[Quantity analysis of information decomposition for near-infrared diffuse reflectance spectra].

Near infrared (NIR) diffuse reflection spectra can be used to obtain samples' chemical component content and physical parameters with few pretreatments. As a fast and nondestructive technique, NIR has been widely accepted. The diffuse reflection light is detected after interaction with sample. Generally, it is thought that the light carries the interior information of sample, but no one can definitely depict how much information of inner sample can be collected. In the present study, three kinds of flue-cured tobacco were used to design our tests. Each kind of tobacco was prepared in two forms, slice and powder. Then we got three slice tobacco samples and three powder tobacco samples. Every experimental sample consisted of one slice tobacco and one powder tobacco. The slice tobacco was put in the bottom of the sample-cup and the powder tobacco was placed on top of the slice tobacco. Combining different slice tobaccos with different powder tobaccos, the authors can get nine experimental samples. Every experimental sample was scanned from the bottom of the sample-cup for each sample using Bruker MPA FT-NIR instrument four times repeatedly, then we got 36 pieces of NIR spectra totally. In order to find the relationship between the deep light penetration and variance contribution rate of different principal components (PC) of NIR spectra, cluster analysis was carried out using different combination of PC. When the first and second PC were chosen, the samples were clustered according to the exterior slice tobacco; Using the third and fourth PC, the samples were clustered according to the interior powder tobacco. Combining the variance contribution rates of different PC, we could elementarily describe NIR spectra information composition according to the path length of the light penetration quantitatively. Results showed that the first and the second PC contained about 98% spectra information which represented the exterior information, and the third and the fourth PC contained about 1.5% which represented the interior information of the sample. These results can help us profoundly understand the importance of PC selection in NIR qualitative and quantitative analysis.