Adam Świętochowski

Mechanical weed control is a crucial sustainable alternative to chemical herbicides, yet optimising implement parameters to balance non-chemical weed suppression with crop safety remains challenging. This study evaluated how forward speed and working depth influence soil fragmentation, weed control efficacy, and immediate plant injury during the mechanical weeding of wide-row wheat. Field experiments tested three tractor speeds (6, 9, and 12 km·h⁻¹) and two working depths of duckfoot sweeps (30 and 50 mm). Key indicators—including the degree of soil crumbling, mean clod diameter, weed control effectiveness, and crop injury rates—were evaluated using analysis of variance. Higher speeds increased soil crumbling and reduced clod size, whereas effective weed destruction depended primarily on depth. Working with duckfoots at 50 mm achieved 95.9% weed removal efficiency, outperforming the 30 mm depth (80.2%). However, increasing speed above 9 km·h⁻¹ caused a sharp rise in the immediate crop injury rate (reaching 26.8%), while direct plant cutting remained low. This indicator represents visible post-treatment injury and should not be interpreted as irreversible crop loss or yield reduction. These findings demonstrate an asymmetric impact of operating parameters: deeper depths maximise weed clearance, but excessively high speeds severely increase crop damage. Optimising these settings is vital for sustainable field operations and underscores the need for improved implement designs to minimise lateral soil discharge.

The scientific objective of this work was to develop an analytical model for predicting the draught force required to overcome soil resistance by row weeders' duckfoots. The model considered variable duckfoot geometry, dynamic soil effects (i.e., changes in density, moisture, cohesion, and friction under tool loading), and nonlinear soil-implement interactions. The model was validated for three duckfoots with widths of 105 mm, 133 mm, and 202 mm. The tools were mounted on two types of flexible tines: a conventional S tine (stiffness 5.3 kN·m−1) and a Vibro Crop tine (VCO, stiffness 8.3 kN·m−1). The experiments were carried out in a soil bin filled with clay sand with a moisture content of 10% and 14% and a compactness of 486 kPa, using an instrumented measurement setup based on strain-gauge, laser, and optical sensors to acquire draught force, working depth and travel speed at duckfoots depths of 30, 50, and 70 mm and working velocities of 0.84, 1.67, and 2.31 m·s–1. The draught forces were predicted considering optimised values of the soil internal friction, soil–tool friction, and tool setting angles identified from the measurement data. The model showed good agreement with the experimental draught force values. For 10% and 14% soil moisture, the global errors were 18.0% and 24.7%, respectively, and the mean relative error was 0.8% in both cases. The model was validated and confirmed the hypothesis, but it requires further refinement and probabilistic analysis.

The study aimed to modify the models of Söhne, McKyes, and Perumpral to predict the draught force acting on duckfoot tools. Classic models, developed for narrow tools, do not consider the specific geometry of the wide duckfoot wings or the dynamic soil–tool interactions. In laboratory studies, duckfoots with widths of 105, 133, and 202 mm were used in the soil bin, operating at depths of 0.03–0.07 m at speeds of 0.84–2.31 m·s⁻¹ in soils with 10% and 14% moisture content. The results showed that the modified models predicted a draught force with a global error δ_g of 23–25% for the whole data, while the classical solutions achieved higher values (25–62%). The best fit and highest prediction were obtained for the Perumpral model (RMSE = 58 N), confirming its suitability for analysing wide tools. The developed modifications increase the reliability of predictions and performance of tillage implements, particularly in compacted soils. The falsification of hypotheses showed that while modifications improve accuracy, they do not eliminate limitations under varying operating conditions. It is necessary to improve the models by considering the three-dimensional effects of soil deformation, the variability of its properties over time, and random terms describing field factors.

The study aimed to modify the models of Söhne, McKyes, and Perumpral to predict the draught force acting on duckfoot tools. Classic models, developed for narrow tools, do not consider the specific geometry of the wide duckfoot wings or the dynamic soil-tool interactions. In laboratory studies, duckfoots with widths of 105, 133, and 200 mm were used in the soil bin, operating at depths of 0.03–0.07 m at speeds of 0.84–2.31 m·s⁻¹ in soils with 10% and 14% moisture content. The results showed that the modified models predicted a draught force with a global error δ_g of 23–25% for the whole data, while the classical solutions achieved higher values (25–62%). The best fit was obtained for the Perumpral model (RMSE = 58 N), while the Söhne and McKyes models had a higher error value (RMSE = 64 N). The developed modifications increase the reliability of predictions and can support the design of tools for work in compacted soils. The falsification of hypotheses showed that while modifications improve accuracy, they do not eliminate limitations under varying operating conditions. It is necessary to improve the models by considering the three-dimensional effects of soil deformation, the variability of its properties over time, and random terms describing field factors.

The study aimed to elucidate the effect of tine stiffness and operational parameters, such as speed, working depth, and soil moisture, on the effectiveness of soil disturbance with duckfoot tools. The experiments were carried out with three types of duckfoots attached to tines of different...

