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Crop yield forecasting is critical in modern agriculture to ensure food security, economic stability, and effective resource management. The main goal of this study was to combine historical multisource satellite and environmental datasets with a deep learning (DL) model for soybean yield forecasting in the United States’ Corn Belt. The following Moderate Resolution Imaging Spectroradiometer (MODIS) products were aggregated at the county level. The crop data layer (CDL) in Google Earth Engine (GEE) was used to mask the data so that only soybean pixels were selected. Several machine learning (ML) models were trained by using 5 years of data from 2012 to 2016: random forest (RF), least absolute shrinkable and selection operator (LASSO) regression, extreme gradient boosting (XGBoost), and decision tree regression (DTR) as well as DL-based one-dimensional convolutional neural network (1D-CNN). The best model was determined by comparing their performances at forecasting the soybean yield in 2017–2021 at the county scale. The RF model outperformed all other ML models with the lowest RMSE of 0.342 t/ha, followed by XGBoost (0.373 t/ha), DTR (0.437 t/ha), and LASSO (0.452 t/ha) regression. However, the 1D-CNN model showed the highest forecasting accuracy for the 2018 growing season with RMSE of 0.280 t/ha. The developed 1D-CNN model has great potential for crop yield forecasting because it effectively captures temporal dependencies and extracts meaningful input features from sequential data.

The literature on the effectiveness of Agri-Environmental Schemes focuses mainly on the environmental effects; only a few studies have focused on economic aspects. The number of papers that address ecological and economic outcomes simultaneously is even more limited. In this paper, we apply the concept of eco-efficiency to integrate these two factors. The aim of the paper is to analyze the impact of participation in the agri-environmental scheme of Hungarian field crop farmers in terms of eco-efficiency. To make unbiased and consistent comparisons we use advances from aggregation and bootstrap theory in Data Envelopment Analysis (DEA) context. The results indicate that there exists a significant potential for enhancing eco-efficiency in Hungarian crop farms. Furthermore, our results reveal that, in terms of eco-efficiency, perceived as the relationship of farm income to pesticide, fertilizers and energy use, no significant differences exist between participating and non-participating farmers. The results are robust to different methods. Our results pose questions about the efficacy of the Agri-Environmental Scheme.

Ungulate populations have surged to unsustainable levels in multiple areas in recent decades due to human intervention, making forestry and conservation practices arduous. The population of ungulates is also currently displaying a rising trend in Hungary, prompting decision-makers to commence substantial reduction efforts. Our study examined the ungulate impact in three forested regions of Hungary, employing field survey sampling plots on almost 50,000 hectares. Our findings revealed that regeneration browsing and soil disturbance were evenly high in these areas, while the cover of the regeneration layer was extremely low. Ungulate pressure was suspected as the cause of the lack of regeneration. Based on habitat and vegetation conditions, we divided our sample as favourable and unfavourable for regeneration. The cover of the regeneration categories was not significantly different between the two sets. The evidence of the direct indicators, including browsing and soil disturbance, coupled with the lack of regeneration, leads us to infer indirect signs of ungulate pressure. The absence of older and taller vegetation in the area also suggests long-standing ungulate pressure. Our investigation suggests that the high ungulate population can cause low abundance, even the lack of regeneration, not only locally but also at a regional scale.

The land use sector is a crucial pillar in achieving the EU climate goals set for 2050. A significant part of the climate change mitigation potential of the land use sector is inherent to agroforestry. Windbreaks are important agroforestry elements of Hungarian agricultural landscapes. The new and improved agroforestry subsidy system may positively affect the extension of windbreaks in Hungary, making it relevant to assess their carbon sequestration potential. In our study, we examined the carbon sequestration of windbreaks at the country level and in two sample areas of 24,000 hectares based on National Forestry Database volume stock data, as well as information collected from the Hungarian Forest Cover Map using orthophoto interpretation. We estimated the total annual carbon sequestration realized in the aboveground biomass pool of Hungarian windbreaks to be −33.1 ktCO2/year, which is 0.67% of the total annual carbon sequestration of the aboveground biomass pool of all Hungarian forests, as reported by the Hungarian Greenhouse Gas Inventory. On the other hand, according to our estimate, the weighted mean annual carbon sequestration in the aboveground biomass of windbreaks was −2.4 tCO2/ha/year in the 2010–2020 period. This value is very close to the average mean annual carbon sequestration per hectare value of all forests, as reported by the Hungarian Greenhouse Gas Inventory. This means that planting a given area of windbreaks in between agricultural fields can have similar climate change mitigation effects as planting forests in the same given area.

