Periodic Reporting for period 3 - PHOTONFOOD (FLEXIBLE MID-INFRARED PHOTONIC SOLUTIONS FOR RAPID FARM-TO-FORK SENSING OF FOOD CONTAMINANTS)
Reporting period: 2023-07-01 to 2024-12-31
Analytical techniques for the measurements of chemical and microbial contaminations along the food chain require detection levels in the ppb range. A direct measurement of contaminants at these concentrations in a food matrix is not possible by any photonics principle. PHOTONFOOD aimed to overcome this barrier by developing an integrated solution that combines innovations in smart paper-based sample treatment, mid-infrared (MIR) sensing and advanced data analysis. Mid-infrared (MIR) spectroscopy has proven to be the most reliable and broadly applicable spectroscopic method for detection, characterization and quantification of chemical and microbial contamination. To transform MIR sensing from existing lab solutions into a portable solution to broad usage in the food chain, PHOTONFOOD aimed to develop novel infrared light sources, specifically interband cascade light emitting diode (IC-LED), and interband and quantum cascade lasers (ICL/QCL). The light sources are combined with sophisticated waveguide technology and 3D-paper microfluidics.
The PHOTONFOOD project is poised to make a significant societal impact by revolutionizing mycotoxin detection and food safety processes. By developing portable, cost-effective, and user-friendly infrared devices, the project enhances the ability to monitor food contaminants throughout the production line, ensuring safer food consumption and potentially reducing food waste through early detection.
The PHOTONFOOD project is poised to make a significant societal impact by revolutionizing mycotoxin detection and food safety processes. By developing portable, cost-effective, and user-friendly infrared devices, the project enhances the ability to monitor food contaminants throughout the production line, ensuring safer food consumption and potentially reducing food waste through early detection.
The PHOTONFOOD project began by identifying the needs of stakeholders through surveys and interviews conducted in five countries. These efforts revealed the challenges organizations face in mycotoxin testing and highlighted a strong demand for quick, standardized testing methods. The research defined target user groups for two devices, MI-FI and HI-FI, designed to meet EU standards for mycotoxin levels. Published findings in the World Mycotoxin Journal and showcased at various events helped refine these devices based on user feedback. Cost assessments showed these technologies are efficient and scalable, indicating potential to reduce reliance on expensive current methods. Market analysis using the UTAUT model informed strategic recommendations for commercialization.
WP2 focused on creating an easy-to-use sample processing workflow for food contaminant analysis using mid-infrared (MIR) spectroscopy. A novel method, Selective Paper-Enhanced Infrared Spectroscopy (S-PEIRS), was developed to detect mycotoxins like deoxynivalenol (DON) at regulatory limits. This method successfully passed validation and proficiency tests, with training provided through kits, pictogram cards, and videos. Integration with photonic devices for detecting DON on paper advanced, though high concentrations were initially required. S-PEIRS was also adapted for detecting Ochratoxin A (OTA) in white wine, showing promising results and improved simplicity with new tools. WP2's developments offer two main products: a 3D-printed grinding and extraction module, and the S-PEIRS methodology, both available as open-source resources.
WP3 advanced the development of epitaxial structures for mid-infrared (MIR) IC-LEDs and tunable lasers, enhancing efficiency, output power, and emission wavelength. These advanced IC-LEDs, featuring optimized out-coupling structures and improved thermal management, were integrated into MI-FI analyzers to support scalable production of low-cost MIR devices. Tunable lasers for HI-FI analyzers achieved improvements in spectral alignment and emission stability. Deliverables included advanced IC-LEDs and tunable lasers, successfully integrated into demonstrator setups. Key exploitable results from WP3 include optimized mid-infrared epitaxy designs, tunable lasers, IC-LEDs, and knowledge to optimize IC-LED emission behavior and directionality.
WP4 developed and optimized interfaces and analyzers for MIR sensing. Thin-film waveguides using GaAs/AlGaAs materials were validated for analyzing DON in samples with the HI-FI analyzer. The MI-FI analyzer, equipped with MEMS-based IR sources and ZnSe ATR waveguides, showed promising results compared to conventional FTIR spectrometers. IC-LEDs were integrated into the MI-FI system, and a pressure stamp for paper-based microfluidics was developed. The HI-FI analyzer demonstrated superior sensitivity and successfully integrated sample preparation protocols. Housing designs for both devices facilitated demonstrations and transportation. The exploitable results from WP4 include the MI-FI handheld device and the HI-FI high-precision lab device, each optimized for different contamination detection scenarios.
