为优化青麦仁复合代餐粉配方，采用单因素和均匀设计进行优化试验，并对结果进行多元回归分析。单因素试验结果表明：青麦仁粉添加量、青麦仁粉粒度、木糖醇添加量、羧甲基纤维素钠(CMC-Na)添加量、柠檬酸钠添加量对代餐粉冲调特性有较大影响。均匀设计及主成分分析结果表明：感官评分受柠檬酸钠添加量的影响程度大于青麦仁粉粒度；润湿性受各因素影响的主次顺序为CMC-Na添加量>青麦仁粉粒度；溶解度、分散性、水合能力受各因素影响情况符合二次多项式回归模型；提取的4个主成分能解释92.72%的指标信息，达到指标降维目的；岭回归分析建立的综合得分回归模型具有较好的拟合度；偏最小二乘法回归分析预测最佳工艺参数为：青麦仁粉添加量61%，小米粉与燕麦粉添加量分别为18%、12%，青麦仁粉粒度125目，木糖醇添加量8%，CMC-Na添加量0.85%，柠檬酸钠添加量0.28%，实际综合得分为1.13，均高于试验组中的最高分。本研究参数为后续青麦仁代餐粉产品推广奠定基础。

To optimize the formula of green wheat berry meal replacement powder, single factor experiment and uniform design methods combined with multiple regression analysis were used to process data. The single factor experiment results illustrated that the additions of green wheat berry powder, xylitol, CMC-Na and sodium citrate and particle size of green wheat berry powder were the factors with a great influences on dissolving quality of meal replacement powder. Uniform design and principal component analysis showed that the factors influencing sensory evaluation were ordered as: sodium citrate addition>particle size of green wheat berry powder; and the factors influencing wettability were ordered as: CMC-Na additions>particle size of green wheat berry powder. Solubility, dispersibility and hydratability were followed by the quadratic polynomial regression models. The four principal components extracted accounted for 92.72 % of the total variation, thus achieving dimensional reduction; Through ridge regression analysis, a regression model for comprehensive score was established with a good degree of fitting. Partial least squares regression analysis predicted the best formula: green wheat berry powder (61%), millet flour (18%), oat powder (12%), xylitol (8%), CMC-Na (0.85%), sodium citrate (0.28%) and green wheat berry powder (125 mesh), under which the comprehensive score was 1.13. The solubility of the product was good. This study laid the foundation for promoting green wheat berry meal replacement powder.

河南省重大科技专项 (151100111300)；河南省鲜食谷物加工工程中心(2016)；河南省全谷物小麦制品加工国际联合实验室(2017)；传统小麦制品加工技术集成基地(2017)