Prediction of pyrazines and identification of flavor intensity in boletus bainiugan at different drying temperatures based on feature variables
文献类型： 外文期刊
作者： Deng, Guangmei 1 ; Li, Jieqing 1 ; Liu, Honggao 3 ; Wang, Yuanzhong 2 ;
作者机构： 1.Yunnan Agr Univ, Coll Agron & Biotechnol, Kunming 650201, Peoples R China
2.Yunnan Acad Agr Sci, Med Plants Res Inst, Kunming 650200, Peoples R China
3.Zhaotong Univ, Yunnan Key Lab Gastrodia & Fungi Symbiot Biol, Zhaotong 657000, Yunnan, Peoples R China
关键词： Boletus bainiugan; Fourier transform near infrared spectroscopy; Attenuated total reflectance Fourier transform; infrared spectroscopy; Data fusion; Volatile compounds
期刊名称：FOOD RESEARCH INTERNATIONAL （ 影响因子：8.0； 五年影响因子：8.5 ）
ISSN： 0963-9969
年卷期： 2025 年 211 卷
页码：
收录情况： SCI
摘要： Low-cost and high-throughput quantitative analysis of volatile compounds is essential for flavor studies in Boletus bainiugan. However, traditional methods are time-consuming and labor-intensive. Herein, a rapid prediction method of pyrazines based on spectroscopic and data fusion techniques for Boletus bainiugan of different drying temperatures is proposed. Four datasets, Fourier transform Near infrared (FT-NIR) spectroscopy, Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, and low-level and middle-level data fusion, are used to build 147 partial least squares regression (PLSR) prediction models based on different preprocessing and feature extraction methods. The results indicates that the second-order derivation- uninformative variable elimination (SD-UVE) based FT-NIR spectral dataset achieved accurate prediction for seven important compounds (pyrazines), with the coefficient of determination of prediction set (R2p) higher than 0.840 and residual predictive deviation (RPD) are all greater than 2.418. The screened 189 feature wavenumbers can be used to accurately predict other pyrazine compounds with the highest R2p of 0.909 and the best RPD of 2.506, and successfully differentiate between Boletus bainiugan with high flavor intensity (65 degrees C) and other drying temperature samples with a validation set accuracy of 95.23 %. This study achieved the work of predicting the relative content of pyrazine volatile compounds in different drying temperatures of Boletus bainiugan, which provides a theoretical basis for the study of other classes of compounds in spectral distribution and prediction.
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