Periodic Reporting for period 3 - WATCHPLANT (SMART BIOHYBRID PHYTO-ORGANISMS FOR ENVIRONMENTAL IN SITU MONITORING)
Période du rapport: 2024-01-01 au 2024-12-31
SO1. Define the working conditions for sap extraction and biomarkers monitoring in vegetal organisms addressing the healing phenomena.
The state of the art in terms of plant physiology (healing phenomena, phloem location in the trunk and sap composition) has been extensively reviewed. Additionally, several experiments have been carried out to select the most convenient specie for the experimental point of view. In this sense, fruit trees as an example of complex plant with lignified trunk have been evaluated towards transversal and longitudinal sections together with less complex plants such as tomato, which has been selected as model species due to its high growth rate and wide lumens in their sieve tubes in terms of diameter. This would facilitate access to the sap and the collection of key molecules.
The strategy used to extract the sap is based on a paper-based strategy to benefit from the hydrophilic properties of the paper and the associated evaporation to create a driving force. Additionally, the capillary pressure in the sap sampling device should be high, ideally matching or surpassing the capillary pressure in the plant. This strategy is compatible with an electrochemical lateral-flow strategy used for biosensing and also compatible with the biofuel cell technology for energy harvesting. T
SO3. Development of sensing strategies for in-situ sap testing by impedance spectroscopy and electrochemical (bio)sensors.
The electrochemical sap biosensor has been developed by using an amplifier signal strategy involving an HRP-labelled Ab. The assay varied differently when analysed with sap samples from healthy and stressed plants under water stress. In this sense, it was demonstrated the suitability of integrating the electrochemical assay with lateral flow strategies used as a platform to collect the sample and carry the additional reagents required in the final prototype. This has also been integrated with the needles for sap extraction for in situ measurements (sap device).
SO4. Development of “smart biohybrid organisms“ with AI components, capable for e.g. decision making and self-adaption
Several sensor and communication devices have been produced, each with different capabilities and uses (Orange Box, PhytoNodes, …). These devices communicate with various wireless communication technologies to provide redundancy, data throughput, long range, and low power consumption. Also, they can run efficient AI models that provide local decision-making ability and predictive behaviour. Algorithms have been developed to ensure resilience and enable self-reconfiguration abilities in case of disturbances or sensor faults.
SO5. Environmental dynamic model for urban monitoring
Long-term sensing data of different species of trees were used in a cross-sectional study to evaluate potential effects of pollutants in the sap parameters using a linear exposure-response function, and tested for departure from linearity compared with a non-linear exposure-response function. Results indicated a significant statistical relationship with the increase of O3 concentrations in olive trees with sap flow sensing.From May 2023 to June 2024, prototypes of impedance and biopotential sensors, transpiration, temperature and humidity were recorded using the selected species (tomatoes and ivies) in three air quality monitoring sites, including with high-traffic, an urban, and a suburban site (the latest with very high O3 concentrations), to record simultaneously the concentrations of air quality pollutants.
The state of the art in terms of plant physiology (healing phenomena, phloem location in the trunk and sap composition) has been extensively reviewed. Additionally, several experiments have been carried out to select the most convenient specie for the experimental point of view. In this sense, fruit trees as an example of complex plant with lignified trunk have been evaluated towards transversal and longitudinal sections together with less complex plants such as tomato, which has been selected as model species due to its high growth rate and wide lumens in their sieve tubes in terms of diameter. This would facilitate access to the sap and the collection of key molecules.
The strategy used to extract the sap is based on a paper-based strategy to benefit from the hydrophilic properties of the paper and the associated evaporation to create a driving force. Additionally, the capillary pressure in the sap sampling device should be high, ideally matching or surpassing the capillary pressure in the plant. This strategy is compatible with an electrochemical lateral-flow strategy used for biosensing and also compatible with the biofuel cell technology for energy harvesting. T
SO3. Development of sensing strategies for in-situ sap testing by impedance spectroscopy and electrochemical (bio)sensors.
The electrochemical sap biosensor has been developed by using an amplifier signal strategy involving an HRP-labelled Ab. The assay varied differently when analysed with sap samples from healthy and stressed plants under water stress. In this sense, it was demonstrated the suitability of integrating the electrochemical assay with lateral flow strategies used as a platform to collect the sample and carry the additional reagents required in the final prototype. This has also been integrated with the needles for sap extraction for in situ measurements (sap device).
SO4. Development of “smart biohybrid organisms“ with AI components, capable for e.g. decision making and self-adaption
Several sensor and communication devices have been produced, each with different capabilities and uses (Orange Box, PhytoNodes, …). These devices communicate with various wireless communication technologies to provide redundancy, data throughput, long range, and low power consumption. Also, they can run efficient AI models that provide local decision-making ability and predictive behaviour. Algorithms have been developed to ensure resilience and enable self-reconfiguration abilities in case of disturbances or sensor faults.
