Quality control of spectroscopic data in non-targeted analysis – Development of a multivariate control chart. (March 2022)

• Record Type: Journal Article
• Authors: Lörchner, Carolin; Horn, Martin; Berger, Felix; Fauhl-Hassek, Carsten; Glomb, Marcus A.; Esslinger, Susanne
• Is Part Of: Food control. Volume 133:Part A(2022)
• Publication Date: 2022-03
• Subjects: Standardisation -- Quality assurance -- Fourier transform-midinfrared spectroscopy -- Fingerprinting -- Outlier score-based algorithms; Food -- Quality -- Periodicals; Food -- Analysis -- Periodicals; Food handling -- Periodicals; Food industry and trade -- Quality control -- Periodicals; Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques; Aliments -- Qualité -- Périodiques; Aliments -- Analyse -- Périodiques; Hygiène alimentaire -- Périodiques; Food -- Analysis; Food handling; Food -- Quality; Periodicals; Electronic journals; 664.07
• DOI: 10.1016/j.foodcont.2021.108601
• Languages: English
• ISSNs: 0956-7135

Abstract

Abstract: In the presented study, an easy to implement workflow based on the evaluation of a quality control sample in non-targeted analysis (outlier detection and time related trend) is proposed for the first time. The novel concept was developed and demonstrated with Fourier transform-midinfrared spectroscopy using a rapeseed oil as quality control sample. Different data evaluation strategies for outlier detection were tested and compared: (i) principal component analysis (PCA), (ii) PCA combined with Hotelling's T-squared distribution and Q-residuals for data assessment as well as (iii) various outlier score-based methods. The build models were challenged by varying measurement and storage conditions to verify the applicability of the three evaluation types (i-iii) to identify these artificially induced variations as outliers. Analogous to a control chart in targeted analysis warning and action limits (numerical decision criteria) were calculated using outlier score-based methods. The best results were achieved by the four outlier score-based methods (pre-period n = 25), where 100 % of the deliberately generated outliers were identified as such. Graphical abstract: Image 1 Highlights: A multivariate control chart is proposed in non-targeted spectroscopic analysis. Proposal using FT-MIR spectroscopy and edible seed oil samples. Comparison of PCA and outlier scores-based approaches for quality assurance. Study showed best results applying outlier score-based algorithms.