Rapid and sensitive recognition of herbal pieces according to different concocted processing is crucial to quality control and pharmaceutical effect.Near-infrared(NIR) and mid-infrared(MIR) technology combined with supervised pattern recognition based on partial least-squares discriminant analysis (PLSDA) was attempted to classify and recognize six different concocted processing pieces of 600 Areca catechu L.samples and the influence of fingerprint information preprocessing methods on recognition performance was also investigated in this work.Recognition rates of 99.24%,100%and 99.49%for original fingerprint,multiple scatter correct(MSC) fingerprint and second derivative(2nd derivative) fingerprint of NIR spectra were achieved by PLSDA models,respectively.Meanwhile,a perfect recognition rate of 100%was obtained for the above three fingerprint models of MIR spectra.In conclusion.PLSDA can rapidly and effectively extract otherness of fingerprint information from NIR and MIR spectra to identify different concocted herbal pieces of A.catechu.
Featuring an assembly of identical pores,through-pore anodic alumina(AAO) makes an ideal monolith-like catalyst support for volatile organic compound(VOC) combustion.This work employs the oxidation of toluene as a model reaction to investigate the applicability of AAO supported Pt catalysts in VOC catalytic combustion.In order to modify the microstructure of AAO.some AAO samples were exposed to hot water treatment(HWT) firstly.Results show that the optimum HWT time is 18 h.Pt/HWT18 gives a toluene conversion of95%at 200 ℃,which is comparable to the initial activity of commercial γ-Al_2O_3 particle supported Pt catalyst.Considering its confinement effect for the supported metal and its monolith-like compact unit,AAO support offers potential applications in VOC catalytic combustion.
