Application of ATR-FTIR and FT-NIR spectroscopy coupled with chemometrics for species identification and quality prediction of boletes

文献类型： 外文期刊

第一作者： Zheng, Chuanmao

作者： Zheng, Chuanmao;Li, Jieqing;Zheng, Chuanmao;Wang, Yuanzhong;Liu, Honggao

作者机构：

关键词： Boletes; Amino acid metabolomics; LC-MS; FT-NIR; ATR-FTIR; 2DCOS

期刊名称：FOOD CHEMISTRY-X （ 影响因子：6.5； 五年影响因子：6.4 ）

ISSN： 2590-1575

年卷期： 2024 年 23 卷

页码：

收录情况： SCI

摘要： The taste and aroma of edible mushrooms, which is a criterion of judgment for consumer purchases, are influenced by amino acids and their metabolites. Sixty-eight amino acids and their metabolites were identified using liquid chromatography mass spectrometry (LC-MS), and 16 critical marker components were screened. The chemical composition of different species of boletes was characterized by two-dimensional correlation spectroscopy (2DCOS) to determine the sequence of molecular vibrations or group changes. Identification of boletes species based on partial least squares discrimination (PLS-DA) combined with Fourier transform near-infrared spectroscopy (FT-NIR) and Fourier transform infrared spectroscopy (ATR-FTIR), residual convolutional neural network (ResNet) combined with three-dimensional correlation spectroscopy (3DCOS) was performed with 100% accuracy. Partial least squares regression (PLSR) analysis showed that FT-NIR and ATR-FTIR spectra were highly correlated with the amino acids and their metabolites detected by LC-MS. All models had achieved an R 2 p of 0.911 and an RPD >3.0. The results show that FT-NIR and ATR-FTIR spectroscopy in combination with chemometrics methods can be used for rapid species identification and estimation of amino acids and their metabolites content in boletes. This study provides new techniques and ideas for the authenticity of species information and the quality assessment of boletes.

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