Dariusz Gozdowski’s research while affiliated with Warsaw University of Life Sciences and other places

W latach 2021/2022-2023/2024 w Sahryniu (powiat hrubieszowski, gmina Werbkowice, woj. lubelskie) przeprowadzono doświadczenie polowe, w którym badano wpływ aplikacji dolistnej nawozu SmartSil SC Power® na plonowanie, jakość nasion, parametry biometryczne roślin rzepaku ozimego przed zbiorem oraz opłacalność produkcji. Nawóz dolistny SmartSil SC Power® (SiO2 – 211 g dm-3, CaO – 235 g dm-3, K2O – 10 g dm-3, MgO – 4 g dm-3, Fe – 9 g dm-3, Ti – 1 g dm-3, Mn – 528 mg dm-3, Zn – 32 mg dm-3) stosowano wiosną dwukrotnie w dawce 2 dm3 ha-1 w okresie wegetacji: BBCH 30-31 i BBCH 50-51, a efekty porównywano z kombinacją kontrolną. Stwierdzono, że aplikacja dolistna nawozu produktem SmartSil SC Power® w dawce 2 dm3 ha-1 w fazie BBCH 30-31 oraz w fazie BBCH 50-51 istotnie zwiększa plon nasion, liczbę nasion w łuszczynie oraz zawartość NDF w nasionach, ma także korzystny wpływ na wzrost wartości produkcji brutto i netto rzepaku ozimego.

Methane (CH4) is a potent greenhouse gas with a significant impact on short- and medium-term climate forcing, and its atmospheric concentration has been increasing rapidly in recent decades. This study aims to analyze spatio-temporal patterns of atmospheric methane concentrations between 2019 and 2025, focusing on comparisons between regions characterized by high and low emission intensities. Level-3 XCH4 data from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite were used, which were aggregated into seasonal and annual composites. High-emission regions, such as the Mekong Delta, Nile Delta, Eastern Uttar Pradesh and Bihar, Central Thailand, Lake Victoria Basin, and Eastern Arkansas, were contrasted with low-emission areas including Patagonia, the Mongolian Steppe, Northern Scandinavia, the Australian Outback, the Sahara Desert, and the Canadian Shield. The results show that high-emission regions exhibit substantially higher seasonal amplitude in XCH4 concentrations, with an average seasonal variation of approximately 30.00 ppb, compared to 17.39 ppb in low-emission regions. Methane concentrations generally peaked at the end of the year (Q4) and reached their lowest levels during the first half of the year (Q1 or Q2), particularly in agriculturally dominated regions. Principal component and cluster analyses further confirmed a strong spatial differentiation between high- and low-emission regions based on both temporal trends and seasonal behavior. These findings demonstrate the potential of satellite remote sensing to monitor regional methane dynamics and highlight the need for targeted mitigation strategies in major agricultural and wetland zones.

This study performed in-season yield prediction, about 2–3 months before the harvest, for cereals and rapeseed at the province level in Poland for 2009–2024. Various models were employed, including machine learning algorithms and multiple linear regression. The satellite-derived normalized difference vegetation index (NDVI) and climatic water balance (CWB), calculated using meteorological data, were treated as predictors of crop yield. The accuracy of the models was compared to identify the optimal approach. The strongest correlation coefficients with crop yield were observed for the NDVI at the beginning of March, ranging from 0.454 for rapeseed to 0.503 for rye. Depending on the crop, the highest R² values were observed for different prediction models, ranging from 0.654 for rapeseed based on the random forest model to 0.777 for basic cereals based on linear regression. The random forest model was best for rapeseed yield, while for cereal, the best prediction was observed for multiple linear regression or neural network models. For the studied crops, all models had mean absolute errors and root mean squared errors not exceeding 6 dt/ha, which is relatively small because it is under 20% of the mean yield. For the best models, in most cases, relative errors were not higher than 10% of the mean yield. The results proved that linear regression and machine learning models are characterized by similar predictions, likely due to the relatively small sample size (256 observations).

