Optimization of a chocolate-flavored, peanut–soy beverage using response surface methodology (RSM) as applied to consumer acceptability data

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• 作者：R.P. Deshp ; e ; M.S. Chinnan ; K.H. McWatters
• 关键词：Optimization ; Chocolate-flavored peanut– ; soy beverage ; Response surface methodology (RSM) ; Three component constrained mixture design ; Nine-point hedonic scale ; Contour plots
• 刊名：Lebensmittel-Wissenschaft und -Technologie
• 出版年：2008
• 出版时间：November 2008
• 年：2008
• 卷：41
• 期：8
• 页码：1485-1492
• 全文大小：296 K

文摘

Optimization of a chocolate-flavored, peanut–soy beverage was done using response surface methodology (RSM). Twenty-eight beverage formulations were processed by mixing three basic ingredients: peanut (X₁=30.6 g/100 g–58.7 g/100 g), soy (X₂=28.3 g/100 g–43.5 g/100 g), and chocolate syrup (X₃=13.0 g/100 g–25.9 g/100 g). The proportions of these ingredients were obtained using a three component, constrained mixture design where the source of soy was either flour (SF) or protein isolate (SPI). Consumer acceptability was measured in terms of nine response variables by 41 consumers using a 9-point hedonic scale. Parameter estimates were determined by performing regression analysis with no intercept option. l-pseudo-components were introduced to get equivalent second degree models further used to generate contour plots. The regions of maximum consumer acceptability [hedonic rating 5.0 since the control (commercial chocolate milk) ratings were 6.0–7.0] were identified and marked on these contour plots for each sensory response. Superimposition of contour plots corresponding to each response variable resulted in optimum regions having consumer acceptability ratings 5.0. Optimum formulations were all the combinations of X₁: 34.1 g/100 g–45.5 g/100 g, X₂: 31.2 g/100 g–42.9 g/100 g, and X₃: 22.4 g/100 g–24.1 g/100 g for SF-based; and X₁: 35.8 g/100 g–47.6 g/100 g, X₂: 31.2 g/100 g–43.5 g/100 g, and X₃: 18.3 g/100 g–23.6 g/100 g for SPI-based beverage formulations.