Plant viruses cause crop losses in agronomically and economically important crops, making global food security a challenge. Although traditional plant breeding has been effective in controlling plant viral diseases, it is unlikely to solve the problems associated with the frequent emergence of new and more virulent virus species or strains. As a result, there is an urgent need to develop alternative virus control strategies that can be used to more easily contain viral diseases. A better understanding of plant defence mechanisms will open up new avenues for research into plant- pathogen interactions and the development of broad-spectrum virus resistance.
The scientific literature was evaluated and structured in this review, and the results of the reliability of the methods of analysis used were filtered. As a result, we described the molecular mechanisms by which viruses interact with host plant cells.
To develop an effective strategy for the control of plant pathogens with a significant intensity on the agricultural market, clear and standardised recommendations are required. The current review will provide key insights into the molecular underpinnings underlying the coordination of plant disease resistance, such as main classes of resistance genes, RNA interference, and the RNA-mediated adaptive immune system of bacteria and archaea – clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated Cas proteins – CRISPR/Cas.
Future issues related to resistance to plant viral diseases will largely depend on integrated research to transfer fundamental knowledge to applied problems, bridging the gap between laboratory and field work.

We compared different net sampling methods for microplastic quantitative collection by sampling different water volumes with nets of different mesh sizes. Sampling covered freshwater lake and reservoir with a significant degree of eutrophication located in Central Poland. The fibres were the main type of plastic collected from sampling sites and constituted 83% of all microplastic particles. Fibres of 700–1900 μm dominated in the samples. The size of mesh affected the amount of fibres collected. Small fibres of 10–200 μm in length were collected using only a fine net of 20 μm mesh size. The total amount of fibres depended on sample volumes; concentrations of microplastics were higher for smaller water volumes. It is likely that clogging with phytoplankton and suspended particles reduced the filtration capacity of the finest nets when large volumes were sampled, which led to an underestimation of microplastic. To our knowledge, this is the first study to provide evidence that the amount of small microfibres depends on mesh size and that the total microplastic abundance in freshwaters in Poland depends on the sample volume. We suggest sampling rather larger than smaller water volumes to assess the level of microplastic contamination more accurately, but clogging, which reduces the filtration capacity of finest nets, should be taken into account when eutrophic freshwater environments are studied.

The proper management of water resources is currently an important issue, not only in Poland, but also worldwide. Water resource management involves various activities including monitoring, modelling, assessment and designing the condition and extent of waters sources. The efficient management of water resources is essential, especially in rural areas where it ensures greater stability and efficiency of production in all sectors of the economy and leads to the well-being of the ecosystem.
The performed analyses have demonstrated that the time of origin of the cadastral data defining the course of water boundaries has a significant effect on their quality. Having analysed the factors (timeliness, completeness, redundancy) used to assess the quality of cadastral data, their clear trend of changes in time was noticed. Thus, it is possible to specify the estimated degree of quality of cadastral data defining the course of watercourse boundaries only based on the information about the method, time and area of data origin in the context of the former partition sector.
This research paper presents an original method of assessing the quality of spatial data that is used to determine the course of the shoreline of natural watercourses with unregulated channels flowing through agricultural land.
The research has also demonstrated that in order to increase the efficiency of work, the smallest number of principal factors should be selected for the final analysis. Limiting the analyses to a smaller number of factors does not affect the final result, yet it definitely reduces the amount of work.

The international community affirms the critical role of forests in climate change mitigation, which includes reducing emissions from degradation and deforestation, carbon stock conservation, sustainable forest management, and increasing carbon stocks in developing countries. It relates to land use and land cover changes. This study aims to review land use and land cover changes (LULC) in two decades, namely 2000–2010 and 2010–2020, and the impact on carbon stocks. Landsat satellite imagery in 2000, 2010, and 2020 are classified into six categories: built-up area, cropland, forest, water body, bareland, and grassland. This classification uses supervised classification. The accuracy kappa coefficient values obtained for the LULC 2000, LULC 2010, and LULC 2020 maps were 89.61%, 83.90%, and 87.10%, respectively. The most dominant systematic LULC change processes were forest degradation in 2000–2020; the transition of forest to cropland (349.20 ha), forest to bareland (171.19 ha), and forest to built-up area (661.68 ha). Loss of using the forest for other uses was followed by a decrease in carbon stock. There was a high decrease in carbon stock in the forest category (11,000 Mg C∙y–1). The results showed a significant change in land use and cover. The decline in the area occurred in the forest category, which decreased from year to year. Meanwhile, the built-up area increases every year. Carbon stocks also decrease from year to year, especially forests as the most significant carbon store, decreasing in the area.

