Optimizing Gear Selection and Engine Speed to Reduce CO₂ Emissions in Agricultural Tractors

Abstract

In modern agriculture, tractors play a crucial role in powering tools and implements. Proper operation of agricultural tractors in mechanized field operations can support sustainable agriculture and reduce emissions of pollutants such as carbon dioxide (CO₂). This has been a recurring concern associated with agricultural intensification for food production. This study aimed to evaluate the optimization of tractor gears and engine speed during crop operations to minimize CO₂ emissions and promote sustainability. The experiment was conducted using a strip plot design with subdivided sections and six replications, following a double factorial structure. The first factor evaluated was the type of agricultural implement (disc harrow, subsoiler, or sprayer), while the second factor was the engine speed setting (nominal or reduced). Operational and energy performance metrics were analyzed, including fuel consumption and CO₂ emissions, travel speed, effective working time, wheel slippage, and working depth. Optimized gear selection and engine speeds resulted in a 20 to 40% reduction in fuel consumption and CO₂ emissions. However, other evaluated parameters remain unaffected by the reduced engine speed, regardless of the implement used, ensuring the operation’s quality. Thus, optimizing operator training or configuring machines allows for environmental impact reduction, making agricultural practices more sustainable.

1. Introduction

Agriculture is the primary human activity responsible for feeding the global population and is relevant to the global economy, ensuring food security and human prosperity [1]. The increasing demand for food due to the increasing world population implies that productivity and efficiency need to be increased in the context of contemporary modern agriculture [2]. To meet the increase in food production, agricultural machinery is indispensable—especially tractors, as they have become the main mobile energy source in agriculture and play an indispensable role in agricultural mechanization [3,4].

The World Health Organization (WHO) recently classified exhaust gases from combustion engines as carcinogens, raising global concern about their impact on health and the environment. As a result, the urgency to address diesel emissions has increased, leading to the development of strict environmental regulations and social pressure around the world [5]. Among the most affected sources are agricultural machinery, as they are predominantly built with combustion engines and increase environmental pollution in many parts of the world [6].

Mechanized operations can determine the positive effect of increasing the efficiency of various crops, which occurs from sowing [7], soil tillage [8], and harvesting [9,10,11]. However, the tractor plays a key role in many operations during the crop cycle. The agricultural tractor can be used as a source of energy for various agricultural implements and machines [12], since, for various reasons, a series of agricultural operations are necessary, including soil preparation with a plow, disc harrow, subsoiler, cultivation, spraying, and seeding. In addition, specialized equipment may also be necessary for various activities [13].

The load factor on engines influences pollutant gas emissions, which occur mainly in tractors that operate under severe conditions and drastic rotation regimes [5]. As agricultural tractors operate under a variety of soil and environmental conditions, optimizing work settings for optimum traction performance is essential to maximizing their operational efficiency [14].

The tractor represents an engine on wheels and plays a crucial role in converting mechanical power into traction capacity and power for machines in the field, as the tractor’s engine power is converted into tractive force through the interaction between the tractor’s drive wheels and the ground [2]. This machine converts engine power into drawbar power, affecting implement productivity and fuel consumption [15,16]. Adjusting tractor operating methods can promote greater sustainability in agriculture. Therefore, research has been conducted to determine these effects under on-farm testing conditions.

However, it is well-known that energy obtained from fossil fuels prevails in the agricultural sector [17]. Selecting agricultural tractors for complex field operations is a difficult task, as it involves several machine characteristics. However, mathematical models and AI can contribute to promoting environmental and economic sustainability in machine selection [18], reducing costs and energy consumption to scientifically evaluate pollutant emissions.

Diesel engines are widely applied in the agricultural sector, contributing to carbon dioxide (CO₂) emissions. Carbon dioxide emissions serve as an indicator of engine activity and are closely linked to fuel consumption [19]. Diesel engines are preferred in agriculture due to their high torque, durability, fuel efficiency, and applicability for large-scale tasks [20]. Agricultural machinery managers can reduce fuel costs by adjusting parameters such as soil moisture, tractor power, and plowing speed [13]. Algorithms embedded in electronic systems can monitor the operating conditions of tractors in real-time [21]; however, digital and telemetry systems that estimate emissions and control the quality of operations are still scarce in agriculture.

