Ilyas Rabia, Nadeem Muhammad, Khan Nimrah, Abid Hafiz Muhammad Rizwan, Barrow Colin J, Khalid Nauman
School of Food and Agricultural Sciences University of Management and Technology Lahore Pakistan.
College of Health Sciences Abu Dhabi University Abu Dhabi UAE.
Food Sci Nutr. 2025 Jun 27;13(7):e70525. doi: 10.1002/fsn3.70525. eCollection 2025 Jul.
The study aimed to incorporate green pea powder (GPP) into muffins at an optimum level that reduces sugar content. Cooking time was optimized with the aim of maintaining the sensory quality of the muffins. The study employed a central composite design (CCD) and response surface methodology (RSM) to systematically optimize pea flour addition, sugar reduction, and cooking time optimization in muffins. The recipe refinement by RSM included muffins physical parameters (height, density, baking loss, volume, and mass) and sensory parameters (color, appearance, texture, taste, after taste, and overall acceptability). However, functional parameters like oil holding and water holding capacity were assessed and optimized for only the flour used for making muffins. RSM profiling optimized explanatory variables as 10% pea flour addition, 50% sugar reduction, and 22.7 min cooking. Based on this, the optimized final product surpassed predicted acceptability levels, particularly in taste (7.40), aftertaste (7.40), and overall liking (7.60). Seventeen runs were designed using various recipe combinations depending upon explanatory and dependent variables, and based on data profiling, an optimized recipe was developed, and point confirmation was done. Statistical analysis detected non-significant results in height, density, and texture ( > 0.05 and < 80%). However, baking loss, volume, and mass exhibited significant results ( < 0.05 and 92%, 87%, and 96%), indicating better model fit. Results of this study indicate that pea protein can be incorporated into muffins while maintaining sensory properties.
该研究旨在将绿豌豆粉(GPP)以最佳水平添加到松饼中,以降低糖分含量。对烹饪时间进行了优化,目的是保持松饼的感官品质。该研究采用中心复合设计(CCD)和响应面方法(RSM)来系统地优化松饼中豌豆粉的添加量、糖分减少量和烹饪时间。通过RSM进行的配方优化包括松饼的物理参数(高度、密度、烘焙损失、体积和质量)和感官参数(颜色、外观、质地、味道、余味和总体可接受性)。然而,仅对用于制作松饼的面粉评估并优化了诸如持油能力和持水能力等功能参数。RSM分析将解释变量优化为添加10%的豌豆粉、减少50%的糖分以及烹饪22.7分钟。基于此,优化后的最终产品超过了预测的可接受水平,尤其是在味道(7.40)、余味(7.40)和总体喜好度(7.60)方面。根据解释变量和因变量使用各种配方组合设计了17次试验,并基于数据分析开发了优化配方并进行了点确认。统计分析在高度、密度和质地方面检测到不显著的结果(>0.05且<80%)。然而,烘焙损失、体积和质量呈现出显著结果(<0.05且分别为92%、87%和96%),表明模型拟合良好。本研究结果表明,豌豆蛋白可以添加到松饼中,同时保持其感官特性。