[FTIR study on the leaf spots, near-spot and normal tobacco leaves].

Fourier transform infrared spectroscopy (FTIR) was used to study three group tobacco leaves of brown spot, angular spot and weather speck, with each group being composed of three samples, namely, leaf spots, near-spot and normal tobacco leaves. The results indicate that the absorption ratio A1631/A1025 of the three group tobacco leaves showed the same change tendency, with the normal tobacco leaves < the near-spot leaves < the leaf spots. For a more objective and comprehensive analysis, the original and second-derivative spectra were selected for distance analysis in the whole region. The results show that the Pearson correlation coefficient of the near-spot leaves and normal leaves is greater than the corresponding coefficient of leaf spots and normal leaves, which suggest that the near-spot leaves and normal leaves have a closer relationship compared with the leaf spots and normal leaves. The ratios of the A1631/A1025 and Pearson correlation coefficients show that the chemical composition of the near-spot leaves changed gradually, that is, the near-spot leaves were in a transient state between normal and disease leaves. In conclusion, FTIR spectroscopy is a promising technique for diagnosing tobacco disease in the incubation period.

[A study of Boletus bicolor from different areas using Fourier transform infrared spectrometry].

It is hard to differentiate the same species of wild growing mushrooms from different areas by macromorphological features. In this paper, Fourier transform infrared (FTIR) spectroscopy combined with principal component analysis was used to identify 58 samples of boletus bicolor from five different areas. Based on the fingerprint infrared spectrum of boletus bicolor samples, principal component analysis was conducted on 58 boletus bicolor spectra in the range of 1 350-750 cm(-1) using the statistical software SPSS 13.0. According to the result, the accumulated contributing ratio of the first three principal components accounts for 88.87%. They included almost all the information of samples. The two-dimensional projection plot using first and second principal component is a satisfactory clustering effect for the classification and discrimination of boletus bicolor. All boletus bicolor samples were divided into five groups with a classification accuracy of 98.3%. The study demonstrated that wild growing boletus bicolor at species level from different areas can be identified by FTIR spectra combined with principal components analysis.