Department of Chemistry, University of Washington , Box 351700, Seattle, Washington 98195, United States.
Anal Chem. 2017 Sep 19;89(18):9926-9933. doi: 10.1021/acs.analchem.7b02230. Epub 2017 Sep 7.
A new approach is presented to determine the probability of achieving a successful quantitative analysis for gas chromatography coupled with mass spectrometry (GC-MS). The proposed theory is based upon a probabilistic description of peak overlap in GC-MS separations to determine the probability of obtaining a successful quantitative analysis, which has its lower limit of chromatographic resolution R at some minimum chemometric resolution, R*; that is to say, successful quantitative analysis can be achieved when R ≥ R*. The value of R* must be experimentally determined and is dependent on the chemometric method to be applied. The approach presented makes use of the assumption that analyte peaks are independent and randomly distributed across the separation space or are at least locally random, namely, that each analyte represents an independent Bernoulli random variable, which is then used to predict the binomial probability of successful quantitative analysis. The theoretical framework is based on the chromatographic-saturation factor and chemometric-enhanced peak capacity. For a given separation, the probability of quantitative success can be improved via two pathways, a chromatographic-efficiency pathway that reduces the saturation of the sample and a chemometric pathway that reduces R* and improves the chemometric-enhanced peak capacity. This theory is demonstrated through a simulation-based study to approximate the resolution limit, R*, of multivariate curve resolution-alternating least-squares (MCR-ALS). For this study, R* was determined to be ∼0.3, and depending on the analytical expectations for the quantitative bias and the obtained mass-spectral match value, a lower value of R* ∼ 0.2 may be achievable.
提出了一种新方法来确定气相色谱与质谱联用（GC-MS）成功定量分析的概率。该理论基于 GC-MS 分离中峰重叠的概率描述，以确定获得成功定量分析的概率，其在某种最小化学计量分辨率 R下的色谱分辨率 R 的下限；也就是说，当 R≥R时，可以实现成功的定量分析。R的值必须通过实验确定，并且取决于要应用的化学计量方法。所提出的方法利用了这样一个假设，即分析物峰在分离空间中是独立的和随机分布的，或者至少是局部随机的，也就是说，每个分析物代表一个独立的伯努利随机变量，然后用它来预测成功定量分析的二项概率。理论框架基于色谱饱和因子和化学计量增强的峰容量。对于给定的分离，通过两种途径可以提高定量成功的概率，一种是通过提高色谱效率来降低样品的饱和度，另一种是通过降低 R和提高化学计量增强的峰容量来提高化学计量学途径。通过基于模拟的研究来证明这一理论，以近似多元曲线分辨交替最小二乘法（MCR-ALS）的分辨率极限 R*。对于这项研究，确定 R约为 0.3，并且根据定量偏差的分析预期和获得的质谱匹配值，可以实现较低的值 R约为 0.2。
