INTRODUCTION

The accentuated use of conventional technology in world agriculture during last decades has generated an unfavorable situation from the point of view of the productive natural resources conservation, especially soil (FAO, 1992; López et al., 2010; Arvidsson & Hakansson, 2014).

Some authors have pointed out that the cost of agricultural machinery in Chile, in terms of fuel, fluctuates between 35 and 45% of the total cost of production1 (Paneque, et al., 1998). On the other hand in Venezuela this aspect has not been studied in depth. In the same sense, several researches have established that energy cost for fuel and machinery represents a high percentage of the total energy cost of production in business agriculture (Pick, 1989; Fluck, 1992; De las Cuevas et al., 2011). Fluck & Baird (1980) calculated that a tractor of the type 75 kW has an energy cost of approximately 1060 MJ/h, of which 77% corresponds to fuel.

Considering that there are no scientific data in this area to quantify the yield and energy cost of the machinery, with the technology of conventional seeding and direct seeding, there is a need to carry out the present research work, which will allow, through the comparison of the two technologies with corn (Zea mays L.), determining the energy and production costs and protecting the soil resource and the environment.

The objective of the research was to compare the energy cost of the main mechanized agricultural operations, emphasizing the tillage using Direct System with Cover (SDC) (Conservation System), in relation to the Conventional System (SC), starting from the hypothesis that it is possible to reduce more than 10% energy cost in the exploitation of agricultural machinery, in the cultivation of corn (Zea mays L.), of Los Riecitos Company in Freites Municipality, Anzoátegui State, Venezuela.

METHODS

The experiment was carried out in the Northern Summer 2014-2015 cycle with irrigation system with central pivot, between September and January, in the agro-industrial complex Los Riecitos, San Tomé, Cantaura Parish, Freitas Municipality of Anzoátegui State, in Venezuela. It is characterized by an average annual precipitation regime of 1100 mm and average temperature 27 °C and 256 msnm, relative humidity of 77, 3 % in the rainy season and 64, 1% in the dry season.

Characterization of Plots and Experimental Design

Each experimental plot occupied an area of 1000 m2 , being 20 m wide and 50 m long, separated by 4 m wide tracks. Along 10 m paths at its longitudinal ends, the maneuvers and agricultural set speed stabilization were performed, studying in them the behavior of bulk density, moisture and soil resistance, fuel consumption and energy cost of two tillage and seeding systems for corn (Zea mays L.). STATGRAPHICS Plus Version 5.0 was used as statistical tool for data processing. Simple ANOVA and Tukey’s test (HSD), p <0.05 was used for mean comparison.

Soil Characterization

The soil of the experimental area is taxonomically classified as Ultisol, characterized by high sand content of up to 88%, highly drained, low fertility, acid pH ranging from 4.5 to 5.5, notably phosphorus deficiency by its high fixation² . Therefore, it requires a high agronomic management to better these limitations and to increase its capacity of use. Physical characterization of the soil was carried out, determining: moisture, bulk density and resistance to penetration from 0 to 30 cm.

Determination of Soil Moisture

Samples were collected in aluminum foil and taken to the Soil Laboratory of José A. Anzoátegui Polytechnic University (UPTJAA), to be weighed in an electronic balance with 0.001 g of precision. All samples were weighed and the paper weight + wet soil was determined and dried for 24 h in a Memmert electric oven at 110 °C. Then they were allowed to rest to re-weigh and to know the data of the weight of aluminum foil + dry soil (NC 67: 2000). Subsequently the corrections were made taking into account the weight of aluminum foil, calculating the moisture through the following expression 1:

(1)

where:

M_shum and M_sseco –Are the masses of wet and dry soil, respectively, g.

Penetration Resistance (PR)

To determine soil resistance to penetration of the experimental area, a dynamic cone penetrometer was used, consisting of an impact mass of 2.3 kg and a free fall distance of 0.6 m. The readings of the number of blows per depth at intervals of 5 cm were recorded at the same sampling points above, the maximum depth being explored depending on the particularities of the soil of the point in question³ . The values obtained were translated to RP values using Scala´s (1956) formulation quoted by Stout et al. (1990) as described in expression 2.

(2)

where:

A- area of the cone base, cm2 ;

g - acceleration of gravity, cm/s2 ;

h- drop height, m;

M-impact mass, kg;

m-mass of the penetrometer without considering, M, kg; X-penetration distance, cm.