In an experiment conducted at Kraski (52°2’42”N, 18°54’6”E) between 2023 and 2024, the effect of soil fertilization with a fertilizer containing Si, Ca, Mg and Mn, and foliar application with a fertilizer containing Si and Ca, and a combination of these combinations on the pre-harvest health of maize plants and the content of mycotoxins in the grain was studied. The soil fertilizer was applied at 100, 300 and 500 kg/ha, while the foliar fertilizer was applied once at a rate of 1 l/ha. It was found that the applied fertilization combinat ions had a favourable effect on reducing the infestation of leaves, stems and cobs by diseases and damage to stems and leaves caused by the European corn borer. The best effects were provided by the application of a 500 kg/ha soil fertilizer in combination with a foliar application. Weather conditions during the study years were not favourable for the development of mycotoxin-producing pathogens, hence their content in grain was mostly below the quantification threshold. W doświadczeniu przeprowadzonym w miejscowości Kraski (52°2’42”N, 18°54’6”E) w latach 2023–2024 badano wpływ nawożenia doglebowego nawozem zawierającym Si, Ca, Mg i Mn oraz aplikacji dolistnej nawozem zawierającym Si i Ca, oraz połączenia tych kombinacji na zdrowotność roślin kukurydzy przed zbiorem oraz zawartość mykotoksyn w ziarnie. Nawóz doglebowy stosowano w dawce 100, 300 i 500 kg/ha, a dolistny jednorazowo w dawce 1 l/ha. Stwierdzono, że zastosowane kombinacje nawożenia miały korzystny wpływ na ograniczenie porażenia liści, łodyg i kolb przez choroby oraz uszkodzeń łodyg i liści powodowanych przez omacnicę prosowiankę. Najlepsze efekty zapewniało zastosowanie nawozu doglebowego w dawce 500 kg/ha w kombinacji z aplikacją dolistną. Warunki pogodowe w latach badań nie sprzyjały rozwojowi patogenów produkujących mykotoksyny, stąd ich zawartość w ziarnie w większości była poniżej progu oznaczalności.

Climate change is forcing the search for innovative solutions to effectively reduce its harmful effects on food production. In addition, increasingly stringent regulations are being introduced in the European Union (the European Green Deal), mandating reductions in mineral fertilizer doses, which can reduce crop yields. One innovative technology could be soil fertilization and foliar application of Si-based fertilizers. A two-year field experiment (2023 and 2024), in commercial crop conditions in Kraski (52°2′42″ N, 18°54′6″ E), in Central Poland, studied the effect of differentiated soil fertilization and the foliar application of Si-based products on the yield and quality of maize grain at two levels of nitrogen/phosphorus/potassium (NPK) fertilization (100% and 50%). The soil fertilizer SiGS® (Si—200 g kg⁻¹, Ca—181 g kg⁻¹, Mg—46 g kg⁻¹, and Mn—45 g kg⁻¹) was applied to the soil at doses of 100, 300, and 500 kg ha⁻¹, alone or with Barrier Si-Ca® (Si—336 g dm⁻³; Ca—207 g dm⁻³) foliar fertilizer (1 dm³ ha⁻¹). The number of combinations assessed is 16. The effects were compared against the control treatment. The experiment evaluated plant physiological parameters, grain and dry matter yield, grain moisture content and quality (protein, fat, and starch content), and grain yield components. The highest grain yields were obtained with soil fertilization at a dose of 500 kg ha⁻¹ (giving an increase of 17.5%), at a dose of 300 kg ha⁻¹ plus foliar application (+16.4%), and at a dose of 500 kg ha⁻¹ plus foliar application (+17.8%). The increase in grain yield in treatments with a half-rate of NPK was of a similar magnitude (on average, +11.9%) to the full rate (+12.6%) compared to the control treatments. Doubling the NPK rate contributed to an increase in grain yield of 7.8%. The applied fertilization had a significant and beneficial effect on the protein and fat content of the grain, while it reduced the starch content.