As mechanization for intensive agricultural production is discussed as a strong influence on the processes that determine global climate change [22], such as CO₂ emissions, which are strictly related to fuel consumption [23], the need to reduce carbon emissions has emerged as a global duty and a collective effort [24]. This is a challenging proposition when seeking to balance agricultural production with sustainable and low-carbon development [25]. Furthermore, the age of tractors and machinery can affect pollutant emissions and fuel consumption. Pollution generated by these old machines can affect air quality and reduce the environmental efficiency of the agricultural process [26].

The deployment of emission-reducing technologies plays a key role in increasing environmental sustainability through several mechanisms [19]. Scientists need to work with farmers to develop technologies that increase the energy efficiency of self-propelled agricultural machinery and reduce emissions [27]. However, tests need to be carried out to assess the performance of machines in terms of pollutant emissions and energy consumption. These tests can be carried out directly on farms or in official institutions.

Engine speed is related to the number of cycles per minute the machine performs, indicating the number of revolutions directly on the machine’s crankshaft. Gear selection, on the other hand, indicates the selection of a set of gears that will determine the tractor’s translational speed. This way, even with high or low engine speeds, the tractor can operate at high or low translational speeds. The combination of engine speed and gear selection can promote greater fuel economy.

According to [28], correctly operated tractors can reduce fuel consumption and pollutant emissions. Furthermore, research centers such as the Nebraska Tractor Test Laboratory at the University of Nebraska conduct performance tests following the Organization for Economic Cooperation and Development (OECD) CODE 2 and provide performance reports, serving as a rational selection parameter for agricultural tractors. In addition, these tests help to develop strategies to save fuel, reduce gas emissions, and improve performance and thermodynamic efficiency [12,29]. Therefore, measuring the energy consumption of machines and emissions in the field becomes essential to achieving the level of sustainability in current agricultural models.

Tractor operating techniques and gear selection can promote greater sustainability; the engine speed reduction can provide savings of up to USD 1 per hectare worked [28]. Among the known techniques is “Gear-up and throttle-down”, where it is possible to save fuel significantly by operating the tractor in a higher gear and at a lower engine speed. In addition, this practice can reduce maintenance, downtime, and expenses generally incurred with the excessive speed of mechanical equipment [30].

This research aimed to evaluate the reduction in CO₂ emissions from agricultural tractors in agricultural operations through the optimization of gears and engine speed to promote sustainable agriculture.

2. Materials and Methods

The experiment was carried out at the University of Mato Grosso do Sul State (19°05′29″ S, 51°48′49″ W, and altitude of 535 m). The soil was classified as Quartzarenic Neosol, according to [31], and as Entisol (Quartzipsamments) according to the Soil Taxonomy [32]. The soil water content at the time of the experiment was 20 ± 1%, based on its approximation to the soil friability point.

The experimental design was completely randomized in strips with six replicates. Sampling was carried out in 25 m long strips, which comprised the experimental units. The treatments consisted of three agricultural equipment (subsoiler, disc harrow, and sprayer) operating at two tractor engine speeds (nominal and low speed). The selection of speeds was based on the tractor manual, which included information provided by the manufacturer regarding the tractor’s engine power. The subsoiler used a nominal speed of 2000 rpm in slow gear (4) and a low speed of 1600 rpm in medium gear (2). The harrow used a nominal speed of 2000 rpm combined with medium gear (3) and a low speed of 1600 rpm in high gear (1). The sprayer used a nominal speed of 1940 rpm in medium gear (2), and a low speed of 1650 rpm in medium gear (3).

Among the equipment used was a disc harrow, model GAICR (TATU Marchesan—Matão, Brazil), with 16 concave cutting discs of 66 cm in diameter, spaced at 270 mm and a cutting width of 2000 mm. The subsoiler, model AST (TATU Marchesan—Matão, Brazil), featured 3 curved rods, spaced at 780 mm, with a working width of 1560 mm. The sprayer, model Condor 600 (Jacto—Pompéia, Brazil), was coupled to the third point of the tractor and driven by the power take-off (PTO) with a 600 L tank and 12 m of bars with nozzles spaced 0.5 m apart and Jacto brand spray tips (JSF11003), with a 50 mesh filter, fan type, a recommended pressure range of 15 to 75 psi, a flow rate of 0.69 to 1.55 L min⁻¹, and a median volumetric diameter (DMV) of medium and fine droplets.

The equipment was pulled and driven by a 4 × 2 TDA agricultural tractor with 66.2 kW of engine power and equipped with BKT front tires with 12.4–24 diagonal ply and BKT rear tires with 18.4–30 diagonal ply. The total mass of the tractor was 3900 kg. The experimental plots were 30 m long (Figure 1).

