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.
Autoxidation of cycloalkanes(C5–C8) with molecular oxygen under catalyst-free and solvent-free conditions was conducted systematically for the first time, focusing on the autoxidation temperature and product distribution. The autoxidation of cyclopentane, cyclohexane, cycloheptane and cyclooctane occurs at 120 ℃,130 ℃, 120 ℃, and 105 ℃ respectively, with obvious oxidized products formation. At 140 ℃, 145 ℃, 130 ℃ and 125 ℃, acceptable yields of the oxidized products could be obtained for them, and the oxidized product distributions were investigated in detail. The autoxidation of cycloalkanes follows the pseudo-first-order kinetic model and the apparent activation energies(E_a) for the autoxidation of cyclopentane and cyclohexane are 159.76 kJ·mol^(-1) and 86.75 kJ·mol^(-1) respectively. This study can act as an important reference in screen of suitable reaction temperature and comparison of the performance of various catalysts in the catalytic oxidation of cycloalkanes in the attempt to enhance the oxidized product selectivity.
Haimin ShenYan WangJinhui DengLong ZhangYuanbin She
