Dehydration as a Tool to improve predictability of sugarcane juice carbohydrates using near-infrared spectroscopy based PLS models
| Autor: | Wilson Cardoso, Márcio Henrique Pereira Barbosa, João G.R. Gomes, Reinaldo F. Teófilo, Jussara V. Roque |
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| Rok vydání: | 2022 |
| Předmět: |
Chromatography
Sucrose Process Chemistry and Technology Near-infrared spectroscopy Fructose medicine.disease Computer Science Applications Analytical Chemistry chemistry.chemical_compound Sample volume chemistry Chromatography detector Partial least squares regression medicine Nir spectra Dehydration Spectroscopy Software |
| Zdroj: | Chemometrics and Intelligent Laboratory Systems. 220:104459 |
| ISSN: | 0169-7439 |
| DOI: | 10.1016/j.chemolab.2021.104459 |
| Popis: | The aim of this work was to study dehydration as a way to improve the prediction of sucrose, glucose, and fructose in sugarcane juice using near-infrared (NIR) spectroscopy and partial least squares (PLS) regression models. The temperature, time, and sample volume involved in the dehydration process were optimized using design of experiments. Six different sample supports were assessed, being the thick couche paper the best support. NIR spectra from liquid (LSJ) and dehydrated sugarcane juice (DSJ) were obtained. Sucrose, glucose, and fructose in LSJ were analyzed using high-performance liquid chromatography with an evaporative light scattering detector (HPLC-ELSD). Sucrose, glucose, and fructose ranged from 99.29 to 249.27 mg/mL, 5.96–14.94 mg/mL and 3.99–16.10 mg/mL. PLS models were built using the sugars content and NIR spectra collected from a benchtop and a portable instrument. Ordered predictors selection (OPS) was applied to select the most informative variable. The results indicated better predictions for all sugars using the DSJ for both instruments, being the benchtop statistically better than the portable instrument. On the benchtop instrument, the PLS-OPS models presented root mean square error of prediction (RMSEP) respectively for sucrose, glucose, and fructose 7.98, 0.82, and 1.00 mg/mL using the DSJ against 12.75, 1.00, and 1.35 mg/mL using the LSJ. For the portable instrument, the RMSEP were respectively 15.90, 1.18, and 1.65 mg/mL using DSJ against 23.23, 1.40, and 2.08 mg/mL using LSJ. To sum up, the dehydration approach showed to be a great technique to improve the predictability of PLS-OPS models for sugarcane juice sugars using NIR spectra by removing the water and concentrating the analytes. |
| Databáze: | OpenAIRE |
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