通过智能方法对粉凝化的有效和快速评估
Guiliang Zhong1, Yican Liu2, Shaobo Zhang1
1School of Food Science and Engineering, South China University of Technology, Guangzhou, China.
International journal of biological macromolecules
|April 10, 2025
概括
智能Mask R-CNN系统准确地实时监控土豆粉的凝化. 这种自动化方法准确地跟踪粉颗粒的转化,增强食品质量控制和流程优化.
科学领域:
- 食品科学与技术 食品科学与技术
- 材料科学 材料科学 材料科学
- 生物技术是生物技术.
背景情况:
- 粉的凝化对于食品的特性,如水结合和粘度至关重要.
- 传统的显微镜方法对于实时粉分析是有限的.
- 监测粉转化对于食品质量控制至关重要.
研究的目的:
- 开发一种智能系统,实时分析粉颗粒凝化.
- 使用Mask R-CNN.准确地细分和识别土豆粉颗粒.
- 在热加工过程中有效计算凝化程度 (DG).
主要方法:
- 使用B型土豆粉进行实验分析.
- 开发和训练了一种用于粉颗粒细分和识别的Mask R-CNN模型.
- 采用自动图像分析来实时监测凝化阶段.
主要成果:
- 面膜R-CNN系统在不到一秒的时间内准确地识别和细分了粉颗粒.
- 观察到明显的相变,颗粒阶段在55°C,60°C和72°C左右发生显著变化.
- 在57°C和68°C之间观察到所有四个凝化阶段的共存.
结论:
- 智能Mask R-CNN系统为分析土豆粉凝化提供了一个高度准确和高效的方法.
- 这种自动化方法提供了有价值的见解,了解粉在不同条件下的行为.
- 该技术在食品配方,工艺优化和质量保证方面具有潜在的应用.
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