Quantification of acid metabolites in complex plant samples by using second-order calibration coupled with GC-mass spectrometry detection to resolve the influence of seriously overlapped chromatographic peaks

Abstract

Accurate quantification of target metabolites, such as organic acid metabolites, in complex natural tobacco samples is a difficult task in metabolic profiling analysis because of the large amount of interferences present in the matrix. Chromatographic peaks of analytes are always overlapped by interferences, although the separation capability of chromatography is optimally enhanced. In this work, the chemometric strategy of second-order calibration of multivariate curve resolution-alternating least squares was employed in combination with gas chromatography-mass selective detection for metabolic profiling analysis to quantify 11 secondary acid metabolites, regardless of interference. The results indicated that the instrumental separation capability can be further improved using a mathematical separation strategy. Chromatographic profiles of analytes can be satisfactorily retrieved from overlapped chromatographic peaks and accurate quantitative results can be obtained. Finally, tobacco samples collected from Henan and Yunnan provinces were successfully grouped based on the obtained quantitative results.