Zheng Chuanmao, Li Jieqing, Liu Honggao, Wang Yuanzhong
College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming, 650201, China.
Medicinal Plants Research Institute, Yunnan, Academy of Agricultural Sciences, Kunming 650200, China.
Food Chem X. 2024 Jul 15;23:101661. doi: 10.1016/j.fochx.2024.101661. eCollection 2024 Oct 30.
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 Rp 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.
食用菌的味道和香气是消费者购买的判断标准，它们受氨基酸及其代谢产物的影响。采用液相色谱 - 质谱联用（LC-MS）鉴定出68种氨基酸及其代谢产物，并筛选出16种关键标记成分。利用二维相关光谱（2DCOS）表征不同种类牛肝菌的化学成分，以确定分子振动或基团变化的顺序。基于偏最小二乘判别分析（PLS-DA）结合傅里叶变换近红外光谱（FT-NIR）和傅里叶变换红外光谱（ATR-FTIR）对牛肝菌物种进行鉴定，采用残差卷积神经网络（ResNet）结合三维相关光谱（3DCOS），准确率达到100%。偏最小二乘回归（PLSR）分析表明，FT-NIR和ATR-FTIR光谱与LC-MS检测到的氨基酸及其代谢产物高度相关。所有模型的Rp均达到0.911，RPD>3.0。结果表明，FT-NIR和ATR-FTIR光谱结合化学计量学方法可用于快速鉴定牛肝菌物种并估计其氨基酸及其代谢产物含量。本研究为牛肝菌物种信息的真实性和质量评估提供了新技术和新思路。
