化学
校准曲线
转化(遗传学)
曲线拟合
功能(生物学)
对数
稳健性
原始数据
色谱法
应用数学
数学
计算机科学
统计
检出限
数学分析
生物化学
进化生物学
生物
基因
程序设计语言
作者
Dezhao Kong,Jun Zhao,Sheng Tang,Wei Shen,Hian Kee Lee
出处
期刊:Analytical Chemistry
[American Chemical Society]
日期:2021-08-30
卷期号:93 (36): 12156-12161
被引量:40
标识
DOI:10.1021/acs.analchem.1c02011
摘要
The article is a response to a recent opinion piece that log concentration values should not be applied in analytical chemistry. An essential aim in the development of analytical chemistry methods is to obtain more sensitive and accurate detection values. For the application of chemical analysis methods, the obtained experiment data need to fit with the mathematical functions in the first place. As influenced by different detection principles and analytical methods, data can be displayed in a coordinate system with two linear axes for linear function fitting, or the data can first be taken through a logarithmic transformation and then for function fitting. Using raw data or data after logarithmic transformation primarily depends on analytical principles, without special rules of data formats. For example, ultraviolet–visible spectrophotometric data are more suitable for direct linear fitting. However, enzyme-catalyzed reaction or electrochemical data in logarithmic form are more appropriate for function fitting. This transformation of data form will not affect the soundness of fit statistics; rather, it simplifies the complexity of function analysis and calculation, which are the essence of analytical chemistry. In this brief article, we provide justification and legitimacy of the application of logarithmic processing in various fields of quantitative analytical chemistry.
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