Climate change is forcing the search for innovative solutions to effectively reduce its harmful effects on food production. In addition, increasingly stringent regulations are being introduced in the European Union (The European Green Deal), mandating reductions in mineral fertiliser doses, which can reduce crop yields. One innovative technology could be the soil fertilisation and dolsit application of silicon (Si). In 2023–2024, in commercial crop conditions in Kraski (52°2’42” N, 18°54’6” E), in Central Poland the effect of differentiated soil fertilization and the foliar application of silicon products on the yield and quality of maize grain at two levels of nitrogen/phosphorus/potassium (NPK) fertilization (100% and 50%) was studied. The soil fertilizer SiGS® (Si – 200 g kg-1, Ca – 181 g kg-1, Mg – 46 g kg-1, Mn – 45 g kg-1) was applied to the soil at doses of 100, 300, and 500 kg ha–1, alone or with Barrier Si-Ca® (Si – 336 g dm-3; Ca – 207 g dm-3) foliar fertilizer (1 dm3 ha–1). The number of combinations assessed is 16. The effects were compared against a control treatment. The experiment evaluated plant physiological parameters, grain and dry matter yield, grain moisture content and quality (protein, fat and starch content) and grain yield components. The highest grain yields were obtained with soil fertilization at a dose of 500 kg ha–1 (giving an increase of 17.5%), at a dose of 300 kg ha–1 plus foliar application (+16.4%), and at a dose of 500 kg ha–1 plus foliar application (+17.8%). The increase in grain yield in treatments with a half-rate of NPK was of a similar magnitude (on average, +11.9%) to the full rate (+12.6%) compared to the control treatments. Doubling the NPK rate contributed to an increase in grain yield of 7.8%. The applied silicon fertilization treatments had a significant effect on the protein, fat, and starch contents of the grain, and, in most treatments, increased the protein and fat contents and reduced the content of starch.

Crop damage caused by wild animals, particularly wild boars (Sus scrofa), significantly impacts agricultural yields, especially in maize fields. This study evaluates two methods for assessing maize crop damage using UAV-acquired data: (1) a deep learning-based approach employing the Deepness plugin in QGIS, utilizing high-resolution RGB imagery; and (2) a method based on digital surface models (DSMs) derived from LiDAR data. Manual visual assessment, supported by ground-truthing, served as the reference for validating these methods. This study was conducted in 2023 in a maize field in Central Poland, where UAV flights captured high-resolution RGB imagery and LiDAR data. Results indicated that the DSM-based method achieved higher accuracy (94.7%) and sensitivity (69.9%) compared to the deep learning method (accuracy: 92.9%, sensitivity: 35.3%), which exhibited higher precision (92.2%) and specificity (99.7%). The DSM-based method provided a closer estimation of the total damaged area (9.45% of the field) compared to the reference (10.50%), while the deep learning method underestimated damage (4.01%). Discrepancies arose from differences in how partially damaged areas were classified; the deep learning approach excluded these zones, focusing on fully damaged areas. The findings suggest that while DSM-based methods are well-suited for quantifying extensive damage, deep learning techniques detect only completely damaged crop areas. Combining these methods could enhance the accuracy and efficiency of crop damage assessments. Future studies should explore integrated approaches across diverse crop types and damage patterns to optimize wild animal damage evaluation.

