This paper presents a machine vision retrofit system designed for upgrading used tractors to allow the control of the tillage implements and enable real-time field operation. The retrofit package comprises an acquisition system placed in the cabin, a front-mounted RGB camera sensor, and a rear-mounted Peiseler encoder wheel. The method combines shape analysis and colorimetric k-nearest neighbor (k-NN) clustering for in-field weed discrimination. This low-cost retrofit package can use interchangeable sensors, supplying flexibility of use with different farming implements. Field tests were conducted within lettuce and broccoli crops to develop the image analysis system for the autonomous control of an intra-row hoeing implement. The performance showed by the system in the trials was judged in terms of accuracy and speed. The system was capable of discriminating weed plants from crop with few errors, achieving a fairly high performance, given the severe degree of weed infestation encountered. The actuation time for image processing, currently implemented in MATLAB integrated with the retrofit kit, was about 7 s. The correct detection rate was higher for lettuce (from 69% to 96%) than for broccoli (from 65% to 79%), also considering the negative effect of shadows. To be implementable, the experimental code needs to be optimized to reduce acquisition and processing times. A software utility was developed in Java to reach a processing time of two images per second.

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 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.

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.