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Mechanism and Multilayer Perceptron prediction model of the removal of α-terpineol, terpinen-4-ol and carvone from pasteurized citrus juices by β-cyclodextrin encapsulation

松油醇 香芹酮 环糊精 化学 食品科学 封装(网络) 麦芽糊精 色谱法 糖精 柠檬烯 精油 计算机科学 生物 喷雾干燥 计算机网络 内分泌学
作者
Ruijie Mai,S. Xue,Jingnan Ren,Gang Fan,Jinchu Yang,Linhua Huang,Guijie Li,Yujiao Cheng,Qiuling Wang,Yongfeng Yang,Zhenzhen Huang,Yingjie Feng,Wenzhao Liu,Aiqun Yu,Jian Feng
出处
期刊:Frontiers in Nutrition [Frontiers Media]
卷期号:12
标识
DOI:10.3389/fnut.2025.1557934
摘要

This study revealed the mechanism of improvement in sensory evaluation of citrus juices after pasteurization by the natural cyclodextrin ( β -CD), and developed a prediction model for encapsulation based on conventional physicochemical indicators. The results of gas chromatography–mass spectrometry indicated that the off-flavor in citrus juice after pasteurization were mainly caused by α -terpineol, terpinen-4-ol and carvone, and the addition of β -CD could effectively reduce the content of these compounds. The inclusion complexes of β -CD and off-flavor compounds were characterized by formation constants, scanning electron microscope, X-ray diffraction, Fourier transform infrared spectroscopy, and thermogravimetric analyses, followed by molecular docking to show the possible conformations of β -CD and off-flavor compounds to form 1:1 inclusion complex by hydrophobic interaction, van der Waals forces and hydrogen bonding. Multiple prediction models were constructed and evaluated by deep learning using basic physicochemical indicators such as sucrose content, citric acid content, pH, temperature and storage conditions as input variables, and peak area of off-flavor compounds as output layer. The results showed that the Multilayer Perceptron Model had great potential in predicting the cyclodextrin embedding effect.
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