Atlan Samuel, Trelea Ioan Cristian, Saint-Eve Anne, Souchon Isabelle, Latrille Eric
UMR Génie et Microbiologie des Procédés Alimentaires, INRA INA P-G, BP 01, 1 Avenue Lucien Bretignères, F-78850 Thiverval-Grignon, France.
J Chromatogr A. 2006 Mar 31;1110(1-2):146-55. doi: 10.1016/j.chroma.2006.01.055. Epub 2006 Jan 31.
The phase ratio variation (PRV) method is widely used for the determination of partition coefficient values (dimensionless Henry's law constants) by headspace gas chromatography. Traditional data processing by linear regression has several drawbacks: potential bias introduced by linearization, absence of quality indicator of the resulting value and, in case of replicate determinations, poor utilisation of the existing measurements leading to unnecessarily large confidence intervals. The paper compares existing PRV data processing methods (linear and nonlinear regression, parametric) and derives confidence intervals for the resulting partition coefficient values. The possibility of using several series of measurements to derive a single partition coefficient value with tighter and more reliable confidence intervals is presented for all three processing methods. The methods are tested on published literature data and new experimental data for 12 volatile organic compounds in water at 25 degrees C. The nonlinear regression based on several series of measurements appears to be the method of choice.
相比变化法（PRV）被广泛用于通过顶空气相色谱法测定分配系数值（无量纲亨利定律常数）。传统的线性回归数据处理存在几个缺点：线性化引入的潜在偏差、所得值缺乏质量指标，以及在重复测定的情况下，对现有测量值的利用率低，导致置信区间不必要地大。本文比较了现有的PRV数据处理方法（线性和非线性回归、参数法），并推导了所得分配系数值的置信区间。针对所有三种处理方法，都提出了使用多个测量系列来得出具有更窄和更可靠置信区间的单个分配系数值的可能性。这些方法在已发表的文献数据以及25摄氏度下水中12种挥发性有机化合物的新实验数据上进行了测试。基于多个测量系列的非线性回归似乎是首选方法。
