一种基于二维相关性光谱分析的方法,用于在储存的土豆中检测无症状腐烂,使用超光谱成像
Fan Zhang1, Wenxiu Wang1, Qianyun Ma1
1College of Food Science and Technology, Hebei Agricultural University, 289th Lingyusi Street, Lianchi District, Baoding 071000, China.
Food chemistry: X
|July 15, 2024
概括
超光谱成像 (HSI) 有效地监测储存的土豆中的Fusarium干腐 (FDR). 这项技术绘制了腐烂进展和组件变化的地图,有助于疾病管理和质量评估.
科学领域:
- 农业科学 农业科学
- 植物病理学 植物病理学
- 频谱学是一种光谱学.
背景情况:
- 菌体干 (Fusarium dry rot,FDR) 显著影响土豆的储存质量和产量.
- 精确监测FDR进展对于有效的疾病管理至关重要.
研究的目的:
- 利用高光谱成像 (HSI) 识别化阶段并监测存储的土豆中的FDR进展.
- 在土豆感染期间评估易感性参数和质量属性.
主要方法:
- 使用超光谱成像 (HSI) 系统,从受感染的土豆样本中获取光谱数据.
- 两维相关谱 (2D-COS) 用于分析光谱数据和映射组件变化.
- 基于二维相关联同步光谱的定量分析模型被开发出来.
主要成果:
- 这项研究确定了20个与粉,可溶性蛋白质,氨酸和有氧细菌含量相关的光谱峰值.
- 定量分析模型显示出高准确度,最佳验证的相关系数从0.9273到0.9634.
- 对超光谱图像的视觉分析有效地显示了这些指标组件的分布.
结论:
- HSI是一种可行的工具,用于非破坏性监测Fusarium干腐烂的进展以及储存的土豆中的相关生化变化.
- 开发的定量模型允许在疾病发展过程中准确评估关键质量指标.
- 这种方法支持改善疾病管理策略和马储存的质量控制.
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