Mauro Pagano

Subsoiling is a highly effective deep tillage method used to mitigate soil compaction in orchard rows, a condition frequently resulting from repeated passes of agricultural machinery. This compaction can reduce water infiltration into deeper soil layers, leading to excessive surface water stagnation and a subsequent reduction in soil fertility. Subsoiling restores the structure of compacted soil by creating a vertical cut and lifting the ground without inverting the soil layers. This action promotes stable soil porosity and enhanced drainage, effectively eliminating the plough sole, and consequently improving root growth and nutrient absorption. Despite its benefits, subsoiling is an energy-intensive practice. Vibrating subsoilers can significantly reduce the high traction force required by conventional subsoilers, thereby enabling the use of smaller, less powerful tractors. This study investigated the performance of a single-shank subsoiler equipped with an innovative oscillating working tool, focusing on its dynamic-energy requirements, tillage quality, and the whole-body vibrations (WBV) transmitted to the tractor driver. Comparative tests were conducted in a compacted poplar grove using two 4WD tractors of different power and mass, with the subsoiler’s oscillating tool alternately activated and deactivated. The results demonstrated that the oscillating tool reduced draft force, traction power requirement, fuel consumption, and tractor slip, while maintaining tillage efficiency, displacing a greater mass of soil. However, a comparison of the measured vibrations indicated that their level reached a hazardous condition for the driver of the lower-power, lower-mass tractor when the oscillating tool was active.

Effective water resource management in agriculture is a pivotal challenge for environmental sustainability and the economic viability of crop production. The present study, conducted at the CREA research station (Monterotondo, Italy), analyzed a precision irrigation strategy based on an automated drip irrigation system with soil moisture sensors, applied to a 15-year-old high-density poplar plantation for energy production. Five treatments were compared: a non-irrigated control (T0) and four irrigation levels based on soil moisture thresholds (T1 ≤ 20%, T2 ≤ 30%, T3 ≤ 40%, T4 ≤ 50%). The aim of this study was to assess the economic feasibility of irrigated poplar plantations, considering expected increases in biomass production and related environmental impacts. The economic evaluation used the Life Cycle Costing (LCC) method, while the environmental assessment applied Life Cycle Assessment (LCA) with the AWARE indicator to quantify the water scarcity footprint. Finally, an integrated assessment using the TOPSIS multi-criteria method was performed to identify the most sustainable treatment. Over the 15-year period, T0 (no irrigation) was the preferred option (Preferred Index Pi = 1.000), followed by T3 (Pi = 0.637) and T4 (Pi = 0.586), considering equal weighting of economic and environmental impacts. Conversely, the low irrigation treatment (T1) was the least sustainable (Pi = 0.379), followed by T2 (Pi = 0.486). While irrigation appears unviable if environmental impacts are prioritized, higher biomass value can improve the economic sustainability of treatments with greater water use (T3 and T4) when economic factors dominate.

This study evaluates the safety aspects of a prototype electric vehicle designed to enable wheelchair users to independently perform simple farm tasks in rural settings, like sample collection and crop monitoring. The vehicle, built at CREA, features four in-wheel electric motors, a pneumatic suspension system, and a secure wheelchair anchoring system. Tests at the CREA experimental farm assessed the vehicle’s whole-body vibrations on different surfaces (asphalt, headland, dirt road) using two tyre models and multiple speeds. A triaxial accelerometer on the wheelchair seat measured vibrations, which were analysed in accordance with ISO standards. Frequency analysis revealed significant vibrations in the 2–40 Hz range, with the Z-axis consistently showing the highest accelerations, which increased with the speed. Tyre A generally induced higher vibrations than Tyre B, likely due to the tread design. At high speeds, the effective accelerations exceeded safety thresholds on asphalt and headland. Statistical analysis confirmed speed as the dominant factor, with the surface type also playing a key role—headland generated the highest vibrations, followed by dirt road and asphalt. The results of these first tests highlighted the high potential of the vehicle to improve the agricultural mobility of disabled people, granting safety conditions and low vibration levels on all terrains at speeds up to 10 km h⁻¹. At higher speeds, however, the vibration levels may exceed the exposure limits, depending on the irregularities of the terrain and the tyre model. Overcoming these limitations is achievable through the optimization of the suspensions and tyres and will be the subject of the next step of this study. This technology could also support wheelchair users in construction, natural parks, and urban mobility.

