| Near infra-red spectroscopy and UV-Vis spectrophotometric and HPLC-DAD were investigated as a rapid and/or economical method to control of wild rice and pharmaceutical wild herbs and spices quality. The analysis data of different phytochemicals compounds such as total phenolic acids and flavonoids contents were predicted by chemometric tools such as PLS and PCA for a quality assurance of wild rice and pharmaceutical wild herbs and spices.Near infrared(NIR) spectroscopy is an analytical tool that is still not fully integrated into the food and pharmaceutical industrial environment. However, its advantages are potentially of considerable benefit for the quality control of food and herbal medicinal products. Eleven preprocessing methods were developed to demonstrate the ability of NIR spectroscopy as a quality control method. NIR method showed several clear benefits, such as speed, low analysis costs and environmental friendliness compared to traditional analytical tools. The results of study as follow:1- Total phenolics and flavonoids contents in Chinese wild rice were predicted using near infrared(NIR) spectroscopy as a rapid method. A partial least square(PLS) algorithm was applied to perform the calibration. The models were calibrated by cross-validation and the chosen number of PLS factor was achieved according to the lowest root mean square error cross-validation(RMSECV) in calibration set. The correlation coefficient(R) and root mean square of error prediction(RMSEP) in the test set were used as the evaluation parameters for the optimal model as follows: R = 0.985; RMSEP = 2.41 and the residual predictive deviation(RPD) = 6.06 for total phenolics content prediction by multiplication scatter correction(MSC) model. For flavonoids content prediction, R= 0.978, RMSEP = 1.23 and RPD = 4.81 by non preprocessing model. It could be concluded that NIR spectroscopy has significant potential in the nondestructive determination of total phenolics and flavonoids.2- Total phenolics and flavonoids contents of thirty two wild pharmaceutical herbs and spices were determined by UV spectrophotometric assays and eleven phenolic compounds were identified and quantified by high-performance liquid chromatography with diode array detection HPLC-DAD. The antioxidant activity of these compounds was determined by three different methods, DPPH radical scavenging assay, superoxide scavenging activity assay and hydroxyl radical scavenging assay. The amounts of total phenolic acids were ranged between 5.26 and 35.14 mg GAL/g dry weight for Flax seed and Galangal respectively. The total flavonids content of pharmaceutical wild herbs and spices were ranged from(4.73 to 120.68 mg RE/g dw) for Cyperus seed and Acacia respectively. The antioxidant activity was between 39.92 ± 0.09% to 94.52 ± 0.057 % for DPPH inhibition, 40.454± 0.66% to 97.69±0.08% for Superoxide anion scavenging and 33.05±0.56% to 88.08±0.29 % for hydroxyl radical(?OH) scavenging.3- Principal component analysis was preformed to the most relevant compounds to find out the statistical association between phenolic compounds and different wild herbs. The results shows that Acacia had the biggest differences compared with other wild herbs due to the highest contents of Catechin, Epicatechin, Caffeic acid, p-coumaric acid and Ferulic acid. Thus, phenolic compounds extracts from Acacia can help disease prevention and cure using simple alternative natural medicine for its antioxidant activity.4- NIRS achieved the purpose of rapid detection of phenolic acids and flavonoids content in different pharmaceutical wild herbs and spices. When eleven mathematic preprocessing including non-preprocessing were used to remove the noises of spectra and to build PLS models to predict the suitable model for quantitative, quality control and all other applications. Compared with other preprocessing methods, first derivative results were better than the others which need to 10 PLS factors and the values of RMSECV and RMSEP were 1.24 and 0.66 respectively. The correlation coefficients R for calibration and test set were 0.977 and 0.993 with RPD 6.71 and 12.52 respectively. For flavonoids content and Compared with other models, first derivative + vector normalization preprocessing was chosen as the optimum model by using 9 PLS factors at lowest RMSECV = 2.57 for calibration set and RMSEP = 1.94, Correlation coefficient R = 0.995 and with higher RPD = 13.81 for test set. The methods established in this work met the requirement of practical application. When it is used to practice, it will help to improve the quality of wild herbs and spices in its production and market circulation, which is better for people's health. |
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