1. Introduction
Climate change is associated with the emission of greenhouse gases, mainly CO
2, the reduction of which has become a top priority. In agriculture, the tractor is one of the machines that contributes significantly to climate change, as it is the main source of energy for various agricultural operations. Tillage uses about a quarter of all energy used in crop production, and currently, more than 90% of this energy comes from fossil fuels [
1]. In particular, tillage operations such as ploughing or rotation are relatively long and require high fuel consumption, which contributes to accelerated climate change [
2,
3,
4]. In response to these circumstances, scientists need to work with farmers to develop technologies that increase the fuel efficiency of self-propelled agricultural machinery and reduce emissions. Researchers from different countries [
2,
3,
4,
5,
6,
7] conducted various field experiments in different soil conditions and found that with the correct selection of engine operating mode, transmission drive, and correct adjustment of the tire inflation pressure, the size of the ballast mass, and the distribution of the tractor’s weight on the axles, fuel consumption during ploughing could be reduced by 10–45%. Over time, more attention has been paid to the performance of agricultural machinery, and the ability to simulate field time has accelerated due to improvements in technology and simulation methods. This work is very helpful in effectively predicting the tillage time required for different fields. The results of this study will help to effectively predict tillage time and tractor fuel consumption required for different field shapes and dimensions. The calculation and planning of the working time of agricultural machinery is closely related to the economic and ecological indicators of the farm and its productivity. The ability to pre-calculate the efficiency of tillage operations, especially fuel consumption and exhaust gas pollution, is one of the more important tasks in order to rationally use energy resources in agricultural production and have less harmful impact on the environment [
8,
9]. Paris et al. conducted a review emphasising the need to create and apply standardized methodologies for the analysis of energy use in agricultural systems [
10].
Practice and scientific research show that fuel consumption during tillage depends not only on the size of the field but also on its shape. Traditional agricultural mechanization is more efficient when the fields are relatively large and have a regular shape. Irregularly shaped small fields are often considered uneconomical [
8]. Many small, irregularly shaped agricultural fields in the United States were abandoned during the 20th century. The European Union has kept small fields in production with subsidies [
11]. Small arable fields for agriculture are often associated with higher costs per unit area, both in terms of field time requirements and energy input, resulting in lower yields and lower farmland values [
12]. Depending on the implement’s working width and working speed, a 1 ha arable plot may require 30–90% more machine field time per unit area compared to a 5 ha arable plot [
13]. Since field operations take longer on a small field plot, smaller arable fields will also use more fuel per unit area than larger fields [
14]. In order to use larger equipment and ensure better fuel economy, field sizes in Lithuania were increased by removing small farms, old buildings, field trees, and bushes. At the same time, scientists have revealed the advantages of small fields. Studies in the European Union, Canada, and the United States have shown that farming in smaller fields naturally increases biodiversity [
8].
When ploughing the soil, the work efficiency is determined by how much time is effectively travelled on the field plot; when the agricultural implement is in the working position, all turning manoeuvres in the headlands are not counted, as they reduce the work efficiency [
12,
15]. Mechanized tillage, such as ploughing, starts from the edge of a cultivated plot, lowers the implement into a working position, accelerates to the technological speed, drives across the field, then slows down the speed of the tractor and finally rotates the unit at the end of the field plot [
2,
12]. Theoretically, the time spent by the tractor in the field during ploughing can be divided into two parts: the time of productive ploughing work (the plough is in working position and the tractor is moving) and the remaining time, called unproductive work time [
7,
16]. Most often, farmers try to shorten the duration of non-productive activities by optimally planning routes in field plots and assessing the shape and dimensions of the field plot, but in practice, there are route restrictions related to terrain features or agro-technological operational requirements. Many studies have proposed methodologies to optimize the tillage route in field plots of various shapes. There are long-known simple methods, according to which the direction of travel during tillage is determined according to the longest edge of the field plot, and then continues as in the rectangular plot scheme [
17,
18]. Optimizing tillage routes can reduce differences in fuel consumption in field plots of the same area with different dimensions, but the actual measured fuel consumption per hectare will still vary here [
15,
19,
20]. In addition, energy consumption in agricultural production is closely related to economic indicators of farm development [
21].
Monitoring of agricultural activities, especially the fuel consumption of machinery, is a very important factor in improving the economic indicators of a farm and reducing environmental pollution. In order to develop a reliable methodology for analysing fuel consumption for tillage operations such as ploughing fields of various shapes and sizes, it is first necessary to find common variables on which to base the monitoring. Previous studies have shown that such a variable can be the time efficiency factor when analysing tractor performance. It has also been shown that the value of time efficiency for a tillage operation can be evaluated by processing data reports from the tractor engine control module (ECM) [
22,
23].
