Automatic time-shift alignment method for chromatographic data analysis

Abstract

Time shift among samples remains a significant challenge in data analysis, such as quality control of natural plant extracts and metabolic profiling analysis, because this phenomenon may lead to invalid conclusions. In this work, we propose a new time shift alignment method, namely, automatic time-shift alignment (ATSA), for complicated chromatographic data analysis. This technique comprised the following alignment stages: (1) automatic baseline correction and peak detection stage for providing useful chromatographic information; (2) preliminary alignment stage through adaptive segment partition to correct alignment for the entire chromatogram; and (3) precise alignment stage based on test chromatographic peak information to accurately align time shift. In ATSA, the chromatographic peak information of both reference and test samples can be completely employed for time-shift alignment to determine segment boundaries and avoid loss of information. ATSA was used to analyze a complicated chromatographic dataset. The obtained correlation coefficients among samples and data analysis efficiency indicated that the influences of time shift can be considerably reduced by ATSA; thus accurate conclusion could be obtained.

Metabolomic Profiling of Carotenoid Constituents in Physalis peruviana During Different Growth Stages by LC‐MS/MS Technology

“…Many fragment ions were formed after the collision ionization process then the characteristic fragment ions were filtered out. Baseline drift and time shift are common phenomena in chromatography that, if not corrected, can affect the accuracy of quantitative analysis (Asnin, ; Zheng et al., ). Therefore, after the metabolic mass spectrometry, data were obtained for different samples, the chromatographic peaks for the carotenoid constituents were automatically integrated by the software.…”

Recent applications of chemometrics in one‐ and two‐dimensional chromatography

“…An additional approach to time-shift alignment, automatic time-shift alignment (ATSA), was developed by Zheng et al [69]. This method comprises three different steps, viz (i) automatic baseline correction and peak detection, (ii) pre-liminary alignment through adaptive segment partition, and (iii) a precise alignment.…”

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Identifikasi Dan Karakterisasi Profil Asam Lemak Virgin Coconut Oil Dengan Penambahan Ekstrak Etanol Kunyit Putih (Curcuma zedoaria Rosc.)

“…Asam palmitat terdeteksi pada waktu retensi berturutturut 19,610 menit dan 20,758 menit dengan area 1,37% pada VCO kontrol dan 1,60% pada VCO dengan penambahan ekstrak etanol kunyit putih. Adanya perbedaan waktu retensi pada deteksi senyawa dapat disebabkan adanya pengotor, kondisi kolom, tipe kolom, maupun waktu analisis dimulai, namun perbedaan di atas masih dapat ditoleransi sebesar 0,5 menit (Zheng et al 2017…”