In the present study, biochar from brewers’ spent grain was used, for the first time, to develop screen-printed electrodes. After having investigated the dispersion behaviour of biochar in different organic solvents, a biochar-based screen-printed electrode was prepared with the drop-casting technique. In order to understand the electrochemical potentiality and performances of the biochar/sensor tool, different electroactive species, i.e., ferricyanide, benzoquinone, epinephrine, ascorbic, and uric acids, were used. The results were compared with those of the same electrodes that were modified with commercial graphene, confirming that the proposed electrode showed improved electrochemical behaviour in terms of resolution, peak-to-peak separation, current intensity, and resistance to charge transfer. Furthermore, a tyrosinase biosensor was developed by direct immobilisation of this enzyme on the biochar/screen printed electrode, as an example of the potential of biochar for disposable biosensor development. The efficiently occurred immobilisation of the biochar on the screen printed electrode’s (SPE’s) surface was demonstrated by the observation of the working electrode with a scanning electron microscope. The detection was performed by measuring the current due to the reduction of the corresponding quinone at low potential, equal to −0.310 V for epinephrine. The experimental conditions for the tyrosinase immobilization and the analytical parameters, such as applied potential and pH of buffer, were studied and optimized. Under these conditions, the electrochemical biosensors were characterized. A linear working range of epinephrine was obtained from 0.05 up to 0.5 mM. The detection limit was 2 × 10⁻⁴ mM for the biosensor.

Biochar is generally considered as an effective soil amendment, which can improve soil organic matter and nutrients content and enhance crop productivity. In this study, biochar derived from brewers’ spent grain (BSG) was used in a pot and field experiment to assess whether its addition to soil could affect hop plant growth. The experiment was conducted in Central Italy during the period March–August 2017. Three different German cultivars of hop plant (Hallertau Magnum, Perle, Spalter spalt) were considered. Biochar was added to the pot soil at 20% level. Its effect on the roots was evaluated using multivariate image analysis (MIA) and the statistical technique of general linear models (GLM), whereas the shoots, bines length and yield using GLM. Results showed that biochar significantly improved root growth (p < 0.0001). Regarding shoots, no variability for the genotypes was observed during the vegetative period, whereas slight differences resulted before plant dormancy, especially for the Hallertau Magnum cultivar. No differences in the number of leaves or bines length were observed between the two treatments for all cultivars. The addition of biochar to the soil significantly improved yield (number of cones). These results highlighted that BSG-derived biochar can be useful to improve hop plant growth and cones production.

The degree of olive maturation is a very important factor to consider at harvest time, as it influences the organoleptic quality of the final product, for both oil and table use. The Jaén index, evaluated by measuring the average coloring of olive fruits (peel and pulp), is currently considered to be one of the most indicative methods to determine the olive ripening stage, but it is a slow assay and its results are not objective. The aim of this work is to identify the ripeness degree of olive lots through a real-time, repeatable, and objective machine vision method, which uses RGB image analysis based on a k-nearest neighbors classification algorithm. To overcome different lighting scenarios, pictures were subjected to an automatic colorimetric calibration method—an advanced 3D algorithm using known values. To check the performance of the automatic machine vision method, a comparison was made with two visual operator image evaluations. For 10 images, the number of black, green, and purple olives was also visually evaluated by these two operators. The accuracy of the method was 60%. The system could be easily implemented in a specific mobile app developed for the automatic assessment of olive ripeness directly in the field, for advanced georeferenced data analysis.

The malaxation step, one of the most important phases of the virgin olive oil (VOO) mechanical extraction process involved in the development of the main quality characteristics of the final product, was carried out at a low temperature (18 °C). The rapid control of malaxer temperature was handled with the same chiller as that of the heat exchanger used in a semi-industrial extraction plant. Low temperature was used during the full olive paste kneading process and also for half of this process, which showed that there was a significant impact on the phenolic and volatile contents of VOO. Trials were conducted on three different cultivars (Canino, Moraiolo and Peranzana), and their phenolic and volatile concentrations showed different quantitative and qualitative effects due to the prolonged use of low temperature after the crushing phase, as a function of the different genetic origins of the olives. The process of phenolic compound solubilization into the oily phase was negatively influenced by the use of low temperature during the entire malaxation period for all the cultivars, whereas the volatile fraction showed an improvement in VOO flavor mainly due to the oil extracted from Canino olives.

Precision irrigation represents those strategies aiming to feed the plant needs following the soil’s spatial and temporal characteristics. Such a differential irrigation requires a different approach and equipment with regard to conventional irrigation to reduce the environmental impact and the resources use while maximizing the production and thus profitability. This study described the development of an open source soil moisture LoRa (long-range) device and analysis of the data collected and updated directly in the field (i.e., weather station and ground sensor). The work produced adaptive supervised predictive models to optimize the management of agricultural precision irrigation practices and for an effective calibration of other agronomic interventions. These approaches are defined as adaptive because they self-learn with the acquisition of new data, updating the on-the-go model over time. The location chosen for the experimental setup is a cultivated area in the municipality of Tenna (Trentino, Alto Adige region, Italy), and the experiment was conducted on two different apple varieties during summer 2019. The adaptative partial least squares time-lag time-series modeling, in operative field conditions, was a posteriori applied in the consortium for 78 days during the dry season, producing total savings of 255 mm of irrigated water and 44,000 kW of electricity, equal to 10.82%.

The development of innovative technologies in the mechanical extraction process of extra virgin olive oil can improve its quality standards through the modulation of physical, chemical and biochemical processes. Extra virgin olive oil quality and varietal differentiation are influenced by many factors, particularly the extraction. The use of ultrasound technology in the extraction process does not affect the quality, the composition, and the thermal properties of the oil, facilitating its separation from solids, and it allows the release of active compounds from the olive paste, with a positive influence on the phenolic content. In this study, the impact of ultrasound technologies was evaluated on merceological parameters, quality profile, and organoleptic features of extra virgin olive oils extracted from whole and destoned olives of the three main Italian cultivars (i.e., Peranzana, Canino, and Coratina). The parameters analyzed were influenced by both genotype and treatment, in particular, sonication did not lead to significant changes in the nutraceutical profile of the oils. The de-stoned olives were able to determine a great improvement of oil quality both for phenolic and volatile composition with a significant enhancement of health and sensory properties of the product.