摘要
本研究建立了一种超高效液相-串联四极杆质谱多反应监测模式法同时定量6种诃子酚类有效成分:诃黎勒酸(chebulagic acid),五没食子酰葡萄糖(pentagalloyl glucose),木麻黄鞣宁(casua-rinin),鞣料云实素(corilagin),鞣花酸(ellagic acid)和没食子酸(gallic acid),选用半合成的酚类化合物4β-(L-乙酰半胱氨酸)-表儿茶素为内标。药材粉碎后用含内标的甲醇溶液超声提取,提取液用安捷伦ZORBAXEclipseX DB-C18(2.1×50mm,1.8建立方法对诃子μm)分析柱分离,甲醇-0.1%甲酸梯度洗脱,电喷雾电离源多反应模式监测。所6种成分的定量限均小于0.0868相关系数均大于μg·mL^(-1),在定量范围内成分与内标的峰面积比与成分质量浓度呈线性关系,0.99;方法回收率为83.4-108.1%;日内及日间精密度RSD分别为0.9-5.9和1.3-4.8。检测结果表明诃子果肉及种皮中这6种有效成分含量均高,以果肉中的含量最高,该法也可用于诃子及其复方的质量控制。
The design and application of ultra short term wind power forecasting system based on trend analysis for Inner Mongolia Power Grid are introduced in this paper. The physical and sta- tistical methods combined are applied in this system based on the trend analysis of numeric weather forecating data,the power forecasting of single wind farm is based on historical data,real-time data and future weather forecast data for learning and prediction, while the regional wind power predic- tion carries on the spatial correlation analysis, considering the spatial distribution of all real-time wind data. Research results show that the prediction system for high precision,fully satisfy the re- quirements of dispatching for Inner Mongolia Power Grid.
出处
《内蒙古大学学报(自然科学版)》
CAS
北大核心
2016年第1期90-95,共6页
Journal of Inner Mongolia University:Natural Science Edition
基金
国家自然科学基金项目(81160511)
高等学校博士学科点专项科研基金(博导类)(20131501110008)