectral measurement methods were studied by comparing the direction of the maize seed’s embryo, diffuse reflectance and transmission mode, devices of holding the sample according to their impacts on the performance of variety identification models. Partial least squares-discriminant analysis (PLS-DA) was used to compress the pretreated spectral data into 9 variables, and then the identification models were built based on biomimetic pattern recognition (BPR). The results show that with the maize grain’s embryo facing the light source the models can be made perform better than with embryo backing toward the light source, diffuse reflectance mode is better than transmission mode, and small sample pool performs better than the small aperture. The measurement method of acquiring the diffuse reflectance near infrared spectra of maize by small pool with the seed embryo facing the light source can make models have the best performance. The average correct identification rate of the models is 94.6%, and the average correct rejection rates for the varieties not belonging to the models reached 96.5%.