The purpose of this research is to present a methodology that would allow calculating tractor fuel demand and CO2 emissions per area unit when ploughing field plots with different shapes and dimensions. The results of this study will help to effectively predict tillage time and tractor fuel consumption required for different field shapes and dimensions and to confirm a suitable variable for such a prediction. The aim was also to approve the methodology for the theoretical determination of the time efficiency coefficient of ploughed field plots of different shapes and dimensions. The results of this study will help to effectively predict tillage time and tractor fuel consumption required for different field shapes and dimensions, evaluating the following variables: the area of the ploughed plot, its average length in the ploughing direction, and the maximum width perpendicular to the ploughing, as well as the duration of the tractor turn in the field headland, the width of the ploughing strip, and the actual speed of the tractor during ploughing.
3. Results and Discussion
During the experimental study, all stubble field plots selected for research were ploughed in the modes indicated in the methodology. To collect tractor performance data, data tables and histograms (engine load profile) were created for each ploughing test field based on the field time distribution in engine speed–fuel quantity modes. Tractor load profile data for each stubble field ploughing test plot were calculated from the ECM data report copied after the completion of the ploughing test in the corresponding field plot, minus the analogue ECM report data copied before that test. One such histogram, that is, the histogram of the ploughing time distribution of the test field plot “I” in the different engine speed–fuel quantity modes is shown in
Figure 4.
From such data tables of tractor load profile histograms, based on the presented methodology, the distribution of ploughing field time, fuel consumption, and CO
2 emissions for productive and non-productive activities of the ploughing process in all test field plots was calculated. The results of the experimental tests obtained from the histogram data of all test plots are presented in
Table 2.
Next, in this section, we will analyse the relationship between fuel consumption, CO
2 emissions, tractor field time, field time efficiency, and different shapes and dimensions of field plots when ploughing stubble fields. For such an analysis,
Figure 5 shows the values of tractor field time (h) and fuel demand (kg ha
−1) for ploughing 6 ha field plots with different shapes and dimensions.
The bar graphs in
Figure 5 show a significant difference in tractor field time and fuel consumption values for different field plot shapes and dimensions. The biggest differences were between the 200 m wide, irregular quadrangular field (I) and the 100 m wide, rectangular field (III): the difference between the tractor field times was 0.66 h and the difference in fuel consumption was 0.85 kg/ha. However, the tractor field time and fuel consumption results (
Figure 5) analysed in various combinations with the field plot shapes shown in
Figure 1 and the dimensions listed in
Table 1 did not show a stable dependence on any of those parameters. This means that the bar graphs in
Figure 5 do not provide a suitable parameter to compare tractor field times and fuel consumption for different field shapes and dimensions. It should be noted that previous studies did not show a relationship between tractor fuel consumption per hectare and other tractor performance characteristics, on the one hand, and the size of the ploughed field area, on the other [
23]. However, previous studies have shown that tractor performance has a reliable linear relationship with field ploughing time efficiency [
23]. In the following analysis, we will look for a relationship between tractor fuel consumption and CO
2 emissions, on the one hand, and field ploughing time efficiency, on the other, when ploughing stubble plots with the same area, but with different shapes and dimensions. The values of the field ploughing time efficiency factor for a tractor unit with a reversible plough when ploughing 6 ha stubble field plots of different shapes and dimensions are presented in
Figure 6. Field ploughing time efficiency values for stubble plots calculated from Equation (5) are shown as dark bar graphs in
Figure 6. The experimental values of the field ploughing time efficiency coefficient of stubble plots with different shapes and dimensions, calculated according to the ratio of ploughing operation duration and field time determined by ECM reports, are presented in the white columns of
Figure 6.
The presented results show that when ploughing field plots of different shapes and dimensions with an area of 6 ha, the coefficient of field ploughing time efficiency varied from 0.68 to 0.82. The difference between the field ploughing time efficiency values of field plots of the same area, shape, and dimensions, calculated by applying Equation (5), and the results of the experimental measurements was small, less than 5 per cent. The data presented in
Figure 6 show that when ploughing field plots V and VI, which have different shapes and dimensions, more or less the same values of the field ploughing time efficiency coefficient were obtained, both calculated and experimental. Such results are explained by the fact that field plots V and VI of different shapes and dimensions have common parameters: the average length of the plot in the direction of ploughing and the maximum width of the plot perpendicular to ploughing are of the same size. The fact that the values of the average length of the plot in the direction of ploughing and the maximum width of the plot perpendicular to the ploughing of field plots V and VI are the same is confirmed by the dimensions describing the investigated plots presented in
Table 2.
