非破坏性质量评估和基于高光谱成像的成熟度分类
Shunan Feng1, Jing Shang2,3, Tao Tan1
1Food and Pharmaceutical Engineering Institute, Guiyang University, Guiyang, 550005, China.
Scientific reports
|August 14, 2023
概括
超光谱成像提供了一种非破坏性的方法来评估loquat的质量,包括颜色,度和可溶性固体含量. 这项技术准确地预测了鱼的成熟度,克服了传统破坏性采样方法的局限性.
科学领域:
- 农业科学 农业科学
- 食品科学 食品科学 食品科学
- 频谱学是一种光谱学.
背景情况:
- 传统的鱼质量评估是破坏性的,耗时的.
- 有效的质量控制需要非破坏性方法.
研究的目的:
- 开发一种非破坏性的方法,使用高光谱成像来评估loquat的质量.
- 为了预测loquats的颜色,度和可溶性固体含量 (SSC).
- 为了分类loquat的到期期水平.
主要方法:
- 超光谱成像技术用于非破坏性分析.
- 竞争适应重权算法 (CARS) 和多重线性回归 (MLR) 用于特征选择和模型校准.
- 部分最小方形歧视分析 (PLSDA) 用于到期分类.
主要成果:
- 汽车-MLR模型实现了颜色 (R2P=0.96),度 (R2P=0.87) 和SSC (R2P=0.84) 的高预测精度.
- 使用伪色技术生成了质量属性的视觉分布图.
- 对于loquat的成熟度,PLSDA实现了98.19% (校准) 和97.99% (预测) 的高分类准确率.
结论:
- 超光谱成像是一种可行的,有效的非破坏性技术,用于洛克瓦特的质量评估.
- 开发的模型准确地预测了关键的质量参数,并对loquat成熟度进行了分类.
- 这项技术有望改善鱼产业的质量控制和管理.
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