The tractor energy performance set was evaluated by quantifying the carbon dioxide (CO₂) emissions generated in operations with the agricultural tractor, determined based on the fuel consumption in each treatment and defining the ratio of 1:3.76, where each liter of diesel oil consumed by the engine emits 3.76 kg of carbon dioxide (CO₂), as described by [33,34].

The fuel consumption in each agricultural operation was evaluated by measuring engine oil consumption. For this purpose, two M-III Oval volumetric flow meters(Oval Corporation, Tokyo, Japan), brand LSF45L, were used, each with a ratio of 0.1 L per voltage pulse generated. These flow meters were installed in the supply pipe between the fuel filter and the fuel injection pump, and the second flow meter was installed in the pipe that returns to the fuel tank, to measure the volumetric fuel consumption (L h⁻¹).

The actual consumption was calculated by the difference between the pulse quantities generated by the flow meters and sent to a programmable logic controller (PLC), with the hourly fuel consumption being generated according to Equation (1).

$$\mathrm{Ch}={\displaystyle \frac{\mathsf{\Sigma }\left(\mathrm{pe}-\mathrm{ps}\right)\times 3.6}{\text{∆}\mathrm{t}}}\times 10$$

(1)

where Ch = hourly fuel consumption (L h⁻¹), Σ (pe − ps) = difference between the sum of the pulses from the engine inlet and return flow meters, equivalent to the volume of fuel used, Δt = time spent covering the terrain (s), and 3.6 = conversion factor.

Operational efficiency and fuel consumption per area were determined using Equations (2) and (3).

$$\mathrm{Td}={\displaystyle \frac{1}{\mathrm{CE}}}$$

(2)

where Td = actual time demanded (h ha⁻¹), and CE = effective field capacity (ha h⁻¹), representing the amount of work effectively obtained by the machine, through the effective working width and travel speed.

$$\mathrm{CC}={\displaystyle \frac{\mathrm{Ch}}{\mathrm{A}}}$$

(3)

where CC = operational fuel consumption (L ha⁻¹); A = total worked area (ha); Ch = hourly fuel consumption (L h⁻¹).

Travel speed was determined by measuring the time spent traveling each section, and a digital stopwatch was used to determine the travel time. Average speed was obtained using Equation (4).

$$\mathrm{V}\mathrm{e}\mathrm{l}={\displaystyle \frac{\mathrm{L}}{\mathsf{\Delta }\mathrm{t}}}3.6$$

(4)

where Vel = speed of travel of the harvester (km h⁻¹); L = length of the experimental plot (m); Δt = time taken to travel the experimental plot (s); and 3.6 = conversion factor.

The tractor slippage in agricultural operations was calculated directly by the difference in the time required to cover the plots with and without the load of the tractor-implement set, with the aid of a manual centesimal stopwatch. To determine the depth of action of the implements, a graduated tape measure was used, and the depth in the soil was directly measured.

The data were organized according to the normal distribution and the homogeneity of variance tests. After detecting significant F values, we proceeded to analyze the difference between the means using the Tukey test (p < 0.05) to detect significant differences at 5% probability. All statistical analyses were performed using Minitab v.16 software.

3. Results and Discussion

3.1. Fuel Consumption and Pollutant Emissions

Pollutant emissions are directly affected by the tractor’s working regime [5]; thus, in operations that impose a greater load on the machine, emissions are high. CO₂ emissions in kg h⁻¹ for nominal and reduced speeds for the equipment used, and the interaction between these factors, are shown in Figure 2. Using nominal speed for the subsoiler resulted in the highest CO₂ emissions, followed by the disc harrow and sprayer. However, when using reduced speed, the subsoiler and disc harrow did not differ, presenting the highest emissions, but the sprayer provided the lowest CO₂ emissions.

In addition, for all equipment, adopting reduced speed interacted and reduced CO₂ emissions. The reduction in fuel consumption occurs due to the lower power demands placed on the tractor engine by the implements used. Thus, the sprayer propelled smaller loads, requiring less power and consequently having a lower environmental impact and pollutant emissions.

In all equipment, it was observed that the use of reduced speed resulted in reduced CO₂ emissions compared to nominal speed (Figure 2), with emphasis on the subsoiler, which provided a 40% reduction in emissions, followed by the sprayer and disc harrow with 30% and 21%, respectively. For the subsoiler and disc harrow, these emission reductions are related to the agricultural tractor’s gear combination, while for the sprayer, this reduction can also be associated with the use of the economic power take-off, a component available in several models of agricultural tractors, which aims to minimize fuel consumption and consequently helps reduce CO₂ emissions. Therefore, the importance of properly selecting the working gear to increase the efficiency of energy use becomes evident, especially in heavy operations such as subsoiling.

