基于近红外光谱和机器视觉的蛋黄颜色检测研究
Yukuan Wen1, Guimei Dong1, Weijian Yin1
1College of Engineering and Technology, Tianjin Agricultural University, Tianjin 300392, China. yaping261@163.com.
Analytical methods : advancing methods and applications
|October 4, 2025
概括
一种新的非破坏性机器视觉方法可以准确预测蛋黄的颜色. 这种客观的方法克服了人类的主观性,为蛋质量评估和消费者偏好提供了显著的进步.
科学领域:
- 农业科学 农业科学
- 食品科学 食品科学 食品科学
- 分析化学 分析化学
背景情况:
- 蛋黄颜色是蛋质量的关键指标,影响消费者偏好和营养价值.
- 目前的卵黄颜色评估依赖于主观的罗氏卵黄颜色风扇 (RYCF) 方法,需要破坏卵.
- 开发非破坏性的客观方法来分析蛋黄的颜色对蛋行业来说非常重要.
研究的目的:
- 开发和验证一种非破坏性机器视觉方法,用于客观地分类蛋黄的颜色.
- 克服人类主观性的局限性固有的传统黄颜色评估.
- 为了建立精确和准确的卵黄颜色分数的定量检测.
主要方法:
- 收集了150个卵样本,卵黄颜色分数从5到11不等.
- 获得的近红外 (NIR) 光谱数据来自完整的蛋和分离的黄.
- 开发了使用部分最小平方 (PLS) 和机器学习技术 (TCN-GRU-Attention,LSSVM,CNN-BiLSTM-Adaboost) 的回归预测模型.
主要成果:
- 部分最小平方 (PLS) 模型显示,完整的卵 (R2=0.9035) 和分离的黄 (R2=0.9274) 均具有更高的预测准确性.
- 在PLS模型中,低根平均平方误差 (RMSE) 为0.3665的完整卵和0.2933的分离黄.
- 这些结果表明,成功地进行了对蛋黄颜色评分的非破坏性定量检测.
结论:
- 开发的机器视觉方法,特别是使用PLS回归,为传统的黄黄颜色评估提供了客观而准确的替代方案.
- 近红外 (NIR) 光谱学与化学测量和机器学习模型相结合,可实现精确的,非破坏性的蛋黄颜色分级.
- 这项技术在改善卵子质量控制和满足消费者对高质量蛋的需求方面具有重大潜力.
相关概念视频
01:32UV–Vis Spectroscopy of Conjugated Systems
Organic compounds with conjugated double bonds show strong absorption features in the UV–visible region of the electromagnetic spectrum attributed to π → π* electronic excitations. Generally, a UV–vis absorption spectrum is recorded as a plot of absorbance vs wavelength. The wavelength of maximum absorbance, which manifests as a peak in the absorption spectrum, is denoted as λmax.
One of the factors influencing λmax is the extent of conjugation in the...
One of the factors influencing λmax is the extent of conjugation in the...
01:24Color Vision
Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.