The highest value of the field ploughing time efficiency coefficient of 0.82 was obtained when ploughing field plot III, the average length of the plot in the direction of ploughing of which was the largest at 600 m, and the maximum plot width perpendicular to ploughing was the smallest at 100 m. The lowest field ploughing time efficiency coefficient value of 0.68 was obtained when ploughing field plot I, whose average length of the plot in the direction of ploughing was the smallest at 300 m, and the maximum width of the plot perpendicular to ploughing was the largest at 200 m. Thus, the research results show that the field ploughing time efficiency coefficient is linearly related to the parameters of the studied field plots: the average length of the plot in the direction of ploughing and the maximum width of the plot perpendicular to ploughing (
Figure 7). A correlation relationship between the field ploughing time efficiency coefficient and field plot length in the ploughing direction was also found in previous studies that examined field plots of different areas [
23]. In addition, the article by Janulevičius et al. [
23] shows that there is no reliable relationship between the coefficient of field ploughing time efficiency and the field area. No other parameters with a reliable relationship with the field ploughing time efficiency coefficient were found during this study.
In addition, in order to facilitate the understanding of the results, an attempt was made to describe the shape of each field with practically known parameters, for example, the ratio of the area of the field to its perimeter. The relationship between the ratio of the field area to its perimeter and the coefficient of field ploughing time efficiency is presented in
Figure 8.
Figure 8 shows that there is no reliable relationship between the coefficient of field ploughing time efficiency and the ratio of the field area to its perimeter. Thus, from a practical point of view, the ratio of the area of the field to its perimeter is an obvious parameter, but it is not suitable for calculating the time efficiency factor of field ploughing.
In the following analysis, we will discuss the dependence of tractor fuel demand and CO
2 emissions per hectare on the shape and dimensions of ploughed field plots, based on the values of field ploughing time efficiency coefficients. Here, the hourly fuel consumption for each field plot, calculated from the tractor ECM reports, was converted to fuel consumption per hectare, as is common practice in many agricultural studies. The dependences of tractor fuel consumption for productive ploughing, non-productive activities, and total field fuel consumption per hectare on the field ploughing time efficiency coefficient are shown in
Figure 9.
The dependences presented in
Figure 9 show that the total field fuel consumption of the tractor, as well as the fuel consumption for non-productive activities when ploughing plots of different shapes and dimensions, have a linear relationship with the field ploughing time efficiency coefficient. Also, the obtained results show that the change in fuel consumption for productive ploughing from the field ploughing time efficiency coefficient was very insignificant—the value was about 14.85 kg ha
−1. This allows us to say that the shape and dimensions of the field plot do not affect the fuel consumption of productive ploughing. Meanwhile, the fuel consumption of non-productive activities during ploughing depends greatly on the field ploughing time efficiency coefficient, which means that those costs also depend on the shape and dimensions of the field plot. As the time efficiency increases, when ploughing stubble plots of the same area but different shapes and dimensions, fuel consumption for non-productive activities decreases. Thus, the variation in field fuel consumption depending on the field ploughing time efficiency coefficient and, accordingly, on the shape and dimensions of the ploughed plot is determined by the non-productive activity of the ploughing process. In the investigated 6 ha stubble field plots, an increase in the field ploughing time efficiency coefficient from 0.68 to 0.82 reduced total fuel consumption per hectare by 0.85 kg ha
−1, that is, from 16.47 kg ha
−1 to 15.62 kg ha
−1.
Figure 10 shows the dependence of productive ploughing, non-productive activities, and total field CO
2 emissions per hectare on the field ploughing time efficiency coefficient when ploughing stubble plots with the same area but different shapes and dimensions.
The dependences presented in
Figure 10 show that the total CO
2 emissions of the tractor, as well as the CO
2 emissions for non-productive activities when ploughing plots of different shapes and dimensions, have a linearly changing relationship with the field ploughing time efficiency coefficient. Also, the obtained results show that the change in CO
2 emissions for productive ploughing from the field ploughing time efficiency coefficient was very insignificant, the value being about 63.10 ± 31 kg ha
−1. The curves presented in
Figure 9 and
Figure 10 confirm the published results of previous studies [
31,
32,
33] that CO
2 emissions are inextricably linked to tractor fuel consumption. The CO
2 emissions of a tractor engine are proportional to the amount of fuel burned [
34,
35]. Due to this relationship, as fuel consumption increases, CO
2 emissions also increase proportionally. Analysis of the results revealed that during ploughing, 4.25 ± 2 kg of CO
2 gas is released into the environment when 1 kg of diesel fuel is burned in the tractor engine. From the research results published by other authors [
34,
35,
36], it can be seen that when 1 kg of diesel fuel is burned in the engine, somewhere between 3.3 and 4.5 kg of CO
2 gas is emitted into the atmosphere. Thus, when ploughing fields with different shapes and dimensions, changes in CO
2 emissions are proportional to changes in fuel consumption, and both actually depend only on non-productive activities in the ploughing process. In the investigated 6 ha field plots, the increase in the field ploughing time efficiency coefficient from 0.68 to 0.82 reduced field CO
2 emissions by 4.30 kg ha
−1, that is, from 70.32 kg ha
−1 to 66.02 kg ha
−1.
