Periodic Reporting for period 1 - h-ALO (photonic system for Adaptable muLtiple-analyte monitoring of fOod-quality)
Reporting period: 2021-01-01 to 2022-06-30
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 prototype will be validated in lab by quantitative comparison with benchmark commercially available methods and demonstrated onsite in small selected agri-food chains such as aquaponics, craft beer, raw milk and organic honey, and introduced into an HACCP manual.
h-ALO will improve sustainability of local production and retail, equipping producers and retailers with the unique real-time quantitativequality information about microbiological and chemical contaminants simultaneously. The photonics-based device will 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
• to address new markets and strengthen local markets and farmers’ market
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 prototype will be validated in lab by quantitative comparison with benchmark commercially available methods and demonstrated onsite in small selected agri-food chains such as aquaponics, craft beer, raw milk and organic honey, and introduced into an HACCP manual.
h-ALO will improve sustainability of local production and retail, equipping producers and retailers with the unique real-time quantitativequality information about microbiological and chemical contaminants simultaneously. The photonics-based device will 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
• to address new markets and strengthen local markets and farmers’ market
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 ICT core of the h-ALO sensor was reported by CNR and PLASM in WP2 (Integrated system for optoplasmonic sensing) by measuring the signal inputs/outputs of the single-components of the OPM. 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 and coordinated 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.
Of fundamental value the activity developed by the System Engineer of the project (FhG-ENAS) in order to define a possible roadmap towards the design of a qualified concept of the functional prototype by collecting the most relevant performance outputs of the as-realized/designed single components of the sensor (i.e. optoplasmonic chip, microsieve membrane and microfluidics system) which is based on the assessment of all the relevant processes affecting the sample preparation, analyte concentration/extraction and effective biorecognition.
In particular, 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,…). The major output of this activity is the proposal of an assembly route for the OPM that is the basis of the h-ALO by considering the synchronization of fabrication processes of various subsystems and modules at different Partners’ sites.
The definition of the data management strategy within the h-ALO project was reported during the reporting period. It was assessed that data will be generated by single partners, internal/external end-users and the h-ALO sensor itself, will be both analytic and unstructured and will be shared internally and externally to the consortium.
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 (WP4), the use of sensor for generating data, management of the data generated by the sensor (WP6) were discussed, optimized and shared with the End-users Committee (EUC) in specific web meetings organized by the reference Partners.
In particular, the demonstration of the working of ICT core of the h-ALO sensor was reported by CNR and PLASM in WP2 (Integrated system for optoplasmonic sensing) by measuring the signal inputs/outputs of the single-components of the OPM. 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 and coordinated 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.
Of fundamental value the activity developed by the System Engineer of the project (FhG-ENAS) in order to define a possible roadmap towards the design of a qualified concept of the functional prototype by collecting the most relevant performance outputs of the as-realized/designed single components of the sensor (i.e. optoplasmonic chip, microsieve membrane and microfluidics system) which is based on the assessment of all the relevant processes affecting the sample preparation, analyte concentration/extraction and effective biorecognition.
In particular, 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,…). The major output of this activity is the proposal of an assembly route for the OPM that is the basis of the h-ALO by considering the synchronization of fabrication processes of various subsystems and modules at different Partners’ sites.
The definition of the data management strategy within the h-ALO project was reported during the reporting period. It was assessed that data will be generated by single partners, internal/external end-users and the h-ALO sensor itself, will be both analytic and unstructured and will be shared internally and externally to the consortium.
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 (WP4), the use of sensor for generating data, management of the data generated by the sensor (WP6) were discussed, optimized and shared with the End-users Committee (EUC) in specific web meetings organized by the reference Partners.
By fully exploiting the potentialities of the innovative multimodal optical detection scheme, the h-ALO photonic 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 (LC-MS) and high-performance LC (HPLC, for chemical contaminants) 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: the sensor is adaptable to different and even cross-correlated analytical needs. 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 which are related to the manufacturing, supply and distribution of food products that are from small producers.
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: the sensor is adaptable to different and even cross-correlated analytical needs. 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 which are related to the manufacturing, supply and distribution of food products that are from small producers.