Ferulic acid (FA) groups esterified to the arabinan side chains of pectic polysaccharides can be oxidatively cross-linked in vitro by horseradish peroxidase (HRP) catalysis in the presence of hydrogen peroxide (H(2)O(2)) to form ferulic acid dehydrodimers (diFAs). The present work investigated whether the kinetics of HRP catalyzed cross-linking of FA esterified to α-(1,5)-linked arabinans are affected by the length of the arabinan chains carrying the feruloyl substitutions. The kinetics of the HRP-catalyzed cross-linking of four sets of arabinan samples from sugar beet pulp, having different molecular weights and hence different degrees of polymerization, were monitored by the disappearance of FA absorbance at 316 nm. MALDI-TOF/TOF-MS analysis confirmed that the sugar beet arabinans were feruloyl-substituted, and HPLC analysis verified that the amounts of diFAs increased when FA levels decreased as a result of the enzymatic oxidation treatment with HRP and H(2)O(2). At equimolar levels of FA (0.0025-0.05 mM) in the arabinan samples, the initial rates of the HRP-catalyzed cross-linking of the longer chain arabinans were slower than those of the shorter chain arabinans. The lower initial rates may be the result of the slower movement of larger molecules coupled with steric phenomena, making the required initial reaction of two FAs on longer chain arabinans slower than on shorter arabinans.
This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar) were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose) and Fourier Transform Infrared Spectroscopy (FTIR) were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0%) gave higher classification accuracy than e-nose data (76.5%) using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data.