化学计量学研究及其应用

本文介绍了化学计量学的产生、发展、研究内容及主要应用,对有关工作进行了评述。     

近红外光谱分析中的化学计量学算法研究新进展

近红外光谱是一种绿色、快捷的分析技术,在科学研究、工业生产以及日常检测中得到广泛应用。化学计量学算法的应用在近红外光谱技术的发展过程中发挥了重要作用。化学计量学方法通过寻找测量变量之间的相关性,构建数学模型,量化样本间的差异性,并发现事物变化的内在规律,实现较合理准确的未知预测。这也是“大数据”战略的重要环节和主旨所在。该文针对近红外光谱吸收信号较弱、谱峰重叠严重,以及光谱测量过程中易受背景、噪声、无信息变量和外界环境因素干扰等,导致借助化学计量学方法建立的光谱与研究目标的定性定量分析模型变差问题,总结了近年来在近红外光谱领域所提出的一些化学计量学新方法,包括光谱预处理、变量选择、多元校正和模型转移,从不同角度阐述了这些方法在消除近红外光谱模型的干扰因素,提高模型的可靠性、预测准确性和适用性等方面的作用。     

化学计量学方法在光谱解析中的应用进展

本文对近20年来化学计量学在光谱分析测试中的应用进行了评述。指出了化学计量学在光谱分析中的重要性和应用前景。引用文献共129篇。     

分析化学计量学的若干新进展

对分析化学计量学的若干新进展进行了讨论, 侧重从作者实验室所进行的研究工作的视角论述了高维数据的分辨、用于化学信号处理的形态学理论和方法、解决复杂化学问题的多元校正和化学模式识别以及联用色谱仪二维数据的分辨新方法的发展.     

信息论与化学计量学

本文讨论了信息论在发展分析化学计量学中的意义和作用以及信息论在化学计量学中应用的一般规律和关系，总结了信息科学对化学计量学发展的贡献。     

化学计量学用于中医药研究

中医药是中华民族的瑰宝,也是中国传统文化的重要组成部分。它的现代化和国际化将对形成具有我国特色的中医药知识经济起到重要作用。中医药的现代化包括探明中医药药效的物质基础、其用药时的化学与药理作用过程等诸多方面。由于中药成分非常复杂,即使是单味药,也是一...     

化学计量学定量分析模型的评价及应用

本文介绍了评价化学计量学校正技术所建立的定量分析模型定量分析效果的一种实用方法，根据定量分析模型对样品待测组分的计算值ｘ与样品待测组分的标准值ｙ建立简单回归模型：ｙ＝ａ＋ｂｘ通过检验回归参数ａ＝０，ｂ＝１的假设能否在一定概率水平上被接受，评价定量分析模型对样品待测组分的预测效果。     

化学计量学在分析化学中的应用

从化学定量构效关系、模式识别法、人工神经网络、波谱化学、多元校正分析法等方面对化学计量学在分析化学中的应用进行了综述。阐明了化学计量学在分析化学中的作用及广阔的应用前景。     

模式识别在食品质量控制方面的应用进展

本文介绍了食品质量研究中常用的一些化学模式识别方法的基本原理,并介绍了模式识别结合红外、原子吸收、原子发射、气相色谱、液相色谱、质谱、电子鼻传感器等检测技术在食品质量控制中的应用.对化学计量学在食品质量控制中的应用前景作了展望.     

Analysis of chemical signals in red fire ants by gas chromatography and pattern recognition techniques

Gas chromatographic (GC) profiles of cuticular hydrocarbon extracts obtained from individual and pooled ant samples were analyzed using pattern recognition techniques. Clustering according to the biological variables of social caste and colony were observed. Pooling individual extracts enhanced the recognition of patterns in the GC profile data characteristic of colony. Evidently, the contribution of the ant's individual pattern to the overall hydrocarbon profile pattern can obscure information about colony in the GC traces of cuticular hydrocarbon extracts obtained from red fire ants. Re-analysis of temporal caste and time period data on the cuticular hydrocarbon patterns demonstrates that sampling time and social caste must be taken into account to avoid unnecessary variability and possible confounding. This and the fact that foragers could not be separated from reserves and brood-tenders in all five laboratory colonies studied suggests that cuticular hydrocarbons as a class of sociochemicals cannot model every facet of nestmate recognition in Solenopsis invicta which in turn suggests a potential role for other compounds in the discrimination of alien conspecifics from nestmates.     

