Optimization of enzymatic degradation of dealginated kelp waste through response surface methodology
Massive alginate production in China, the major producer of cultivated brown seaweeds in the world, produces a substantial amount of organic kelp waste which is often dumped as landfill. Reutilization of the dealginated kelp waste is a timely point of research in the alginate industry. Kelp waste extracts (KWE) produced via enzymatic hydrolysis of the dealginated residue of the kelp Saccharina japonica were found to render a biostimulant effect that improved the growth of vegetables such as the pak choi and color pepper and microalgae such as Chlorella sorokiniana. Thus, owing to the far-reaching importance of KWE in agriculture and biofuel production, the objective of this study is to optimize the enzymatic degradation of the dealginated kelp waste. The optimization process was carried out by integrating single-factor method, orthogonal experimental design, and response surface method (RSM) based on central composite design (CCD) experiments. The optimization parameters were enzyme ratio, enzymolysis time, temperature, and phosphate buffer solution (PBS) pH. An orthogonal experimental design (L16 (34)) was followed to achieve the optimum combination ratio for cellulase, pectinase, and papain enzymes. Results of the experiment that asserted highest results could be attained at 4, 2, and 1.5% (w/v) ration of cellulase, pectinase, and papain, respectively. Furthermore, optimized conditions of the enzymolysis time (3.8 days), reaction temperature (50 °C), and initial phosphate buffer solution pH (5.8) were predicted through RSM based on CCD experiments. The prediction was confirmed through a triplicate experiment giving a mean total soluble sugar yield of 12.20% ± 0.04. The optimization process was successful in reducing the enzymolysis time by more than 50% from 8 days to 3.8 days. Moreover, the extract was found to contain 18 types of amino acids, alanine being the major one.
KeywordsBiofuel Kelp waste extracts CCD RSM
This work is supported by the Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Collaborative Innovation Center for Jiangsu Marine Bio-Industry Technology, National Natural Science Foundation of China (31770436).
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