Climate change has become one of the biggest challenges for farmers, advisors, researchers, and policymakers in recent years. Concerns about food security and the economic future have led these groups to search for methods to adapt to and mitigate climate change. In this context, cover crops have emerged as an important tool to improve soil health, prevent nitrate leaching, and increase crop productivity. The main objective of this review is to explore the multiple benefits of cover crops, including their role in improving soil health, sequestering CO₂, fixing N₂, and enhancing gas exchange, all of which contribute to the sustainability of agricultural systems under climate change conditions. One of the key findings of this research is that cover crop cultivation must be carefully tailored to the specific site, farm, intended purpose, and top priority, taking into account factors such as species selection, crop duration, and termination methods. Certain cover crop species have the potential to mitigate important climate change factors, such as soil erosion and nitrogen leaching, while increasing soil organic matter. However, many studies often focus on only one aspect of cover crops, overlooking the full range of ecosystem services they provide. In addition, future research must also address the economic challenges associated with cover crops.

Agroecological weed management is important for agriculture’s shift toward sustainability. This study evaluated stale seedbed and intercropping combinations for weed management in vetch (Vicia sativa L.) cultivation in Greece during the 2023–2024 and 2024–2025 growing seasons. A Randomized Complete Block Design was established using a split-plot arrangement. Two weed management practices served as the main plots: untreated control (CON) and stale seedbed (SSB). Four intercropping methods formed the subplots: vetch monocropping (VM), vetch–barley mixed intercropping (VBMXIC), vetch–barley row intercropping (VBROWIC), and vetch–barley relay intercropping (VBRELIC). The interaction between weed management and intercropping influenced weed NDVI (p < 0.001), weed biomass, and vetch NDVI (p < 0.01). Weed NDVI and biomass were highest for CON × VM, CON × VBMXIC, CON × VBROWIC, and CON × VBRELIC interactions. Vetch NDVI was highest (0.71) for SSB × VM. Grain yield was affected by growing season (p < 0.05), weed management (p < 0.001), and intercropping (p < 0.001). SSB resulted in a 42% higher yield compared to CON. VBRELIC and increased yields by 7%, 22%, and 29% compared to VBROWIC, VM, and VBMXIC, respectively. Further research is needed to evaluate additional agroecological weed management practices in more crops and environments.

Lolium rigidum is among the most prevalent and noxious weeds in cereal and perennial cropping systems worldwide and has developed resistance to several herbicide modes of action. This study employed a sensor-based smart farming method for the early screening of herbicide resistance across three L. rigidum accessions in Greece, followed by dose–response experiments with clodinafop-propargyl, glyphosate, and mesosulfuron-methyl + iodosulfuron-methyl. In the preliminary screening, herbicides were applied at their highest recommended rates, whereas the dose–response experiments included five application rates (0, 1/4X, X, 2X, and 4X). The EM2 accession exhibited confirmed resistance to mesosulfuron-methyl + iodosulfuron-methyl, with a resistance index of 5.31 and a five-fold increase in the herbicide rate required compared to the susceptible EM1 accession. For clodinafop-propargyl, the GR50 value of the resistant EM3 accession (147.97 g a.i. ha⁻¹) was approximately 2.5-fold higher than that of the susceptible EM2 accession (60.28 g a.i. ha⁻¹). Glyphosate application provided only partial biomass reduction in resistant accessions, indicating reduced susceptibility. In parallel, TaqMan assays were developed and validated to detect target-site mutations linked to resistance against EPSPS-, ACCase-, and ALS-inhibiting herbicides, supporting the molecular interpretation of the observed resistance patterns. Overall, the results demonstrate that sensor-based smart farming approaches can provide a rapid and reliable tool for the early screening of herbicide resistance, enabling more informed crop protection strategies and supporting sustainable weed management. Further research across diverse soil types and climatic conditions is warranted to validate and extend the applicability of these approaches.