摘要
为了综合利用芝麻粕资源,以芝麻粕为原料,利用硬脂酸、吐温80、十二烷基硫酸钠三种表面活性剂对其进行脱脂处理,再采用水剂法去除表面活性剂,最后利用中性蛋白酶、碱性蛋白酶和木瓜蛋白酶对芝麻粕蛋白进行水解,以芝麻粕蛋白溶出率为考察指标优选出最佳水解酶。在此基础上,通过单因素试验和正交试验对酶解工艺条件进行优化,并利用2,4-二硝基氟苯柱前衍生高效液相色谱法分析水解物成分。结果表明,吐温80脱脂效果最好,芝麻粕脱脂率达93.49%;碱性蛋白酶为最佳水解酶,其最佳酶解条件为料水比1∶10(g∶m L)、酶解温度50℃、加酶量0.04%、酶解时间3.0 h。在此最佳酶解条件下,芝麻粕蛋白溶出率为88.94%。水解物中含有20种氨基酸,其中8种人体必需氨基酸含量高于FAO/WHO的推荐值。
In order to comprehensively utilize sesame meal resources, the sesame meal was degreased by 3 surfactants including stearic acid, Tween 80,and sodium dodecyl sulfate, then the surfactants were removed through water washing, and finally the sesame meal protein was hydrolyzed using neutral protease, alkaline protease and papain. The optimal hydrolase was selected based on the dissolution rate of protein from sesame meal. On the basis, the enzymatic hydrolysis process conditions were optimized by single-factor tests and orthogonal tests, and the hydrolysate was analyzed by pre-column derivatization with 2,4-dinitrofluorobenzene combined with HPLC. The results showed that the Tween 80 had the optimal degreasing effect, and the degreasing rate of sesame meal was 93.49%. The alkaline protease was the optimal hydrolase, and the optimal enzymatic hydrolysis conditions were material to liquid ratio 1∶10(g∶ml), enzymatic hydrolysis temperature 50 ℃, enzyme addition 0.04%, and enzymatic hydrolysis time 3.0 h. Under the optimal enzymatic hydrolysis conditions, the dissolution rate of protein from sesame meal was 88.94%. The hydrolysate contained 20 amino acids, and the contents of 8 human essential amino acids were higher than the recommended value of FAO/WHO.
作者
皮诗宇
王常高
杜馨
蔡俊
PI Shiyu;WANG Changgao;DU Xin;CAI Jun(Hubei Provincial Cooperative Innovation Center of Industrial Fermentation,Hubei Key Laboratory of Industrial Microbiology,Key Laboratory of Fermentation Engineering,Ministry of Education,Hubei University of Technology,Wuhan 430068,China)
出处
《中国酿造》
CAS
北大核心
2020年第7期202-207,共6页
China Brewing
基金
国家自然科学基金(31401807)。
关键词
芝麻粕蛋白
脱脂
酶解
优化
组成成分分析
sesame meal protein
degrease
enzymatic hydrolysis
optimization
component analysis