Researchers [
2,
4,
5,
7,
37] have conducted field tillage and ploughing experiments with different implements, working regimes, and soil conditions, and obtained different fuel consumption per hectare, from 17 to 24 L ha
−1. According to A. Soysal and H.H. Ozturk, the average fuel consumption for ploughing in 540 farms in Germany is 21.8 L/ha [
38]. According to the data of A. Soysal and H.H. Ozturk, the results covering many farms are clearly defined, but the non-detailed limits of the conditions do not allow comparison of these data with specific research results. Tillage operations are quite complex and due to their complexity and differences in soil physical and mechanical properties, fuel consumption and CO
2 emission values are widely dispersed in published research results [
35,
36]. Research reports provide the basic conditions of experimental studies, implement characteristics, working regimes, soil conditions, and field size, but often do not provide data on the shape and dimensions of the field. Moreover, in widely applied practice, fields of regular shape are often chosen for studies of one or other conventional properties. These studies show that fuel consumption results are affected by the shape and dimensions of the field, and without taking this into account the analysis will not be accurate under the given conditions.
Validation of the field ploughing time efficiency coefficient as an index of connectivity of field plots with different shapes and dimensions, which allows characterizing tractor fuel consumption and CO2 emissions when ploughing stubble field plots of the same area but with different shapes and dimensions, shows the novelty and uniqueness of this study. In addition, the specificity of this work is supplemented by the confirmed dependence of the linear relationship between the field ploughing time efficiency coefficient and tractor fuel consumption and CO2 emissions when ploughing stubble field plots of the same area, but with different shapes and dimensions. It is expected that the relationship between fuel consumption, CO2 emissions, and the shape and dimensions of the field plot, expressed in the time efficiency of field ploughing, determined in this study will contribute to the formation of cultivated fields and the management of their cultivation in order to reduce the impact on the environment.
4. Conclusions
Accelerating climate change requires scientists to develop new technologies to reduce CO2 emissions. Today, agriculture is dominated by arable fields of various sizes, shapes, and dimensions, and in order to evaluate the efficiency of the fuel used and CO2 emissions during their tillage, comparison methodology and criteria are needed.
This study presents a reasonable method for calculating the real field ploughing time efficiency coefficient based on field and tillage data and a practical determination method using tractor engine load reports. Using the theoretical method, the ploughing time efficiency for a particular field is calculated based on the area of the plot, its average length in the direction of ploughing, and the maximum width perpendicular to the direction of ploughing, as well as the duration of the tractor turning in the field headland, the width of the ploughing strip, and the actual speed of the tractor. In the practical determination method, the ploughing time efficiency of a particular field is determined by processing tractor ECM reports copied before and after work in that field. Theoretical calculations and experimental tests have shown that the field ploughing time efficiency coefficient is a useful metric for comparing field plots with different shapes and dimensions. This coefficient effectively describes tractor fuel consumption and CO2 emissions during ploughing operations on differently configured field plots.
It has been theoretically calculated and experimentally confirmed that tractor fuel consumption and CO2 emissions when ploughing fields of the same area, but of different shapes and dimensions, have a reliable linear relationship with the field ploughing time efficiency coefficient. It was found that during the research, when ploughing six field plots of different shapes and dimensions, with an area of 6 ha, the field ploughing time efficiency coefficient varied from 0.68 to 0.82, fuel consumption between 15.6 and 16.5 kg/ha, and CO2 emissions between 79.7 and 84.2 kg/ha. In the field plot of 6 ha, where the field ploughing time efficiency coefficient was 15% higher, the fuel consumption and CO2 emissions per unit area were lower by about 5.5%.
The results of this study make it possible to more effectively predict the tillage time and tractor fuel consumption required for different field shapes and dimensions. In order to determine the limits of fuel consumption prediction when operating in fields of various shapes and dimensions, research should be continued by expanding the variety of field sizes and shapes.