在乳制品溶液的热处理过程中测量和预测污染的方法
Justyna Tarapata1,2, Tara R Murphy1,2, Eoin W Finnegan1,2
1School of Food and Nutritional Sciences, University College Cork, Cork, Ireland.
Comprehensive reviews in food science and food safety
|June 13, 2025
概括
乳制品加工污染是一个主要问题. 本次审查侧重于用于污染控制的预测驱动方法,整合人工智能和实时数据以优化效率和可持续性.
科学领域:
- 食品科学与技术 食品科学与技术
- 化学工程是化学工程的重要组成部分.
- 过程控制 过程控制
背景情况:
- 乳制品的热加工面临着过程中的污染造成的重大挑战,影响效率,能源使用和清洁.
- 现有的审查主要集中在污染量化上,忽视了对预测性污染控制的日益增长的需求.
研究的目的:
- 批判性地评估当前和新兴的测量和预测乳制品加工污染的方法.
- 突出向有效污染管理和最小化预测驱动方法的转变.
主要方法:
- 评估传统的测量技术 (热阻,压力下降) 和新型传感器技术 (声学,光谱,电化学).
- 探索先进的预测工具,包括深度学习,计算流体动力学和维度分析.
- 考虑小规模的实验系统,以弥合实验室研究和工业应用.
主要成果:
- 新兴传感器在灵敏度,可扩展性和工业稳定性方面比传统方法具有潜在的优势.
- 预测工具,特别是与实时数据集成的AI,对动态污染建模和决策充满希望.
- 人工智能与实时数据采集的整合是改善污染管理和优化清洁的关键.
结论:
- 向预测驱动的污染控制转变对于优化乳制品加工至关重要.
- 通过实时监控和预测分析,可以提高工艺效率,减少清洁时间和可持续制造.
- 跨学科的合作对于将新技术转化为可扩展的工业化污染控制解决方案至关重要.
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