基于高光谱技术的铁观音茶叶等级判别

Identification of Tieguanyin Tea Grades Based on Hyperspectral Technology

应用高光谱技术结合支持向量机分类理论对不同等级的铁观音茶叶进行判别分析。采集铁观音各等级茶样的高光谱数据,提取红边幅值、蓝边位置、黄边面积、红谷反射率、归一化植被指数等共20个光谱特征参数,以其作为输入量带入以径向基函数作为核函数的支持向量机分类模型,探讨惩罚参数C和核参数g的最佳取值,构建判别模型,并对其进行验证和评价。结果显示,当惩罚参数C和核参数g分别为106和0.007 5时,所建模型对未知等级的铁观音样品正确判别率可达92.86%,表明应用高光谱技术进行铁观音茶叶等级的快速无损准确鉴别是可行的。

Hyperspectral technology combined with support vector machine(SVM) as a classification theory was applied to identify the grades of Tieguanyin tea. Twenty characteristic spectral parameters were extracted based on the hyperspectral data of tea samples, including red edge amplitude, blue edge position, yellow edge area, red valley reflectivity, normalized difference vegetation indexes, etc. The optimal values for the penalty parameter(C) and the kernel parameter(g) were determined based on the SVM classification model with the radial basis function(RBF) as the kernel function by using these characteristic spectral parameters as the inputs. An identification model for Tieguanyin tea grades was constructed and verified. The best experimental results were obtained using the RBF SVM classifier with C = 106 and g = 0.007 5. The discrimination accuracy rate for unknown Tieguanyin tea samples was 92.86%, suggesting that hyperspectral technology can be utilized for rapid, nondestructive and accurate identification of Tieguanyin tea grades.