A. Hayati; A. Marzban; M. A. Asoodar
Abstract
Despite the development of dairy farm mechanization, milking operations are still associated with heavy workloads which result in human physiological strains. This study investigated the role of gravity force in the linkage between load carriage and workers’ physiological strains in milking work ...
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Despite the development of dairy farm mechanization, milking operations are still associated with heavy workloads which result in human physiological strains. This study investigated the role of gravity force in the linkage between load carriage and workers’ physiological strains in milking work tasks of two major cow milking systems (milking in stanchion barns and tandem parlors). These two milking methods similarly included washing the teats, attaching the cluster, and detaching the cluster. Human energy expenditure (EE) was calculated and load carriage direction in comparison with gravity (LCG) was tracked among twenty-four male workers. The highest heart rate (107 beats min-1) and EE (35.5 kJ min-1) were reported for attaching the cluster in the tandem parlor milking method. Tandem parlor milking caused higher human physiological strains and higher proportions of converse LCG compared with stanchion barn milking. By developing dairy farm mechanization from stanchion barn to tandem parlor, cow milking workers are induced to apply higher forces including converse LCG causing higher human physiological strains. Mechanization of dairy farms should be developed not only for improving the rate of work and performance but also for making conditions toward a reduction in the use of human physical forces.
Image Processing
F. Behzadi Pour; M. Ghasemi-Nejad Raeini; M. A. Asoodar; A. Marzban; S. Abdanan Mehdizadeh
Abstract
Introduction Today, attention to safety and environmental issues in all sectors in agriculture, industry and services is very important. Chemical poisons play an important role in rapid progress of agricultural products. Every year about 25 to 35 percent of the world's crops are affected by insects, ...
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Introduction Today, attention to safety and environmental issues in all sectors in agriculture, industry and services is very important. Chemical poisons play an important role in rapid progress of agricultural products. Every year about 25 to 35 percent of the world's crops are affected by insects, weeds and plant pathogens disappear and this figure would be raised to 80% if no control was applied. Drift problem and its devastating effects are the most important issue which related to users and sprayers manufacturers. Spray drift reduction and improvements in the efficiency of pesticide application processes are global goals. Where ever spraying is applied, drift will be produced and it must be controlled by controlled of the droplet size. The application of these sprayers is the high in the farms (the number of 2303 in Iran). So, this research was carried out to improve the quality of work in these sprayers by studying the droplets diameter and the spray quality index. Materials and Methods The research was conducted at the University of Khouzestan Ramin Agriculture and Natural Resources. Tests were done with 20 m of water sensitive papers at a distance of 2 meters from each other. To evaluate the technical items affecting on drift, an experiment was conducted using a turbo liner sprayer (TURBINA S.A. 800) and the John Deer (JD) 3140 tractor. A completely randomized factorial design was applied. By using 3 replications and the factors were spraying pressure applying three levels (10, 25 and 35 bar), the fan speed with two levels (1998 and 2430 rpm) and forward speed with two levels (9 and 13.5 km hr-1). The sprayer started the application, spraying a solution of water and tracer (yellow Tartrazine E 102), 15m before the water sensitive papers and then moved over the water sensitive papers. The spraying was continued 15 m after the end of the sampling area. After spraying, sensitive papers were photographed and then volume diameter of 50% (DV50) and median numerical diameter (NMD) and spraying quality indicator were calculated. A Spectrophotometry device at the wavelength of 427 nm, Image J and sas 9.2 software were used for measurement. This research was carried out in accordance with the calendar crop canola spraying in field conditions and the weather was calm that the wind speed was 0- 2.5 km hr-1, relative humidity was 29.7% - 32.5% and air temperature was 18.8˚C – 20.7˚C. Results and Discussion According to the results sprayer pressure, fan speed and forward speed were shown significantly different (P≤0.01) on the volume diameter of 50% (DV50) and median numerical diameter (NMD). The effect of spraying pressure on distributing quality indicator was shown significant (P ≤ 0.01), but the fan and forward speed