中文摘要：

[Objective] The paper was to study the application of Fourier transform infrared spectroscopy(FTIR technology) in identification of peanut diseases.[Method] By using FTIR technology,combined with the methods of principal component analysis and hierarchical cluster analysis,the healthy leaves and three kinds of diseased leaves (cercospora black spot,cercospora brown spot and web blotch) were identified in the paper. [Result] IR spectra of both diseased and healthy samples were similar,but tiny differences in wave-numbers and absorption intensities of peaks were observed in the range of 1 750-800 cm-1. Significant differences were found in second derivative spectra in the range of 3 600-2 800 and 1 750-650 cm-1which were selected to perform principle component and hierarchical cluster analysis. Three principal components had the cumulative contribution rate of 94. 9%; the correct rate of principal component analysis for classification was 100% and the correct rate of hierarchical cluster analysis for identification reached 94. 6%. [Conclusion] Fourier transform infrared spectroscopy has a potential to be developed as a powerful means for identification of crop diseases.

英文摘要：

[ Objective] The paper was to study the application d Fourier transform infrared spectroscopy （FTIR technology） in identification of peanut diseases. [Method] By using FFIR technology, combined with the methods of principal component analysis and hierarchical cluster analysis, the healthy leaves and three kinds of diseased leaves （ eereospera black spot, cercospora brown spot and web blotch） were identified in the paper. [ Result ] IR spectra of both diseased and healthy samples were similar, but tiny differences in wave-numbers and absorption intensities of peaks were observed in the range of 1 750 -800 cm-1. Significant differences were found in second derivative speclra in the range of 3 600 - 2 800 and 1 750 -650 cm-1 which were selected to perform principle component and hier- archical cluster analysis. Three principal components had the cumulative contribution rate of 94.9% ; the correct rate of principal component analysis for classifica- tion was 100% and the correct rate of hierarchical cluster analysis for identification reached 94.6%. [ Conclusion] Fourier transform infrared spectroscopy has a tmtential to be develoned as a nowerful means for identification of cren diseases.