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Modeling of Temperature-Induced Near-Infrared and Low-Field Time-Domain Nuclear Magnetic Resonance Spectral Variation: Chemometric Prediction of Limonene and Water Content in Spray-Dried Delivery Systems

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Abstract:

The influence of temperature on near-infrared (NIR) and nuclear magnetic resonance (NMR) spectroscopy complicates the industrial applications of both spectroscopic methods. The focus of this study is to analyze and model the effect of temperature variation on NIR spectra and NMR relaxation data. Different multivariate methods were tested for constructing robust prediction models based on NIR and NMR data acquired at various temperatures. Data were acquired on model spray-dried limonene systems at five temperatures in the range from 20 °C to 60 °C and partial least squares (PLS) regression models were computed for limonene and water predictions. The predictive ability of the models computed on the NIR spectra (acquired at various temperatures) improved significantly when data were preprocessed using extended inverted signal correction (EISC). The average PLS regression prediction error was reduced to 0.2%, corresponding to 1.9% and 3.4% of the full range of limonene and water reference values, respectively. The removal of variation induced by temperature prior to calibration, by direct orthogonalization (DO), slightly enhanced the predictive ability of the models based on NMR data. Bilinear PLS models, with implicit inclusion of the temperature, enabled limonene and water predictions by NMR with an error of 0.3% (corresponding to 2.8% and 7.0% of the full range of limonene and water). For NMR, and in contrast to the NIR results, modeling the data using multi-way N-PLS improved the models' performance. N-PLS models, in which temperature was included as an extra variable, enabled more accurate prediction, especially for limonene (prediction error was reduced to 0.2%). Overall, this study proved that it is possible to develop models for limonene and water content prediction based on NIR and NMR data, independent of the measurement temperature.

Keywords: CHEMOMETRICS; DIRECT ORTHOGONALIZATION; DO; EISC; EXTENDED INVERTED SIGNAL CORRECTION; MSC; MULTI-WAY PLS; MULTIPLICATIVE SIGNAL CORRECTION; NEAR-INFRARED SPECTROSCOPY; NIR SPECTROSCOPY; NMR; NUCLEAR MAGNETIC RESONANCE; PARTIAL LEAST SQUARES; PCA; PLS; PRINCIPAL COMPONENT ANALYSIS

Document Type: Research Article

DOI: http://dx.doi.org/10.1366/000370209787392094

Affiliations: 1: University of Nottingham, School of Biosciences, Division of Food Sciences, Sutton Bonington Campus, Loughborough, LE12 5RD, UK 2: Firmenich SA, Route de la Bergère 7, 1217 Meyrin, Switzerland 3: University of Copenhagen, Faculty of Life Sciences, Department of Food Science, Quality & Technology, Rolighedsvej 30, DK-1958 Frederiksberg C, Denmark

Publication date: February 1, 2009

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