نشریه مکانیزاسیون کشاورزی
سال یکم شماره 1 (بهار 1392)

In recent decades, growth and development of countries have been coincided with great increase in water demand. So renewable and sustainable water resources used in the past, have been replaced with sustainable and energy dependent resources. Scattered information indicates that the irrigation pump efficiency is undesirable. Therefore, the present research was conducted to evaluate the irrigation pumps efficiencies. To implement the project, 104 pumping stations were selected in Zanjan province, Iran, considering the feasibility of efficiency measurement, for this purpose, the discharge rate, water pressure and its temperature were measeared. Also, input voltage and current for electrically driven, and, fuel consumption for diesel engine driven pumps were measured. Results showed that the average efficiencies were 36%, 20/78%, 11/57%, 6/82%, 17/83% for submersible pumps, drainage electro pumps, centrifugal electro pumps diesel engine driven centrifugal pumps and diesel engine driven multistage centrifugal pumps respectively. Results suggested that, replacing diesel engine driven pumps with electric pumps, using a single large pumps instead of several small pumps, organizing training courses for farmers, improving extension services, periodic inspection of the stations and in place measurement of pumps efficiencies by responsible bodies, can significantly improve the efficiency of the pumps efficiencies, and significant amount of savings in annual energy consumption and investment in electricity industry as well as reducation in environmental pollution can be achieved.

Plum is one of the most important crops in Iran. To reduce postharvest losses and increase shelf life of the produce, suitable preservation methods such as drying are used. Application of ultrasound and osmotic dehydration pretreatments in order to improve quantitative and qualitative characteristics such as shrinkage seems to be necessary and promising compared to hot air dried low quality products. Int his study, the effect of simultaneous application of ultrasound and osmotic dehydration pretreatments on plums shrinkage during drying at 80°C temperature and 1.4 m/s air velocity was examined. Pretreatments including ultrasound time at two levels (10 and 30minutes), osmotic solution concentrations at two levels (50 and70 Brix), and immersion time in osmotic solution at four levels (60, 120, 180 and 240 min) were performed. Afterwards, experimental results obtained from experiments were compared to that of available and proposed shrinkage models and then, one of the models was selected as a proposed model to predict shrinkage of plums under the selected experimental conditions. The results showed that shrinkage is significantly reduced by the simultaneous use of ultrasound and osmotic dehydration compared to control samples. Moreover, increasing the ultrasound time, osmotic solution concentration, and immersion time in osmotic solution, decreased shrinkage compared to control samples.

Potato is a strategic agricultural product. Due to a high economic value, it is necessary to separate the tubers from clods and stones before being transferred into storage tanks. This is one of the most important tasks in potato harvesting machineries. Despite many advantages, potato harvesting combines are not welcomed by farmers in Iran due to the lack of suitable agricultural soil textures and missuse of chemical fertilizers. Therefore, it is necessary to install an extra system in the combines to enable them to carry out an efficient separation task. In this article, a feasibility study was carried out on the separation of potatoes from clod and stone using the coefficient of restitution. A pendulum apparatus was used to determine those factors affecting the coefficient of restitution and the latter was compared in potato, stone and clod. A special device was designed, constructed, and evaluated in order to study the distribution pattern of tubers and clods after colliding with a separator surface. It was a semicircular plate, mounted at its center a quarter sphere made of steel. The surface of the aforementioned plate was divided into sections using wooden and rubber strips. The results showed that the effect of mass, velocity, and material of the colliding body as well as the effect of the velocity and material of the colliding body on the coefficient of restitution is significant at 5% level. An efficient separation of potato from clods and stones was achieved for the masses of greater than 60 g, and when the moisture content of the clods was 12 to 39%. The distribution pattern of potato tubers and clods on catch surface showed that the device could successfully be installed on the combines in Iran and it could be used to separate tubers from other materials efficiently using the coefficient of restitution.

Due to variation in economic value of different rice varieties, reports indicate the possibility of mixing different varieties on the market. Applying machine vision techniques to classify rice varieties is a method which can increase the accuracy of classification process in real world applications. In this study, several textural feature groups of rice grains’ images were examined to evaluate their efficacy in identification of three Iranian rice varieties (Tarom, Fajr, Shiroodi) in the mixed samples of these three varieties. On the whole, 666 images of rice grains (222 images of each variety) were acquired at a stable illumination condition and totally, 41 textural features were extracted from different matrices of grain images. Fisher's coefficient method, Principal Component Analysis method and a combination of these two methods were employed to rank and select the most significant features for the classification. The so called LVQ4 neural network classifier was employed for classification using top selected features. The classification accuracy of 97.96, 100 and 97.83 percent by using gray level matrix, 96.23, 100 and 100 percent by using co-occurrence matrix, 100, 97.50 and 100 percent by using local binary pattern matrix, and 100, 97.67 and 100 percent by using the whole textural features were obtained for Fajr, Tarom and Shiroodi, respectively. These results indicate that image processing can be a suitable tool for identification of different rice varieties. Although using the features of all matrices leads to less classification error, the features of each matrix also provides reasonable accuracy.

