用多个弱酸模拟大树糖的配方pH值
Nicholas Fragedakis1, Caitlin R Skinner2, Mileah Shriner1
1Department of Food, Bioprocessing and Nutrition Sciences, North Carolina State University, Raleigh, North Carolina, USA.
Journal of food science
|June 16, 2023
概括
这项研究开发了缓冲模型,以预测酸化大树糖的pH值. 这些模型根据成分缓冲能力 (tBeta) 准确估计了产品的pH值,有助于食品产品的开发和安全.
科学领域:
- 食品化学 食品化学
- 食品科学 食品科学 食品科学
- 化学工程是化学工程的重要组成部分.
背景情况:
- 酸性食品,如桑糖,需要精确的pH控制,以确保安全和质量.
- 了解成分的缓冲能力对于预测最终产品pH至关重要.
- 在复杂的食物矩阵中预测pH值的现有方法可能是有限的.
研究的目的:
- 开发和验证缓冲模型,用于预测酸化大树糖的pH值.
- 量化个别食品成分的缓冲能力 (tBeta).
- 评估成分组成对最终产品pH的影响.
主要方法:
- 定义的总成分缓冲 (tBeta) 是缓冲容量曲线下的面积 (pH 2-12).
- 测量了tBeta对于主要的树糖成分,如酸,树汁,酸,酸和汁.
- 使用Matlab软件开发和应用联合缓冲模型,根据成分度和tBeta值预测糖的pH值.
主要成果:
- 酸,桑汁和酸表现出最高的缓冲能力 (tBeta值).
- 预测的糖pH值 (2.78) 与观察到的pH值 (2.67) 非常接近,差异为0.11个pH单位.
- 对16种模型配方的回归分析显示,观察到的pH和预测的pH之间非常适合,根平均平方误差为0.076pH单位.
结论:
- 使用成分tBeta值的缓冲模型为酸性食品配方的pH值提供了精确的in silico估计.
- tBeta指标对于识别对pH值产生最显著影响的成分是有价值的.
- 这些模型可以增强产品开发和酸性食品的安全评估.
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