نشریه مکانیزاسیون کشاورزی
سال ششم شماره 1 (بهار 1400)

 Nowadays, tractors are almost driven by drivers. A driver does not only has to steer it, but also keep the mounted implements in a given position for some operations, including soil tilling, seed planting, weed controlling, spraying, … . In tillage operation, tractor and attached implements guidance is obtained by fallowing a furrow created by the plow in the soil during the previous passage. Driver has to fallow it to ensure a correct lateral position, but this continuous tiresome work affects his performance. In this research, a tractor driver assistance system was implemented for tillage operation. This system design was based on image processing technique. A test frame was designed and fabricated and a camera and lightening sources were mounted on it. The different positions of the camera on the frame were evaluated to find the best installation place. The experiments were conducted on some different farms. The important factors that affected the system accuracy including soil moisture content, environmental conditions and sunny or cloudy day situations were evaluated. The effects of farm surface conditions, last crop residues, natural or artificial light sources on the system performance were evaluated. LED lightening sources showed the best result, especially when they were used horizontally. Artificial lightening did not show visible differences with natural lightening in dry farming and sandy soils. Remaining cereal stubbles caused the worse system inaccuracy between the studied farms.

 Iran is one of the main producers of fruits in the world. Grading, sizing and sorting of fruit is an important factor in the Iranian marketing and exportation. In this research, the performance of a mechanical sorter machine of semi spherical fruit and fruit damage during process were evaluated. This machine was operates based on the belt-roller mechanism. The effect of some operational characteristics of the machine such as feeding conveyor speed, transportation conveyor speed and fruit kind (two varieties of apple; Red and Golden delicious; and orange) was evaluated on the machine performance factors such as purity index, efficiency of process and fruit damage. The results showed that the purity index was 95.80% and 95.83% for apple and orange sorting, respectively and the optimum capacity of machine was 1 ton per hour at this condition. The fruit damage was negligible at the optimum operational condition such as feeding and transportation conveyor speed and feeding rate. It indicates that the designing and operational characteristics of machine were optimum and the sorting machine was very suitable to sort semi spherical products usable in gardens or cold storages.

 Tillage implement and those which are made inside the country, and considering the importance of tillage depth and speed in different tiller performances, this investigation was carried out based on random blocks in the form of split plot experimental design. The main factor was tillage depth (10 and 20cm at both levels) and the sub factor was tillage speed, 6, 8, 10, 12 km per hour on four levels for Bostan Abad and 8,10,12,14 km per hour for HashtroudRegarding tillage speed effect for studies characteristics at 1% probability level (p < 0/01) remaining amount of plants was effective. From tillage depth effect in probability level of 5% (p < 0/05) on plant remaining amount was influential. The mutual effect of tillage amount of remaining plants on was significant at probability level of 1% (p < 0/01). In Hashtroud, effect of tillage speed remaining amount of plants at probability level of 1% (p < 0/01). Through an increase in tillage speed, remaining amount of plants Moreover, the optimum speed was concluded 10km per hour. Through an increase in tillage depth, the amount of remaining plants reduced. Tillage depth had significant effect on soil water content (p < 0/05). Regarding sampling depth effect on soil water content, was significant at 1% (p < 0/01) and 5% (p < 0.05) probability level, respectively. In Hashtroud, tillage depth effect on soil water content at probability level of 1% (p < 0.01). Depth of sampling was significant on humidity percent at probability level of 1% (p < 0.01). Through an increase in tillage depth, soil water content increases accordingly. The most appropriate tillage.

 Soybean is mostly harvesteds by conventional grain combine harvesters. Harvesting losses is one of the major issues in this way. Harvesting losses cannot be reduced to zero, but using the correct methods and proper equipments could reduce it to an acceptable level. Estimate of the losses rate in harvesting stage and recognition of effective factors in essentioal to decrease the losses. For reaching to a minimum loss, each one of harvesting processes (cutting, threshing, separation and …) must be optimized in operation. In this study the influence of forward speed, moisture content and plant density factors were used to make a mathematical model for John Deere 955 combine harvester rear losses. The experiments were conducted in soybean farms in Moghan plain, which is one of the major soybean prodcution areas in Ardabil province, Iran. For statistics a 3×3×3 factorial pattern based on randomized complete block design with 3 replications (in total 81 tests) was used. The effects of forward speed (in three levels of 1.8, 2.5 & 3.2 km h-1), moisture content (15, 19 & 23%) and soybean plant density  (40, 50 and 60 plant m-2) were tested again combine harvester rear losses (%). ANOVA results showed that the effects of all three factors with the double and triple interactions were significant at 1% probability level on rear losses. The losses were increased with increasing forward speed, plant density and moisture content. Linear regression was used to determine the relationship between dependent and independent parameters. The results of regression analysis of the model showed that 77% of the combine harvester rear losses is justified by the three variables studied in this study. The higher standardized coefficient of combine forward speed in the model make it the greatest effect on the rate of combine harvester rear losses.

