Determination of antioxidant capacities of vegetable oils by ferric-ion spectrophotometric methods

Two ferric-ion-based total antioxidant capacity methods: 1,10-phenanthroline (Phen) and ferric reducing antioxidant power (FRAP) were used for determination of antioxidant capacities (AC) of the acetonic and methanolic extracts of vegetable oils. The obtained mean Phen and FRAP values for acetonic extracts of olive oils, rapeseed, rice and four sunflower oils (39.3–336.5 and 39.5–339.6 μmol Fe/100 g) were higher than for methanolic extracts (22.8–307.3 and 23.5–300.1 μmol Fe/100 g). However, antioxidant capacities of methanolic extracts of corn oil, blended oils and two sunflower oils with garden green flowers (56.5–312.9 and 53.9–306.5 μmol Fe/100 g for Phen and FRAP methods, respectively) were higher than for acetonic extracts of these oils (54.2–249.2 and 52.9–244.7 μmol Fe/100 g for Phen and FRAP methods, respectively). There is a linear and significant correlation between these two analytical methods (r = 0.9989 and 0.9986 for acetonic and methanolic extracts). Also, total phenolic compounds (TPC) in the studied oils correlated with their antioxidant capacities determined by Phen and FRAP methods (r = 0.9012, 0.7818 and 0.8947, 0.7830 for acetonic and methanolic extracts, respectively). The comparable precision (R.S.D. = 0.8–4.6%, 0.9–4.9% and 0.7–4.0%, 0.6–4.0% for acetonic and methanolic extracts, respectively) and sensitivity ( = 1.27 × 10⁴, 1.11 × 10⁴ and 2.62 × 10⁴ dm³ mol⁻¹ cm⁻¹) for the proposed Phen and the modified FRAP methods, demonstrate the benefit of the Phen method in the routine analysis of antioxidant capacities of vegetable oils.     

神经网络法在使用裂解气相色谱鉴别中草药中的应用

将以误差反向传播为训练算法的前馈式人工神经网络（ＢＰ－ＡＮＮ）首次艇于中草药的裂解气相色谱谱图解析。重点考察了如何表征和提取复杂的裂解色谱图中有价值信息,用于主成分分析方法处理后输入到有数经优化的神经网络中。实验证明,该广阔示仅可以正确识别样品所属种类,耐用对一示同实验时间、数据残缺等原因造成的噪音具有优异的抗干扰能力。     

催化燃烧去除VOCs污染物的最新进展

催化燃烧是目前最有效的处理挥发性有机物(VOCs)技术之一. 本文从催化剂活性组分、催化剂载体、有效组分颗粒大小、水蒸汽的影响及催化燃烧反应中的积碳等几个方面, 对近年来催化燃烧处理VOCs的研究进行了总结. 分析表明: 贵金属催化剂的研究主要着重于选择有效的载体和双组分贵金属催化剂; 非贵金属催化剂的研究主要集中在高活性的过渡金属复合氧化物、钙钛矿和尖晶石型等催化剂的研制, 还有这些活性组分粒径大小及载体对催化燃烧VOCs反应活性的影响;此外, 在实际应用中,水蒸汽和催化剂积碳失活等问题对催化燃烧VOCs的反应也有很大影响. 本文的评述将为选择合适的催化燃烧技术处理VOCs污染物提供一定参考.     

柚子果皮油挥发性成分的气相色谱-质谱分析

采用溶剂萃取提取柚子果皮的精油,经气相色谱和质谱联机分析,同时依据各成分的保留指数,鉴定出71种挥发性物质,其中有21种碳氢化合物,50种含氧化合物。在碳氢化合物中以柠烯、γ－萜品烯为主要成分;而在含氧化合物中主要是沉香醇、α－萜品醇、百里酚以及一些脂肪族醛。     

基于非负分解方法的质谱成像数据特征提取

质谱成像技术能够在同一个实验里无需标记手段而获得样品表面的分子信息及其分布信息,是当前质谱分析的热点.其分析所得数据量大且复杂,使其特征难以提取.多元统计分析方法,特别是主成分分析法已应用于质谱成像数据的压缩和特征提取.然而由于主成分分析常产生负的数据结果,其意义难以解释且不易分解为单一的特征.本研究开发出一种基于非负分解的质谱成像数据提取方法,能够提取单一的分子特征及其在样品上的分布特征,并将多个单一的特征分布通过红、绿、蓝三色叠加显示,获得轮廓直观的综合特征分布.应用本方法对小鼠脑组织切片质谱成像数据进行分析,可直观分解出灰质区域、白质区域和背景区域,相对主成分分析方法更直观且易于解释.应用本方法对在同一个样品靶上的人膀胱癌变组织和其相邻非癌变组织切片质谱成像数据进行分析,癌变与非癌变组织间差异清晰直观.本研究设计的质谱成像软件可由http://www.msimaging.net获取.     

