工业塔皮奥卡粉水解产品的分类,基于它们的布里克斯和乳糖等价值,使用近红外光谱学
Chayanid Sringarm1, Sonthaya Numthuam2, Sudarat Jiamyangyuen3
1Department of Agro-Industry, Faculty of Agriculture Natural Resources and Environment, Naresuan University, Phitsanulok, Thailand.
Journal of the science of food and agriculture
|April 17, 2024
概括
近红外 (NIR) 谱学可以通过预测布里克斯和乳糖等效 (DE) 值来分类塔皮奥卡粉水解产品. 这种方法为传统评估提供了更快的替代方案,在产品分类中达到95%的准确性.
科学领域:
- 分析化学 分析化学
- 频谱学是一种光谱学.
- 食品科学 食品科学 食品科学
背景情况:
- 工业粉水解产生基于布里克斯和乳糖等价物 (DE) 的功能多样化的糖.
- 目前对这些产品的评估方法耗时且劳动密集.
- 需要有效的方法来评估粉水解产品.
研究的目的:
- 调查近红外 (NIR) 光谱技术在分类塔皮奥卡粉水解产品方面的潜力.
- 开发一种快速而准确的方法来控制粉衍生物的质量.
主要方法:
- 近红外 (NIR) 光谱从7种不同的塔皮奥卡粉水解产品的410个样本中收集.
- 建立了直角部分最小平方 (OPLS) 回归模型来预测Brix和DE值.
- 支持向量机器 (SVM) 使用原始光谱和OPLS衍生潜变量 (LVs) 来进行分类.
主要成果:
- OPLS模型成功地预测了来自NIR光谱的Brix和DE值.
- 在使用OPLS模型用于DE预测的潜变量时,SVM分类实现了95%的准确性.
- 这表明了NIR光谱学与产品分类化学计量学相结合的有效性.
结论:
- 尼尔光谱显示,根据功能性质对塔皮奥卡粉水解产品进行分类有很大的潜力.
- 开发的方法为传统分析技术提供了快速而准确的替代方案.
- 这种方法可以帮助进行粉制糖的质量控制和表征.
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