Alfalfa is one of the main forage plants used for animal feed. Four percent of the total cultivated area in Iran is dedicated to this crop. Due to the fact that alfalfa has several harvests during its growth period, mowers have a special role for farmers. The purpose of this study was to evaluate and optimize the performance of cylindrical mower by designing two new blade types, and investigating the effect of blade type, forward speed and blade rotational speed on parameters such as fuel consumption, cutting height, harvest loss and damage index. The modeled blades were designed in Solidworks software environment and the force stresses were analyzed in Ansys software. Data analysis was performed using response surface method and Design Expert 12 software. The results of analysis of variance showed that the forward speed, blade rotational speed and the interaction between forward speed and rotational speed had a significant effect on tractor fuel consumption. But blade length and other mutual effects ofthis factor had no significant effect on tractor fuel consumption. Also, none of the independent parameters had any significant effect on cutting height, harvest loss and damage index. The relationship between independent and dependent variables was modeled in the form of regression equations. The optimal value for forward speed was 15 km/h, for rotational speed was 1596 rpm and for the blade lengh was 6.15 cm.

A field study was conducted to evaluate the effects of conservation tillage systems and different super absorbent polymer (SAP) rates on soil physical properties, grain yield and irrigation water use efficiency at Darab Agricultural Research Station during two growth seasons. The experimental design was done as split-plot based on a randomized complete blocks with three replications. The different tillage systems were in three levels of conventional tillage, reduced tillage and no-tillage as the main plot and rates of SAP as the subplot include: 0, 80, 100, 120, 140 kg ha-1 super absorbentapplication. The results showed that the no-tillage and reduced tillage systems increased soil bulk density in the 0-10 cm soil layer by 19.3% and 9.2%, respectively, compared with the conventional tillage. The findings also revealed that the effect of different tillage systems and rates of super absorbent polymer on soil bulk density and cone index of soil in the surface soil layer were significant. The highest porosity, the lowest cone index and bulk density were seen in the application of 120 and 140 kg ha-1 super absorbent polymer. Corn yield and irrigation water use efficiency had a different reaction to the different rates of super absorbent polymer. The highest corn yield and irrigation water use efficiency was obtained at the combination of no-tillage with 120and 140 kg ha-1 super absorbent polymerapplication, although there was no significant difference between them. According to our findings and based on the crop yield and irrigation water use efficiency, the application of 120 kg ha-1 super absorbent in combination with no-tillage method were seen suitable in the south of Fars province and areas with similar climate.

 Agricultural sector has a considerable and increasing share from total energy consumption of societies. The growth in population and living standards increase the demands for agricultural products. The limitations in cultivatable land area forces the need for increase in yield per area unit. It emphasis on the importance of energy and resources analysis in agriculture. Several researches in the world have been conducted around the energy consumption in agricultural farms, as well in Iran. However, there is a need for comprehensive studies analyzing the results of these researches. The aim of this study was the analysis of the consumed and produced energy for one of maize corn in Iran. The energy indices, obtained from related published studies were analyzed. The energy indices were determined as the energy output-input ratio (OIR), energy productivity (EP), energy intensity (EI) and net energy yield (NEY). The results indicated that, the average yield of maize corn in different provinces of Iran is around 6167 kg ha-1, requires an average energy input of 55 GJ ha-1. The largest share from total energy input was related to nitrogen fertilizer 29%, followed by electricity and diesel fuel with 28% and 16%, respectively. The average OIR was 2.92 MJ/MJ where the highest and lowest values were for Fars (5.8) and Khuzestan (0.8) provinces. The average EI was 9.47 MJ/kg, where it was the highest with 21.02 MJ/kg for Alborz and the lowest with 4.61 MJ/kg for Gholston.

 Anaerobic digestion of municipal organic waste faces numerous challenges. This process is often lengthy, requires a large reactor volume and produces insufficient methane to supply the process energy need, as well as uncertain digestate to be utilized in farmlands. Thermal pretreatment sometimes can be considered as an efficient method to address these problems. Many researchers, on the other hand, suggest that applying high temperature thermal pretreatment for easily biodegradable organics such as food waste will result in reduced methane production. In the current study, the contribution of the independent variables, including pretreatment temperature at 70, 90 and 110 ̊C, pretreatment duration of 30, 75 and 120 minutes as well as the digestible concentration at 8, 12 and 16% to methane production were considered. To optimize the aforementioned variables, modeling was conducted using Box-Behnken design followed by Genetic Algorithm to find the optimal quantities for mentioned parameters. The results of Genetic Algorithm revealed that the optimum pretreatment temperature and time and organic concentration to achieve the highest amount of methane from anaerobic digestion of organic waste would be 96 ̊C, 95 minutes and 12%. The predicted amount of methane applying the optimal conditions of temperature and pretreatment time and solid content resulting from Genetic Algorithm was 354 mL per gram of volatile solids. This value was in a good agreement with the actual amount of methane obtained applying these pretreatment conditions to organic wastes (354  ±4.58).