نشریه ماشین های کشاورزی
سال دوازدهم شماره 1 (پیاپی 23، بهار 1401)

All over the world, farmers choose different implements for tillage, which depend on crop type, soil type, the amount of plant residue from the previous crop, etc. Tillage implement selection is also affected by the availability of implements, power consumption, labor costs, and fund. In this research, the draft force, soil disturbance area, soil cone index, and fuel consumption were considered. The effects of rake angle, forward speed, and soil moisture content on the above-mentioned parameters were investigated. In this research, a comparison between the performance of a Fiber Reinforced Polymer (FRP) composite blade and a conventional steel blade was carried out. Tests were based on the split-split plot in a completely randomized design. The factors of soil moisture content, rake angle, and forward speed were included in three levels. Three levels for the soil moisture content (9.3, 13, 16.7 %), rake angle (20°, 30°, 40°), and forward speed (3, 5, 7 km.h-1), were considered. The FRP composite blade (on average in the desired range for variables) has reduced the draft force, fuel consumption, and soil cone index, 14.97%, 16.63%, and 35.08%, respectively, than the steel blade. Also, the soil disturbance area created by the FRP composite blade was 4.93% higher than the steel blade. Based on the results of this study, it is clear that the FRP composite blade has better performance rather than the conventional steel blade for the aforementioned test variables. The FRP composite is inexpensive than the steel, this leads to remarkable save money in the production of the FRP composite blade used in the chisel and combined tillage tools that is economical for the farmer and manufacturer.

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.

The main aim of this study was to optimize the design parameters of the fruit shakers for efficient harvesting of Shengy olive. A single-degree-of-freedom spring-mass model was established to determine the natural frequency and damping coefficient of the limb. A tractor-mounted shaker that transmits vibration to limbs and fruits via a reciprocating mechanism was fabricated for field evaluation of the forced vibration modes. A 3×4 factorial experiment with a completely randomized design was conducted to investigate the effects of shaking amplitudes and frequencies on fruit removal. The shaking mode with a frequency of 10 Hz and amplitude of 80 mm transmitted the average power of 92 W to remove 95% of fruits in the field trial. This oscillation characteristic should be used to redesign the fruit shakers to pass human safety standards and efficient harvesting.

Every organization needs an evaluation system in order to be aware of the level of performance and desirability of its units. It is more important for agricultural companies, including agro-industries. In this study, 20 sugarcane harvesting units were selected. After modeling based on input-oriented CCR and BCC models, efficiency values for sugarcane harvesting units were calculated and the CART decision tree was used to extract rules to predict the efficiency of these units. The results of a study of 20 sugarcane harvesting units in the CCR model showed that 6 units had an efficient score and 14 units had an inefficient score, and their technical efficiency score was in the range of 0.73-0.95. The results of the BCC model study also showed that out of a total of 20 sugarcane harvesting units, 8 units had efficient scores. As can be seen, in the BCC model, more units are introduced as efficient units and there is less dispersion between inefficient units. Also, the distribution of efficient units in the BCC model is less than the CCR model. The average technical efficiency, pure technical efficiency, and scale efficiency were 93%, 88%, and 93%, respectively. Also, the accuracy of the decision tree model for technical efficiency and pure technical efficiency was 86% and 93%, respectively.

To enhance the fuel efficiency of the engines of agricultural tractors, the optimal control of interacting surfaces for improving engine performance becomes extremely significant, especially in developing the surface of cylinder liners. Therefore, plateau honing technology was designed on the cylinder liner of automotive and tractor engines. A substantially flat or plateau is left on the sliding surfaces along with more bearing areas, although a cross hatch model of valleys is kept for retaining oil. On the contrary, the created valley by honing functions as an oil repository can negatively affect creating fluid dynamic pressure on the surfaces. Accordingly, a better understanding of generated surfaces during plateau honing is essential for optimizing process. To this end, some experiments were performed on a cylinder liner of the Perkins 4-248 engine (related to the Massey Ferguson 285 tractor) which was manufactured by Keyhan Sanat Ghaem Company. Then, friction and wear tests with reciprocating motions were conducted to compare the lubricity of sliding cylinder liner surfaces with each different mark of plateau honing. Then, a comparison was made between the friction and wear of the surfaces including various depth of profiles, which were used as the honing mark of the agricultural tractors diesel engine, and those which had randomly ground surfaces. Based on this study results, higher amounts of wear volumes were produced by creating more interactions from asperity contacts and relatively thin films, compared to the test with the shallow-grooved honing marks.