did not shown any significant effect. Mean comparison of the interaction of pressure and forward speed on the spray quality index and the number median diameter were shown significant (P ≤ 0.01), but they did not shown any significant effect on the volume diameter of 50% (DV50). With increasing spraying pressure and fan speed, the droplet size, volume diameter of 50% (DV50) at 72% and numerical median diameter (NMD) at 69% and distributing quality indicator at 46% were decreased that were corresponded with the result of Czaczyk et al. (2012), Peyman et al. (2011), Nuyttens et al. (2009) and Landers and Farooq (2004). With increasing spraying pressure and forward speed, the droplet size, numerical median diameter (NMD) at 63% and distributing quality indicator at 35% were decreased that these resulted were corresponded with the results of Naseri et al. (2007) and Dorr et al. (2013). Conclusion With increasing spraying pressure, fan and forward speed, the droplet size, volume diameter of 50% (DV50) and numerical median diameter (NMD) were decreased. Therefore, spraying quality indicator was decreased. The maximum pressure (35 bars), maximum fan speed (2430 rpm) and maximum forward speed (13.5 km hr-1) were able to produce the minimum spraying quality indicator (10.3). At the minimum pressure (10 bars), maximum fan speed (2430 rpm) and minimum forward speed (9 km hr-1), the maximum spraying quality indicator (2.91) was resulted.
Z. Abdolahzare; M. A. Asoodar; N. Kazemi; M. Rahnama; S. Abdanan Mehdizadeh
Abstract
Introduction: Since the application of pneumatic planters for seeds with different physical properties is growing, it is essential to evaluation the performance of these machines to improve the operating parameters under different pressures and forward speeds. To evaluate the performance of precision ...
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Introduction: Since the application of pneumatic planters for seeds with different physical properties is growing, it is essential to evaluation the performance of these machines to improve the operating parameters under different pressures and forward speeds. To evaluate the performance of precision vacuum seeders numerous procedures of laboratory and field have been developed and their feed mechanism evaluation is of great importance. The use of instrumentation is essential in laboratory procedures. Many systems have been designed, using instrumentation, to be able to monitor seed falling trajectory and as a result, in those systems the precise place of falling seed in the seed bed could be determined. In this study, the uniformity of seed spacing of a seed drill was determined using of high speed camera with a frame rate of 480 frames s-1. So that, the uniformity of planting was statistically significant under the influence of the speed of seed metering rollers (Karayel et al., 2006). Singh et al. (2005) studied the effects of disk rotation speed, vacuum pressure and shape of seed entrance hole on planting spacing uniformity using uniformity indices under laboratory and field conditions. They reported miss index values were reduced as the pressure was increased but they were increased with increasing of the speed. The multiple indices on the other hand were low at higher speed but they were increased as the pressure was increased. Ground speed was affected by changes in engine speed and gear selection, both of which effect on amount of fan rotation speed for different pressures. The aim of this study was to identify and determine the effects of forward speed and optimum vacuum pressure amount of the pneumatic seeder.Materials and Methods: The pneumatic planter (Unissem) was mounted on a tractor (MF399) and passed over the soil bin. Thus, the acquired data would be more reliable and practical. To do so, the tractor was equipped with electronic devices for online measurement of various parameters, including: the actual forward speed, wheel sleep percent, drawbar pull, motor RPM, and fuel consumption. Wheel drive of the seed metering mechanism was equipped with Rotary Encoder model S48-8-0360ZT (TK1) to determine the seed disk rotation. For more precise vacuum pressure monitoring, a Vacuum Transmitter model BT 10-210 was used to measure relative pressure from 0 mbar to -1000 mbar. Investigation of seed falling trajectories was conducted using the AVI video acquisition system consisted of CCD (charge-coupled device) camera (Fuji F660EXR) capable of capturing images with a constant speed of 320 frames per second and a spatial resolution of 320×240 pixels. All data were transmitted to a data logger and displayed online on the PC's screen.For optimization of the factors affecting the performance of the pneumatic planter, the experiments were conducted with: two ranges of forward speeds [3 to 4 km h-1, and 6 to 8 km h-1; three levels of vacuum pressure [-2.5kPa, -3.5kPa and -4.5 kPa]; and two types of seed [cucumber