Detection of low numbers of bacterial cells in a pharmaceutical drug product using Raman spectroscopy and PLS-DA multivariate analysis

Grosso, Rubén Adrián; Walther, Anders Runge; Brunbech, Ellen; Sørensen, Annette; Schebye, B.; Olsen, Katharina E. P.; Qu, Haiyan; Hedegaard, Martin A.B.; Arnspang, Eva C.

doi:10.1039/d2an00683a

Cited by 4 publications

(2 citation statements)

References 41 publications

(74 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Raman spectroscopy is a non-destructive, fast method that eliminates the need for sample preparation [30,31]. This technique coupled with diverse chemometric methods [32][33][34] has been applied extensively for the identification of unknown substances in fields such as materials science, biology, pharmaceuticals, and food science [35][36][37][38]. Furthermore, it has also been employed for the analysis of different types of fuels including gasoline, kerosene, and alcohol fuels [39][40][41].…”

Section: Introductionmentioning

confidence: 99%

Quantitative Analysis of Biodiesel Adulterants Using Raman Spectroscopy Combined with Synergy Interval Partial Least Squares (siPLS) Algorithms

Su,

Li,

Yan

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

Biodiesel has emerged as an alternative to traditional fuels with the aim of reducing the impact on the environment. It is produced by the esterification of oleaginous seeds, animal fats, etc., with short-chain alcohols in an alkaline solution, which is one of the most commonly used methods. This increases the oxygen content (from the fatty acids) and promotes the fuel to burn faster and more efficiently. The accurate quantification of biodiesel is of paramount importance to the fuel market due to the possibility of adulteration, which can result in economic losses, engine performance issues and environmental concerns related to corrosion. In response to achieving this goal, in this work, synergy interval partial least squares (siPLS) algorithms in combination with Raman spectroscopy are used for the quantification of the biodiesel content. Different pretreatment methods are discussed to eliminate a large amount of redundant information of the original spectrum. The siPLS technique for extracting feature variables is then used to optimize the input variables after pretreatment, in order to enhance the predictive performance of the calibration model. Finally, the D1-MSC-siPLS calibration model is constructed based on the preprocessed spectra, the selected input variables and the optimized model parameters. Compared with the feature variable selection methods of interval partial least squares (iPLS) and backward interval partial least squares (biPLS), results elucidate that the D1-MSC-siPLS calibration model is superior to the D1-MSC-biPLS and the D1-MSC-iPLS in the quantitative analysis of adulterated biodiesel. The D1-MSC-siPLS calibration model demonstrates better predictive performance compared to the full spectrum PLS model, with the optimal determination coefficient of prediction (R2P) being 0.9899; the mean relative error of prediction (MREP) decreased from 9.51% to 6.31% and the root--mean-squared error of prediction (RMSEP) decreased from 0.1912% (v/v) to 0.1367% (v/v), respectively. The above results indicate that Raman spectroscopy combined with the D1-MSC-siPLS calibration model is a feasible method for the quantitative analysis of biodiesel in adulterated hybrid fuels.

show abstract

Section: Introductionmentioning

confidence: 99%

Quantitative Analysis of Biodiesel Adulterants Using Raman Spectroscopy Combined with Synergy Interval Partial Least Squares (siPLS) Algorithms

Su,

Li,

Yan

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…In recent years, Raman spectroscopy advancements have opened new research insight by allowing rapid and non-destructive analysis. This optical method, which relies on the inelastic scattering of light, is used in several domains of applications: medical, pharmaceutical, food, and microbial detection [4][5][6][7]. The main objective of Raman spectroscopy is to simplify the analysis process and to reduce the investigation time of samples.…”

Section: Introductionmentioning

confidence: 99%

Raman Spectroscopy Application in Food Waste Analysis: A Step towards a Portable Food Quality-Warning System

et al. 2022

View full text Add to dashboard Cite

Food waste is one of the main problems contributing to climate change, as its piling up in landfills produces the greenhouse gas methane. Food waste occurs at every stage of food production; however, a major source of food waste occurs at businesses that supply food to consumers. Industry 4.0 technologies have shown promise in helping to reduce food waste in food supply chains. However, more innovative technologies, such as Raman spectroscopy, hold great promise in helping to reduce food waste, although this has largely been ignored in the literature. In this context, we propose a portable Raman platform to monitor food quality during transportation. The developed system was tested in conditions mimicking those present in a refrigerated truck by analyzing chicken samples stored at temperatures of 4 °C. Raman spectra were acquired for non-packaged and packaged samples over the duration of 30 days resulting in 6000 spectra. The analysis of Raman spectra revealed that the system was able to detect noticeable changes in chicken quality starting on day six. The main Raman bands contributing to this change are amide I and tyrosine. The proposed system will offer the potential to reduce food losses during transportation by consistently checking the food quality over time.

show abstract

A Monte Carlo resampling based multiple feature-spaces ensemble (MFE) strategy for consistency-enhanced spectral variable selection

Li,

Wu,

Dai

et al. 2023

Analytica Chimica Acta

View full text Add to dashboard Cite

Detection of low numbers of bacterial cells in a pharmaceutical drug product using Raman spectroscopy and PLS-DA multivariate analysis

Abstract: Sterility testing is a laborious and slow process to detect contaminants present in drug products. Raman spectroscopy is a promising label-free tool to detect microorganisms and thus gaining relevance as...

Cited by 4 publications

References 41 publications

Quantitative Analysis of Biodiesel Adulterants Using Raman Spectroscopy Combined with Synergy Interval Partial Least Squares (siPLS) Algorithms

Quantitative Analysis of Biodiesel Adulterants Using Raman Spectroscopy Combined with Synergy Interval Partial Least Squares (siPLS) Algorithms

Raman Spectroscopy Application in Food Waste Analysis: A Step towards a Portable Food Quality-Warning System

A Monte Carlo resampling based multiple feature-spaces ensemble (MFE) strategy for consistency-enhanced spectral variable selection

Contact Info

Product

Resources

About