This paper presents the development of empirical mathematical models of draught force, F_x, and vertical force, F_y, acting on duckfoots attached to the tines with different stiffness and working in various soil conditions. The models consider technical variables such as stiffness, k, tool depth-to-width ratio, d/w, tool movement speed, v, and soil moisture content, MC, which have not been thoroughly analysed in the literature. The correlation coefficients for predicting F_x and F_y values were 0.4996 and 0.6227, respectively. Statistical analysis confirmed the significant effect of these parameters on the forces acting on the tools, with the variables d/w and v having the most critical impact on F_x and F_y. The SLSQP (sequential least squares programming) optimisation method was used to determine the optimal values of technical variables. The maximum value of F_x was 438.55 N, and the minimum was 98.98 N, with variable values at the edges of the studied ranges. Similarly, F_y values of 135.25 N and −84.55 N, respectively, were obtained. The optimisation results showed good fitness with experimental results, and the negative relative errors (from −1.72% do −4.81%), indicating overestimating, confirmed the accuracy of the model’s predictions. The justification of the research results allowed us to conclude that there is no basis for rejecting the explanatory hypotheses. The developed models have a generalisable value in the analysed ranges, and further research should focus on creating more universal, theoretical models of soil–tool interactions.

The paper presents the development of empirical mathematical models of draught force, F_x, and vertical force, F_y acting on duckfoots attached to the tines with different stiffness and working in various soil conditions. The models consider technical variables such as stiffness, k, tool depth-to-width ratio, d/w, tool movement speed, v, and soil moisture content, MC, which have not been thoroughly analysed in the literature. The correlation coefficients for predicting F_x and F_y values were 0.4996 and 0.6227, respectively. Statistical analysis confirmed the significant effect of these parameters on the forces acting on the tools, with the variables d/w and v having the most critical impact on F_x and F_y. The SLSQP (Sequential Least Squares Programming) optimisation method was used to determine the optimal values of technical variables. The maximum value of F_x was 438.55 N, and the minimum was 98.98 N, with variable values at the edges of the studied ranges. Similarly, F_y values of 135.25 N and -84.55 N, respectively, were obtained. Optimisation results showed good fitness with experimental results, and minor relative errors confirmed the accuracy of the model predictions. The justification of the research results allowed us to conclude that there is no basis for rejecting the explanatory hypotheses. The developed models have a generalisable value in the analysed ranges, and further research should focus on creating more universal, theoretical models of soil-tool interactions.

The rapid development of agricultural technologies has triggered new possibilities of using plant waste as fuel. Briquetting plant material is one of the methods of using crop residue as permanent energy carriers. Nevertheless, to maintain the normalised properties of briquettes, their small-scale production should follow an established and well-considered deliberate technological process limiting production costs. The material to be used for energy production should, in particular, be pre-prepared in terms of crushing and moisture content to ensure the right product parameters. The article aims to provide an analysis of briquettes with varied physicochemical parameters to determine and order homogenous groups for selected parameters characteristic for briquettes made from various bioenergy materials. The specific aim of the article required a statistical analysis as a tool for separating the selected factors. An analysis of variance (ANOVA) was involved, together with a post-hoc Duncan test. The analyses demonstrated that the briquette composition, such as bulk value, moisture, and ash content can enhance the briquette quality. In discussion, the straw used was compared with other kinds of agricultural biomass samples and considerable differences were identified. The chemical analysis showed a high content of carbon (from 42.64 to 45.66%) and oxygen (from 47.60 to 49.68%). The percentage share of hydrogen in the chemical structure of the materials accounted for approximately 6%. The ash content found while investigating various straw types ranged from 3.67 to 4.26%, making it lower than reported in the literature. The study also looked at the energetic potential of straw and wood biomass. It was noticed that bioenergetic sources are much potentially higher than the materials used in the traditional power sector. Especially where it concerns an unlimited source that can be provided to the bio-energetic sector. The study is intended to focus the future energy sector on the use of bioenergy in terms of applying straw to energy production purposes.

Analysis of the state of knowledge showed a gap in the description of tool–stone feedback. Therefore, the aim of this study was to investigate tool–stone interactions. Spherical-like silicate stones were hit by stiff and flexible tines with a duckfoot or a coulter. The tools worked with various parameters in the depth range of 0.05–0.10 m and a speed of 0.83–2.22 m·s^–1. The characteristics of stone movement were specific to the type of tool and were described by the Numerical Stone Movement Scale developed for the purpose of the research. After the impact with the stiff tine, the stones were thrown the greatest distance of 0.26–1.08 m, and these distances were strongly dependent on the working speed and slightly dependent on the working depth. Large vibrations of the flexible tine and the location of the contact point of the tine in relation to the centre of the stone thickness contributed to the random behaviour of stones that were slightly moved, rotated or displaced. The specific work required to remove the stone reflected the distance travelled by the stone as well as the specific force which largely contributed to increasing the differences in this work between both tines.