The table olive sector is highly important to the Italian agri-food industry. To produce quality table olives without defects in appearance, flavors, or aroma and to meet consumer expectations, special precautions must be taken to limit side effects associated with transformation and storage processes. During these processes, essential to debitter and stabilize the final product, drupes may undergo undesirable fermentations due to changes in the olive-to-brine ratio, temperature changes, and alteration of the brine’s chemico–physical parameters, thus decreasing their commercial and nutritional value. An innovative user-friendly system, equipped with low-cost digital and sensorized devices, has been engineered and realized for step-by-step batch monitoring of table olive storage brines. The main fermentation parameters (i.e., temperature, pH, salinity, free acidity, volatile acidity, and residual sodium hydroxide) of virgin, compliant, and altered brines were analyzed with both the automated prototype and Official reference methods, with the aim of testing the functionality of the prototype device and verifying the reliability and repeatability of the measurements. Good linearity was observed for all parameters examined, with a relatively low mean deviation between the two approaches. It is therefore possible to constantly monitor brine conformity automatically during the processing stages, benefiting product quality and environmental, energy, and economic sustainability.

Although it is often assumed that physically disabled individuals have different behaviors towards environment, there has been very little empirical evidence supporting this statement. For this reason, this study aimed to explain the different behaviors and preferences of potential users by analyzing their attitudes towards an electric vehicle specifically designed for rural mobility. In other words, this study analyzed both the willingness of disabled people to drive an electric vehicle and their willingness to pay (WTP) for such a vehicle. A total of 209 data were collected from a sample of physically disabled consumers in Italy using a structured questionnaire. Therefore, a stated preferences Italian dataset was used, and an exploratory factor analysis, a probit model, and an ordered logit regression model were applied. The results suggested that to encourage the use of electric cars for rural mobility, it should be necessary to manage environmental concerns, vehicle-related attributes, attitudes towards eco-friendly cars, people’s emotional experience, and their purchase intention. In addition, to improve customer intention, development plans and service features must be synergistically organized to mutually support each other.

Water resources are increasingly limited and less available, so improving water use efficiency is particularly pressing in the agricultural sector, where inefficient irrigation systems are often in operation. Drip irrigation is one of the most water-saving systems that can optimize distribution according to the actual needs of the crop. In the present study, an engineered drip irrigation system was applied to a poplar crop dedicated to the production of biomass for energy use. The aim was to evaluate the influence of the supply of different volumes of irrigation water on crop growth. Four levels of water supply were tested (theses T1, T2, T3, and T4), each determined by different intervention thresholds established by using four soil moisture sensors, one for each thesis (PLOT) (20, 30, 40, and 50 percent, respectively). In the third growing season, the effect of the different amounts of irrigation water supplied on plant growth was particularly evident between control T1 (104 m³ ha⁻¹) compared with T2 (540 m³ ha⁻¹), T3 (1924 m³ ha⁻¹) and T4 (4549 m³ ha⁻¹). Regarding biomass production, no statistical differences were found between T2 (8.97 Mg DM ha⁻¹ year⁻¹), T3 (9.99 Mg DM ha⁻¹ year⁻¹) and T4 (10.02 Mg DM ha⁻¹ year⁻¹), but they were all different from T1 (7.09 Mg DM ha⁻¹ year⁻¹. This leads to the conclusion, at least up to the third growing season, that with equal satisfactory levels of biomass production, water and energy savings can be achieved by choosing intermediate levels of water supply (e.g., with the sensor at 30%) as compared to the maximum value tested.

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.

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.

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.

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%.