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相关实验视频

Updated: Jun 28, 2025

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提高大头鱼的切割:冷藏储存洞察力和基于机器视觉的细分算法开发.

Qing Li1, Xinyi Wen1, Shijie Liang1

  • 1Beijing Laboratory for Food Quality and Safety, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China.

Food chemistry
|April 17, 2024
PubMed
概括
此摘要是机器生成的。

鱼类加工可以提高利用率. 大头鱼的切片表现出多种变质,眼肌 (EM) 具有高脂肪氧化和尾肌 (TM) 快速蛋白质降解. 一个机器视觉算法帮助处理.

关键词:
算法开发的发展算法.大头鱼的切割大头鱼的切割冷藏储存的冷藏方式机器视觉 机器视觉 机器视觉质量评估 质量评价 质量评价

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科学领域:

  • 食品科学 食品科学 食品科学
  • 水产养殖是水产养殖的一种方式.
  • 微生物学 微生物学

背景情况:

  • 鱼类加工,特别是切割,对于增加市场需求和鱼类利用至关重要.
  • 大头鱼是一个重要的水产养殖物种,需要优化加工技术.

研究的目的:

  • 评估不同大头鱼切片 (头部,背部,腹部,尾部) 的储存质量.
  • 为了研究微生物的增殖和生化变化冷藏的大头鱼肌肉.
  • 开发和评估用于自动化大头鱼加工的机器视觉算法.

主要方法:

  • 大头鱼被切成四个初级切片,并在4°C冷藏10天.
  • 微生物分析的重点是Pseudomonas.fragi和Aeromonas.sobria的丰度和生长.
  • 生物化学分析包括脂肪氧化和蛋白质降解评估.
  • 使用颜色值和形态参数的机器视觉算法被开发用于图像细分和鱼类区域识别.

主要成果:

  • 眼肌 (EM) 显示出最快的 Pseudomonas.fragi 扩散和最高的脂肪氧化.
  • 尾部肌肉 (TM) 呈现出最快的蛋白质降解,并支持Aeromonas.sobria的生长.
  • 每个鱼切片都表现出独特的储存质量特征.
  • 机器视觉算法有效地细分和划分大头鱼区域进行处理.

结论:

  • 冷的大头鱼的切片具有不同的储存质量,受到微生物活动和生化变化的影响.
  • 机器视觉技术为大头鱼的自动化和高效处理提供了可行的解决方案.
  • 优化的加工策略可以提高大头鱼的销售能力和利用率.