Deng Zeyuan

Effect of green tea and black tea on the metabolisms of mineral elements in old rats

A 2-mo experiment with the white Sprague-Dawley (SD) rats was conducted to investigate the effect of the water extracts of black tea (BTWE) and green tea (GTWE) and the black tea leaves (BTF) and the green tea leaves (GTF) on the metabolism of mineral elements. One hundred eight 12-mo-old white SD rats were randomly divided into 13 groups; 6 of these drank the BTWE or GTWE in which the water extracts concentrations of black tea or green tea were, respectively, 0.6%, 1.2%, and 2.4%, and 6 of these had black tea leaves (BTF) and green tea leaves (GTF) added in which the contents of BTF or GTF were, respectively, 0.5%, 1.0%, and 2.0%, one of these was control. The teas and their water extracts could promote the absorption of manganese and copper. In GTF, BTF, GTWE, and BTWE, the apparent absorption rates of manganese were significantly increased. The manganese contents in the tibia were also elevated, and the differences between GTWE and GTF were significant. The apparent absorption rates of copper and the copper contents in the tibia were increased, but not significantly. The teas and their water extracts inhibited the absorption of calcium (p > 0.05) and iron (p < 0.05). The cerebrum calcium contents were significantly decreased, but the contents of calcium and iron in tibia were not significantly changed. Compared with the control, although the apparent absorption rates of aluminum in all experimental groups were not observed to be different, the aluminum contents in the tibia (p > 0.05) and cerebrum (p < 0.05) were increased. GTF and GTWE decreased the apparent absorption rates of zinc, but BTF and BTWE increased them; the zinc contents in tibia were a little improved, whereas its contents in the cerebrum were gradually decreased with the increase of tea leaves dose and tea concentration.

Rapid Determination of Docosahexaenoic Acid in Powdered Oil by Near-Infrared Spectroscopy

Near-infrared spectroscopy (NIRS) was used as a rapid and nondestructive method to determine the content of docosahexaenoic acid (DHA) in powdered oil samples. A total of 82 samples were scanned in the diffuse reflectance mode by Nicolet 5700 FTIR spectrometer and the reference values for DHA was measured by gas chromatography. Calibration equations were developed using partial least-squares regression (PLS) with internal cross-validation. Samples were split in two sets, one set used as calibration (n = 66) whereas the remaining samples (n=16) were used as validation set. Two mathematical treatments (first and second derivative), none (log(1/R)) and standard normal variate as scatter corrections and Savitzky-Golay smoothing were explored. To decide upon the number of PLS factors included in the PLS model, the model with the lowest root mean square error of cross-validation (RMSECV=0.44) for the validation set is chosen. The correlation coefficient (r) between the predicted and the reference results which used as an evaluation parameter for the models is 0.968. The root mean square error of prediction of the final model is 0.59. The results reported in this article demonstrate that FT-NIR measurements can serve as a rapid method to determine DHA in powdered oil.Near-infrared spectroscopy (NIRS) was used as a rapid and nondestructive method to determine the content of docosahexaenoic acid (DHA) in powdered oil samples. A total of 82 samples were scanned in the diffuse reflectance mode by Nicolet 5700 FTIR spectrometer and the reference values for DHA was measured by gas chromatography. Calibration equations were developed using partial least-squares regression (PLS) with internal cross-validation. Samples were split in two sets, one set used as calibration (n = 66) whereas the remaining samples (n=16) were used as validation set. Two mathematical treatments (first and second derivative), none (log(1/R)) and standard normal variate as scatter corrections and Savitzky�Golay smoothing were explored. To decide upon the number of PLS factors included in the PLS model, the model with the lowest root mean square error of cross-validation (RMSECV=0.44) for the validation set is chosen. The correlation coefficient (r) between the predicted and the reference results which used as an evaluation parameter for the models is 0.968. The root mean square error of prediction of the final model is 0.59. The results reported in this article demonstrate that FT-NIR measurements can serve as a rapid method to determine DHA in powdered oil