Rapid detection of the reducing sugar and amino acid nitrogen contents of Daqu based on hyperspectral imaging

高光谱成像 还原糖 化学 主成分分析 氮气 氨基酸 氨基糖 食品科学 色谱法 人工智能 生物化学 计算机科学 有机化学
作者
Haoping Huang,Xinjun Hu,Jianping Tian,Xinna Jiang,Huibo Luo,Dan Huang
出处
期刊:Journal of Food Composition and Analysis [Elsevier BV]
卷期号:101: 103970-103970 被引量:50
标识
DOI:10.1016/j.jfca.2021.103970
摘要

In this research, the hyperspectral imaging technique was employed to realize the rapid and accurate detection of the reducing sugar and amino acid nitrogen contents of Daqu during fermentation. Different preprocessed data were employed to establish cascade forest (CF) models to determine the best preprocessing method. Principal component analysis (PCA) and the successive projection algorithm (SPA) were then combined to extract the characteristic wavelengths. Four types of models (CF, BPNN, SVR, and PLSR) were established based on the full and characteristic wavelengths, respectively. Among all the models, the CF model established by the characteristic wavelengths was determined to be superior for the detection of the reducing sugar and amino acid nitrogen contents: for reducing sugar, RP2 = 0.9862, RMESP = 0.0812 g/100 g, and RPD = 6.0402; for amino acid nitrogen, RP2 = 0.9876, RMSEP = 0.0500 g/100 g, and RPD = 6.3698. The best model achieved the visualization of the reducing sugar and amino acid nitrogen contents in the region of interest. The satisfactory detection results demonstrate that the hyperspectral imaging technique can be used to realize the rapid and accurate detection of the reducing sugar and amino acid nitrogen contents of Daqu during fermentation.
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