WP5 focused on developing a data analysis strategy and user-friendly software for MI-FI and HI-FI devices. Achievements include effective spectral pre-processing methods, calibration and classification models using PLS-based techniques, and the development of a centralized Global Control System (GCS) for data management. The GCS was integrated with cloud services and planned for future integration with IBM FoodTrust and FoodSafeR platforms. WP5's results include pre-processing methods and predictive models for contaminant detection, utility software for efficient data analysis, and tools for further development and validation of MI-FI and HI-FI devices in food safety applications.
WP6 focused on validating and demonstrating PHOTONFOOD developments. Tasks included building a sample base of wheat and peanut samples for analysis using photonic prototypes, followed by LC-MS/MS analysis. These samples were used for validation trials and chemometric modeling. An interlaboratory comparison study replaced the initially planned mini ring trial. Spectroscopic solutions were demonstrated to stakeholders at conferences and labs, with feedback collected to refine the technology. WP6's exploitable results include data from sample screening trials and device validation, aiding in future prototype refinements.
WP7 supported other work packages in disseminating scientific results. Achievements include establishing a project website with substantial visitor.
WP2 focused on creating an easy-to-use sample processing workflow for food contaminant analysis using mid-infrared (MIR) spectroscopy. A novel method, Selective Paper-Enhanced Infrared Spectroscopy (S-PEIRS), was developed to detect mycotoxins like deoxynivalenol (DON) at regulatory limits. This method successfully passed validation and proficiency tests, with training provided through kits, pictogram cards, and videos. Integration with photonic devices for detecting DON on paper advanced, though high concentrations were initially required. S-PEIRS was also adapted for detecting Ochratoxin A (OTA) in white wine, showing promising results and improved simplicity with new tools. WP2's developments offer two main products: a 3D-printed grinding and extraction module, and the S-PEIRS methodology, both available as open-source resources.
WP3 advanced the development of epitaxial structures for mid-infrared (MIR) IC-LEDs and tunable lasers, enhancing efficiency, output power, and emission wavelength. These advanced IC-LEDs, featuring optimized out-coupling structures and improved thermal management, were integrated into MI-FI analyzers to support scalable production of low-cost MIR devices. Tunable lasers for HI-FI analyzers achieved improvements in spectral alignment and emission stability. Deliverables included advanced IC-LEDs and tunable lasers, successfully integrated into demonstrator setups. Key exploitable results from WP3 include optimized mid-infrared epitaxy designs, tunable lasers, IC-LEDs, and knowledge to optimize IC-LED emission behavior and directionality.
WP4 developed and optimized interfaces and analyzers for MIR sensing. Thin-film waveguides using GaAs/AlGaAs materials were validated for analyzing DON in samples with the HI-FI analyzer. The MI-FI analyzer, equipped with MEMS-based IR sources and ZnSe ATR waveguides, showed promising results compared to conventional FTIR spectrometers. IC-LEDs were integrated into the MI-FI system, and a pressure stamp for paper-based microfluidics was developed. The HI-FI analyzer demonstrated superior sensitivity and successfully integrated sample preparation protocols. Housing designs for both devices facilitated demonstrations and transportation. The exploitable results from WP4 include the MI-FI handheld device and the HI-FI high-precision lab device, each optimized for different contamination detection scenarios.
WP5 focused on developing a data analysis strategy and user-friendly software for MI-FI and HI-FI devices. Achievements include effective spectral pre-processing methods, calibration and classification models using PLS-based techniques, and the development of a centralized Global Control System (GCS) for data management. The GCS was integrated with cloud services and planned for future integration with IBM FoodTrust and FoodSafeR platforms. WP5's results include pre-processing methods and predictive models for contaminant detection, utility software for efficient data analysis, and tools for further development and validation of MI-FI and HI-FI devices in food safety applications.
WP6 focused on validating and demonstrating PHOTONFOOD developments. Tasks included building a sample base of wheat and peanut samples for analysis using photonic prototypes, followed by LC-MS/MS analysis. These samples were used for validation trials and chemometric modeling. An interlaboratory comparison study replaced the initially planned mini ring trial. Spectroscopic solutions were demonstrated to stakeholders at conferences and labs, with feedback collected to refine the technology. WP6's exploitable results include data from sample screening trials and device validation, aiding in future prototype refinements.
WP7 supported other work packages in disseminating scientific results. Achievements include establishing a project website with substantial visitor.
PHOTONFOOD delivers for the first time smart, cheap and user-friendly paper microfluidic devices to extract, separate and preconcentrate chemical and microbial contaminants prior to spectroscopic analysis. The preconcentration and separation of contaminants for the first time allowed infrared spectroscopy detection of contaminants in the ppm level. For monitoring of the contaminants along the whole food production line, PHOTONFOOD developed handheld and portable infrared devices based on novel light sources in the infrared developed in the project. Novel data processing tools and software targeted to the new instrumentation has been provided. Early detection of contaminants will in future provide safer food and reduce food waste.