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微波和超声诱导的蘑菇混合物4D打印:麦角甾醇高效转化为维生素D

4D printing induced by microwave and ultrasound for mushroom mixtures: Efficient conversion of ergosterol into vitamin D.

作者信息

Chen Jieling, Zhang Min, Mujumdar Arun S, Phuhongsunge Pattarapon

机构信息

State Key Laboratory of Food Science and Technology, Jiangnan University, 214122 Wuxi, Jiangsu, China; International Joint Laboratory on Food Safety, Jiangnan University, 214122 Wuxi, Jiangsu, China.

State Key Laboratory of Food Science and Technology, Jiangnan University, 214122 Wuxi, Jiangsu, China; Jiangsu Province International Joint Laboratory on Fresh Food Smart Processing and Quality Monitoring, Jiangnan University, 214122 Wuxi, Jiangsu, China.

出版信息

Food Chem. 2022 Sep 1;387:132840. doi: 10.1016/j.foodchem.2022.132840. Epub 2022 Mar 29.

DOI:10.1016/j.foodchem.2022.132840
PMID:35405556
Abstract

This study hoped to use microwave and ultrasound combined with 4D printing technology to promote the conversion of ergosterol into vitamin D in printing model with mushroom scraps. Under the UV irradiation, the conversion was different in the printed model with different irradiation areas and different physical field pretreatment. Compared with raw materials, vitamin D2 concentrations in the printed models was 4.6 time higher. Vitamin D in the product after physical field pretreatment was 2.2-3.8 times higher than that without pretreatment. From partial least square regression (PLS) analysis, irradiation area had the greatest impact while ultrasound treatment had the least. Pretreatment enhanced vitamin D content, possibly because pretreatment meant ergosterol was more susceptible to UV radiation, and expansion of the irradiated area increased the beneficial effect. This study established an artificial neural network model to predict ergosterol and vitamin D content.

摘要

本研究希望利用微波和超声结合4D打印技术,促进蘑菇残渣打印模型中麦角甾醇向维生素D的转化。在紫外线照射下,不同照射面积和不同物理场预处理的打印模型中的转化率有所不同。与原材料相比,打印模型中维生素D2的浓度高出4.6倍。经过物理场预处理的产品中维生素D的含量比未预处理的高出2.2至3.8倍。从偏最小二乘回归(PLS)分析来看,照射面积的影响最大,而超声处理的影响最小。预处理提高了维生素D的含量,可能是因为预处理意味着麦角甾醇更容易受到紫外线辐射,且照射面积的扩大增加了有益效果。本研究建立了一个人工神经网络模型来预测麦角甾醇和维生素D的含量。

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