In the present study, the effects of reduced and conventional tillage on the grain yield of winter wheat were investigated during the extremely dry 2021/2022 growing season in Karcag, Hungary. The research was conducted within the framework of the local long-term soil tillage experiment, where the reduced tillage plots have been managed since 1997 using non-inversion, loosening-based primary tillage and mulch farming. The soil of the experimental site is a clayey loam textured, deep-saline meadow chernozem. The experiment was carried out in four replications on meso-plots (1890 m²). For the evaluation of the results, key local meteorological data were considered, including precipitation totals, temperature data, and potential evapotranspiration (PET), from which the climatic water balance (CWB) was calculated. Descriptive statistical parameters were determined, and following a (positive) homogeneity test, a one-way analysis of variance (ANOVA) was performed. Based on the results, reduced tillage achieved an experimental average of 4.45 (±0.10) t ha⁻¹, significantly outperforming (p<0.05) the conventional, moldboard ploughing-based tillage yield of 3.62 (±0.29) t ha⁻¹. The processing and evaluation of meteorological data revealed that the 2021/2022 growing season in Karcag was extremely dry for winter wheat production, particularly during the critical spring vegetative and especially the reproductive stages. This drought intensified the differences in soil water management between reduced and ploughing-based conventional tillage systems. Based on these findings, the previously described soil moisture-conserving effect of reduced tillage was confirmed, and it was concluded that significant yield surpluses can be achieved with reduced tillage in winter wheat production during drought years.

Oats are one of the world’s major feed and food crops, possessing outstanding nutritional value. The development of the plant’s root system plays a decisive role in nutrient uptake, thereby indirectly influencing crop yield as well. In the present study, we analyzed the effect of silicon, sulfur, and the combined application of these nutrients on the vegetative development of winter oats in a pot experiment under natural weather conditions—with the exception of water supply - in a non-controlled environment.
Sulfur (S) is an essential nutrient, as it is a component of the amino acids cysteine and methionine, making it vital for protein synthesis, and it plays an important role in enzymatic processes and plant defense mechanisms. Silicon (Si) is generally not considered an essential element; however, it has been shown to have numerous beneficial physiological effects in cereal crops, as it increases plant strength by incorporating into the cell wall and improves plants’ resistance to abiotic and biotic stresses. The combined use of these two elements can result in a synergistic effect. Due to the effects of climate change in Hungary, the use of technological elements to mitigate plant stress is becoming increasingly important; foliar fertilizers containing sulfur and silicon can serve as a good alternative, thereby enhancing yield stability even under less predictable climatic conditions. The studies were conducted using instrumental measurements and objective analytical methods
Based on our results, plants treated with silicon and sulfur showed the most favorable SPAD values, while no detectable difference was observed among treatments in terms of NDVI values. When examining plant height, the combined treatment yielded the highest average values, similarly to the tillering rate; however, these differences were not statistically significant compared to the control. For root length, the highest average values were also measured with the combined treatment, which was statistically significantly different from the results of the other treatments. Regarding root mass, the sulfur treatment yielded the highest values; however, in this case, the difference was not significant. Based on the results of our experiment, it can be concluded that the use of the combined treatment had a positive effect on SPAD, plant height, tillering rate, and root length, promoting plant growth and thereby indirectly influencing crop yield.

The observable signs of climate change manifest themselves in various ways across space and time; examining these phenomena is essential for gaining a deeper understanding of the often extreme events and atmospheric conditions occurring around us – in the Earth’s atmosphere.
The aim of this study is to present the spatial and temporal changes in temperature and precipitation conditions occurring during the dormant season (November–March) by analysing daily temperature and precipitation data from 10 meteorological stations in Hungary using statistical methods. This study covers the past 60+ years (1961–2023), evaluating changes – specifically in the frequency of selected indicators – that occurred between the reference period (1961–1990) and the recent climate cycle (1991–2023).
Based on the results, a significant (p<0.05) decrease in the occurrence of low-temperature days can be observed for the entire dormant period (November–March) – for both minimum and maximum temperature indicators – while there was a significant (p<0.05) increase in the number of days with high – and sometimes extremely high – temperatures. In addition to these findings, there was a noticeable increase in the number of days – characterised by increasingly large temperature fluctuations exceeding the freezing point (Tmin<0 °C and Tmax≥5 °C; Tmin<0 °C and Tmax≥10 °C; Tmin<0 °C and Tmax≥15 °C). These changes are essentially applicable to the entire country, as well as to all 10 meteorological stations examined. Based on the performed analyses, it can be concluded that the excess heat observed during the dormant period is not accompanied by a clear increase in precipitation. When examining precipitation indicators, significantly greater uncertainty and variability were observed both spatially and temporally; thus, a clear, unidirectional trend in precipitation data has not been characteristic of the past 63 years (1961–2023).