Changes in river channel morphological parameters are influenced by anthropogenic factors, such as climatic changes, river catchment management changes, and hydrotechnical development of rivers. To assess the intensity of individual pressures and the resulting changes in abiotic and biotic factors in the riverbed, water quality monitoring is conducted, including the assessment of the hydromorphological status. The assessment can be based on the River Habitat Survey (RHS) which is a synthetic method that includes the evaluation of habitat character and river quality based on their morphological structure.
The input data, which characterise any river include physical features of hydrotechnical structures, bed granulation, occurrence of bedforms, visible morphodynamic phenomena, and a sediment transport pattern. The RHS method allows to determine two quantitative indices used to evaluate the hydromorphological status: Habitat Modification Score ( HMS), which determines the extent of transformation in the morphology of a watercourse, and Habitat Quality Assessment ( HQA), which is based on the presence and diversity of natural elements in a watercourse and river valley.
The proposed method can be divided into three stages. The first assesses the river section hydromorphological indices, describing the degree of technical modification ( HMS) and the ecological quality of the reach ( HQA), using the RHS method. The second stage describes morphological changes resulting from the technical regulation and estimates indices for the regulated reach. Finally, we compare HQA and HMS indices before and after the regulation. This comparison is described by numerical indicators and related to reference values.

The article presents results of monitoring carried out in barns with milking robots. The use of milking robots makes it possible, with proper stocking, to milk cows without human intervention. The analysis included all barns with Lely robots located in the Podlaskie Voivodeship in 2018–2021. In 2018–2019, there were seven such barns, and in 2020–2021 nine. In all barns, high milk yields were obtained of more than 1000 kg compared to the average milk yield obtained from stock of cows under monitoring in the Podlaskie Voivodeship. In 2021, four barns milked more than 9.5 thous. kg, three barns more than 10 thous. kg and two barns almost 12 thous. kg of milk. Fat and protein contents were typical for the breed. Three barns were monitored more closely in 2021, with varying numbers of robot milking stations in barns, i.e. A one, B two and C three milking stations. In 2021, over 700,000 kg was milked per stall in stall A, over 750,000 kg in B and over 850,000 kg of milk in C. The average milk per cow per milking was high, with over 11 kg in barn A, 12 kg in B and 13 kg in C.

The study was carried out to assess ecological risks at the closed landfill in Cai Dau town, Chau Phu district, An Giang province. Soil samples were collected at six locations (S1–S6) at depths of 0–20 cm and 60–80 cm in the rainy season (November 2020) and dry season (March 2021). The soil quality was evaluated using eight heavy metals (Mn, Fe, Cu, Zn, Ni, Pb, Cr and As). The results showed that most monitoring sites had heavy metal contents within the allowable limits for agricultural land of QCVN 03-MT:2015/BTNMT. Some heavy metals have been found to migrate to the soil layer of 60–80 cm. The heavy metals accumulation ( I_geo) in the two soil layers did not differ; Ni, Cr, Pb and As accumulated at non-polluting levels – moderate to high in the rainy season, while Cr and As only accumulated in the dry season. The composite pollution index ( PLI) indicated that the locations around the landfill were polluted; however, the ecological risk ranged from low to moderate (potential ecological risk index ( PERI) = 102–195) in the rainy season. Only about 50% of study sites during the dry season were contaminated and the risk was low ( PERI = 44– 68). However, the area around the landfill always poses potential risks due to the presence of heavy metals, including Ni, Cr, As and Pb. Monitoring the heavy metals in the surrounding landfill for the potential risks to human health and environment is needed.

The Sianjo-anjo reservoir is used to meet the need for downstream clean water. Land activity at the Sianjo- anjo reservoir watershed can potentially increase the rate of erosion and the silting of rivers and reservoirs due to sedimentation. Reservoir siltation is a crucial challenge for reservoir management because it can reduce its function and affect its service life. However, sediment yield is often overlooked in reservoir planning and environmental assessment. This study aims to predict the rate of land erosion and sediment yield, and create an erosion hazard map of the Sianjo-anjo reservoir watershed. The study used a Geographic Information System, GIS-based Universal Soil Loss Equation (USLE) method and discovered that the erosion rate of the Sianjo-anjo reservoir watershed was between 35.23 Mg∙ha ^–1∙y ^–1 until 455.08 Mg∙ha ^–1∙y ^–1, with 95.85% classified as the low level, 0.03% as moderate, and 4.12% as high. Meanwhile, the sediment yield from the Sianjo-anjo reservoir watershed was 218,812.802 Mg∙y ^–1. USLE is vital to identify areas susceptible to erosion and crucial for reservoir sustainability. Furthermore, it is necessary to plan good sediment management. Long-term land conservation is required to maintain storage capacity and ensure effective operation of the reservoir.

Water erosion in mountainous areas is a major problem, especially on steep slopes exposed to intense precipitation. This paper presents the analysis of the topsoil loss using the SWAT (Soil and Water Assessment Tool) model. The SWAT model is a deterministic catchment model with a daily time step. It was designed to anticipate changes taking place in the catchment area, such as climate change and changes in land use and development, including the quantity and quality of water resources, soil erosion and agricultural production. In addition to hydrological and environmental aspects, the SWAT model is used to address socio-economic and demographic issues, such as water supply and food production. This program is integrated with QGIS software. The results were evaluated using the following statistical coefficients: determination (R2), Nash–Sutcliff model efficiency ( NS), and percentage deviation index ( PBIAS). An assessment of modelling results was made in terms of their variation according to different land cover scenarios. In the case of the scenario with no change in use, the average annual loss of topsoil (average upland sediment yield) was found to be 14.3 Mg∙ha ^–1. The maximum upland sediment yield was 94.6 Mg∙ha ^–1. On the other hand, there is an accumulation of soil material in the lower part of the catchment (in-stream sediment change), on average 13.27 Mg∙ha ^–1 per year.