ZHAO Li-juan, XU Jiang-he, WANG Xing-min, SHAO Cheng-bin, ZENG Xue. 2017: Optimization of enzymatic saccharification for perilla stem. Journal of Southern Agriculture, 48(6): 1054-1061. DOI: 10.3969/j.issn.2095-1191.2017.06.19
Citation: ZHAO Li-juan, XU Jiang-he, WANG Xing-min, SHAO Cheng-bin, ZENG Xue. 2017: Optimization of enzymatic saccharification for perilla stem. Journal of Southern Agriculture, 48(6): 1054-1061. DOI: 10.3969/j.issn.2095-1191.2017.06.19

Optimization of enzymatic saccharification for perilla stem

  • ObjectiveThe appropriate conditions for compound enzyme preparation to catalyze hydrolysis of perilla stem were studied in order to improve the resource utilization of perilla stem. MethodUsing compound enzyme with cellu-lase, xylanase and laccase(mass ratio 4:25:12), on the basis of single factor experiment, response surface methodology was conducted. With reducing sugar content(Y) as response value, the mathematical model and optimization process parame-ters of hydrolysis and saccharification of perilla stem were established. And effects of compound enzyme dosage(A), en-zyme hydrolysis time(B), enzymolysis temperature(C) and pH(D) on hydrolysis of perilla stem tissue fiber by compound enzyme preparation were investigated. ResultTwo regression equations of catalytic hydrolysis of perilla stem were estab-lished: Y=107.28+7.26A+6.88B+3.09C-1.68D-20.57A2-19.41B2-18.42C2-28.26D2-3.63AB-4.98AC-2.93AD+1.93BC-1.20BD-1.33CD. The dosage of compound enzyme had extremely significant influence on content of reducing sugar in per-illa stem(P<0.01), and enzymolysis time had significant influence on it(P<0.05). When 1.0 g compound enzyme prepara-tion were applied for saccharification of perilla stem, saccharification rate of 108.8 mg/g was obtained after 5.4 h hydrolysis at 45 ℃ and pH 5.Relative deviations was 0.1 mg/g compared to expected value. This was the optimum process for hydroly-zing perilla stem by compound enzyme preparation. ConclusionThe optimization of enzyme catalyzed hydrolysis of perilla stem saccharification process obtained by response surface method has a short test period and low energy consump-tion. The mathematical model of the optimization process is feasible, and can be used in actual forecast.
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