预测油炸食品质量参数的图形用户界面

IF 2.7 3区 农林科学 Q3 ENGINEERING, CHEMICAL Journal of Food Process Engineering Pub Date : 2024-09-15 DOI:10.1111/jfpe.14737
Siti Nabihah Othman, Norazaliza Mohd Jamil
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引用次数: 0

摘要

受热和传质现象的影响,油炸过程会使食品的颜色和水分含量发生显著的物理化学变化。油炸食品(如炸鸡块、炸薯条和炸鸡派)要达到稳定的质量具有挑战性,这就凸显了预测这些变化的重要性。本研究深入探讨了薯条在油炸过程中颜色和水分含量的动态变化。为了模拟这些变化,研究采用了颜色和水分含量的一阶动力学方程,并利用 Runge-Kutta 四阶法以及 MATLAB 中的 Nelder-Mead 算法等数值解决方案。阿伦尼乌斯方程在该模型中起着关键作用。使用均方根误差 (RMSE) 和 Akaike 信息准则 (AIC) 将修改后的模型与现有模型进行比较。需要注意的是,调查评估了油温(150、170 和 190°C)以及样品厚度(5、10 和 15 毫米)在油炸过程中对薯条水分和颜色含量的影响。结果表明,与现有模型相比,改进后的模型精度更高,RMSE 和 AIC 值更低,为了解油炸过程提供了更可靠的工具。因此,由于加入了用户友好型图形界面(GUI),即使数学或编程专业知识有限的人也可以使用这种建模方法,从而使寻求对油炸过程有更深入了解的专业人员受益匪浅。 实际应用 本研究中提出的用于预测油炸食品质量的图形用户界面(GUI)具有广泛的工业应用价值。在食品工业中,它是确保薯条和炸鸡块等产品的质量一致性的关键工具,使制造商能够优化油炸过程。快餐连锁店可以利用图形用户界面最大限度地降低成本和能耗,同时保持产品质量。此外,它还有助于设备校准,成为操作员寻求油炸设备最佳性能和使用寿命的宝贵财富。烹饪学校可将该图形用户界面作为一种教育工具,让有抱负的厨师切实了解油炸科学,从而从中受益。研究人员和食品科学家可以通过有效评估变量的影响来加快研发周期。中小型企业、监管机构和食品零售商可以利用图形用户界面进行质量控制、合规性和消费者教育,共同促进行业的透明度、可持续性和全球健康水平的提高。
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A graphical user interface for predicting quality parameters of deep-fried foods

The process of deep-frying brings about significant physicochemical changes in the color and moisture content of foods, influenced by heat and mass transfer phenomena. Achieving consistent quality in fried foods, such as nuggets, fries, and chicken pies, is challenging, highlighting the importance of predicting these changes. This study delves into the evolving dynamics of color and moisture content, specifically in French fries during deep frying. To model these changes, the study employs a first-order kinetic equation for color and moisture content, utilizing numerical solutions like the Runge–Kutta fourth-order method as well as the Nelder–Mead algorithm in MATLAB. The Arrhenius equation plays a key role in this model. The modified model is compared against an existing model using the root mean square error (RMSE) and Akaike information criterion (AIC). Note that the investigation evaluates how oil temperature (at 150, 170, and 190°C) as well as sample thickness (at 5, 10, and 15 mm) impact the French fries' moisture and color content during frying. Results indicate that the modified model, with its improved accuracy and lower RMSE and AIC values compared to the existing model, provides a more reliable tool for understanding the frying process. Consequently, the inclusion of a user-friendly graphical interface (GUI) makes this modeling approach accessible even to those with limited mathematical or programming expertise, benefiting professionals seeking more profound insights into the frying process.

Practical applications

The graphical user interface (GUI) for predicting deep-fried food quality presented in this study holds broad industrial applications. It serves as a pivotal tool in the food industry for ensuring consistent quality across products like fries and nuggets, enabling manufacturers to optimize frying processes. Fast-food chains can use the GUI to minimize costs and energy consumption while maintaining product quality. In addition, it aids in equipment calibration, becoming an invaluable asset for operators seeking optimal performance and longevity in deep-frying equipment. Culinary schools benefit from this GUI as an educational tool, offering aspiring chefs a practical understanding of deep-frying science. Researchers and food scientists can accelerate R&D cycles by efficiently assessing the impact of variables. SMEs, regulatory bodies, and food retailers find utility in the GUI for quality control, compliance, and consumer education, collectively contributing to industry transparency, sustainability, and improved global health outcomes.

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来源期刊
Journal of Food Process Engineering
Journal of Food Process Engineering 工程技术-工程:化工
CiteScore
5.70
自引率
10.00%
发文量
259
审稿时长
2 months
期刊介绍: This international research journal focuses on the engineering aspects of post-production handling, storage, processing, packaging, and distribution of food. Read by researchers, food and chemical engineers, and industry experts, this is the only international journal specifically devoted to the engineering aspects of food processing. Co-Editors M. Elena Castell-Perez and Rosana Moreira, both of Texas A&M University, welcome papers covering the best original research on applications of engineering principles and concepts to food and food processes.
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