用可见光和近红外光谱仪在完整的水果上分析不同储存时间的波梅罗皮精油
Panmanas Sirisomboon1, Jittra Duangchang1, Thitima Phanomsophon2
1Department of Agricultural Engineering, School of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok 10520, Thailand.
Foods (Basel, Switzerland)
|August 10, 2024
概括
葡萄皮是一种废弃产品,含有有价值的精油 (EO). 可见和近红外光谱学 (VIS/NIRS) 可以预测储存期间完整的果皮中的EO成分,特别是nootkatone.
科学领域:
- 农业科学 农业科学
- 分析化学 分析化学
- 生物技术是生物技术.
背景情况:
- 葡萄 (Citrus maxima) 皮是一种重要的生物废物流.
- 皮皮含有有价值的生物活性化合物,特别是精油 (EO).
- 了解EO生物合成和化学成分对于工业应用和育种研究至关重要.
研究的目的:
- 评估可见和近红外光谱学 (VIS/NIRS) 的有效性,以预测果皮中的精油 (EO) 成分.
- 在冷藏期间建立NIR光谱数据和主要EO组件之间的关系.
- 评估VIS/NIRS作为一种快速,非破坏性的技术,用于果皮EO分析的潜力.
主要方法:
- 葡萄果 (Citrus maxima cv Kao Nam Pueng) 的皮在10°C和70%的相对湿度下保存了120天.
- 用气色谱-质谱法 (GC-MS) 在各种储存间隔分析了精油成分.
- 可见和近红外 (VIS/NIRS) 频谱数据采集并使用部分最小方程 (PLS) 回归进行分析,并进行光谱预处理 (MSC,第二导数).
主要成果:
- 开发了部分最小平方 (PLS) 回归模型,以将VIS/NIRS数据与主要EO成分相关联:nootkatone,geranial,β-phellandrene和 limonene.
- 使用乘数分散校正 (MSC) 的nootkatone的PLS模型显示了最高的预测能力 (r = 0.82,SEP = 0.11%).
- 基拉尼亚,β-费兰德烯和利蒙的模型表现出较低的相关系数 (r = 0.75,0.75和0.67,分别).
结论:
- 在冷藏期间,VIS/NIRS显示了在完整的果皮中预测nootkatone含量的潜力,适合选和近似校准.
- 这项研究是第一个关于在冷藏期间使用NIR光谱在完整水果上的NIR光谱研究报告,用于皮EO成分.
- 对NIR模型的进一步改进可能会提高果皮中的其他主要EO成分的预测准确性.
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