在桃番茄中检测出白烯,其功能增强和数据融合
Yuanhao Zheng1, Xuan Luo2, Yuan Gao3
1College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, PR China; Key Laboratory of Intelligent Equipment and Robotics for Agriculture of Zhejiang Province, Hangzhou 310058, PR China.
Food chemistry
|September 15, 2024
概括
这项研究通过结合光谱和图像数据,增强了桃番茄中烯的检测. 这种新的方法改善了水果的非破坏性质量预测.
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:
- 百合素是桃番茄中重要的植物化学物质和质量指标.
- 准确的烯检测对于质量控制至关重要.
- 现有的方法面临着低度和在线检测的挑战.
研究的目的:
- 为了提高在桃番茄中非破坏性烯检测的准确性.
- 调查光谱和图像数据的联合使用,以提高预测.
- 为了验证使用UV/Vis/NIR光谱和图像特征的可行性.
主要方法:
- 使用紫外/可见/近红外 (UV/Vis/NIR) 光谱和图像分析.
- 实施了光谱特征增强,专注于与烯相关的频段.
- 采用光谱图像融合技术进行数据集成.
主要成果:
- 光谱特征增强提高了最初光谱模型的性能.
- 直接的光谱图像融合进一步提高了预测准确度.
- 在RP2=0.95,RMSEP=8.96 mg/kg,RPD=4.25.5的情况下,实现了高预测准确度.
结论:
- 通过图像信息来补充光谱数据,可以显著提高非破坏性莱科检测.
- 开发的方法为在线水果质量预测提供了实际意义.
- 这项研究提供了一个可靠的方法来评估农产品中的甘含量.
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