Determination of Soil Bulk Density

Bulk density. It is defined as the relationship between the dry mass of a soil sample and the volume occupied by that sample in the field. The result of the ratio (mass / volume) is obtained in grams per cubic centimeters (g/cm³ ).

To determine the bulk density of the soil, Uhland cylinder method was used using five cylinders per plots to extract soil samples, each length and diameter were measured with a caliper gauge (Vernier). To determine the volume, samples were taken at the 10 chosen points, placed in aluminum foil, weighed and taken to an oven at 110 °C for 24 hours, in order to determine the weight of the soil. The procedure for sampling was calculated by equation 3.

(3)

Where:

Da- soil bulk density, g/cm³ ;

M_ss-dry soil mass, g;

V_c -volume of the cylinder, cm3 .

Characterization of Machines

A Massey Ferguson tractor model 680 4x4, 6,000 kg, and 292 4x2 TDA with a maximum power of 48 kW (65 hp) in the engine at 2,000 rpm and a mass of 3 150 kg was used as the energy source in the experimental tests.

The implements and machines used in conducting the experiment were the following:

• Rotating Disc Harrow (Trail) with 36 discs: 18 teeth in the front, 18 smooth edges in the back and 1 800 kg mass.

• Jacto bar sprayer of 2000 L capacity and 850 kg of mass and working width of 14 m.

• Vence Tudo Seeding machine SA 14600 A, of 6 lines for grains with 1 300 kg.

• Vicon Fertilizer for application of granulated fertilizer and mass of 130 kg.

• Massey Ferguson harvester machine (combine, model 5680 with mass of 8060 kg).

Energy and Operation Costs in Agricultural Sets

For the determination of the energy and operation costs, the work of several specialists was studied and different methodologies were used. Burhan et al. (2004); Meul et al. (2007); Fumagalli, et al. (2011) and Mohammadhossein et al. (2012). The computer program “Energy and Exploitation Costs (CEE)” was used, which is an automated system elaborated in the CEMA by De las Cuevas, et al. (2009), this system allowed the analysis of the primary data of the observations, as well as the determination of the aforementioned costs.

RESULTS AND DISCUSSION

Characterization of Experimental Researches

The experimental area is characterized by an average annual rainfall of 1100 mm and a mean temperature of 27 °C and 256 msnm, relative humidity of 77.3% in the rainy season and 64.1% in the dry season.

Soil Characteristics, Energy and Operation Indicators

Physical-Mechanical Properties of the Soil

Each physical-mechanical characteristic of the soil was analyzed in the two plots studied. The treatment consisting of Conventional System (SC) was applied to plot 1 and Conservation System treatment (direct seeding with cover (SDC)) was applied to plot 2. As a general aspect evaluated in both plots, it is emphasized that datum populations studied for all variables analyzed (moisture, bulk density and resistance to penetration), normally distribute with homogeneous variances, which is the basis of variance analysis for determining the existence of significant differences between population means of each variable and the treatments applied.

Moisture

The studied variable was measured for each treatment at two different depths, up to 20 cm and from 20 to 30 cm, yielding 5 samples per depth per plot.

For the Conventional System (SC) treatment it was obtained that the average moisture up to 20 cm depth is 2.52% in a range from 1.04 to 3.55% with a coefficient of variation of 43.42%. In the case of the Conservation System (SDC) an average of 4.26% was obtained in a range from 0.8% to 13.69%, with the Conservation System being more variable with a coefficient of variation of 125.61 % as it is seen in Table 1.

Table 1

Statistical Summary of Moisture at 20 and 30 cm for Each Treatment

As for the analysis of moisture in the depth between 20 and 30 cm, it was obtained, on average, that in the Conventional System it is of 3.64% in a range from 2.63% to 4.62%, with a coefficient of variation of 22.98% and in the Conservation System the average value is of 2.27% with a range from 1,18% to 2,97% being more variable the Conservation System with coefficient of variation of 34, 51%.

From the previous analysis it was concluded that:

The plot in which the Conservation System treatment was applied has greater variability with respect to mean values of moisture than the plot to which the Conventional System was applied.

The average moisture depth between 20 and 30 cm is slightly higher than 0 to 20 cm in the plot to which the Conventional System was applied.