Adapting to climate change is crucial in maize production. Changes in climatic factors are particularly noticeable in Hungary, which is why special attention must be paid to nutrient and water supply when growing maize hybrids.
In our analysis of agrotechnical studies for the year 2025, we focused primarily on the weather characteristics and meteorological conditions during the growing season and their effects, as well as soil and air temperature as the main factors determining crop yield.
We conducted our measurements and observations at the University of Debrecen’s Látókép Experimental Station. Here, we performed important analyses by comparing precise measurement data collected over several years. This time, the subjects of our study were maize hybrids H320 and H420. Based on the results of our long-term experiments, we can conclude that both maize hybrids possess good phenotypic traits, have a stable structure, and exhibit good root and stem characteristics. H320 produced a yield of 15.99 t/ha with relatively rapid water loss dynamics; its grain moisture content at harvest was 16.9%. The H420 corn hybrid achieved a higher yield of 18.12 t/ha with water loss dynamics that can be described as moderate. Grain moisture content at harvest was 17.67%.
Monitoring the plant’s nitrogen supply provides important information. One of the most commonly used methods is the NDVI index. We consistently measured higher NDVI values for the H420 hybrid.
Grain drying proceeded at a moderate rate following physiological maturity; the harvest date was slightly later than in previous years, but weather conditions did not hinder harvesting operations.
For the H320 hybrid, 140 days and 1,399 HU were required from emergence to physiological maturity, while for the H420 hybrid, 145 days and 1,446 HU were required from emergence to physiological maturity.

Increasing drought caused by climate change poses a significant challenge to potato production. In our experiment conducted in Sonkád (Hungary), different leaf treatments and irrigation regimens were tested over two growing seasons in a randomized block design using the Manitou variety. During the experiment, three irrigation rates (full, 50%, and dry control) were used, along with four foliar treatments – salicylic acid, hydrogen peroxide, silicon, and micronutrients – which were applied exclusively to the non-irrigated plots. A total of seven different treatments were carried out in four replicates. Based on the results from the two growing seasons, the silicon, hydrogen peroxide, microcomplex, and salicylic acid foliar treatments significantly increased the relative chlorophyll content (SPAD) compared to the control and the irrigated treatments. On average over the two years, the NDVI value was significantly increased by the silicon, hydrogen peroxide, microcomplex, and salicylic acid foliar treatments compared to the control, and no statistical difference was observed in performance between the full-dose irrigation treatment and the listed treatments. NDVI measurements taken at various time points confirmed that treatments with the tested substances were able to slow chlorophyll degradation and maintain the integrity of the photosynthetic apparatus even during the critical post-flowering period. In the case of the leaf area index, the highest value was observed in the treatment irrigated with the full dose, but no significant difference was found compared to the performance of the silicon, hydrogen peroxide, microcomplex, and salicylic acid treatments. At the same time, the most important indicator in terms of yield was irrigation, which had a significant impact in both years. Although the foliar treatments mitigated stress and improved plant vitality, they did not result in a statistically significant increase in yield compared to the untreated control.

The genetic purity and homogeneity of seed are essential prerequisites for achieving the expected agronomic performance of hybrids and ensuring high yield potential. The aim of the present study was to evaluate five maize hybrids (K1–K5) with respect to the homogeneity of their seed lots originating from different certified seed batches. The assessment of homogeneity (varietal purity) was carried out based on the evaluation of morphological and phenological traits, following the requirements of the official control protocol (small-plot post-control variety testing). The experiment was conducted in 2025 at the Variety Post Control Station of NÉBIH, where off-type plants (differing in phenological and/or morphological traits) were identified during the growing season using official variety descriptions. Based on the obtained results, the homogeneity of the examined hybrids was consistently high, well above the official threshold value. No statistically significant differences were detected among the hybrids (p = 0.259); however, graphical analyses revealed minor variability among individual seed lots. All examined samples met the varietal purity requirements specified in the current standards.
The results indicate that even under high average homogeneity, subtle differences among seed lots can be detected, which may serve as important indicators of hybrid genetic stability and seed production quality.

This study presents a literature review that traces the evolution of decision support for crop production, from process-based yield modeling through precision data sources to the application of artificial intelligence and hybrid models. Its aim is to provide a comparative analysis of how DSSAT, WOFOST, and AquaCrop-type models, as well as sensor, remote sensing, and yield mapping data, and AI-based methods, enhance the reliability of crop production decisions under various decision-making scenarios and conditions. The main finding of the review is that the practical value of decision support does not stem from the application of a single model or technology, but rather from the integration of scientifically sound models, quality-controlled site-specific data, and interpretable, adaptive algorithms. The study concludes that the key to domestic applicability lies in local calibration, strengthening long-term experimental and operational databases, and developing user competencies.