通过化学测量预测粉红胡 (Schinus terebinthifolius Raddi) 的质量参数的NIR和MIR光谱
Amanda Beatriz Sales de Lima1, Jessica Souza Coqueiro1, Elton Ferreira da Silva2
1Departamento de Tecnologia Rural e Animal, Universidade Estadual do Sudoeste da Bahia, Itapetinga, Bahia, Brazil.
概括
接近和中红外光谱为分析粉红质量提供了快速,无试剂的方法. 这种技术有效地预测了多种物理化学和抗氧化剂参数,克服了传统方法的局限性.
科学领域:
- 农业科学
- 分析化学
- 食品科学
背景情况:
- 传统的食品质量控制方法往往耗时且资源密集.
- 开发快速,高效的分析技术对于食品工业至关重要.
研究的目的:
- 探索近红外和中红外光谱学与化学分析分析粉红色胡的应用.
- 预测粉红胡的物理化学成分,成分和抗氧化剂.
主要方法:
- 使用部分最小平方 (PLS) 和间隔部分最小平方 (iPLS) 回归的34个模型的优化.
- 基于相关系数,误差值,RPD和RER的模型验证.
主要成果:
- iPLS模型显示出出色的预测能力 (相关系数≥0.7) 和实用性.
- 与全谱PLS模型相比,iPLS模型显示出更高的线性和适配参数.
- 能够同时预测 17 个质量参数.
结论:
- 接近和中红外光谱为粉红胡的常规质量分析提供了有效的替代方案.
- 这种方法避免了繁的传统色谱法和光谱法程序.
- 这项研究强调了光谱技术在食品中快速同时进行质量评估的潜力.
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