Climate-driven changes have raised concerns about their long-term impacts on the yield resilience of cereal crops. This issue is critical in Poland as it affects major cereal crops like winter triticale, spring wheat, winter wheat, spring barley, and winter barley. This study investigates how soil nutrient profiles, fertilization practices, and crop management conditions influence the yield resilience of key cereal crops over a thirteen-year period (2009–2022) in the context of changing climate expressed as varying Climatic Water Balance. Data from 47 locations provided by the Research Centre for Cultivar Testing were analyzed to assess the combined effects of agronomic practices and climate-related water availability on crop performance. Yield outcomes under moderate and enhanced management practices were contrasted using Classification and Regression Trees to evaluate the relationships between yield variations and agronomic factors, including soil pH, nitrogen, phosphorus, potassium fertilization, and levels of phosphorus, potassium, and magnesium in the soil. The study found a downward trend in Climatic Water Balance, highlighting the increasing influence of climate change on regional water resources. Crop yields responded positively to increased agricultural inputs, especially nitrogen. Optimal soil pH and medium phosphorus levels were identified as crucial for maximizing yield. The findings underscore the importance of tailored nutrient management and adaptive strategies to mitigate the adverse effects of climate variability on cereal production. The results provide insights for field crop research and practical approaches to sustain cereal production in changing climatic conditions.

The use of legumes in rotation is beneficial and is of great importance in sustainable agricultural production in line with the assumptions of the European Green Deal. The aim of the presented research was to evaluate the cultivation of red clover as an undersown crop for spring barley and as a forecrop for winter wheat on the yield and quality of spring barley and winter wheat. To achieve this goal, two long-term static experiments set up in 1955 were used, in which diversified mineral and organic fertilization were used in two rotations: rotation without red clover (sugar beet–spring barley–winter rapeseed–winter wheat) and rotation with red clover (sugar beet–spring barley with undersown red clover–red clover–winter wheat). The obtained results indicate that the Norfolk rotation with red clover, as well as varied fertilization and years of research, influence the yield of plants. The highest grain yields of spring barley (5.7 t ha⁻¹) were ensured by mineral fertilization (NPK) and mineral fertilization in combination with manure (½NPK + ½FM). However, the highest yields of winter wheat grain (6.4 t ha⁻¹) were recorded in the treatments with exclusive mineral fertilization (NPK), significantly lower yields in the treatments where mineral fertilizers were used in combination with manure (5.7 t ha⁻¹) (½NPK + ½FM) and only manure (5.1 t ha⁻¹) (FM). The lowest yields of both cereals were found on soil that had not been fertilized since 1955 (0). The grain yield of spring barley was not significantly differentiated by the sowing method and was similar for spring barley grown with and without undersown red clover. Including legumes in the rotation had a positive effect on the yield of winter wheat. Fertilization had the greatest impact on the protein content in cereal grains. The use of mineral fertilization (NPK) and mineral fertilization in combination with manure (½NPK + ½FM) ensured the highest protein content in the grain of spring barley and winter wheat. Mineral fertilization (NPK) increased the protein content in spring barley grain by 2.9 percentage points compared to the unfertilized treatment (0) and by 2.1 percentage points compared to exclusive manure fertilization (FM), and in winter wheat grain by 2.3 and 1.4 percentage points, respectively. The cultivation of red clover in the rotation also had a positive effect on the protein content in spring barley and winter wheat grains.

Agricultural soil maps (ASMs) showing the agricultural land of Poland were prepared at a 1:5000 scale in the 1960s and 1970s. These maps show land suitability groups, soil type, and soil texture (ST) to a depth of 150 cm. Nowadays, these maps are being digitalized and might be a basis for the preparation of modern soil maps at the local, regional, national, and international levels. The agreement between the ST of the topsoil derived from ASMs and the recently evaluated one for eleven fields located in three voivodeships (regions) of Poland was studied. This study considered the examination of soil profiles or augerings and the laboratory analysis of the ST. The agreement between the ST status in the field and that according to the ASMs was field-specific. A complete agreement (purity) within the field was assessed for 5–79% of ST classes and for 23–100% of agronomic categories (ACs), i.e., groupings of similar ST classes. However, the averaged agreement, which treated adjacent ST classes as having a partial agreement, varied from 37 to 88% for ST classes and from 61 to 100% for the ACs among studied fields. These results indicate the variable quality of the information shown on ASMs and the necessity of improving these maps.