In this study, the effects of infrared (IR) dryer system parameters such as IR power, the distance of mucilage from lamp surface, mucilage thickness on drying kinetics and, color indexes (L*, a*, b* and ΔE) of wild sage seed mucilage (WSSM) were investigated in an IR dryer system. Experimental moisture ratio (MR) data were fitted to 7 various empirical thin-layer models. It was found that the Page model has the best fit to show the kinetic behavior and acceptably described the IR drying behavior of WSSM with the lowest mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and standard error (SE) values and the highest correlation coefficient (r) value. The values of MSE, RMSE, and MAE for all experiments were in the range of 0.1×10-3-1.1×10-3, 1.04×10-2-3.25×10-2 and 8.7×10-3-27.1×10-3, respectively. The average effective moisture diffusivity (Deff) increased from 4.61×10-9 m2s-1 to 15.8×10-9 m2s-1 with increasing lamp power from 150 W to 375 W, while it was decreased from 14.4×10-9 m2s-1 to 5.16×10-9 m2s-1 and 13.2×10-9 m2s-1 to 4.31×10-9 m2s-1 with increasing the distance of mucilage from 4 to 12 cm and the reduction of mucilage thickness from 1.5 to 0.5 cm, respectively. Increasing in IR radiation power has a positive influence on the yellowness (increasing 19.78% in b* index) of dried WSSM. Also, it increased the color changes index (ΔE) from 16.05 to 17.59.

Early diagnosis of plant diseases before the occurrence of symptoms can reduce the loss of the yield and increase the quality of agricultural crops. It also reduces the consumption of pesticides, environmental risks, and the cost of production. For this reason, the objectives of the present study were non-destructive diagnosis of early blight of tomato plant and discrimination of the most important agents of early blight (A. solani and A. alternate) in the primary stages of incidence of the disease before appearing visual symptoms using Vis-NIR spectroscopy (400-900 nm). The spectral data were acquired from the leaves of the plants infected with A. solani and A. alternate, 48 hours, 72 hours, 96 hours, and 120 hours after inoculation. To develop the recognition model based on the spectral data, principal components analysis (PCA) coupled with artificial neural network (ANN) was used. The results showed that the PCA-ANN model could diagnose the infected plants and pathogen species with accuracy of 93-100% for test set samples. In 96 hours after inoculation, in addition to the simpler model (8 PCs and 3 neurons in hidden layer), accuracy of 100% was obtained. At all times after inoculation, there was no error in diagnosis of the plants infected with A. solani that is more pathogenic and aggressive than other species, from healthy plants. Early blight in tomato plant and the type of pathogen before visual symptoms, without any plant sample preparation, could be diagnosed non-destructively (with accuracy of 93-100%) using Vis-NIR (400-900 nm) spectroscopy coupled with PCA-ANN. It was concluded that this technology could be used for rapid, low-cost, and early diagnosis of this disease in tomato plant instead of time-consuming, expensive, and destructive laboratory methods.

Fractional vegetation cover (FVC) and normalized difference vegetation index (NDVI) are the most important indicators of greenness and have a strong correlation with green biomass. The objective of this study was to evaluate a hand-held GreesnSeeker (GS) active remote sensing instrument to estimate NDVI and FVC in the spinach plant. In this study, the color indices of the G-B index and Excess Green (ExG) were used as color vegetation indices to discriminate leaves from soil background. During 28 to 44 days after emergence (DAG), the results showed good correlations between chlorophyll yield and NDVI (R = 0.61 to 0.91), and the correlation between NDVI of GS and biomass was significant. In addition, in this growth stage, the results showed a good coefficient of correlation between NDVI of GS and FVC (R = 0.67 to 0.82). In assessing the nitrogen rate on the NDVI of GS, the results showed significant differences only at the short period of growth stage (28 to 36 DAG). The results revealed that GreenSeeker performed well for estimation both chlorophyll and biomass yield of spinach crop and it could be used as a suitable instrument for estimation of leaf area index in the middle of the plant growth period.