| Author: | Man, Ka Yi |
| Title: | Food authentication using mass spectrometry-based integrated foodomics : exploring beef and leafy vegetables |
| Advisors: | Mok, Kam-wah Daniel (FSN) |
| Degree: | Ph.D. |
| Year: | 2025 |
| Department: | Department of Food Science and Nutrition |
| Pages: | xxxii, 431 pages : color illustrations |
| Language: | English |
| Abstract: | Ensuring the authenticity of food products through effective food authentication is paramount in the continuous battle against adulteration. The increasing consumer demand for authenticating the geographic origin and cultivation method of a food product has emerged as a significant concern, especially for high-value food such as beef and organic vegetables. Consequently, guaranteeing the authenticity of food products has become essential for preserving consumer confidence and ensuring safety. However, the existing analytical techniques for authentication in these areas are currently inadequate in reflecting food quality. Addressing this gap requires developing and validating robust scientific analytical methods specifically tailored to authenticate the geographic origin of beef and the organic origin of vegetables. Foodomics is an outstanding technique for providing a comprehensive profile of the constituents and nutrients in food at the molecular. It stands out by effectively capturing the influence of environmental factors, offering valuable insights into the intricate composition of food. It enables us to understand how environmental conditions shape the molecular profile of food, providing crucial information for assessing food quality and authenticity. In this dissertation, the mass spectrometry (MS)-based integrated foodomics approach was used to authenticate beef's geographic origin and leafy vegetable's organic origin. In this study, two databases were established to facilitate the application of foodomics in authentication. Firstly, to deal with the difficulties in lipid annotation, an in-house lipidomics database was established to maximize the confidence of the lipid identification and has achieved a level 2 compliance with the Metabolomics Standards Initiative (MSI). Secondly, based on the comprehensive literature review, a metabolite database on vegebolomics, which focuses on the application of metabolomics in vegetable analysis, was established to support future researchers. In the authentication of the geographic origin of beef, an integrated MS-based untargeted metabolomics and lipidomics platform with the extensively validated analytical platform and statistical models for beef samples was established. The integrated foodomics platform proved to be highly effective in authenticating the geographical origin, feeding practices, and regimen of beef. Several promising biomarkers, such as amino acids, sugars, phosphatidylcholines and phosphatidylethanolamines, were identified for differentiating beef samples from three distinct countries. In the authentication of the organic origin of leafy vegetables, HILIC-MS based untargeted metabolomics approach was applied for water spinach and discovered isorhammetin and jasmonic acid as the common organic origin authenticating markers in two cultivars of water spinach. Then, the study has been extended and the results suggested that the lipid profile exhibited a higher sensitivity to organic farming practices in comparison to the metabolite profile. Finally, seven leafy vegetables commonly consumed in Asia, including Chinese kale, choy sum, green stem water spinach, Indian lettuce, lettuce, red amaranth, and white stem water spinach, were analysed using untargeted lipidomics. With the help of validation set samples, the study findings indicate that the lipid composition of leafy vegetables is significantly influenced by both the plant species and the year of production. From a thorough examination of lipid profiles of three leafy vegetables over an extended period, five lipids (LysoPG (16:0), PG (16:0/18:3), Cer (t18:0/24:0), SQDG (18:2/18:3), and SQDG (18:3/18:1)) serve as potential biomarkers strongly associated with organic farming. This study has significantly contributed to food authentication by establishing foodomics platforms and databases. It has made significant breakthroughs in identifying biomarkers for authenticating the geographic origin of beef and the organic origin of leafy vegetables using MS-based integrated untargeted foodomics. These achievements underscore the potential of this approach and offer valuable insights for future research and applications in food authentication. |
| Rights: | All rights reserved |
| Access: | open access |
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