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  • Title: Chemometric optimisation of enzymatic hydrolysis of beechwood xylan to target desired xylooligosaccharides.
    Author: Díaz-Arenas GL, Lebanov L, Sanz Rodríguez E, Sadiq MM, Paull B, Garnier G, Tanner J.
    Journal: Bioresour Technol; 2022 May; 352():127041. PubMed ID: 35318144.
    Abstract:
    Generation of specific xylooligosaccharides (XOS) is attractive to the pharmaceutical and food industries due to the importance of their structure upon their application. This study used chemometrics to develop a comprehensive computational modelling set to predict the parameters maximising the generation of the desired XOS during enzymatic hydrolysis. The evaluated parameters included pH, temperature, substrate concentration, enzyme dosage and reaction time. A Box-Behnken design was combined with response surface methodology to develop the models. High-performance anion-exchange chromatography coupled with triple-quadrupole mass spectrometry (HPAEC-QqQ-MS) allowed the identification of 22 XOS within beechwood xylan hydrolysates. These data were used to validate the developed models and demonstrated their accuracy in predicting the parameters maximising the generation of the desired XOS. The maximum yields for X2-X6 were 314.2 ± 1.2, 76.6 ± 4.5, 38.4 ± 0.4, 17.8 ± 0.7, and 5.3 ± 0.2 mg/g xylan, respectively. These values map closely to the model predicted values 311.7, 92.6, 43.0, 16.3, and 4.9 mg/g xylan, respectively.
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