The results obtained in the analysis of variance show that there are no significant differences in moisture at both depths for the two treatments applied since the P-value equal to 0.49 and 0.39, respectively, for all cases are greater than 0,05

Bulk Density (DA)

The statistical analysis for the two treatments, Conventional (SC) and Conservation (SDC) Systems indicates that the bulk density mean of the plot in which SC was applied is 1.46 g/cm³ and in the SDC treatment yielded a mean value of 1.54 g/ cm³ . The results of the variance analysis allow determining that bulk density (DA), did not affect the behavior of none of the two systems of seeding, since it is shown that there is no statistically significant difference, according to the P-value of 0.62 that is superior to 0.05. Therefore, it can be affirmed that the selection of the two plots under study guarantees homogeneity with respect to the variable studied. As shown in Table 2 the data taken distribute normally according to the calculated statistics.

Table 2

Statistical Summary of Bulk Density

From the analysis it can be concluded that:

Mean bulk density in both treatments is homogeneous. The mean bulk density of 1.69 and 1.68 g/cm³ for treatments 1 and 2, respectively, obtained as shown in Table 2, did not cause interference in the application of treatments between plots.

The sandy loam soils of Guanipa table, according to Casanova (1996), have a real bulk density of 1.6 g/cm³ and according to USDA (1999), a bulk density equal to 1.69 g/cm³ can affect the crop development.

Resistance to Penetration

The penetration resistance (RP) was obtained as explained in the methodology. In the statistical processing of the results it was analyzed the existence of significant differences between the means of the RP measured in the depth intervals for each treatment obtaining 25 observations per plot. According to the analysis of variance from the depth of 10 to 30 cm there is no statistically significant difference between the two plots to which Conventional System and Conservation System were applied. The determinations were made with 95% confidence.

Figure 1, shows the behavior of the results obtained in the Conventional System. It is observed that the resistance to penetration increases with the depth at which the measurements were obtained. The behavior is similar in the Conservation System, because at the depth of 25 to 30 cm there is variation: at 25 cm depth it is 4.25 MPa and at 30 cm it is 3.41 MPa as shown in Figure 2.

Figure 1
Behavior of Depth Penetration Resistance in the Conventional System (RP vs Depth).

Figure 2
Behavior of Depth Penetration Resistance in the Conservation System (RP vs Depth).

The analysis of variance performed with the objective of determining if there were differences between the plots to which SC and SDC treatments were applied allowed us to verify that there is no significant difference for the PR measured at depths of 10 to 30 cm between the two treatments. The analysis was performed with 95% confidence, which indicates homogeneity among the plots selected for the study.

The cone index value for the SC treatment is 2.39 MPa while in the SDC treatment it is 2.50 MPa, both obtained at the beginning of the experimentation. This indicates that there is homogeneity in the compaction of both plots by comparing their soil profiles. The above is based on the non-existence of statistically significant differences of the studied variable among the treatments applied.

Tables 3 and 4 show the statistical summary of soil penetration resistance in MPa for each of the depths evaluated for the two treatments applied. As a general behaviour it is observed that the mean values of PR for the treatment of SC in relation to those obtained for the SDC are lower, being in ranges of minimum values between 0.14 and 3.48 MPa and 0.56 and 3, 48 MPa, respectively, there being a lower value in this treatment below 25 cm as a different behaviour. This can be caused by a continuous action of compaction due to the agricultural machinery used; however this value does not interfere in the applied treatments.

Table 3

Statistical Summary of the Penetration Resistance (RP), MPa. SC Treatment

Sample 1: Depth 5 cm SC, Sample 2: Depth 10 cm SC, Sample 3: Depth 15 cm SC, Sample 4: Depth 20 cm SC, Sample 5: Depth 25 cm SC, Sample 6: Depth 30 cm SC

Table 4

Statistical Summary of the Resistance to Penetration (RP), Mpa. Treatment SDC

Sample 1: Depth 5 cm SDC, Sample 2: Depth 10 cm SDC, Sample 3: Depth 15 cm SDC, Sample 4: Depth 20 cm SDC, Sample 5: Depth 25 cm SDC, Sample 6: Depth 30 cm SDC

The maximum RP values behave similar for both treatments, being between 0.98 and 4.85 MPa in SC and 2.24 and 4.85 MPa in SDC, coinciding the end of both treatments.

Likewise, the statistical summary shows that there is no regular behaviour of the coefficient of variation between treatments, since for the depths of 15 and 30 cm it is higher for the SDC treatment, while in the rest of the depths there is greater variability in the SC treatment. In spite of this variability, it does not imply that there is interference of the plot characterization for the application of the treatments. Similar behaviours were obtained in Spain (Hernandez, 1998).

From the statistical analysis of the results obtained it was concluded that:

The mechanical-physical characteristics of the soils in the plots tested do not interfere in the application of SC and SDC treatment.