Reducing emissions is a global concern, and currently, several manufacturers provide economic power take-off technology in agricultural tractors, which, depending on the activity to be carried out, can help reduce fuel consumption [27,30]. Operating the tractor at an appropriate engine speed, in addition to providing a lower environmental impact by reducing emissions, also reduces costs and promotes greater mechanization efficiency.

Matching agricultural tractor gears to engine speed can optimize hourly fuel consumption and CO₂ emissions in accordance with American Society of Agricultural and Biological Engineers (ASABE) technical standards, contributing to more sustainable and economical agricultural operations. Subsoiling is an agricultural operation that requires more energy from the machine. Therefore, it must be carried out carefully and by qualified workers. In addition to being a high-cost operation, deep decompaction can cause greater environmental impact and emissions. According to [35], improving the use of soil preparation equipment can be a practical way of sustainable and environmentally friendly production, reducing fuel and CO₂ emissions.

Soil preparation equipment, such as subsoilers and disc harrows, interacts with the soil subsurface to perform the operation, and this requires greater energy demand from the agricultural tractor engine, resulting in higher fuel consumption and, consequently, CO₂ emissions in kg h⁻¹. However, because it only acts on the soil surface and the engine operates in a relatively constant regime, the sprayer can reduce energy demand and minimize CO₂ emissions [17].

Ref. [34] indicated that shallow cultivation requires less diesel than deep cultivation. This is due to the reduced interaction of the tools with the ground and lower contact resistance. Ref. [36] indicated that subsoiling consumes a lot of energy, as it reaches an uncultivated layer of the soil, requiring greater fuel consumption from the agricultural tractor, corroborating the results obtained in this research [37].

The highest CO₂ emissions per hectare were found when operating with the subsoiler at the nominal working speed of the agricultural tractor engine, followed by the disc harrow and sprayer at the same speed (Figure 3). When using reduced speed, the same emission pattern was observed when comparing the equipment used.

Ref. [37] obtained higher results for CO₂ emissions resulting from fuel consumption when working with the subsoiler than those of this research, with 261.89 kg CO₂ ha⁻¹, and the authors associate this result with a working depth of 35 cm. Emissions can be accounted for in creating the ecological footprint of agricultural activity; thus, the correct dimensioning of operations and reduction in emission levels can promote access to the level of sustainability in the production of some crops.

When analyzing the working rotation of each implement, it is observed that at reduced rotation, the subsoiler and the leveler harrow presented a difference in comparison with the nominal rotation; however, the sprayer did not differ statistically when adopting nominal and reduced rotation. Despite this, the work configuration with reduced speed in the sprayer provided a 30% reduction in emissions. In addition, the subsoiler resulted in an even more significant reduction in emissions per hectare of 39% and the heavy disc harrow of 24% (Figure 3). The machine selection methodology, as noted by [18], can be applied to other sectors involving complex decisions, such as energy management and urban planning. In addition, mathematical models can predict emissions based on the energy demand of machines.

Tractor engines operate within a power map, and engine fuel consumption varies with load and engine speed. Therefore, it is possible to use a technique called “Gear-up and throttle-down”, which makes it possible to save fuel significantly by operating the tractor in a higher gear and with a lower engine speed [30]. In addition, with the use of this technique, fuel savings of 30% can be achieved while maintaining the same speed and field capacity—values like those obtained in this research.

The type of work performed by the equipment impacts hourly fuel consumption and consequently CO₂ emissions, but when evaluating emissions per hectare, the width of the equipment and operating speed must be considered, which are related to fuel consumption and CO₂ emissions per hectare. Predicting tractor fuel consumption can provide alternatives for mitigating energy expenditure and promoting greater sustainability in agriculture [13]. Our findings indicate that fuel consumption prediction models can also be applied in studies of greenhouse gas and pollutant emissions.

The subsoiler presented the highest emissions per hectare, because in addition to the greater working depth, the width and operating speed were lower in comparison to the other equipment, such as the disc harrow, which operated at a lower depth. Ref. [38] concluded that reducing the depth of the equipment in the soil caused a decrease in fuel consumption, which directly affects CO₂ emissions [39].

