Permanent grasslands play a crucial role in ruminant nutrition, providing cost-effective and nutritionally rich forage. Their effective management is essential for improving agricultural productivity and sustainability. This review examines factors affecting forage quality, including environmental conditions, botanical composition, conservation methods, and fertilization strategies. The impact of grassland management practices, such as cutting frequency, grazing systems, and soil fertility enhancement, on forage nutritional value is discussed. Advances in breeding, including genomic selection and molecular techniques, offer opportunities to improve digestibility and resistance to environmental stress. Furthermore, conservation methods, including haymaking and silage production, significantly influence forage quality. Special attention is given to the role of legumes and multi-species swards in enhancing protein content and mineral composition. The review highlights that optimizing forage quality requires an integrated approach, combining agronomic practices, genetic improvements, and sustainable management strategies. Future research should focus on developing resilient forage systems that maintain high nutritional value while adapting to changing climatic conditions.

An overview was made of dry matter (DM) and quality losses that occur during the ensiling process. The aim was to review the current knowledge on the course of the fermentation pathways in various raw materials and the loss of DM accompanying this process. This review discusses the main groups of microorganisms involved in the ensiling process, the accompanying fermentation patterns, and the resulting DM losses. The possibility of reducing DM and quality losses during the ensiling process in practice is presented. The paper concludes with future perspectives and recommended management practices to reduce losses over the whole ensiling process.

Progressive climate changes are the most important challenges for modern agriculture. Permanent grassland represents around 70% of all agricultural land. In comparison with other agroecosystems, grasslands are more sensitive to climate change. The aim of this study was to create deterministic models based on artificial neural networks to identify highly significant factors influencing the yield and digestibility of grassland sward in the climatic conditions of central Poland. The models were based on data from a grassland experiment conducted between 2014 and 2016. Phytophenological data (harvest date and botanical composition of sward) and meteorological data (average temperatures, total rainfall, and total effective temperatures) were used as independent variables, whereas qualitative and quantitative parameters of the feed made from the grassland sward (dry matter digestibility, dry matter yield, and protein yield) were used as dependent variables. Nine deterministic models were proposed Y_G, DIG_G, P_G, Y_GB, DIG_GB, P_GB, Y_GC, DIG_GC, and P_GC, which differed in the input variable and the main factor from the grassland experiment. The analysis of the sensitivity of the neural networks in the models enabled the identification of the independent variables with the greatest influence on the yield of dry matter and protein as well as the digestibility of the dry matter of the first regrowth of grassland sward, taking its diverse botanical composition into account. The results showed that the following factors were the most significant (rank 1): the average daily air temperature, total rainfall, and the percentage of legume plants. This research will be continued on a larger group of factors influencing the output variables and it will involve an attempt to optimise these factors.

The content of structural carbohydrates and lignin are important assessment criteria of the feed value of meadow plants. It is affected by many independent factors, including among others its development stage during the harvest as well as climatic conditions, especially the amount of rainfall. During the years 2014–2016, plant samples were harvested at weekly intervals, respectively five times from late April to late May. The effect of harvest date on cellulose, hemicelluloses and lignin contents was evaluated. The chemical composition of plants was varied, depending not only on harvest date but also on the year of study. Regardless of the course of meteorological conditions in subsequent growing seasons, the increase of cellulose (from 236.5 to 297.9 g∙kg–1 DM), hemicelluloses (from 159.3 to 210.8 g∙kg–1 DM), and lignin (from 31.5 to 43.1 g∙kg–1 DM) in the following dates of harvest were observed. These parameters were also positively correlated with the total rainfall from the begging of vegetation season to the date of plants sampling (R2 = 0.65, 0.12 and 0.44 for cellulose, hemicelluloses and lignin, respectively), and with the average daily air temperature in the moment of harvest (R2 = 0.66, 0.32 and 0.52 for cellulose, hemicelluloses and lignin, respectively). The cellulose and lignin content, regardless of the harvest date, were significantly higher in the first year of the study (2014), when moisture conditions for plant development were optimal.

The article presents the results of research aimed at determining the catchment areas that pose a risk of nitrogen pollution of the waters of the Mała Panew river. The research was carried out in 13 permanent monitoring points located on the Mała Panew. The location of the points ensured the representativeness of the water quality results for parts of the catchment area with a homogeneous type of land use. Concentrations of nitrate-nitrogen (NO3-N) and total nitrogen (TN) were determined in the samples taken. The content of (NO3-N) in the third quarter of the year and its relation to the value obtained for the first year quarter may be an indicator of the impact of agricultural activities on the quality of water in streams. In the case of agricultural catchments, the lowest concentrations of NO3-N and TN occur in the third quarter of the year and are significantly lower than in the first quarter of the year. The demonstrated seasonal variability of nitrate nitrogen concentrations in agriculturally used areas may be used to determine the type of pressure not allowing to achieve good water status in the surface water body. It was shown that the highest unit increments occurred in areas with a high proportion of forest.

Marginal land is the area remaining in agricultural use, which is not suitable for food production because of its unfavorable ecological, anthropological, and economic conditions. A certain amount of such land exists in mountainous areas. An analysis was undertaken on the example of the Polish Sudeten mountain range of energy use. The study aimed to estimate the biomass potential for the efficient use of agricultural land in mountain areas. The characteristics of the Polish Sudeten Mountains mountain range were characterized using Geographic Information System (GIS) methods. The Polish Sudeten Mountains covers an area of 370,392 ha, 95,341 ha of which is arable land, 35,726 ha of which is class 5 bonitation land with a northern exposure of 19,030 ha and southern exposure of 16,696 ha. Depending on the sowing structure, we can obtain 331,639 tons/year of dry biomass (Miscanthus sacchariflorus on the southern and Helianthus tuberoses on northern exposure). Fertilization levels will significantly affect low yielding plants, and water stress significantly reduced yields in all cases. Due to the steep slope of the 5th-grade halves and intensive rainfall in the mountain region, the establishment of perennial plantations is recommended. The research shows that after the first year of cultivation, yields of 9.27 tons/ha of dry matter can be obtained with a low yield of trees, shrubs and perennials.