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

Bos, Tijmen S.; Knol, Wouter C.; Molenaar, Stef R.A.; Niezen, Leon E.; Schoenmakers, Peter J.; Somsen, Govert W.; Pirok, Bob W.J.

doi:10.1002/jssc.202000011

Cited by 53 publications

(40 citation statements)

References 309 publications

(460 reference statements)

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“…These statistical approaches help in gather information and speed up the processing of analytical data. Hence, chemometrics is a great tool to support the development of rapid analytical methods when some analytical problems or big data are acquired [ 90 ].…”

Section: Rapid Methods For Non-nutritive Sweeteners Determinationmentioning

confidence: 99%

Analytical Methods for Determination of Non-Nutritive Sweeteners in Foodstuffs

et al. 2021

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Sweeteners have been used in food for centuries to increase both taste and appearance. However, the consumption of sweeteners, mainly sugars, has an adverse effect on human health when consumed in excessive doses for a certain period, including alteration in gut microbiota, obesity, and diabetes. Therefore, the application of non-nutritive sweeteners in foodstuffs has risen dramatically in the last decade to substitute sugars. These sweeteners are commonly recognized as high-intensity sweeteners because, in a lower amount, they could achieve the same sweetness of sugar. Regulatory authorities and supervisory agencies around the globe have established the maximum amount of these high-intensity sweeteners used in food products. While the regulation is getting tighter on the market to ensure food safety, reliable analytical methods are required to assist the surveillance in monitoring the use of high-intensity sweeteners. Hence, it is also necessary to comprehend the most appropriate method for rapid and effective analyses applied for quality control in food industries, surveillance and monitoring on the market, etc. Apart from various analytical methods discussed here, extraction techniques, as an essential step of sample preparation, are also highlighted. The proper procedure, efficiency, and the use of solvents are discussed in this review to assist in selecting a suitable extraction method for a food matrix. Single- and multianalyte analyses of sweeteners are also described, employing various regular techniques, such as HPLC, and advanced techniques. Furthermore, to support on-site surveillance of sweeteners’ usage in food products on the market, non-destructive analytical methods that provide practical, fast, and relatively low-cost analysis are widely implemented.

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Section: Rapid Methods For Non-nutritive Sweeteners Determinationmentioning

confidence: 99%

Analytical Methods for Determination of Non-Nutritive Sweeteners in Foodstuffs

et al. 2021

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“…These strategies have been developed over the years with increasing knowledge of the parameters influencing retention. An example of this is the development of the Drylab, ChromSword, and PEWS 2 method development software [18,19,42,69–71]. Many of these papers are limited to RPLC, but there are three software packages that can be used for liquid chromatography in general.…”

Section: Methodsmentioning

confidence: 99%

“…The sum‐of‐squares error ( SSE ) is corrected by the number of parameters ( p ) and the number of observations ( n ). A lower (more negative) value represents a better fit, thus aiding in the selection of a correct model [15,41–45].…”

Section: Background Theorymentioning

confidence: 99%

Recent applications of retention modelling in liquid chromatography

Uijl

Schoenmakers

Pirok

et al. 2020

J of Separation Science

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Recent applications of retention modelling in liquid chromatography (2015–2020) are comprehensively reviewed. The fundamentals of the field, which date back much longer, are summarized. Retention modeling is used in retention‐mechanism studies, for determining physical parameters, such as lipophilicity, and for various more‐practical purposes, including method development and optimization, method transfer, and stationary‐phase characterization and comparison. The review focusses on the effects of mobile‐phase composition on retention, but other variables and novel models to describe their effects are also considered. The five most‐common models are addressed in detail, i.e. the log‐linear (linear‐solvent‐strength) model, the quadratic model, the log–log (adsorption) model, the mixed‐mode model, and the Neue–Kuss model. Isocratic and gradient‐elution methods are considered for determining model parameters and the evaluation and validation of fitted models is discussed. Strategies in which retention models are applied for developing and optimizing one‐ and two‐dimensional liquid chromatographic separations are discussed. The review culminates in some overall conclusions and several concrete recommendations.

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“…Approaches for optimization of 2DLC were reviewed, and while the bulk of the paper focused on rationales for choosing selectivities for analytes of interest, several examples of applications to synthetic polymers were highlighted . Finally, chemometric approaches for data preprocessing, analysis of chromatograms and optimization of methods were reviewed for applications in 2DLC, and although polymers were not the main focus of the article, extension of these data treatment techniques to polymer applications may be feasible …”

Section: Multidimensional Separations Of Polymers and Oligomersmentioning

confidence: 99%