and watermelon], keeping a three-factor factorial experimental design. The tests were replicated three times. The uniformity of seed spacing was measured with indicators described by kachman and smith (1995) which are defined as:I_miss=N_1/N×100 (1)I_mul=N_2/N×100 (2)I_qf=100-(I_mul+I_miss) (3)P=s_d/x_ref (4)Which for planting distance of 45 cm, N1 is number of spacing > 1.5Xref; N2 is number of spacing ≤ 0.5Xref and N is total number of measured spacings, Sd is standard deviation of the spacing more than half but not more than 1.5 times, the set spacings Xref, Imiss is the miss index, Imul is the multiple index, quality of feed index Iq is the percentage of spacings that are more than half but not more than 1.5 times, the set planting distance and P is error index.Results and Discussion: According to the studies on both watermelon and cucumber, the ‘quality of feed index’ value in forward speed rang of 6 to 8 km h-1 was less than one in forward speed rang of 3 to 4 km h-1. Also, the ‘error index’ value in forward speed rang 3 to 4 km h-1 was little rather than forward speed rang of 6 to 8 km h-1, but it was desirable.For watermelon and cucumber seeds, the ‘quality of feed index’ were the maximum with mean of 97% and 87% under vacuum pressures of -2.5 kPa and -4.5 km h-1, respectively and forward speed of 3 to 4 km h-1; so that for cucumber seed in the mention treatment, the ‘miss index’ was lowest with mean of zero.The ‘multiple index’ was highest with mean of 6% at 3 to 4 km h-1 forward speed and vacuum pressures of -4.5 for watermelon seed. Values of this index at both forward speed and three levels of vacuum pressures, for cucumber seed was more than watermelon seed.Miss index values were reduced as the pressure was increased but increased with increasing of speed. With lower vacuum pressure and at higher speeds, the metering disc did not get enough time to pick up seeds, resulting the higher miss indices. On the other hand, the multiple indices were low at higher speed but were increased as the pressure was increased (Panning et al. 2000; Zulin et al. 1991).Conclusions: It was observed that seed spacing uniformity was affected by both speed and pressure but not equally. Extracted regression models showed that the best uniformity of spacing for watermelon seed obtained at the rang of speed of 3 to 4 km/h and pressure of -3.5 kPa with a error in spacing of 7% in laboratory condition. Furthermore, in field condition the best uniformity of the seed space occurred at the pressure of -2.5 kPa and rang of speed of 6 to 8 km/h with a 9% error. Similarly, for cucumber seed results showed that the best uniformity obtained at the rang of speed of 3 to 4 km.h-1 and pressure of -4.5 kPa in laboratory condition, and at the low speed and pressure of -2.5 kPa in the field.
B. Goudarzi; M. A. Asoodar; N. Kazemi
Abstract
Introduction: Mulch tillage system is an intermediate system which covers some of disadvantages of no tillage and conventional tillage systems. In farms in which tillage is done with a chisel plow, runoff and soil erosion have a less important relation to moldboard and disk plow and naturally absorption ...
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Introduction: Mulch tillage system is an intermediate system which covers some of disadvantages of no tillage and conventional tillage systems. In farms in which tillage is done with a chisel plow, runoff and soil erosion have a less important relation to moldboard and disk plow and naturally absorption of rainfall will be developed. Thus, the mulch tillage system is an appropriate alternative to conventional tillage and no tillage (Backingham and Pauli, 1993). The unwanted vibration in machinery and industry mainly processes most harmful factors, for example: bearing wear, cracking and loosening joints. And noise is produced in electrical systems by creating a short circuit (Wok, 2011). Self-induced and induced vibration are used in tillage systems. Induced vibration is created by energy consumption and self-induced vibration is created by collision among the blades and soil at the shank (Soeharsono and Setiawan, 2010). A study by Mohammadi-gol et al. (2005) was conducted. It was found that on the disk plow, plant residues maintained on the soil are more than that of moldboard plow. 99% frequency and amplitude, speed and rack angle of blade directly affect soil inversion and indirectly affect preservation of crop residue on the soil. The effect of vibration frequency and rack angle of blade to reduce the tensile strength is also clear. Moreover, in contrast to previous studies when speed progressing is less than (λ), not only the relative speed (λ), but also frequency can reduce the tensile strength (Beiranvand and Shahgoli, 2010; Awad-Allah et al., 2009). Therefore, aim of this study was to determine the effect of vibration and the speed of tillage on soil parameters and drawbar power in using electric power.