3.2. Operational Speed and Efficiency

Embedded systems can facilitate the evaluation of machine performance in the field, creating information regarding the quality of operational work in the field [21]. In addition, embedded systems could be applied for environmental validation of applications and determination of the ecological footprint in agriculture. For this, specific algorithms can be developed and installed in machine monitoring and telemetry systems.

The speed of the agricultural tractor influences the equipment performance, and for each operation, there is an ideal speed range for the activity, as shown in Figure 4a, where a statistical difference was observed among the equipment used. According to [40], adequate speed in agricultural tractor operations is reflected in high efficiency. Higher operating speeds are desirable because they reduce the total working time in a field, but high speeds can compromise the quality of operations, reducing efficiency.

No significant differences were observed in relation to engine speed, which is a favorable result since the reduced speed effectively reduced CO₂ emissions without compromising operational performance. The operational speed remained constant, likely due to the influence of operating depth. Increasing working depth requires greater traction force to modify a larger soil mass, creating additional resistance that naturally reduces the tractor’s speed [41,42].

The operational time results highlight the stability in displacement speed, as no significant differences were observed between reduced and nominal speed (Figure 4b). Regarding the equipment, the subsoiler required the longest operational time due to its lower displacement speed and narrower operating width, necessitating more passes to cover the work area. In contrast, the sprayer, with its greater operating width and higher speed, exhibited the shortest operational time (Figure 4b).

3.3. Working Depth and Slippage

The depth at which machines operate plays a key role in determining the energy demand of tractors and agricultural equipment. Greater depth increases resistance to movement, leading to higher fuel and energy consumption. Figure 5a illustrates these depth measurements. The sprayer, which functions solely on the surface, registers a depth value of zero. Meanwhile, both the subsoiler and disc harrow displayed consistent depth levels regardless of whether nominal or reduced speeds were used. The only variation observed was linked to the type of equipment.

The subsoiler presented the greatest operating depth in relation to the disc harrow, which was expected since the subsoiler is a piece of equipment that operates underground at a depth of over 30 cm [43] and the disc harrow, more superficial at a maximum depth of 20 cm [44].

The highest slippage rates were observed with soil preparation equipment such as the subsoiler and disc harrow, reflecting the nature of their operational demands. In contrast, the sprayer exhibited lower slippage due to its reduced load ratio during use (Figure 5b). Slippage refers to the difference in speed between wheels without corresponding forward movement, indicating a peak in instantaneous inefficiency—where energy is consumed without generating work. Maintaining slippage within acceptable limits is essential to ensure greater operational efficiency and sustainability.

Slippage is affected by the load applied during soil-related tasks and by the operational efficiency of the tractor, serving as a crucial indicator for optimizing tractor performance within acceptable slippage thresholds under specific agricultural conditions [45,46]. Moreover, slippage significantly influences key operational parameters—including fuel consumption and field capacity—where excessive slippage can contribute to increased CO₂ emissions [47].

The system developed by [21] was an effective tool for improving operational efficiency in precision agriculture, providing insights into the performance of tractors and implements in different field conditions. Our results show that different operations can present different performance in the field. Thus, crop management methods can be improved to consider planning the use of machines more efficiently and in real time.

The use of reduced engine speed showed no difference from nominal speed in terms of operating depth and wheel slippage (Figure 5b). This indicates that reduced speed effectively maintains operational parameters, making it a viable technique whenever possible. Its adoption helps minimize fuel consumption and, as a result, lowers CO₂ emissions.

In addition, the adoption of more modern technologies to reduce emissions and improve energy efficiency is an important issue for the future of agriculture, especially since the fleet of machines is getting older and has a greater polluting potential [26]. Incentive programs for the acquisition of new, less polluting machines, the use of alternative fuels, and the electrification of machines represent promising solutions in the coming years.

4. Conclusions

This study highlighted the differences in emissions from an agricultural tractor in soil preparation and spraying field operations. Optimizing gears and working speeds in agricultural tractors during operations provides a reduction in CO₂ emissions from agricultural tractors, promoting sustainable agriculture. The main conclusions are as follows:

(a)

Fuel consumption and CO₂ emissions were reduced by 20 to 40% by optimizing gears and working speeds based on technical standards, but the other parameters evaluated did not differ with the reduction in engine agricultural tractor speed regardless of the implement used, ensuring operational quality.

(b)

The reduced gears must follow technical recommendations for operator training and best practices for machine driving.

(c)

The correct selection of working gears in the field and diesel engine speeds is crucial for sustainability and reduced environmental impact.