超光谱成像作为一种非破坏性技术的应用,用于识别番茄成熟度和量化预测烯含量
Chunxia Dai1, Jun Sun1, Xingyi Huang2
1School of Electrical and Information Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, China.
Foods (Basel, Switzerland)
|August 12, 2023
概括
超光谱成像可以有效地监测番茄的成熟度和烯含量. 这项技术准确地分类成熟度,并预测烯水平,为质量评估提供了可行的工具.
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:
- 番茄的质量评估至关重要,成熟度与柳科含量直接相关.
- 需要准确的,非破坏性的方法来监测西红的成熟度和烯水平.
研究的目的:
- 开发和验证高光谱成像技术,以评估番茄成熟度和预测柳科含量.
- 为了比较不同的化学测量模型进行定性和定量分析.
主要方法:
- 使用标准正常变量 (SNV) 转换进行超谱成像数据预处理.
- 通过竞争性适应性重权采样 (CARS) 进行特征波长选择.
- 开发支持矢量分类器 (SVC) 用于成熟度分类和支持矢量回归 (SVR) 和部分最小平方回归 (PLSR) 用于烯预测.
主要成果:
- 在使用特征波长对番茄成熟度进行分类时,SVC实现了95.83%的准确性.
- 基于选定的波长,SVR模型显示出优越的烯预测 (R2P = 0.9652,RMSEP = 0.0166 mg/kg).
- 视觉分布图提供了对烯含量的直观评估.
结论:
- 超光谱成像是一种可行的技术,用于对番茄成熟度和烯含量进行非破坏性监测.
- 化学测量分析,特别是使用选定的波长,提高了成熟度分类和烯预测的准确性.
- 这种方法为番茄生产和储存的实时质量控制提供了潜力.
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