Materials and Methods: To perform this test, three different modes of vibration (fixed, variable and induced vibration) and two levels of speed in real terms at a depth of 20 cm were used for farming. The test was performed with a split plot and randomized complete block design and three replications, and the fixed factors were: the depth of tillage: 20 cm, soil moisture: 16 to 17 percent and rack angle: 15 degrees; and the variable factors were the rate of progress in both 4.5 and 7.5 kilometers per hour and six levels of frequency, 1 fixed (zero) 2 variables (self-induced), 3 (positive19) and 4 (negative19), 5 (positive37) and 6 (negative37) Hz were performed. An electric generator was used to create vibration power. The equation (1) was used to calculate the vibration power:
(1)
Where P: Electric power (W), V: voltage (V), I: current (amps) and Ǿ: phase angle (degrees) between the voltage and current. After the calculation, the required power of 19 Hz was calculated to be 0.6, and the required power of 37Hz, was calculated to be 0.75 kilowatts, respectively. The sample of mean weighted diameter, after tillage in each plot, was about 10 kg soil (0 to 20 cm depth) with 3 replicates and through the equation (2), mean weight diameter was calculated as follows:
(2)
Where MWD: Mean weight diameter (cm), Xi: Two Elk consecutive mean diameters (cm) and Wi: weight ratio of the soil remaining on the sieve to the total weight of the sample. In order to calculate the specific energy tension due to the width of tillage (28 Cm), equation (3) was used.
(3)
Where E: tensile special energy in kilojoules per square meter, P1: drawbar pulling power required in kW, P2: the vibration according to equation (1) based on kilowatt, T: tillage time in one square meter per second.
Results and discussion: According to analysis of variance (Table 2) interaction effects of frequency and speed to keep the residue are significant at 1%, and this situation was shown well in Fig.2 Therefore, in practice, with increasing frequency in both induction and self-induction vibration, the tillage blades created a groove at the soil surface with less turmoil, and this would maintain the maximum residue on the surface of the soil.
As is clear from Fig.3, treatment of the frequency of 37+ (code 5) in both the first and second average forward speed is highest in remaining residue with 85% and 74%, respectively (Liu and Chen, 2010) and (Awad-Allah et al., 2009). By applying induced vibrations, a significant reduction in tensile strength occurs, because it reduces the time to deal with the blade of soil tillage and soil fractures with blows of the blade. It is clear that vibration reduces slip and real wheel speed is progressing, and following it, the increase in tensile strength occurs and it should not be considered due to the in efficiency of vibration tillage, since vibration may increase the depth of tillage, with the same vertical force component (Sahaya et al., 2009). Specific energy (plus drawbar and vibration) are shown in Figure.5 and the lowest energy consumption in both the first and the second speeds was on treatment of frequency +19, being 18.9 kJ m and 23.2 kJ m to first and second speeds, respectively.
Conclusions: In general, both factors (vibration and speed) affected tillage parameters and energy consumption and induced vibration caused by the system of unequal mass and electrical power properties was very easy to change phase vibration and transfer of power. This study was designed because of the significant effects on the important parameters of quality by vibration frequency of tillage and different frequencies to control the way in which tillage parameters are controlled. We can take it as a precision tillage that introduced variable control rate of percent residue on the soil, clod mean weight diameter that is suitable for the cultivation combined with reduced energy consumption.
