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.
