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使用图像分析技术预测轻羊肉尸体的组成.

João J Afonso1, Mariana Almeida2, Ana Catharina Batista2

  • 1Centre for Interdisciplinary Research in Animal Health (CIISA), Faculty of Veterinary Medicine, University of Lisbon, Avenida da Universidade Técnica, 1300-477 Lisboa, Portugal.

Animals : an open access journal from MDPI
|June 19, 2024
PubMed
概括
此摘要是机器生成的。

视频图像分析 (VIA) 准确地预测轻羊肉尸体中的组织组成. 这种客观方法使用摄影测量来评估羊肉体的肌肉,脂肪和骨含量.

关键词:
尸体的组成 尸体的组成轻光的羔羊羔羊的灯光视频图像分析 视频图像分析

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科学领域:

  • 动物科学动物科学
  • 农业工程 农业工程
  • 食品科学 食品科学 食品科学

背景情况:

  • 评估绵羊尸体的成分对于质量评估至关重要.
  • 传统的方法可能是劳动密集型和主观的.
  • 需要客观的,非侵入性的技术来处理轻质的羊肉.

研究的目的:

  • 评估视频图像分析 (VIA) 的有效性,以确定轻羊肉尸体的组织组成.
  • 使用VIA开发肌肉,脂肪和骨含量的预测模型.
  • 建立VIA作为羊肉尸体评估的客观工具.

主要方法:

  • 收集了55只轻羊肉尸体的摄影图像 (侧面和背面).
  • 提取了 21 个侧面和 29 个背面测量 (长度,宽度,角度,面积,周边).
  • 利用K-Folds渐进式多重回归来构建组织重量和百分比的预测模型.

主要成果:

  • 使用冷尸体重量 (CCW) 和图像数据的VIA模型解释了组织重量的显著变化 (K-fold-R2: 0.830.98).
  • 组织百分比的模型显示解释变化略低 (K-fold-R2:0.410.78),但仍然依赖VIA测量.
  • 当将CCW与侧面和背面视图测量相结合时,预测准确度最高.

结论:

  • 视频图像分析是一种非常有效和客观的工具,用于评估轻羊肉尸体的组成.
  • VIA提供了有价值的数据,用于预测羊肉体的肌肉,脂肪和骨含量.
  • 该技术为肉类行业的质量评估提供了一个非侵入性和高效的替代方案.