一种基于免疫识别的主因子数判断方法

根据免疫算法的基本思想,提出了一种基于免疫识别(IR)的主因子数判断方法.对模拟数据和HPLC-DAD数据的处理结果表明,IR比嵌入误差(IE)、因子指示函数(IND)和交叉验证(CV)更能有效地克服噪音的影响.当实际数据中的非线性和不等性方差噪音使其它方法失效时,IR仍能得到正确的主因子数.     

顶空固相微萃取-气相色谱法测定环保水性涂料中的挥发性有机物

建立了一种固相微萃取．气相色谱同时测定环保水性涂料中的苯系物和卤代烃的方法。选择涂层厚度为70μm的聚乙二醇-二乙烯苯(CW-DVB)萃取纤维,对固相微萃取的萃取条件进行了优化。该法相对标准偏差小于10％,样品的加标回收率大于72．2％,已成功地测定了11种水性涂料中的苯系物和卤代烷。     

Multivariate analysis for the classification and differentiation of Madeira wines according to main grape varieties

In order to differentiate and characterize Madeira wines according to main grape varieties, the volatile composition (higher alcohols, fatty acids, ethyl esters and carbonyl compounds) was determined for 36 monovarietal Madeira wine samples elaborated from Boal, Malvazia, Sercial and Verdelho white grape varieties. The study was carried out by headspace solid-phase microextraction technique (HS-SPME), in dynamic mode, coupled with gas chromatography–mass spectrometry (GC–MS). Corrected peak area data for 42 analytes from the above mentioned chemical groups was used for statistical purposes. Principal component analysis (PCA) was applied in order to determine the main sources of variability present in the data sets and to establish the relation between samples (objects) and volatile compounds (variables). The data obtained by GC–MS shows that the most important contributions to the differentiation of Boal wines are benzyl alcohol and (E)-hex-3-en-1-ol. Ethyl octadecanoate, (Z)-hex-3-en-1-ol and benzoic acid are the major contributions in Malvazia wines and 2-methylpropan-1-ol is associated to Sercial wines. Verdelho wines are most correlated with 5-(ethoxymethyl)-furfural, nonanone and cis-9-ethyldecenoate. A 96.4% of prediction ability was obtained by the application of stepwise linear discriminant analysis (SLDA) using the 19 variables that maximise the variance of the initial data set.     

Development of a volatile amine sensor for the monitoring of fish spoilage

A sensor with potential for the development of a “chemical barcode” for real-time monitoring of fish freshness is described. This on-package sensor contains a pH sensitive dye, bromocresol green, that responds through visible colour change to basic volatile spoilage compounds, such as trimethylamine (TMA), ammonia (NH₃) and dimethylamine (DMA) collectively known as Total Volatile Basic Nitrogen (TVB-N). The sensor characteristics were studied as well as its response with standard ammonia gas. Trials on cod and under-utilised species have verified that the sensor response correlates with bacterial growth patterns in fish samples thus enabling the “real-time” monitoring of spoilage in various fish species. The sensor response can be interrogated with a simple, inexpensive reflectance colorimeter that we have developed based on two light emitting diodes (LEDs) and a photodetector.     

主成分分析-支持向量回归建模方法及应用研究

将主成分分析(PCA)用于近红外光谱的特征提取,并与支持向量回归(SVR)相结合,实现了主成分分析-支持向量回归(PCA-SVR)用于近红外光谱定量分析的建模方法。与单纯的SVR方法相比,不仅提高了运算速度,而且提高了模型的预测准确度。将PCA-SVR方法用于烟草样品中总糖和总挥发碱含量的测定,所得结果的预测均方根误差分别为1.323和0.0477;回收率分别为91.8%~112.6%和88.9%~120.2%。