Gergő Hegedüs

The intensive use of chemical fertilisers has reduced nutrient uptake efficiency in plants, mainly due to salinisation. This effect has prompted the investigation of alternative forms of plant nutrient management. One of the promising solutions to this is the use of microbial inoculants, specifically arbuscular mycorrhizal fungi and the plant growth-promoting rhizobacteria (PGPR). This systematic review, conducted in accordance with PRISMA 2020 guidelines, analysed 36 peer-reviewed studies published between 2008 and 2025 across 18 countries to assess the effects of inoculation with arbuscular mycorrhizal fungi (AMF), both alone and in combination with plant growth-promoting rhizobacteria (PGPR), on maize growth, physiology, and biochemical responses. The main finding was that soil P availability was the primary factor determining whether inoculation was successful. This was especially noted in soils with soil-available P of less than 17 mg P kg⁻¹ of soil. Soil texture and pH also played key roles in both single AMF inoculation and dual AMF-PGPR inoculation. Several studies showed that dual inoculation improved maize stress tolerance by coordinating antioxidant activity, osmotic balance, and hormonal signalling, rather than through simple additive growth effects. Overall, the findings suggest that AMF-based inoculation is most effective when applied strategically in reduced-input, phosphorus-limited, or drought-prone maize systems, rather than as a universal solution. These results support targeting inoculation toward resource-constrained systems where returns are most likely, especially P-deficient soils.

Onions (Allium cepa L.) are widely cultivated and consumed vegetable crops around the world. Weed interference is the main limitation to onion production. Onions grow slowly, are short-statured, and are non-branching, which makes them difficult to compete with weeds. The aim of this study was to summarise the literature published between 2020 and 2025 that evaluated the effectiveness of different weed control methods used in onion cultivation using a systematic review following the PRISMA guidelines. Based on the results, pendimethalin and oxyfluorfen were the most used and most effective herbicides. Combining pre- and post-emergence treatments and spraying herbicide mixtures improved weed control efficiency compared with single treatments. Acetolactate synthase (ALS) inhibitors can adversely affect onions and reduce yield, making them unsuitable for use in onion production. Integrated weed management practises, such as combining herbicides with manual weeding and using plant-based extracts, offer a sustainable approach that can reduce reliance on chemicals. Mechanical weed management is not widely adopted in onion production because its application poses numerous challenges. The future direction of weed management should focus on technological advances in mechanical weed control and the development of bioherbicides to reduce reliance on synthetic herbicides.

Agriculture must balance productivity with greenhouse gas emissions, biodiversity, and resource concerns. This study examined how tillage (conventional, CT; minimum, MT), nitrogen fertilisation (0–221 kg N ha⁻¹), and herbicide rates (0–100%) interactively affected soil CO₂ emissions, vegetation vigour, and weed diversity in maize production during 2022. A factorial experiment was conducted on a 1 ha with 40 plots monitored soil temperature, moisture, penetration resistance, normalised difference vegetation index (NDVI), weed diversity (Simpson’s Index), and CO₂ emissions (closed-chamber method). Minimum tillage increased soil water retention (9.3 ± 6.5% vs. 5.4 ± 4.3%), soil temperature (28.0 ± 1.5), and compaction (0.6 ± 0.3 vs. 0.1 ± 0.0 MPa), while enhancing weed diversity (0.53–0.80 vs. 0.38–0.67). MT produced higher CO₂ emissions than CT, especially at 147 kg N ha⁻¹ (49.9 ± 15.7 vs. 29.1 ± 11.6 μmol m⁻² s⁻¹), peaking under MT-147 kg N ha⁻¹-H75 (79.4 ± 1.2 μmol m⁻² s⁻¹). NDVI responses varied between tillage systems; under CT, vegetation vigour peaked at 75% herbicide application, while under MT vegetation was more responsive to nitrogen and more sensitive to herbicide, highlighting nitrogen × herbicide interaction trade-offs. Overall, MT enhanced water conservation and weed diversity but increased short-term CO₂ emissions. This study reports first-year, site-specific results from an ongoing multi-year field experiment; therefore, the findings were interpreted as short-term, season-specific responses. This highlights the need for site-specific, climate-smart management that integrates emissions, soil health, biodiversity, and productivity.

Low-cost air temperature sensors are an emerging theme in environmental monitoring. These sensors offer the advantage of making microclimate monitoring feasible due to their affordability. However, they are limited by the quality of the data they provide; in many cases, they have been reported to have presented errors in the sensor readings. These errors have been shown to improve after calibration was applied. The lack of a comprehensive understanding of the available calibration techniques, models, and sensor types has led to studies presenting heterogeneity in models and techniques alongside different performance metrics. To address this gap, this study conducted a systematic review following the PRISMA guidelines, reviewing studies from 2015 to 2024 across the databases Web of Science and Scopus, alongside the search engine Google Scholar. The aim was to identify the calibration techniques and models, the commercially available low-cost air temperature sensors used, the performance metrics utilised, and the calibration settings. The findings presented three main categories of calibration models utilised in the collected studies: linear, polynomial, and machine learning. Twenty-two commercially available low-cost sensors were identified, with the DHT22 sensor being the most utilised. Indoor settings were identified as the most preferred for conducting calibrations. Key challenges included limitations in reported results for calibration by the studies, the use of different performance metrics across studies, insufficient studies conducting calibration, and the diversity in sensor types utilised.