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在线奶酪监测研究:近红外和核磁共振光谱对半硬质奶酪的探索。

Towards on-line cheese monitoring: Exploration of semi-hard cheeses using NIR and H NMR spectroscopy.

机构信息

Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark.

Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark; FOSS Analytical A/S, Nils Foss Allé 1, 3400 Hillerød, Denmark.

出版信息

Food Chem. 2024 Oct 1;454:139786. doi: 10.1016/j.foodchem.2024.139786. Epub 2024 May 21.

Abstract

This study aims to investigate the potential of using advanced spectroscopies for cheese quality monitoring. For this purpose, six semi-hard cheeses manufactured using lactic acid bacteria (LAB) and/or propionic acid bacteria (PAB) were explored using near-infrared spectroscopy (NIRS) and Proton Nuclear Magnetic Resonance (H NMR) spectroscopy. The spectral data were analyzed using principal component analysis for extraction of possible discriminative patterns in quality parameters. The results show that the green analytical, but primarily bulk-sensitive, NIRS method was able to discriminate the cheese varieties primarily due to differences in the first overtone CH stretching region between 1650 and 1720 nm, in particular by the lactate methylene absorption at 1674 nm. A total of 25 metabolites were identified in the H NMR spectra of the cheese extracts, several of which were associated with the LAB and PAB metabolic pathways. PAB-associated metabolites include propionate, acetate, and glutamate, while LAB-associated metabolites include lactate and acetoin among others.

摘要

本研究旨在探讨利用先进的光谱技术进行奶酪质量监测的潜力。为此,使用近红外光谱(NIRS)和质子核磁共振(H NMR)光谱法对六种使用乳酸菌(LAB)和/或丙酸菌(PAB)生产的半硬奶酪进行了研究。使用主成分分析对光谱数据进行了分析,以提取质量参数中可能存在的有区别的模式。结果表明,绿色分析但主要是整体敏感的 NIRS 方法能够区分奶酪品种,主要是由于 1650 至 1720nm 之间的第一泛音 CH 伸缩区域的差异,特别是由于 1674nm 处的乳酸甲酯吸收。在奶酪提取物的 H NMR 光谱中鉴定出了 25 种代谢物,其中一些与 LAB 和 PAB 代谢途径有关。与 PAB 相关的代谢物包括丙酸、乙酸和谷氨酸,而与 LAB 相关的代谢物包括乳酸和乙酰基等。

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