近红外光谱丸剂关键辅料炼蜜水分的快速测定

doi:10.3964/j.issn.1000-0593(2019)08-2590-05

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Abstract Near-infrared spectroscopy(NIRS) was used to quantify moisture content about refined-honey, and the practicability to classify the samples degree through refining was investigated. Process Analysis Technology is vital to affecting the quality stability of traditional Chinese medicines, with the lagging nature of detection methods, accurate real-time control of them cannot be achieved, ultimately affecting the homogeneity and stability of quality about traditional Chinese medicines. Sweetpill has a wide application market. The honey refining process is a critical process to affect the quality of it. However, the transition from tender to medium honey takes only a few to several tens of seconds. The traditional detection method cannot monitor it, leading to the fact that the uniformity of honey quality cannot be achieved. In order to identify and predict moisture content for tender, medium and old honey at the same time, the 88 different honeies were refined, and the qualitative and quantitative models were established based on Near Infrared Spectroscopy (NIRS). Using refractometer to measure the moisture content, and near infrared spectra of samples were also measured. Combined with partial least squares(PLS) algorithm were conducted on the calibration of regression model; the qualitative prediction model was used to establish the level of the refined honey by the factorization method. For the quantitative calibration model, the R², RMSEE, RMSECV were 99.43, 0.299, 0.34, respectively. For the prediction model, the R², RMSEP were 98.19, 0.347, respectively. Through the discriminant analysis, the qualitative model showed obvious clustering phenomenon. NIRS has good application prospects to be applied to real-time monitoring and moisture determination of refined honey.

Key words：NIRS; Refined honey; Moisture content; Real-time monitoring; Discriminant analysis

Received: 2018-06-14 Accepted: 2018-10-30

ZTFLH:

O657.3

Corresponding Authors: LI Hui E-mail: lihuiyiren@163.com

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https://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2019)08-2590-05 OR https://www.gpxygpfx.com/EN/Y2019/V39/I08/2590

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