The setting up of innovative irrigation water management might contribute to the mitigation of negative issues related to climate change. Our hypothesis was that globe artichoke irrigated with a traditionally drip system could be converted to an innovative water management system based on precision irrigation techniques and on evaporative cooling application in order to improve crop physiological status with positive impacts on earliness, total heads yield and water saving. Over two experiments carried out at plot- and field-scale, two irrigation management systems, differing in type and application time, were compared: (i) conventional, and (ii) canopy-cooling. Plant physiological status at a weekly sampling interval and the head atrophy incidence (as the ratio of the total primary heads collected) were monitored. We also recorded and determined heads production, and yield components. In both experiments, throughout the application period of evaporative cooling (three months), canopy-cooling showed the lowest value of leaf temperature and the highest photosynthesis values compared with the conventional one (+3 °C and -30%, respectively). The physiological advantage gained by the crop with evaporative cooling has led to a higher production both in terms of total yield (+30%), and in terms of harvested first order heads that from an economic viewpoint are the most profitable for farmers. At farm-scale, the canopy-cooling treatment resulted in a higher earliness (35 days) and water productivity (+36%) compared with conventional one. Our findings show that by combining evaporative cooling practice with precision irrigation technique the heads yield can be optimized also leading to a relevant water saving (-34%). Moreover, the study proved that canopy-cooling set up might be a winning strategy in order to mitigate climatic changes and heat stress conditions.

The adoption of agricultural robots is revolutionizing the agricultural sector, offering innovative solutions to optimize production and reduce environmental impact. This review examines the main functions and applications of agricultural robots, with a focus on the crops handled and the technologies employed. The study analyzes the current state of the art regarding the market trend of agricultural robots used in field and greenhouse operations. Several solutions are emerging, some already implemented and others still in the prototype or project stage. These solutions are beginning to spread, though they may still seem far from widespread field application, particularly given the peculiarities and heterogeneity of the global agricultural landscape. In the face of the many benefits associated with the use of agricultural robots, even today some technical bottlenecks and costs limit their widespread use by farmers. The review provides a fairly comprehensive and up-to-date overview of current trends in agricultural automation, suggesting new areas of research to improve the efficiency and adaptability of robotic systems to different types of crops and environments.

Over the last decades, traditional olive production has been converted to intensive and super-intensive cultivation systems, characterized by high plant density and irrigation. Although this conversion improves product quality and quantity, it requires a larger amount of energy input. The new contributions in this paper are, first, an analysis of the energy and environmental performance of two commercial-scale high peak-power hybrid photovoltaic irrigation systems (HPVIS) installed at intensive and super-intensive Mediterranean olive orchards; second, an analysis of PV hybrid solutions, comparing PV hybridization with the electric power grid and with diesel generators; and finally, a comparison of the environmental benefits of HPVIS with conventional power sources. Energy and environmental performances were assessed through energy and carbon payback times (EPBT and CPBT). The results show EPBT of 1.98 and 4.58 years and CPBT of 1.86 and 9.16 years for HPVIS in Morocco and Portugal, respectively. Moreover, the HPVIS were able to achieve low emission rates, corresponding to 48 and 103 g CO2e per kWh generated. The EPBT and CPBT obtained in this study were directly linked with the irrigation schedules of the olive orchards; therefore, weather conditions and irrigation management may modify the energy and environmental performances of HPVIS. The consumption of grid electricity and diesel fuel, before and after the implementation of HPVIS, was also analyzed. The results obtained show fossil energy savings of 67% for the Moroccan farm and 41% for the Portuguese installation. These savings suggest that the energy produced by HPVIS in olive orchards will avoid the emissions of a large amount of greenhouse gas and the exploitation of natural resources associated with fossil fuel production.

The growing interest in Augmented Reality (AR) systems is becoming increasingly evident in all production sectors. However, to the authors’ knowledge, a literature gap has been found with regard to the application of smart glasses for AR in the agriculture and livestock sector. In fact, this technology allows farmers to manage animal husbandry in line with precision agriculture principles. The aim of this study was to evaluate the performances of an AR head-wearable device as a valuable and integrative tool in precision livestock farming. In this study, the GlassUp F4 Smart Glasses (F4SG) for AR were explored. Laboratory and farm tests were performed to evaluate the implementation of this new technology in livestock farms. The results highlighted several advantages of F4SG applications in farm activities. The clear and fast readability of the information related to a single issue, combined with the large number of readings that SG performed, allowed F4SG adoption even in large farms. In addition, the 7 h of battery life and the good quality of audio-video features highlighted their valuable attitude in remote assistance, supporting farmers on the field. Nevertheless, other studies are required to provide more findings for future development of software applications specifically designed for agricultural purposes.

The multivariate statistical approach is one of the most common techniques applied in livestock classification, where quantitative and qualitative variables are used throughout the statistical analysis to obtain farms descriptions. The aim of this study was to divide dairy farms on the bases of farm size, mechanization level, energy profile and availability of building and facilities. A population of 285 conventional dairy cow farms located in the south of Italy was involved in this project. Using the principal component analysis and the k-means cluster analysis allowed to obtain 3 different groups. Results showed a repartition where 156 farms were located in cluster 2 “semi-intensive, low structural and mechanized farms”, 110 farms in cluster 1 “semi-intensive, high structural and mechanized farms”, and 19 farms were positioned in cluster 3 characterized by “intensive, high structural and mechanized farms. Larger farms are equipped with a wide number of appliances, holding higher level of power installed, but when reported to the number of raised heads or to the cultivated land area as indices, larger farms resulted more efficient and utilized less power per unit

In recent years, smartglasses for augmented reality are becoming increasingly popular in professional contexts. However, no commercial solutions are available for the agricultural field, despite the potential of this technology to help farmers. Many head-wearable devices in development possess a variety of features that may affect the smartglasses wearing experience. Over the last decades, dairy farms have adopted new technologies to improve their productivity and profit. However, there remains a gap in the literature as regards the application of augmented reality in livestock farms. Head-wearable devices may offer invaluable benefits to farmers, allowing real-time information monitoring of each animal during on-farm activities. The aim of this study was to expand the knowledge base on how augmented reality devices (smartglasses) interact with farming environments, focusing primarily on human perception and usability. Research has been conducted examining the GlassUp F4 smartglasses during animal selection process. Sixteen participants performed the identification and grouping trials in the milking parlor, reading different types of contents on the augmented reality device optical display. Two questionnaires were used to evaluate the perceived workload and usability of the device. Results showed that the information type could influence the perceived workload and the animal identification process. Smart glasses for augmented reality were a useful tool in the animal genetic improvement program offering promising opportunities for adoption in livestock operations in terms of assessing data consultation and information about animals.