基于数字图像的化学计量用于食品分析:一个实用的教程和路线图
Adriano de Araújo Gomes1, Paulo Henrique Gonçalves Dias Diniz2, David Douglas de Sousa Fernandes3
1Universidade Federal do Rio Grande do Sul, Instituto de Química, Zip Code 90650-001, Porto Alegre, RS, Brazil; Institute of Analytical Chemistry, Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 812 37 Bratislava, Slovakia.
Food chemistry
|May 14, 2025
概括
数字成像和化学测量为食品质量控制和安全提供了强大的分析方法. 标准化对于可靠的结果至关重要,但最近的进步,如深度学习,对更广泛的应用有希望.
科学领域:
- 食品科学 食品科学 食品科学
- 分析化学 分析化学
- 化学测量 化学测量 化学测量
背景情况:
- 数字成像越来越多地用于食品质量控制,超越传统信号提取化学信息.
- 化学测量技术显著提高了图像数据在食品分析中的实用性.
- 现有的文献显示了各种应用,但缺乏方法的标准化.
研究的目的:
- 审查数字成像在食品分析中的应用.
- 提供从单变量到多变量方法的路线图.
- 突出挑战和该领域的最新进展.
主要方法:
- 关于食品分析中数字成像应用的文献综合.
- 通过三个案例研究来说明方法.
- 讨论单变量和多变量化学测量技术.
- 审查最近的进展,如深度学习和混合色彩描述器.
主要成果:
- 数字成像,加上化学测量,显示出食品安全和质量评估的巨大潜力.
- 案例研究说明了这些技术的实际应用.
- 最近的进展提高了数字成像在食品科学中的稳定性和适用性.
结论:
- 数字成像为食品分析提供了一个多功能平台,补充了传统方法.
- 方法标准化对于确保现场可靠性和可重复性至关重要.
- 像深度学习这样的新兴技术已经准备好在食品科学中增强数字成像的能力.
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