Continuous statistical modelling in characterisation of complex hydrocolloid mixtures using near infrared spectroscopy

Georgouli, Konstantia; Carrasco, Beatriz; Vincke, Damien; Rincón, Jesús Martínez del; Koidis, Anastasios; Baeten, Vincent; Pierna, Juan Antonio Fernández

doi:10.1016/j.chemolab.2019.103910

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…Finally, the identification and quantification of hydrocolloids, compounds that alter the properties of food when dispersed in water, is a notoriously difficult task due to the similar chemical makeup of these compounds. Recently, this challenge was overcome by pairing NIR spectroscopy with partial least squares regression and continuous locality preserving projections dimensionality reduction technique as a chemometric framework, allowing for 100% discrimination between pure solutions and blends of kappa and iota carregeenans and tara, guar, and locust bean gum [109].…”

Section: Food Additivesmentioning

confidence: 99%

QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs

Bwambok

Siraj

Macchi

et al. 2020

Sensors

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Quality checks, assessments, and the assurance of food products, raw materials, and food ingredients is critically important to ensure the safeguard of foods of high quality for safety and public health. Nevertheless, quality checks, assessments, and the assurance of food products along distribution and supply chains is impacted by various challenges. For instance, the development of portable, sensitive, low-cost, and robust instrumentation that is capable of real-time, accurate, and sensitive analysis, quality checks, assessments, and the assurance of food products in the field and/or in the production line in a food manufacturing industry is a major technological and analytical challenge. Other significant challenges include analytical method development, method validation strategies, and the non-availability of reference materials and/or standards for emerging food contaminants. The simplicity, portability, non-invasive, non-destructive properties, and low-cost of NIR spectrometers, make them appealing and desirable instruments of choice for rapid quality checks, assessments and assurances of food products, raw materials, and ingredients. This review article surveys literature and examines current challenges and breakthroughs in quality checks and the assessment of a variety of food products, raw materials, and ingredients. Specifically, recent technological innovations and notable advances in quartz crystal microbalances (QCM), electroanalytical techniques, and near infrared (NIR) spectroscopic instrument development in the quality assessment of selected food products, and the analysis of food raw materials and ingredients for foodborne pathogen detection between January 2019 and July 2020 are highlighted. In addition, chemometric approaches and multivariate analyses of spectral data for NIR instrumental calibration and sample analyses for quality assessments and assurances of selected food products and electrochemical methods for foodborne pathogen detection are discussed. Moreover, this review provides insight into the future trajectory of innovative technological developments in QCM, electroanalytical techniques, NIR spectroscopy, and multivariate analyses relating to general applications for the quality assessment of food products.

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Section: Food Additivesmentioning

confidence: 99%

QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs

Bwambok

Siraj

Macchi

et al. 2020

Sensors

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Efficient identification of Bachu mushroom by flourier transform infrared (FT-IR) spectroscopy coupled with PLS-GS-SVM

Gao

Han

et al. 2020

Optik

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Development, optimization, and characterization of vitamin C-fortified oleogel-based chewable gels and a novel nondestructive analysis method for the vitamin C assay

Sabourian,

Dorkoosh,

Khoshayand

et al. 2024

Food Prod Process and Nutr

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Chewable gels represent an excellent alternative to oral dosage forms, such as tablets and capsules, owing to their appealing appearance, easy swallowing, and attractive colors. Given the inherent instability of vitamin C, particularly within chewable gels, it is imperative to enhance its stability and mitigate its degradation during processing and storage. Oleogel, systems prepared through an environmentally friendly and pollution-free method, exhibit a three-dimensional network structure that eliminates oxygen, alleviates oxidation, and enhances vitamin C stability. This study focused on optimizing vitamin C-fortified oleogel-based chewable gels using Plackett–Burman and D-Optimal design methodologies to maximize vitamin C stability while maintaining favorable mechanical properties. The optimal formulation, Opt-C, was achieved by crystallizing the gel at -18 °C, incorporating 2.5 g of distilled monoglyceride (DMG), and maintaining an oleogel-to-chewable gel ratio of 10%. Opt-C was comprehensively characterized using differential scanning calorimetry (DSC) and Fourier transform infrared spectroscopy (FT-IR), and its stability was rigorously assessed. Furthermore, a nondestructive assay method for vitamin C determination in chewable gels was developed employing near-infrared spectroscopy (NIR) and chemometric techniques. Storage studies demonstrated that Opt-C retained 85% of its vitamin C content during accelerated tests over ten weeks, surpassing the 69% retention observed in the control chewable gel. Opt-C exhibited a slower release of vitamin C in simulated digestive fluids; however, this release profile did not adversely impact the overall availability of vitamin C. Ultimately, the developed multivariate model successfully predicts vitamin C concentration: root mean square error of calibration (RMSEC): 0.284, $${\text{R}}_{\text{cal}}^{2}$$ R cal 2 : 0.9906; RMSE cross-validation (RMSECV): 0.501, $${\text{R}}_{\text{val}}^{2}$$ R val 2 : 0.9722; RMSE prediction (RMSEP): 0.670, $${\text{R}}_{\text{pred}}^{2}$$ R pred 2 : 0.9154. This innovative approach enhances the stability of water-soluble vitamins in chewable gels. Graphical Abstract

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Continuous statistical modelling in characterisation of complex hydrocolloid mixtures using near infrared spectroscopy

Cited by 3 publications

References 27 publications

QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs

QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs

Efficient identification of Bachu mushroom by flourier transform infrared (FT-IR) spectroscopy coupled with PLS-GS-SVM

Development, optimization, and characterization of vitamin C-fortified oleogel-based chewable gels and a novel nondestructive analysis method for the vitamin C assay

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