Iterative Multivariate Peaks Fitting—A Robust Approach for The Analysis of Non-Baseline Resolved Chromatographic Peaks

نویسندگان

چکیده

Selectivity in separation science is defined as the extent to which a method can determine target analyte free of interference. It backbone any and be enhanced at various steps, including sample preparation, optimization detection. Significant improvement selectivity also achieved data analysis step with mathematical treatment signals. In this manuscript, we present new approach that uses functions model chromatographic peaks. However, unlike classical peak fitting approaches where parameters are optimized single profile (one-way data), over multiple profiles (two-way data). Thus, it allows high confidence robustness. Furthermore, an iterative number peaks increased each until convergence developed manuscript. demonstrated simulated real algorithm is: (1) capable mathematically separating component minimal user input (2) areas accurately measured even resolution low 0.5 if peak’s intensities does not differ by more than factor 10. This was conclusively quantification diterpene esters standard mixtures.

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ژورنال

عنوان ژورنال: Separations

سال: 2021

ISSN: ['2297-8739']

DOI: https://doi.org/10.3390/separations8100178