SO5. Environmental dynamic model for urban monitoring
Long-term sensing data of different species of trees were used in a cross-sectional study to evaluate potential effects of pollutants in the sap parameters using a linear exposure-response function, and tested for departure from linearity compared with a non-linear exposure-response function. Results indicated a significant statistical relationship with the increase of O3 concentrations in olive trees with sap flow sensing.From May 2023 to June 2024, prototypes of impedance and biopotential sensors, transpiration, temperature and humidity were recorded using the selected species (tomatoes and ivies) in three air quality monitoring sites, including with high-traffic, an urban, and a suburban site (the latest with very high O3 concentrations), to record simultaneously the concentrations of air quality pollutants.
WP2. The plant model and structures were defined. Capillary pumping devices were conceptualized. The resulting model was a capillary pumping device with a nanoporous membrane and an inserter tube/needle. Materials with suitable characteristics were investigated. The state of the art regarding energy harvesting and sensing was reviewed.
WP3. The mathematical model of the BFCs was defined. Miniaturized and flexible supports were developed. Energy harvesting using glucose BFCs based on bioelectrodes was achieved. Preliminary testing and validation were performed. Several strategies were tested for ABA electrochemical biosensors. Impedance dynamic-sensors were developed.
WP4. Fifteen phytosensing systems with electrochemical and physiological electrodes, as well as environmental sensors, were prepared and shipped. Additional phytosensors were allocated and shipped to CSIC to enable statistically significant measurements of plant parameters. Specific thermal impulse sensors for sap flow measurements were in production. Collaboration took place between CYB, UZL, FER, and CSIC regarding measurements in multiple locations and co-dependencies between air quality, soil, and physiological parameters of plant organisms. UKON-CYB cooperation was established for sap flow measurements using impedance spectroscopic methods. RTD activities were carried out on thermal-balance, heat-impulse methods, and electrochemical sensors for in vivo, in vitro, and in-situ measurements. Sap device for in situ biochemical sap analysis was developed and shipped to CSIC to perform the validation.
WP5. A sensor network with key functionality was implemented. Statistical analysis and machine learning approaches were developed. A distributed method to estimate and actively manage the topology of the sensor network was created. A series of experiments were performed on plant tissue impedance in response to environmental stimulation. A literature overview of various modern wireless communication technologies was conducted. An ultra-low power sensor node, "PhytoNode," was developed to measure the electrophysiological signals of plants, perform real-time machine learning classification, and disseminate results via Bluetooth Low Energy.
WP6. A state-of-the-art review in environmental modelling was completed. A list of sap compounds susceptible to monitoring was finalized. The response of plant sensors in the prototype was studied. A new approach to evaluating the impact of air pollutants on sap (bio)sensors, sap flow, and stomatal conductance was developed and validated.
WP3. The mathematical model of the BFCs was defined. Miniaturized and flexible supports were developed. Energy harvesting using glucose BFCs based on bioelectrodes was achieved. Preliminary testing and validation were performed. Several strategies were tested for ABA electrochemical biosensors. Impedance dynamic-sensors were developed.
WP4. Fifteen phytosensing systems with electrochemical and physiological electrodes, as well as environmental sensors, were prepared and shipped. Additional phytosensors were allocated and shipped to CSIC to enable statistically significant measurements of plant parameters. Specific thermal impulse sensors for sap flow measurements were in production. Collaboration took place between CYB, UZL, FER, and CSIC regarding measurements in multiple locations and co-dependencies between air quality, soil, and physiological parameters of plant organisms. UKON-CYB cooperation was established for sap flow measurements using impedance spectroscopic methods. RTD activities were carried out on thermal-balance, heat-impulse methods, and electrochemical sensors for in vivo, in vitro, and in-situ measurements. Sap device for in situ biochemical sap analysis was developed and shipped to CSIC to perform the validation.
WP5. A sensor network with key functionality was implemented. Statistical analysis and machine learning approaches were developed. A distributed method to estimate and actively manage the topology of the sensor network was created. A series of experiments were performed on plant tissue impedance in response to environmental stimulation. A literature overview of various modern wireless communication technologies was conducted. An ultra-low power sensor node, "PhytoNode," was developed to measure the electrophysiological signals of plants, perform real-time machine learning classification, and disseminate results via Bluetooth Low Energy.
WP6. A state-of-the-art review in environmental modelling was completed. A list of sap compounds susceptible to monitoring was finalized. The response of plant sensors in the prototype was studied. A new approach to evaluating the impact of air pollutants on sap (bio)sensors, sap flow, and stomatal conductance was developed and validated.
The impact of using a biohybrid system based on the plant for air quality monitoring (and eventually agro-food industry and ecosystem surveillance), has been proved to be even broader than expected in terms of smart agriculture management. It is especially key the impact that the new generated (bio)sensors could add in smart agriculture. In case of the sap device, it can be easily adapted to any biomarker in sap, including not only stress detection but also pest or pathogens infections. In this sense, exploitation strategies and market identification have been carried out to identify further uses of the technology beyond WatchPlant and envision exploitation actions when the device would be developed and tested in the project. More details can be seen in D7.8.