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基于合理氨基酸配比杂粮馒头工艺及评价研究 被引量:2

Study on the technology and evaluation of steamed bread based on reasonable amino acid ratio
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摘要 目的探索合理氨基酸配比杂粮馒头的加工工艺与评价方法。方法以燕麦、荞麦、藜麦为原料研究符合人体需要的最佳氨基酸配比,磨粉后进行杂粮馒头制作工艺的研究,利用主成分分析对杂粮馒头的加工指标进行分析。结果燕麦、荞麦和藜麦的最佳配比为85:20:59(m:m:m),最接近人体最佳氨基酸模式;研究获得杂粮馒头的最佳配方为:燕麦含量44.8%、藜麦含量10.5%、荞麦含量31.2%、磨粉目数120目、酵母用量1.5%、谷朊粉用量12%(m:m)、加水量9:10(g:mL)。结论此配方制备的杂粮馒头质量最佳,为杂粮馒头的制作提供理论基础及建立评价方法,为杂粮开发加工提供数据参考。 Objective To explore the processing technology and evaluation method of reasonable ratio of amino acid to coarse grain steamed bread.Methods Using oats,buckwheat,and quinoa as raw materials,the best amino acid ratio that met the needs of the human body was studied,after grinding,the processing technology of coarse grain steamed bread was studied,and the processing index of coarse grain steamed bread was analyzed by principal component analysis.Results The optimum ratio of oats,buckwheat and quinoa was 85:20:59(m:m:m),which was close to the optimum amino acid model of human body.According to the reasonable ratio of grinding powder to study the process of coarse grain steamed bread,it was concluded that the best process was oats content 44.8%,quinoa content 10.5%,buckwheat content 31.2%,milling mesh 120,yeast consumption 1.5%,gluten consumption 12%(m:m),water content 90%(g:mL).Conclusion The quality of coarse grain steamed bread prepared with this formula is the best,which provides the theoretical basis and evaluation method for the production of coarse grain steamed bread,and provides data reference for the development and processing of coarse grain steamed bread.
作者 刘文婷 白静 张新军 杨晓虹 李天亮 刘晶晶 闫文静 周海涛 LIU Wen-Ting;BAI Jing;ZHANG Xin-Jun;YANG Xiao-Hong;LI Tian-Liang;LIU Jing-Jing;YAN Wen-Jing;ZHOU Hai-Tao(Zhangjiakou Academy of Agricultural Sciences,Hebei Oat Technology Innovation Center,Zhangjiakou 075000,China)
出处 《食品安全质量检测学报》 CAS 2020年第18期6678-6686,共9页 Journal of Food Safety and Quality
基金 国家燕麦荞麦产业技术体系项目(CARS-08-B-04)。
关键词 氨基酸配比 杂粮馒头 工艺研究 感官评价 主成分分析 amino acid matching proportion multi-cereal steamed bread technical study sensory evaluation principal component analysis
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