基于近红外光谱的铁皮石斛粉末实时放行测试方法

    Near-infrared Spectroscopy for Real-time Release Testing of Dendrobii Officinalis Caulis Powder

    • 摘要:
      目的  提出一种基于近红外光谱的铁皮石斛粉末实时放行测试方法,解决现行多糖检测方法(苯酚-硫酸法)检测时间较长,客观上造成了生产效率低下的问题。
      方法 首先,获取粉末的短波近红外光谱、长波近红外光谱和多糖含量数据。其次,使用预处理、特征波段和定量模型相结合的方式处理光谱信号。然后,使用预处理融合算法继续处理数据质量更高的长波近红外光谱数据。最后,优选多糖含量快速预测模型,生成预测值分布图,估计概率风险,并决定当前批次粉末中间品是否放行。
      结果 预处理融合算法在测试集上预测多糖含量的均方根误差为1.297%,决定系数为0.924,预测值和真值的误差较小。预测值的分布图能够直观地量化特定样品的概率风险。
      结论 所提方法可应用于铁皮石斛粉末的放行测试,缩短生产周期,并有望推广至其他药食两用产品。

       

      Abstract:
      OBJECTIVE To propose a real-time release test for Dendrobii Officinalis Caulis powder using near-infrared spectroscopy and address the inefficiency of the current polysaccharide detection method(phenol-sulfuric acid assay), which suffers from prolonged analysis time and consequently reduces production efficiency.
      METHODS  Initially, data on the short-wave and long-wave near-infrared spectrum and polysaccharide content of the powder were collected. Then, the spectral signals were processed using preprocessing, characteristic band, and a quantitative model. A pretreatment fusion algorithm enhanced the long-wave near-infrared spectral data quality. Finally, a rapid prediction model for polysaccharide content was chosen, with generated a predicted value distribution map, estimated probabilistic risk, and determined the release of the current batch of powder intermediates.
      RESULTS  The root mean squared error of the preprocessing fusion algorithm in predicting the polysaccharide content on the test set was 1.297%, and the coefficient of determination was 0.924, indicating a small error between predicted and true values. The predicted value distribution effectively quantified the probabilistic risk of a sample.
      CONCLUSION  The proposed method can be used for Dendrobii Officinalis Caulis powder release tests, reduces production time, and may be applicable to other medicinal and edible products.

       

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