Analysis of chemical signals in red fire ants by gas chromatography and pattern recognition techniques

Gas chromatographic (GC) profiles of cuticular hydrocarbon extracts obtained from individual and pooled ant samples were analyzed using pattern recognition techniques. Clustering according to the biological variables of social caste and colony were observed. Pooling individual extracts enhanced the recognition of patterns in the GC profile data characteristic of colony. Evidently, the contribution of the ant's individual pattern to the overall hydrocarbon profile pattern can obscure information about colony in the GC traces of cuticular hydrocarbon extracts obtained from red fire ants. Re-analysis of temporal caste and time period data on the cuticular hydrocarbon patterns demonstrates that sampling time and social caste must be taken into account to avoid unnecessary variability and possible confounding. This and the fact that foragers could not be separated from reserves and brood-tenders in all five laboratory colonies studied suggests that cuticular hydrocarbons as a class of sociochemicals cannot model every facet of nestmate recognition in Solenopsis invicta which in turn suggests a potential role for other compounds in the discrimination of alien conspecifics from nestmates.     

Supervised pattern recognition to discriminate the geographical origin of rice bran oils: a first study

Supervised pattern recognition appears to be a useful tool to authenticate foodstuffs according to their geographical or varietal origin, when a set of samples whose classification is known a priori are available. In this work, linear discriminant analysis and artificial neural networks trained by the back-propagation algorithm have been used to discriminate rice bran oils manufactured in three different countries (Italy, Thailand and Switzerland) according to their geographical origin. The variables to be included in the mathematical models have been chosen by means of Fisher F-ratio value among the chemical indices routinely determined on vegetable oils (particularly fatty acids, triglycerides and sterol composition). The prediction ability of all the classifiers was 100% as evaluated by cross-validation.     

Minimum spanning tree: ordering edges to identify clustering structure

Ordering edges to identify clustering structure (OETICS), the clustering algorithm presented here, is based on the minimum spanning tree connecting the objects. The edges of the tree are ordered, beginning from the longest edge, to form groups of objects separated by large edges. The plot of ordered edges is the main result of the algorithm. In some aspects OETICS is similar to OPTICS, a known clustering technique that orders the objects with reference to the local density, but the solution is unique, because it does not select the value of some parameters, as the generating distance in OPTICS.OETICS is applied to many simulated and real data sets, with very different number of objects and variables, and the results are compared with those obtained by OPTICS.     

Improvement in LC-MS calibration by addition of fragment signals

Liquid chromatography-mass spectrometry has become a powerful analytical tool, with high selectivity and sensitivity. Usually in this technique, the calibration function is estimated from the molecular peak signal. This report describes the improvement in sensitivity when the signals from several fragments in addition to the molecular peak are used to establish the calibration function. The influence of the dwell time has also been analysed as an important instrumental parameter that influences the signal range, and consequently, the sensitivity. The calibration function obtained by adding fragment signals was used to estimate the instrumental detection limit using three different procedures, comparing and discussing the results obtained.     

光谱多元分析的校正模型检验及干扰物的检出

提出了一种在校正模型不确定时分析体系的光谱多元分析方法,首先构造投影阵以检验校正模型的合理性,通过检验可以发现分析体系是否含有其它不纯物,继用不纯物在投影空间中的矢量与可能存在物质的投影光谱进行检索比较,检出不纯物并测出各组份含量.将此法应用于3个分析体系,获得满意的结果.