Periodic Reporting for period 2 - h-ALO (photonic system for Adaptable muLtiple-analyte monitoring of fOod-quality)
Reporting period: 2022-07-01 to 2024-06-30
h-ALO project aims to develop and demonstrate in real-setting a new photonic-based sensor which will allow local food producers and retailers to control food quality and safety, therefore increasing competitiveness in the whole food production value chain.
The sensor will provide:
• Unprecedented high sensitivity, low limit-of-detection and large dynamic range compared to previously developed portable systems through the
combination of an analyte pre-concentration and a multi-modal detection scheme;
• Miniaturization and integration of optoelectronic and plasmonic components allowing portability in optical detection;
• Multiplex-analyte recognition, allowing the unprecedented detection of both microbiological and chemical contaminants such as pesticides/antiparasitic, heavy metals, micro-organisms;
• Easy and fast sample preparation protocols which are adaptable for a wide range of food samples;
• Measurement automation and fast response, making the sensor reliable for on-site use by farmers, retailers and non-expert operators;
• Mobile-phone connectivity and cloud-based data management allowing a distributed, anonymous food monitoring along the farm-to-fork chain.
The h-ALO system demonstrated the potential utility as an in-field and real-time screening test for providing a preliminary indication based on a predefined threshold of the analyte concentration. While the number of tests conducted in the ultimate part of project is limited, the chosen approach aligns with the fundamental principles of a screening test, if we consider that the primary objective of a screening test is to rapidly and efficiently identify samples requiring further, more detailed analysis.
It is acknowledged that to validate the h-ALO sensor as a method, additional work is required to optimize reproducibility, minimize false positives and negatives, and accurately calculate the statistical error. However, the h-ALO system is consistent with the general principles of screening tests, providing an effective initial assessment of the examined samples.
The system is expected to represent a competitive advantage for small/medium-sized companies in the food value chain since it will allow:
• to better comply with quality and safety standards
• to reduce use of resource and production costs
• to meet the consumers increasing demand for high quality and safe regional, organic and specialty products
• to meet the global challenge by increasing production sustainability and lowering overall environmental footprint of agriculture and food sector
The sensor will provide:
• Unprecedented high sensitivity, low limit-of-detection and large dynamic range compared to previously developed portable systems through the
combination of an analyte pre-concentration and a multi-modal detection scheme;
• Miniaturization and integration of optoelectronic and plasmonic components allowing portability in optical detection;
• Multiplex-analyte recognition, allowing the unprecedented detection of both microbiological and chemical contaminants such as pesticides/antiparasitic, heavy metals, micro-organisms;
• Easy and fast sample preparation protocols which are adaptable for a wide range of food samples;
• Measurement automation and fast response, making the sensor reliable for on-site use by farmers, retailers and non-expert operators;
• Mobile-phone connectivity and cloud-based data management allowing a distributed, anonymous food monitoring along the farm-to-fork chain.
The h-ALO system demonstrated the potential utility as an in-field and real-time screening test for providing a preliminary indication based on a predefined threshold of the analyte concentration. While the number of tests conducted in the ultimate part of project is limited, the chosen approach aligns with the fundamental principles of a screening test, if we consider that the primary objective of a screening test is to rapidly and efficiently identify samples requiring further, more detailed analysis.
It is acknowledged that to validate the h-ALO sensor as a method, additional work is required to optimize reproducibility, minimize false positives and negatives, and accurately calculate the statistical error. However, the h-ALO system is consistent with the general principles of screening tests, providing an effective initial assessment of the examined samples.
The system is expected to represent a competitive advantage for small/medium-sized companies in the food value chain since it will allow:
• to better comply with quality and safety standards
• to reduce use of resource and production costs
• to meet the consumers increasing demand for high quality and safe regional, organic and specialty products
• to meet the global challenge by increasing production sustainability and lowering overall environmental footprint of agriculture and food sector
The work carried out until M18 was related to the (i) engineering of the active/passive constituent components of the optoplasmonic chip -OPM (i.e OLEDs, OPD, optical filter and nanoplasmonic grating - NPG) and the realization of the single-component prototypes and (ii) design, development and testing of the multiplex assays at the basis of the biorecognition at the NPG surface and of the capture/release at the microsieve membrane.
In particular, the demonstration of the working of the sensing module was reported by CNR and PLASM in WP2 (Integrated system for optoplasmonic sensing) by measuring the signal inputs/outputs of the single-components. In the case of the photonic module comprised by OLED, OPD and optical filter the interaction of the single components into an integrated configuration of the module was demonstrated. Moreover, the effectiveness of the signal enhancement of PEF detection was estimated in lab conditions which allowed the identification of a resonated risk assessment of the dual detection-modality approach.
The continuous collaboration among WFSR, INN and PLASM aimed at defining and implementing a shared and exhaustive action plan for determining the most effective and reliable approaches in the multiplex biorecognition of analytes (i.e. aptamer- vs antibody-based assays in the case of heavy-metal detection) and in biofunctionalization of both the NPG and microsieve membrane surfaces. The most relevant output of the general overview is the identification of the need of an amplification step of microbial DNA in the detection of microbes localized at the microsieve membrane of the sensor.
A risk management activity was dedicated to the identification and solving of the possible issues related to (i) the integration of the single components into the different modules of the sensor, and (ii) the optimization of the different treatment affecting the processing of the target compounds (i.e. thermal treatment, surface biofunctionalization, DNA amplification,…).