P. Najafi; M. A. Asoodar; A. Marzban; M. A. Hormozi
Abstract
Introduction: The performance of agricultural machines depends on the reliability of the equipment used, the maintenance efficiency, the operation process, the technical expertise of workers, etc. As the size and complexity of agricultural equipment continue to increase, the implications of equipment ...
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Introduction: The performance of agricultural machines depends on the reliability of the equipment used, the maintenance efficiency, the operation process, the technical expertise of workers, etc. As the size and complexity of agricultural equipment continue to increase, the implications of equipment failure become even more critical. Machine failure probability is (1-R) and R is machine reliability (Vafaei et al., 2010). Moreover, system reliability is the probability that an item will perform a required function without failure under stated conditions for a stated period of time (Billinton and Allan, 1992). Therefore, we must be able to create an appropriate compromise between maintenance methods and acceptable reliability levels. Precision failure data gathering in a farm is a worthwhile work, because these can represent a good estimate of machine reliability combining the effects of machine loading, surrounding effects and incorrect repair and maintenance. Each machine based on its work conditions, parts combinationand manufacturing process follows a failures distribution function depending on the environment where the machine work and the machine’s specifications (Meeker and Escobar, 1998). General failures distributions for contiguous data are normal, log-normal, exponential and Weibull (Shirmohamadi, 2002). Each machine can represent proportionate behavior with these functions in short or long time.
Materials and methods: The study area was the Hakim Farabi agro-industry Company located 35 kilometers south of Ahvaz in Iran. Arable lands of this company are located in 31 to 31°10 N latitude and 45 to 48°36 E longitudes. The region has dry and warm climate. A total of 24 Austoft 7000 sugarcane chopper harvester are being used in the company. Cane harvesters were divided into 3 group consisting of old, middle aged and new. From each group, one machine was chosen. Data from maintenance reports of harvesters which have been recorded within 400 hours were used. Usually, two methods are usedfor machine reliability modeling. The first is Pareto analysis and the second is statistical modeling of failure distributions (Barabadi and Kumar, 2007). For failures distribution modeling data need to be found, that are independent and identically (iid) distributed or not. For this, trend test and serial correlation tests are used. If the data has a trend, those are not iid and its parameters are computed from the power law process. For the data that does not havea trend, serial correlation testare performed. If the correlation coefficient is less than 0.05 the data is not iid. Therefore, its parameters reach via branching poison process or other similar methods; if the correlation coefficient is more than 0.05, the data are iid. Therefore, the classical statistical methods will be used for reliability modeling. Trend test results are compared with statistical parameter.
A test for serial correlation was also done by plotting the ith TBF against the (i-1)th TBF, i ¼ 1; 2; . . . ; n: If the plotted points are randomly scattered without any pattern, it can be interpreted that there is no correlation in general among the TBFs data and the data is independent. To continue, one must choose as the best fit distribution for TBF data. Few tests can be used for best fit distribution that include chi squared test and Kolmogorov–Smirnov (K-S) test. Chi squared test is not valid when the data are less than 50. Therefore, when the TBF data are less than 50, K-S test must be used. Hence, the K-S test can be used for each TBF data numbers. When the failure distribution has been determined, the reliability model may be computed by equation (2).Results and discussion: Results of trend analysis for TBF data of sugarcane harvester machines showed that the calculated statistics U for all machines was more than chi squared value that was extracted fromthe chi square table with 2 (n-1) degrees of freedom and 5 percent level of significance. Hence, it is possible that all of the machines’ TBF data will have identically and independent distributions. For validating this hypothesis, correlation testwas performed on TBF data that verified prior results. Then, Kolmogorov- Simonov test was done on TBF data. Results showed that all three machines followed Weibull 3 parameters function, but the shape parameter was different for them. The analysis showed the shape parameter for old, middle aged and new cane harvesters was 1.5, 1.42 and 1.35, respectively.
Conclusions: In order to control and reduce failures and to plan and schedule the harvester operations in optimum time, machine reliability must be known. In this paper, three sugarcane harvesters were studied individually. From the trend analysis and serial correlation, it is seen thatthe assumption of identically and being independently distributed was valid for all machines’ TBF data of sugarcane chopper harvesters.
