Modern agriculture is related to a revolution that occurred in a large group of technologies (e.g., informatics, sensors, navigation) within the last decades. In crop production systems, there are field operations that are quite labour-intensive either due to their complexity or because of the fact that they are connected to sensitive plants/edible product interaction, or because of the repetitiveness they require throughout a crop production cycle. These are the key factors for the development of agricultural robots. In this paper, a systematic review of the literature has been conducted on research and commercial agricultural robotics used in crop field operations. This study underlined that the most explored robotic systems were related to harvesting and weeding, while the less studied were the disease detection and seeding robots. The optimization and further development of agricultural robotics are vital, and should be evolved by producing faster processing algorithms, better communication between the robotic platforms and the implements, and advanced sensing systems.

Circular economy is emerging as a regenerative concept that minimizes emissions, relies on renewable energy, and eliminates waste based on the design of closed-loop systems and the reuse of materials and resources. The implementation of circular economy practices in resource-consuming agricultural systems is essential for reducing the environmental ramifications of the currently linear systems. As the renewable segment of circular economy, bioeconomy facilitates the production of renewable biological resources (i.e., biomass) that transform into nutrients, bio-based products, and bioenergy. The use of recycled agro-industrial wastewater in agricultural activities (e.g., irrigation) can further foster the circularity of the bio-based systems. In this context, this paper aims to provide a literature review in the field of circular economy for the agrifood sector to enhance resource efficiency by: (i) minimizing the use of natural resources (e.g., water, energy), (ii) decreasing the use of chemical fertilizers, (iii) utilizing bio-based materials (e.g., agricultural/livestock residues), and (iv) reusing wastewater from agrifood operations. The final objective is to investigate any direct or indirect interactions within the water-energy-nutrients nexus. The derived framework of synergetic circular economy interventions in agriculture can act as a basis for developing circular bio-based business models and creating value-added agrifood products.

Various types of sensors technologies, such as machine vision and global positioning system (GPS) have been implemented in navigation of agricultural vehicles. Automated navigation systems have proved the potential for the execution of optimised route plans for field area coverage. This paper presents an assessment of the reduction of the energy requirements derived from the implementation of optimised field area coverage planning. The assessment regards the analysis of the energy requirements and the comparison between the non-optimised and optimised plans for field area coverage in the whole sequence of operations required in two different cropping systems: Miscanthus and Switchgrass production. An algorithmic approach for the simulation of the executed field operations by following both non-optimised and optimised field-work patterns was developed. As a result, the corresponding time requirements were estimated as the basis of the subsequent energy cost analysis. Based on the results, the optimised routes reduce the fuel energy consumption up to 8%, the embodied energy consumption up to 7%, and the total energy consumption from 3% up to 8%.

A computational tool is developed for the estimation of the energy requirements of Miscanthus x giganteus on individual fields that includes a detailed analysis and account of the involved in-field and transport operations. The tool takes into account all the individual involved in-field and transport operations and provides a detailed analysis on the energy requirements of the components that contribute to the energy input. A basic scenario was implemented to demonstrate the capabilities of the tool. Specifically, the variability of the energy requirements as a function of field area and field-storage distance changes was shown. The field-storage distance highly affects the energy requirements resulting in a variation in the efficiency if energy (output/input ratio) from 15.8 up to 23.7 for the targeted cases. Not only the field-distance highly affects the energy requirements but also the biomass transportation system. Based on the presented example, different transportation systems adhering to the same configuration of the production system creates variation in the efficiency of energy (EoE) between 12.9 and 17.5. The presented tool provides individualized results that can be used for the processes of designing or evaluating a specific production system since the outcomes are not based on average norms.