Summary
Food fraud and mislabeling undermine public trust in the food industry and regulatory bodies. The scale of these issues is heightened by the so-called Protein Gap.
PeptInsure offers a new solution to authentication of protein in the food and feed industries by leveraging the strengths of ZooMS for peptide mass fingerprinting (PMF) and the novel LAP-MALDI technology, enhancing the specificity, affordability, and efficacy of protein analysis.
This unique combination, alongside advanced software tools, enables PeptInsure to transcend the limitations of existing methods, such as specificity issues, costliness, and the impact of processing on detectability, positioning it as a pioneering solution capable of redefining protein analysis standards. These factors combine to position PeptInsure as a pioneering approach that could redefine standards for protein analysis in food and feed, with implications for safety, quality, and consumer trust. While existing methods each contribute valuable tools for protein analysis in food and feed, they are often hampered by limitations related to specificity, cost, and the impact of processing on detectability. PeptInsure's innovative integration of technologies aims to overcome these challenges, offering a comprehensive, reliable, and cost-effective solution for protein authentication and quality assurance in the food industry. If successful, PeptInsure stands to offer groundbreaking innovations in the field of protein analysis, with far-reaching implications for food safety, quality assurance, and market integrity.
However, the project's high-risk elements, including the integration of complex technologies, adaptation to diverse matrices, and the need for advanced data analysis approaches, pose significant challenges. Overcoming these challenges will require innovative solutions, interdisciplinary collaboration, and a commitment to research and development, underscoring the high-risk/high-gain nature of the PeptInsure project.
PeptInsure offers a new solution to authentication of protein in the food and feed industries by leveraging the strengths of ZooMS for peptide mass fingerprinting (PMF) and the novel LAP-MALDI technology, enhancing the specificity, affordability, and efficacy of protein analysis.
This unique combination, alongside advanced software tools, enables PeptInsure to transcend the limitations of existing methods, such as specificity issues, costliness, and the impact of processing on detectability, positioning it as a pioneering solution capable of redefining protein analysis standards. These factors combine to position PeptInsure as a pioneering approach that could redefine standards for protein analysis in food and feed, with implications for safety, quality, and consumer trust. While existing methods each contribute valuable tools for protein analysis in food and feed, they are often hampered by limitations related to specificity, cost, and the impact of processing on detectability. PeptInsure's innovative integration of technologies aims to overcome these challenges, offering a comprehensive, reliable, and cost-effective solution for protein authentication and quality assurance in the food industry. If successful, PeptInsure stands to offer groundbreaking innovations in the field of protein analysis, with far-reaching implications for food safety, quality assurance, and market integrity.
However, the project's high-risk elements, including the integration of complex technologies, adaptation to diverse matrices, and the need for advanced data analysis approaches, pose significant challenges. Overcoming these challenges will require innovative solutions, interdisciplinary collaboration, and a commitment to research and development, underscoring the high-risk/high-gain nature of the PeptInsure project.
Unfold all
/
Fold all
More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101189467 |
| Start date: | 01-01-2025 |
| End date: | 30-06-2026 |
| Total budget - Public funding: | - 150 000,00 Euro |
Cordis data
Original description
Food fraud and mislabeling undermine public trust in the food industry and regulatory bodies. The scale of these issues is heightened by the so-called Protein Gap.PeptInsure offers a new solution to authentication of protein in the food and feed industries by leveraging the strengths of ZooMS for peptide mass fingerprinting (PMF) and the novel LAP-MALDI technology, enhancing the specificity, affordability, and efficacy of protein analysis.
This unique combination, alongside advanced software tools, enables PeptInsure to transcend the limitations of existing methods, such as specificity issues, costliness, and the impact of processing on detectability, positioning it as a pioneering solution capable of redefining protein analysis standards. These factors combine to position PeptInsure as a pioneering approach that could redefine standards for protein analysis in food and feed, with implications for safety, quality, and consumer trust. While existing methods each contribute valuable tools for protein analysis in food and feed, they are often hampered by limitations related to specificity, cost, and the impact of processing on detectability. PeptInsure's innovative integration of technologies aims to overcome these challenges, offering a comprehensive, reliable, and cost-effective solution for protein authentication and quality assurance in the food industry. If successful, PeptInsure stands to offer groundbreaking innovations in the field of protein analysis, with far-reaching implications for food safety, quality assurance, and market integrity.
However, the project's high-risk elements, including the integration of complex technologies, adaptation to diverse matrices, and the need for advanced data analysis approaches, pose significant challenges. Overcoming these challenges will require innovative solutions, interdisciplinary collaboration, and a commitment to research and development, underscoring the high-risk/high-gain nature of the PeptInsure project.
Status
SIGNEDCall topic
ERC-2024-POCUpdate Date
21-11-2024
Images
No images available.
Geographical location(s)
Search