From M18 to the end of the project (extended end at M42) we established the potentiality of h-ALO sensor technologies to ensure quality and safety across different food chains, by demonstrating the applicability of the multiple modules of the sensor in real settings. We tested real samples belonging to matrices as model systems, such as skimmed milk, aquaponic water, and craft beer. Each sample was chosen for its relevance to specific contaminants, namely Albendazole in milk, Cadmium and E. Coli in aquaponic water, and Lactobacillus in beer.
We highlight that the overall usability of the h-ALO instrument comprised by the reagent and sensor cartridges is guaranteed by all the sample matrices ought to be filtered by using a single microsieve membrane in the reagent cartridge where microbes are retained on the membrane while pesticides and heavy metals run through. Heavy metals and pesticides are transported directly into the sensing module in the sensor cartridge for SPR detection, while the microbes are processed for nucleic acids extraction, collection and amplification. After amplification, real-time detection of double stranded DNA is performed in the amplification chamber.
Multiple protocols of use and guidelines such as the ones correlated to preparation of the samples from different food matrices to be used in the sensor, the use of sensor for generating data, management of the data generated by the sensor were discussed, optimized and shared with the End-users Committee.
In particular, the demonstration of the working of the sensing module was reported by CNR and PLASM in WP2 (Integrated system for optoplasmonic sensing) by measuring the signal inputs/outputs of the single-components. In the case of the photonic module comprised by OLED, OPD and optical filter the interaction of the single components into an integrated configuration of the module was demonstrated. Moreover, the effectiveness of the signal enhancement of PEF detection was estimated in lab conditions which allowed the identification of a resonated risk assessment of the dual detection-modality approach.
The continuous collaboration among WFSR, INN and PLASM aimed at defining and implementing a shared and exhaustive action plan for determining the most effective and reliable approaches in the multiplex biorecognition of analytes (i.e. aptamer- vs antibody-based assays in the case of heavy-metal detection) and in biofunctionalization of both the NPG and microsieve membrane surfaces. The most relevant output of the general overview is the identification of the need of an amplification step of microbial DNA in the detection of microbes localized at the microsieve membrane of the sensor.
A risk management activity was dedicated to the identification and solving of the possible issues related to (i) the integration of the single components into the different modules of the sensor, and (ii) the optimization of the different treatment affecting the processing of the target compounds (i.e. thermal treatment, surface biofunctionalization, DNA amplification,…).
From M18 to the end of the project (extended end at M42) we established the potentiality of h-ALO sensor technologies to ensure quality and safety across different food chains, by demonstrating the applicability of the multiple modules of the sensor in real settings. We tested real samples belonging to matrices as model systems, such as skimmed milk, aquaponic water, and craft beer. Each sample was chosen for its relevance to specific contaminants, namely Albendazole in milk, Cadmium and E. Coli in aquaponic water, and Lactobacillus in beer.
We highlight that the overall usability of the h-ALO instrument comprised by the reagent and sensor cartridges is guaranteed by all the sample matrices ought to be filtered by using a single microsieve membrane in the reagent cartridge where microbes are retained on the membrane while pesticides and heavy metals run through. Heavy metals and pesticides are transported directly into the sensing module in the sensor cartridge for SPR detection, while the microbes are processed for nucleic acids extraction, collection and amplification. After amplification, real-time detection of double stranded DNA is performed in the amplification chamber.
Multiple protocols of use and guidelines such as the ones correlated to preparation of the samples from different food matrices to be used in the sensor, the use of sensor for generating data, management of the data generated by the sensor were discussed, optimized and shared with the End-users Committee.
By fully exploiting the potentialities of the innovative multimodal optical detection scheme, the h-ALO sensor will have unique advantages in terms of high sensitivity and multiplex capabilities when compared to other microfluidic-based biosensors or to commercial dipsticks. Analytical accuracy similar to the standard techniques such as liquid chromatography–mass spectroscopy (for chemicals) or conventional plating and real-time PCR (microbial contaminants) is expected. In addition, measurement automation and automatic advanced data analysis, read-out, storage and share, render the sensor both reliable and easy-to-use by non-experts.
The h-ALO sensor is unique through its simultaneous detection of microbiological and chemical contaminants in a broad number of different farm-to-fork agri-food chains. In fact, the design of the surface bio-functionalization in the h-ALO sensor can be tailored on-demand according to in-field needs of the end-users. In the h-ALO project we outline a detailed model for demonstrating the use of the sensor in real-setting applications focusing on short value chains. In the final phase of the project when demonstrating the performance of the multiple modules of the sensor, a direct comparison with the output of benchmark instrumentation (i.e. INPx for SPR measurement and qPCR and MuSCAN for bacteria and DNA detection) was performed.
The h-ALO sensor is unique through its simultaneous detection of microbiological and chemical contaminants in a broad number of different farm-to-fork agri-food chains. In fact, the design of the surface bio-functionalization in the h-ALO sensor can be tailored on-demand according to in-field needs of the end-users. In the h-ALO project we outline a detailed model for demonstrating the use of the sensor in real-setting applications focusing on short value chains. In the final phase of the project when demonstrating the performance of the multiple modules of the sensor, a direct comparison with the output of benchmark instrumentation (i.e. INPx for SPR measurement and qPCR and MuSCAN for bacteria and DNA detection) was performed.