Determination of molecular-weght distribution of chitosan by high-performance liquid chromatography

Abstract

Optimal conditions for using high-performance liquid chromatography (HPLC) in the size exclusion mode have been determined for measuring the molecular-weight (MW) distribution of chitosan samples. Physical separation according to molecular size was accomplished on the stationary phase of glass supports having controlled pore sizes ranging from 2500 to 40 Å. Selection of column combinations was based on the requirements to resolve the higher MW fraction of chitosan and to give a linear calibration curve within the required MW range. The best combination of glass pore sizes and column lengths in two foot sections joined sequentially was: 2500 Å (2 ft.), 1500 Å (4 ft.), 550 Å (6 ft.), 250 Å (2 ft.), 100 Å (2 ft.), and 40 Å (2 ft.). a loading study showed that an injection load of 500 μg, i.e. 100 μl at 5 g/l or 50 μl at 10 g/l (w/v), was the optimal load to give reproducible elution volumes, precision in quantitation, and minimum viscosity effects. The best calibration curve using defined dextran standards was obtained from the geometric mean of M w (weight average MW) and M n (number average MW) values and peak elution volumes. Precision in determining MW distributions of chitosan as well as dextran standards was better than 5% relative standard deviation, and the differences between these results and the manufacturer's data on the dextran standards were t 60 −17%. The MW distribution of a selected chitosan sample in 2% acetic acid thus determined was M w = 2,055,000, M n = 936,000, dispersity = 2.16, and the most abundant species was around 1,103,000. Analysis time for the HPLC separation was less than 20 min per sample. Chitosan is an effective coagulating agent for the treatment of food processing wastes and activated sludge from biological treatment systems. It is manufactured from chitin in shrimp and crab wastes. The rapid methods developed here for determining the MW distribution of chitosan preparations will be used to optimize the manufacturing process and guide the selection of more effective chitosan products.