Energy Cost and Operating Expenses

Energy cost

In the analysis of variance of energy cost behavior, the main objective of this study, according to the F test, significant differences were detected between the treatments of the two tillage and seeding systems under study (P <0.000). The coefficient of variation was 0.005%, indicating an optimum experimental precision. The comparisons between the means are shown in the graph of Figure 3.

Figure 3
Average Values of Energy Cost (MJ⋅ha-1) of the Conventional and Conservation Systems for Corn

According to the analysis of variance with a confidence level of 95%, it can be seen that the energy costs of both systems differ from one another. The Conservation System has an energy cost lower than the cost of the Conventional System. The results of energy cost of the two systems under study are shown in Table 5.

Table 5

Energy Cost (MJ⋅ha-1) of the Conventional and Conservation Systems for Corn

Total energy costs of the Conventional System were higher. The Conservation System results in a total energy cost of 13 650.00 MJ∙ha-1, corresponding to 88.19% of the cost of the Conventional System, saving 1 827.00 MJ ha-1. Energy corresponding to the fuel used amounted to 6 560.26 MJ∙ha-1 for the Conventional System and 1 381.43 MJ•ha-1 for the Conservation System, which equals 137.24 L∙ha-1 and 28,9 L∙ha-1, respectively. Conservation System saves 108 L of diesel fuel for each hectare worked, equivalent to 21% of fuel savings. The results obtained coincide with that reported by Hetz (1998), Stout (1990) and ASAE (1993). In cultural work (irrigation, weeding and fertilization) there were no significant differences in energy costs. The energy cost in both systems was similar. According to the results obtained, the highest energy costs corresponded to the spraying work in the Conservation System (11 269.00 MJ∙ha-1), which coincides with the results indicated by Paneque et al. (2002) and those reported by Paneque and Soto (2007). This is due to the fact that primary tasks were not performed (harrowing pass) in this system. The technology used in the Conservation System meant a saving of labor, by spending less time (4 h∙ha-1) of use of the machinery and an increase in the efficiency of it.

Operating Expenses

The total expenses of the work carried out were lower in the Conservation System than in the Conventional System. A difference of 444.18 Bs⋅ha^-1 was recorded. The lowest total expenses of the Conservation System is due to the decrease in soil preparation (Table 6).

Table 6

Operating Costs (Bs⋅ha^-1) of the Conventional and Conservation Systems for Corn

The results agree with those established by Collins et al. (1981), Frisby and Summers (1979), Hetz (1998), Summers et al. (1986) and Dos Reis (2000). These authors point out that the difference derives mainly from the amount of soil removed and the friction that occurs with each one of the tillage implements. In the Conservation System one operation less was performed (harrow pass) compared to the Conventional System, which meant 76% savings in total expenses and 44% savings in working time.

The costs (Bs) of the two corn systems are shown in Table 7, and direct costs are lower in the Conservation System 94% than in the Conventional System.

Table 7

Costs (Bs) of Conventional and Conservation Systems for Corn

In addition to this, the innumerable benefits inherent to the Conservation System can be summed up as less degradation of soils and the environment (Unger & Mccalla, 1980): FAOINTA, 1992). In this sense Derpsch et al. (1986) argue that “direct seeding” can represent a 64-74% reduction in fuel oil consumption, that this system is a guarantee for sustainable, low-cost and perennial agriculture. With the development already achieved in direct seeding, it can be seen that Brazil already has technologies to subsidize other tropical and subtropical regions around the world.

CONCLUSIONS

• The results obtained in the analysis of variance show that there are no significant differences in moisture at both depths for the two treatments applied since the Pvalue equal to 0.49 and 0.39, respectively, for all cases are greater than 0,05.

• The mean bulk density obtained of 1.69 and 1.68 g/ cm3 for treatments 1 and 2, respectively, does not cause interference in the application of treatments between plots.

• There is no statistically significant difference for resistance to penetration between both plots since all P values are higher than 0.05 according to the analysis of variance, from the depth of 10 to 30 cm, with 95% confidence in the applied treatments.

• The system that consumed less fuel was Conservation, with mean value of 28.9 L•ha^-1, compared to the Conventional System, whose mean value 137.24 L•ha^-1.

• The technology used in the Conservation System meant a saving of labor for consuming less time (4 h•ha^-1) of use of the machinery, an increase in its efficiency and a lower total energy costs, which represented 89% of the Conventional System, saving 3 400.40 MJ ha-1, making it possible to save 108 L•ha^-1 of fuel.

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Notes