利用傅里叶变换红外光谱技术结合主成分分析(PCA)及系统聚类分析(HCA)对不同葡萄品种苗的叶片进行鉴别研究。结果表明五个不同葡萄品种苗红外光谱整体相似,但在1800~750 cm^-1范围内吸收峰的位置、峰形及吸收强度有一定差异。选取该范围内的二阶导数光谱数据做主成分分析和聚类分析,前三个主成分累计贡献率达到94.9%,其分类正确率达100%;而聚类分析,其正确率达到96%。结果表明傅里叶变换红外光谱结合统计方法能够很好地鉴别五个不同品种的葡萄苗,有望发展成为鉴别农作物品种的有力手段。

Fourier transform infrared(FTIR)spectroscopy combined with principal component analysis(PCA)and hierarchical cluster analysis(HCA)was used to identify the leaves of different grapevine cultivars seedlings.The results showed that the infrared spectra of five varieties were similar,but tiny differences in wave-numbers and absorption intensities of peaks were observed in the range of 1800~750 cm^-1.The second derivative spectra in the range of 1800~750 cm^-1 were selected to perform principle component analysis and hierarchical cluster analysis,the first three principle components had the cumulative contribution rate of 949%,and yield classification accuracies of 100%;whereas hierarchical cluster analysis accuracies is 96%.It is proved that FTIR spectroscopy combined with statistical analysis could identify five different grapevine cultivars seedlings,and has a potential to be developed as a powerful means for identifying crop cultivars.