| Autor: |
R. Zhang, W. Jia |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Journal of Dairy Science, Vol 106, Iss 3, Pp 1712-1733 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
0022-0302 |
| DOI: |
10.3168/jds.2022-22654 |
| Popis: |
ABSTRACT: Brown goat milk products have gained popularity for their unique taste and flavor. The emergence of chain-reversal phenomenon makes the design and development of goat milk products gradually tend to a consumer-oriented model. However, the precise mechanism of how browning and fermentation process causes characteristics is not clear. In an effort to understand how the treatments potentially lead to certain metabolite profile changes in goat milk, comprehensive, quantitative metabolomics and peptidomics analysis of goat milk samples after browning and fermentation were undertaken. An intelligent hybrid z-score standardization-principal components algorithm-multimodal denoizing autoencoder was used for feature fusion and hidden layer fusion in high-dimensional variable space. The fermentation process significantly improved the flavor of brown goat yogurt through the tricarboxylic acid-urea-glycolysis composite pathway. Bitter peptides HPFLEWAR, PPGLPDKY, and PPPPPKK have strong interactions with both putative dipeptidyl peptidase IV and angiotensin-converting enzyme, proving that brown goat yogurt can be considered as effective provider of potential putative dipeptidyl peptidase IV and angiotensin-converting enzyme inhibitors. The level of health-promoting bioactive components and sensory contributed to consumer selection. The proposed multimodal data integrative analysis platform was applicable to explain the effect of the dynamic changes of metabolites and peptides on consumer preferences. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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