Agrivoltaics (AV) represents a synergistic land-use strategy that combines solar energygeneration with high-value fruit production. As climate change intensifies heatwaves,droughts, and sunburn-related crop damage, AV offers a promising solution for improving the resilience and sustainability of perennial orchards. This review synthesizes datafrom experimental field trials, modeling studies, and analog shading systems, focusingon apples, pears, cherries, berries, kiwifruit, and olives. Studies were selected based onmethodological clarity and relevance to temperate and Mediterranean climates. Parameters such as panel geometry (height, tilt, ground coverage ratio), light transmittance,and microclimatic effects were compared across species. Findings indicate that properlydesigned AV systems can reduce fruit surface temperatures by up to 3.3 °C and decreasesunburn incidence by over 90%, especially in apples and pears. Berry crops displayedspecies-specific light tolerance, with strawberries and blueberries performing well undermoderate shading. In kiwifruit and olives, partial coverage (<30%) maintained yield while improving water efficiency. Integrating lightweight AV modules into existing orchardstructures proved technically feasible for cherries. Despite promising agronomic andenergy outcomes, large-scale adoption of AV remains constrained by policy, legal, andfinancial barriers. Strategic support is needed to align AV deployment with climate andenergy goals. In conclusion, AV offers a multifunctional approach to land use that enhances farm resilience, enables dual revenue streams, and supports EU decarbonizationstrategies particularly in permanent fruit cropping systems.

The Robot4Plants consortium (intervention IRP38, Common Agricultural Policy (CAP) Strategic Plan of Slovenia) introduced agricultural robots and unmanned aerial systems (UASs) on partner farms and at public events in 2026. This Project Report documents that commissioning and demonstration phase at six purposively selected locations. Evidence comprises operator and advisor records, farm management records, an application record, robot telemetry, and photographs. An AgXeed AgBot autonomous tractor with a six-row seed drill sowed a 2.68 ha maize field at a mean moving speed of 4.30 km h⁻¹ and a mean engine-reported fuel rate of 8.27 L h⁻¹; the field yielded approximately 11.8 t ha⁻¹ in a hot, dry season. A UAS applied Bacillus thuringiensis against European corn borer under a research permit at 59.5 L ha⁻¹. An autonomous air-assisted sprayer followed recorded routes in vineyard and apple rows, with water-sensitive paper used as a qualitative setup check. Limitations were unwanted stops near vegetation, two spray-hose failures, and two mower collisions in a hazelnut orchard. No replicated, efficacy, or economic assessment was made. The records form a descriptive baseline for replicated experiments starting in the 2026/2027 season.

Photon-based technologies, grounded in the controlled application of light energy, are becoming a key component of modern digital and precision agriculture. This article examines three complementary approaches: laser-based targeted weed control, UV-C light for managing fungal diseases, and laser-induced breakdown spectroscopy (LIBS) for soil analysis. Each of these technologies offers high spatial and spectral selectivity, automation potential, and the ability to reduce reliance on chemical agents and conventional laboratory diagnostics. We present the scientific foundations of each approach, current applications, agronomic effects, and technical challenges, and analyze their potential integration into broader agro-digital systems. Special emphasis is placed on the role of photonics in the transition toward environmentally responsible, low-input, and data-driven food production. This contribution provides a foundation for further research and practical implementation of these technologies across diverse crop production models.