HPTLC-based fingerprinting: An alternative approach for fructooligosaccharides metabolism profiling.

Fructans are categorized as fructose-based metabolites with no more than one glucose in their structure. species possess a mixture of linear and ramified fructans with different degrees of polymerization. Among them, fructooligosaccharides are fructans with low degree of polymerization which might be approachable by high performance thin layer chromatography (HPTLC). Thus, this study used two emblematic species collected at different ages as models to explore the feasibility of HPTLC-based fingerprinting to characterize fructooligosaccharides (FOS) production, accumulation, and behavior through time. To do so, high performance anion exchange was also used as analytical reference to determine the goodness and robustness of HPTLC data. The multivariate data analysis showed separation of samples dictated by species and age effects detected by both techniques. Moreover, linear correlations between the increase of the age in agave and their carbohydrate fraction was established in both species by both techniques. Oligosaccharides found to be correlated to species and age factors, these suggest changes in specific carbohydrate metabolism enzymes. Thus, HPTLC was proven as a complementary or stand-alone fingerprinting platform for fructooligosaccharides characterization in biological mixtures. However, the type of derivatizing reagent and the extraction color channel determined the goodness of the model used to scrutinize agavin fructooligosaccharides (aFOS).