Nuclear magnetic resonance (NMR) spectroscopy with multivariate analysis as a traceability tool for raw and commercial material for authentication and classification purposes in the sugar industry.
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Date
2025
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Publisher
Universidad de ConcepciĆ³n
Abstract
In the context of an increasingly globalized food system, the authenticity and traceability of food products have become critical factors for ensuring quality and origin. This is particularly relevant in the sugar industry, a key sector of the agroindustrial economy, which is highly susceptible to adulteration and production variability. Traditional quality parameters used in the evaluation of raw materials, commercial brown sugars, and derivative products such as pectin show a limited capacity to discriminate samples from different cultivation fields, botanical origin, or production method, and do not provide a detailed chemical profile. The main objective of this Ph.D. thesis was to evaluate the potential of proton nuclear magnetic resonance (1H NMR) spectroscopy combined with multivariate analysis as an alternative methodology for the quality assessment and authentication of sugar beet roots and commercial brown sugars. Complementarily, the potential of time-domain NMR supported by multivariate analysis was explored to differentiate pectin samples produced by distinct production methods. To reduce spectral complexity, extract meaningful spectral components, enhance predictive model performance, preserve essential spectroscopic information (e.g., signal multiplicity and coupling constants), and identify relevant variables, a processing strategy based on multivariate curve resolution (MCR) was implemented. The latter approach was complemented by exploratory and supervised models, which allowed effective discrimination according to the cultivation field of sugar beet roots, the botanical origin of commercial brown sugars and the method of production of pectin samples, even in the presence of simulated adulteration and highly similar spectral profiles. Furthermore, a novel graphical user interface, termed interval resonance analysis (InRA), was developed to flexibly automate critical processing steps in 1H NMR spectroscopy (e.g., automated signal detection and signal decomposition via MCR), thus reducing manual intervention and analysis time, while promoting accessibility and for non-expert operators. The combined use of 1H NMR spectroscopy and TD-NMR with multivariate analysis proved to be a robust, selective and reproducible analytical tool for chemical characterization and authentication in the sugar industry, offering an effective alternative to conventional quality control and traceability methods within the agro-industrial sector.
Description
Tesis presentada para optar al grado de Doctor en Ciencias y TecnologĆa AnalĆtica.
Keywords
Nuclear magnetic resonance, Spectroscopy, Food products, Sugar industry