Climate change is affecting all sectors of human activities worldwide, including crop production. The aim of the paper was to evaluate the average daily air temperatures measured at one hundred meteorological stations across Slovakia in 1961–2010 and calculate the maximum length of the vegetation period for Solanum lycopersicum L., Brassica oleracea L. var. capitata and Daucus carota L. Future trends predictions of the temporal and spatial development across the duration of the vegetation period in Slovakia were elaborated for decades 2011–2020, 2041–2050, 2071–2080 and 2091–2100. Our results show that there was an earlier start to the vegetation period in spring and a later termination in autumn for past 30 years. There is a predicted trend of prolongation of the maximum duration of the vegetation period up to 20 days (Solanum lycopersicum L., Brassica oleracea L. var. capitata) and 15 days (Daucus carota L.) in comparison with the refence decade 2001–2010. The maximum vegetation period duration will extend from the south of Slovakia towards the north of the country. The predicted potential increase in crop vegetation periods will be limited by other constraints such as the availability of arable land and soil water availability.

The global mean near-surface temperature between 2012 and 2021 was 1.11 to 1.14 °C warmer than the pre-industrial level. This makes it the warmest period on record. The aim of this article was to investigate vegetation period changes (onset and termination of the temperature T ≥ 5 °C, T ≥ 10 °C, and T ≥ 15 °C) due to climate change from the average air temperature for the periods 1931–1961, 1961–1991, and 1991–2020 for 24 stations in Slovakia and forecast the length of vegetation periods for the periods 2021–2050, 2051–2080, and 2081–2110. The number of days with these characteristic temperatures was used as an input dataset, from which map outputs were generated in ArcGIS software. Spatial analysis of the vegetation periods in the past, present, and future showed an earlier start of the vegetation period in spring and a later ending in autumn during the last 30 years. The maximum duration of the vegetation period will expand from the south to the north of Slovakia. Future scenarios showed an extension of the vegetation period duration. On the other hand, this potential advantage for crop cultivation is limited by a lack of arable land in the north of Slovakia and by a lack of precipitation in the south of Slovakia.

Changes in the distribution of annual rainfall totals, together with the increase in temperature over the last 40 years, are causing more frequent periods of drought, and plants are more often exposed to water stress. The aim of this study was to monitor the effect of different water regimes (irrigated and non-irrigated) of individuals of walnut tree (Juglans regia L.) in a private orchard located in the West of Slovakia. Our research was focused on dendrometric and sap flow measurements in the period from 28 March to 2 June 2019. The results showed differences in the sap flow of walnut trees during the budbreak period: when trees were irrigated, sap flow in the diurnal cycle was around 130 g·h⁻¹ (20.48%), higher than in the non-irrigated treatment. Dendrometric differences between the irrigated and non-irrigated treatments were not significant. The sap flow data in the flowering period of the irrigated variant were slightly higher at 150 g·h⁻¹ (35.62%) than non-irrigated. Dendrometric differences were more significant when the difference between the variants was more than 1.5 mm. Continuation of this research and analysis of the data obtained in the coming years will allow us to evaluate the effects of the environment on fruit trees in the long term.

Global climate change is likely to influence evapotranspiration (ET); as a result, many ET calculation methods may not give accurate results under different climatic conditions. The main objective of this study is to verify the suitability of machine learning (ML) models as calculation methods for pan evaporation modeling on the macro-regional scale. The most significant PE changes in the different agroclimatic zones of the Slovak Republic were compared, and their considerable impacts were analyzed. On the basis of the agroclimatic zones, 35 meteorological stations distributed across Slovakia were classified into six macro-regions. For each of the meteorological stations, 11 variables were applied during the vegetation period in the years from 2010 to 2020 with a daily time step. The performance of eight different ML models—the neural network (NN) model, the autoneural network (AN) model, the decision tree (DT) model, the Dmine regression (DR) model, the DM neural network (DM NN) model, the gradient boosting (GB) model, the least angle regression (LARS) model, and the ensemble model (EM)—was employed to predict PE. It was found that the different models had diverse prediction accuracies in various geographical locations. In this study, the results of the values predicted by the individual models are compared.

Water stress is an indicator that plant are suffering from drought. For optimization of the crop production is necessary to indicate physiological changes, those can be represented by stem expansion or shrinkage and sap flow rate. We used the Dynagage SGA5-WS (Dynamax) sensors for the sap flow...

Municipalities in Slovakia have a duty to separate biodegradable municipal waste (BDMW) from family houses. This duty can be achieved by home composting or by collection of green waste in bio-bins, which are regularly emptied by a collection company. Collected waste is recycled in a composting...