摘要
为降低油炸挂糊鸡块的油脂含量,本文在传统油炸面糊基础配方中添加高筋面粉和黄原胶,以感官评价、挂糊率、油脂含量等为指标,对油炸挂糊鸡块的品质进行单因素试验,结合响应面-主成分分析法优化低脂油炸面糊配方。结果表明,响应面法优化试验得出最优配方为玉米淀粉添加量为42%、高筋面粉添加量为62%、黄原胶添加量为0.3%,此时油炸挂糊鸡块的挂糊率为33.27%、油脂含量为17.04%、硬度为262.73 g、感官评分为80.25;相较于传统油炸面糊条件下,挂糊率提高28.8%、油脂含量降低4.19%、硬度提高57.18 g、感官评分提高8.81%。通过主成分分析法得到规范化综合评分为1.320,与预测值(1.289)基本相符。此优化工艺下,产品色泽金黄,外酥里嫩,香气浓郁,无油腻感。
To reduce the fat content of fried batter chicken nuggets,in this experiment,high-gluten flour and xanthan gum were added to the traditional batter base formula.Sensory evaluation,batter coverage rate,and fat content were used as indicators to conduct single-factor experiments on the quality of fried batter chicken nuggets.The low-fat batter formula was optimized by response surface-principal component analysis method.The results showed that the optimal formula obtained by the response surface method was 42%of corn starch,62%of high-gluten flour,and 0.3%of xanthan gum.At this time,the batter coverage rate of fried batter chicken nuggets was 33.27%,the fat content was 17.04%,the hardness was 262.73 g,and the sensory score was 80.25.Compared with the traditional frying batter conditions,the batter coverage rate increased by 28.8%,the fat content decreased by 4.19%,the hardness increased by 57.18 g,and the sensory score increased by 8.81%.Through the principal component analysis method,the normalized comprehensive score was 1.320,which was basically consistent with the predicted value(1.289).Under this optimized process,the product had a golden color,crispy outside and tender inside,rich aroma,and no greasiness.
作者
葛成荡
纪维凡
余健
杜浩
闫晗
王欣怡
吴晓伟
李培燕
GE Chengdang;JI Weifan;YU Jian;DU Hao;YAN Han;WANG Xinyi;WU Xiaowei;LI Peiyan(College of Food Science and Engineering,Anhui Science and Technology University,Chuzhou 239000,China)
出处
《安徽科技学院学报》
2025年第6期30-38,共9页
Journal of Anhui Science and Technology University
基金
安徽省人社厅安科吴晓伟省级技能大师建设项目(811526)
寿县科技计划项目(2023SY33)
安徽科技学院引进人才项目(SPYJ202106)
国家级大学生创新创业训练计划项目(202410879087)。
关键词
挂糊
鸡块
油脂含量
主成分分析
响应面
paste
chicken nugget
oil content
principal component analysis
response surface analysis
