Biomimetics is the interdisciplinary cooperation of biology and technology that offers solutions to practical problems by analyzing biological systems and transferring their principles into applications. This review article focused on biomimetic innovations, including bio-inspired soft robots and swarm robots that could serve multiple functions, including the harvesting of fruits, pest control, and crop management. The research demonstrated commercially available biomimetic innovations, including robot bees by Arugga AI Farming and the Robotriks Traction Unit (RTU) precision farming equipment. Additionally, soft robotic systems have made it possible to mitigate the risk of surface bruises, rupture, the crushing destruction of plant tissue, and plastic deformation in the harvesting of fruits with a soft rind such as apples, cherries, pears, stone fruits, kiwifruit, mandarins, cucumbers, peaches, and pome. Even though the smart farming technologies, which were developed to mimic nature, could help prevent climate change and enhance the intensification of agriculture, there are concerns about long-term ecological impact, cost, and their inability to complement natural processes such as pollination. Despite the problems, the market for bio-inspired technologies with potential agricultural applications to modernize farming and solve the abovementioned challenges has increased exponentially. Future research and development should lead to low-cost FEA robotic grippers and FEA-tendon-driven grippers for crop harvesting. In brief, soft robots and swarm robotics have immense potential in agriculture.

The digital transformation of agriculture is a promising necessity for tackling the increasing nutritional needs on Earth and the degradation of natural resources. Toward this direction, the availability of innovative electronic components and of the accompanying software programs can be exploited to detect malfunctions in typical agricultural equipment, such as water pumps, thereby preventing potential failures and water and economic losses. In this context, this article highlights the steps for adding intelligence to sensors installed on pumps in order to intercept and deliver malfunction alerts, based on cheap in situ microcontrollers, sensors, and radios and easy-to-use software tools. This involves efficient data gathering, neural network model training, generation, optimization, and execution procedures, which are further facilitated by the deployment of an experimental platform for generating diverse disturbances of the water pump operation. The best-performing variant of the malfunction detection model can achieve an accuracy rate of about 93% based on the vibration data. The system being implemented follows the on-device intelligence approach that decentralizes processing and networking tasks, thereby aiming to simplify the installation process and reduce the overall costs. In addition to highlighting the necessary implementation variants and details, a characteristic set of evaluation results is also presented, as well as directions for future exploitation.

The interpretation of geologic processes on Mars from sparse meteorite, remote sensing and rover data is influenced by knowledge gained from well-characterized terrestrial analogues. This calls for detailed study of candidate terrestrial analogues and comparison of their observable features to those encountered on the surface of Mars. We evaluated the mineralogical, geochemical, and physical properties of the Balos cove basalts (BCB) from the island of Santorini and compared them to Martian meteorites, Mars rover surface measurements, and other verified Martian analogues obtained from the International Space Analogue Rockstore (ISAR). Twenty rock samples were collected from the Balos cove area based on their freshness, integrity, and basaltic appearance in the field. Optical microscopy of BCB revealed a pilotaxitic to trachytic texture, with olivine and clinopyroxene phenocrysts in a fine groundmass of olivine, clinopyroxene, plagioclase, magnetite, and devitrified glass. All major minerals show normal zoning, including calcic plagioclase (An 78-85 at the core and An 60-76 at the rim), augite (En 36-48 Wo 41-44 Fs 11-21), and olivine (Fo 74-88). The dominant bands in the infrared-attenuated total reflectance (IR-ATR) spectra from BCB can be assigned to olivine (~875 cm-1), calcic plagioclase (~1130 cm-1), and augite (~970 cm-1). The whole-rock chemical compositions and mineralogy of the BCB are similar to published analyses of typical olivine-phyric shergottites and basalts and basaltic materials analyzed in Gusev and Gale craters on Mars. BCB porosity is in the range of 7-15 % and is similar to the porosities of the ISAR samples. Although no terrestrial rock is ever a perfect match to Martian compositions, the differences in mineralogy and geochemistry between BCB and some classes of Martian samples are relatively subtle and the basalts of Santorini are as close a match as other accepted Mars basalt analogues. The Santorini site offers excellent field logistics that, together with the petrology of the outcrop, makes it a valuable locality for testing and calibration deployments, field training, and other activities related to current and future Mars exploration.

Inevitably, the rapid growth of the electronics industry and the wide availability of tailored programming tools and support are accelerating the digital transformation of the agricultural sector. The latter transformation seems to foster the hopes for tackling the depletion and degradation of natural resources and increasing productivity in order to cover the needs of Earth’s continuously growing population. Consequently, people getting involved with modern agriculture, from farmers to students, should become familiar with and be able to use and improve the innovative systems making the scene. At this point, the contribution of the STEM educational practices in demystifying new areas, especially in primary and secondary education, is remarkable and thus welcome, but things become quite uncertain when trying to discover efficient practices for higher education, and students of agricultural engineering are not an exception. Indeed, university students are not all newcomers to STEM and ask for real-world experiences that better prepare them for their professional careers. Trying to bridge the gap, this work highlights good practices during the various implementation stages of electric robotic ground vehicles that can serve realistic agricultural tasks. Several innovative parts, such as credit card-sized systems, AI-capable modules, smartphones, GPS, solar panels, and network transceivers are properly combined with electromechanical components and recycled materials to deliver technically and educationally meaningful results.

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