One method for digging onions up during harvest operation is using a rod cultivator in which, combination of rotational and linear movements of the rod underneath the bulbs, dig the onions out. Total power consumed by rod cultivator comprises two parts; one for driving the rod, and the other, for pulling the rod along the field. Travel speed as well as operation depth (depth to width ratio) of onion rod digger are both important factors that affect the total power consumption. In the present research, the effect of travel speed as well as operation depth on power demand of an onion rod digger was studied using a split plot in randomized complete block design with three replications. The treatments were operation depth in two levels, namely, 5-7 and 10-12 cm as the main plots and travel speed in three levels, namely, 0.3, 0.4 and 0.5 m/s as the subplots. During each treatment, draft force, drawbar power, torque and rotational power were measured. Based on results, draft force and drawbar power were between 4865 and 6400N, and, 1857.5 and 3125.5 W per meter of work width, respectively. In addition, the measured torque and rotational power were between 25.2 and 35.1 N.m, and, 1079 and 1814.5 W per meter of work width, respectively. Considering 2 m of work width for onion digger, tractors capable of delivering about 6.5 kW of drawbar power and about 4 kW of PTO power, are able to run onion digger. Most of the tractors currently used by farmers in Iran, fall within this category.

In order to help policy makers, this article attempts to identify the most important socio-economic factors affecting ownership of agricultural machines and discriminate two groups, namely, machine owners and non-machine owners in Khorasan-Razavi province, Iran. A Discriminate Analysis Model was used and 175 farmers were interviewed during year 2011 to gather data required. Results showed that variables such as farmer’s record of loans, farm acreage, and income are the most important factors, and farmer's investment record, membership in rural cooperatives, family size, farming experience, non-farming income and age, stand in the second place. Therefore, providing credits for purchasing new agricultural machinery in particular, establishment of leasing companies for agriculture machines and encouraging membership in cooperatives were proposed.

Draft of different tillage tools is an important parameter for performance measurement, evaluation of tillage tools and also for determining the amount of required energy. Prediction of this parameter could be beneficial in many farm management practices, prediction of energy requirements and selecting appropriate tractor. In this study, field experiments were carried out at two soil types, namely, clay loam and loam clay, for predicting draft of a vertical narrow tillage tool, using artificial neural network and also, for comparison of developed model accuracy with that of regression models. Some parameters such as soil types, soil conditions, tools parameters and operational parameters were selected as inputs to artificial neural network. Within each type of soil, experiments were conducted in the form of factorial experiment based on randomized complete block design (RCDB) with three replications. Different levels of soil moisture content (factor A) 5-16 percent for dry soil and 17-38 percent for wet soil, tractor speed (factor B) at four levels of 1, 1.5, 1.8 and 3 km/hr, working depth (factor C) at four levels of 10, 20, 30 and 40cm and blade width (factor D) in four levels of 2.5, 3, 3.5 and 4cm were selected. Back propagation neural networks with three different training algorithms (gradient descending algorithm with momentum, descending scaled gradient and Levenberg-Marquardt) were adopted to predict the draft. Back propagation neural networks with Levenberg-Marquardt training algorithm presented better accuracy in simulation (95.05%) and correlation coefficient (R2 ) of 0.9935 as compared to others. The obtained data from neural network model were compared to ASAE and Ashrafizadeh (2006) models; the result showed that the predicted data by artificial neural network were very close to real data obtained from field experiments and the regression models did not have much proficiency for predicting draft at the studied area.

A New product development as a new approach, and its importance in companies, even though is accompanied by some risks, identifying the key factors can be helpful in terms of decreasing the aforementioned risks. Since any decision about new product development can have a significant effect on degree of success, using a powerful technique that can assist managers in their decision making process is inevitable. Therefore this research was carried out through literature review and surveying method with the aim of identifying and ranking of key factors, to help decision makers to make an appropriate decision in their way towards a new product development. Managers and experts in the product development departments were all consulted in Arak Combine Manufacturing Co, and key factors were identified. Four key factors, namely, "Technology", "Marketing", "Commercialization", and, "Product development team management" were identified and 5 important indicators were chosen for each factor. The AHP hierarchical comparisons test approach was used and questionnaires were filled out by reliable sources, including directors and experts. Then the comments merged, and factors and indicators were determined by paired comparisons. Results showed that, factors of "Technology", "Marketing", "Product development team management", and "Commercialization" were the important factors respectively in this process.

Limitation of fossil fuels and the growing awareness of the detrimental environmental consequences resulting from greenhouse gas emissions have reinforced the importance of biomass as an energy resource. The conversion of rice straw and rice bran into briquettes as solid fuel is an important issue. The aim of this study was to determine the physical and chemical properties of rice straw and rice bran, and also the energy required for milling rice straw by hammer mill. Particle size distribution and particle density were determined for the milled straws, produced by four sizes of hammer mill screens at six particle size levels. FTIR test was carried out for determination of rice straw factor groups and distinction relation test. The required energy for grinding decreased with increasing of moisture content of the materials and the size of hammer mill screen. Normal distribution was observed for particle sizes of rice straw, grinded at 2 and 4 mm hammer mill screen sizes. The friction angle and bulk density of rice straw decreased with increasing the rice straw particle size. For the friction surfaces, the highest and lowest friction angles belonged to iron and aluminum surfaces, respectively. Based on the results of FTIR, during the burning process, lignin was fully destroyed in the oxidation reaction.