The topicality of our research topic is justified by the significant change in traditional grassland management in the grassland areas of the Pannonian Basin. Due to several factors, the proportion of fallow grassland, and in parallel of over-exploited pastures, is continuously increasing. In the medium term (11 years), the effects of fallowing (Z), annual mowing (M), mowing and grazing (meadow treatment M + G), and permanent overgrazing (OG) as treatments on the population structure of grassland plants were investigated in a semi-natural grassland community in the Solonyec soil. It was found that the lowest degradation rates in the studied grassland biotope were obtained for the treatment presenting the utilisation pattern of mowing the main grassland phytomass followed by sheep grazing of the coltgrass. The highest degradation levels, which threatened the condition of the grassland community, were measured for the treatment presenting overgrazing with sheep at the end of the experimental period.

Regenerative farming systems are gaining increasing attention in crop production worldwide. The challenge of the future is to find and apply farming methods that not only reduce the carbon footprint of cultivation, but also produce sustainably through an optimal choice of inputs. We set up our crop rotation experiment in 2019 in order to evaluate the role of common vetch (Vicia sativa L.) as a green manure crop in a crop rotation system. The results were compared with nitrogen fertilizer (80 kg ha−1 N) and control (no green manure and no fertilizer) treatments. Based on the three years of results, it can be concluded that the biomass production capacity of common vetch sown in August is determined by the amount of precipitation in October under continental climatic conditions. In an optimum year for corn, common vetch as a forecrop was found to be equivalent to the effect of fertilizer application at all three applied seed rates, but under stress conditions in a drought year, significantly higher corn yields were obtained when common vetch green manure was applied. Our results suggest a justified role for the use of common vetch green manure in crop rotation systems.

Soil moisture reserves are a key factor in maintaining soil fertility and all other related ecosystem services (including carbon sequestration, soil biodiversity, and soil erosion control). In semiarid blown-sand areas under aridification, water preservation is a particularly crucial task for agriculture. The international Diverfarming project (2017–2022), within the EU Horizon 2020 Program, focused on the impacts of crop diversification and low-input practices in all pedoclimatic regions of Europe. In this three-year experiment conducted in the Pannonian region, the impact of intercropping asparagus with different herbs on some provisioning and regulating ecosystem services was evaluated in the Kiskunság sand regions. Relying on findings based on a range of measured physical and chemical soil parameters and on crop yields and qualitative properties, advice was formulated for farmers. The message drawn from the experiment is somewhat ambiguous. The local farmers agree that crop diversification improves soil quality, but deny that it would directly influence farm competitiveness, which primarily depends on cultivation costs (such as fertilization, plant protection, and labour). Further analyses are needed to prove the long-term benefits of diversification through enriching soil microbial life and through the possible reduction of fertilizer use, while water demand is kept at a low level and the same crop-quality is ensured.

Based on historical facts and past achievements, the work is designed to update the importance and prove the possibility of successful breeding work at the regional level in order to increase the production of high-quality, socially significant food products to ensure food security. At the beginning of the formation of agricultural science in the Magadan region, scientists were faced with the task of selecting the optimal breeds for the region. More than 4000 cows were examined during 1964–1967. It was found that in extreme natural and climatic conditions of the Magadan region the Kholmogory breed proved to be the best one. In 1967, in order to further improve the Kholmogory breed, the first attempt was made to study the genealogical structure of the herd, to identify and evaluate highly productive lines. In 1974, in order to increase the milk fat content of crossbred cows of the Kholmogory breed, introductory crossing with the bulls of the Ayrshire breed, tested for the quality of the offspring, was used. In order to improve dairy herds, the selection of cows for hereditary traits is combined with checking them for the first lactation. Since 1976, state farms began to study the breeding and productive qualities of the Ayrshire cattle, which were distinguished by high milk production and high fat content in milk. Since 1982, the Ayrshire breed has been approved as a planned breed for breeding in the farms of the Okhotsk zone. In the same year, absorptive crossbreeding of the animals of the Kholmogory breed with the sires of the Ayrshire breed began. In order to increase the efficiency of breeding for abundant milk production, work began on the farms to increase the hereditary variability of this trait through breeding along lines and families. At the same time, the work on improving the Kholmogory cattle by introductory crossbreeding with the purebred bulls of the Holstein-Friesian breed continued. By the 1990s, the main vector of development was the creation of highly productive herds of dairy cattle, but the difficult financial situation at farms in the 1990s led to a sharp decrease in the number of cattle and the productivity of the remaining animals.