مجله پژوهش های مکانیک ماشین های کشاورزی
سال هشتم شماره 2 (پاییز و زمستان 1398)

In this project precision planting method has been tested and evaluated for planting sugarcane billet. For this purpose a single devise known as “billet planting simulator” built and two metering devise were tested. For this research three different treatments that were applied: forward speed in three levels of 1, 2 and 3 Km/h, Billet transferring system in two levels of angled surface and conveyor and metering devices in two levels of toothed shaft and star wheel model. Factorial design based on Randomized complete design with three repetition were used. Four indexes had been measured and calculated which consist of: quality of feed index, precision index, multiple index and miss index. Teethed Shaft showed higher multiple indexes while star wheel showed higher miss index. Two metering devise had no significant differences in quality of feed index. In forward speed has been found that higher speed means less desirable planting. It also cleared that using conveyor with positive billet feed to metering devise, had significant rising in good planting indexes. Best mode can be found with QFI index and precision index. By using star wheel devise and conveyor with 2 Km/h speed the best planting can be reached. In fact it seems that using star wheels, conveyor and low speed is essential properties of a suitable precision billet planting system.

There is an especial importance in machines used for washing the agricultural tuber products. Optimized use of water, energy and attention to the economical aspects are important factors in design of these machines. Regarding these factors, a device was designed, constructued and tested. Experiments were carried out to measure and analyze the amount of impurities and wastes, and the percentage of damage based on a randomized complete block design with factorial experiment with two products, three levels of input weight; three levels of speed of conveyor belt each with four replications. The results showed that the weight of the input product and the speed of the conveyor belt had no significant effect on the amount of waste materials per kg of product, but had a significant effect on the percentage of damages. The damage for potato was significantly higher than carrot. The optimum speed of the conveyor belt was found at 2.4 m s-1 for 5 kg min-1 feeding. The amount of water saved by the machine was one l min-1. Based on the results, with use of a filter in water circulation system and recycling the water, water saving of 50% was obtained.

Increasing use of fossil fuels, rising oil prices and reducing existing reserves, as well as increasing environmental pollution by fossil fuels, have encouraged researchers to find new sources of non-oil energy. The main use of fossil fuels is in internal combustion engines. Bioethanol is one of the most important and most used alternative fossil fuels. As a result, many countries have been developing various methods for the elimination of the environmental pollution and the reduction of fossil fuels.Diesel engines are considered as an essential part in providing power to road and off-road vehicles. Biological fuels have intrinsic physical and chemical properties that make them in practice more clean than other fuels. In this study, the effect of blend diesel fuel, bioethanol and nano oxide cerium particles on the torque, power and fuel consumption of the engine was investigated. In the first phase of experiments, several experiments were carried out to stabilize the combustion of diesel-bioethanol with nano-oxide cerium particles. The results showed that ultrasonic bathing can be beneficial. In the second phase, the effect of different blend of fuels on the torque, power and specific fuel consumption of the engine was tested on a four-stroke single-cylinder diesel engine. The data were obtained at different speeds (1800 - 2600 rpm) for various fuels, bioethanol (0-12%), diesel fuel(88-100%) and nano oxide cerium between (5-15) PPm. Results showed power of fuel containing 5 PPm nano particles is the highest. It also has an impact on diesel fuel consumption × speed and diesel fuel × nano Became meaningfulon power and torque at 1% level. The results showed that the addition of nanoparticles to fuel increases heat transfer to fuel and, by accelerating burning, reduces the flame retardation time. Nanoparticles also improve the fuel-injection mechanism, resulting in better penetration of fuel jets into compressed air, resulting in more complete combustion and increased power.

Legumes with more than 700 thousand hectares are the most important crops in the country. Currently, legumes have a mean consumption of 4.8 kg, although their consumption is lower than the average world (6.6 kg) and is 7.8 kg promising a head, but at the same time plays an important role in Feeding people. Harvesting grains and especially rain-fed chickpeas are often harvested manually and with great time and money because of lack of access to a suitable machine. Crop losses because of plant characteristics, farm conditions and nonconformity of machines with product conditions. Therefore, to assess complying the new ONER combine harvester imported from Turkey is important for the harvesting of rain-fed chickpeas. In this research, to perform a new combine harvester for rain-fed chickpea harvest in the fields of farmers in the region is studied and evaluated. Experiments were carried out in strip plot design with five repeats. The horizontal factor is combine speed, and vertical factor is variety. The test will be on the farmland and the minimum length of the plantations is 25-30 meters. The crop features that are measured and considered are: plant height, plant width, number of plants per hectare, 100 seed weight, height of the first pod of soil, and grain moisture content. Cropping density, harvest coefficient. The technical evaluation features are: harvesting rates in machine and hand harvesting; gathering and processing loss, quality losses, distance between threshing cylinder and concave, forward speed and drum speed, and combine capacity. The results show that minimum total combine loss is 4.37% in engine speed of 1500 rpm or 3-3.5 km/s traveling speed. Also, total harvest loss is 10.42%. Minimum quality loss is gained 4.88%. The results of economical features analysis show the cost of hand harvesting is 4.8 times more than combine harvesting. Annual income of combine harvesting is 84 and cost of it, is 249.69 million Rails. Finally the profit/cost ratio is 3.36 so mechanized harvesting using the chickpea combine have economical affect and its purchase price will be depreciated during two crop years.

Grading of agricultural products, especially fruits and vegetables, improves packaging, transportation and marketing processes, reduces losses, and leads to an added value of the product. It is therefore important that the appropriate technology is adopted for this purpose. In this study, performance of four onion sorting mechanism, namely sieving screen, fixed divergent rollers, expandable rollers with plate spacer and expandable roller with roller spacer were compared by both Analytical Hierarchy Process (AHP) and fuzzy analytical hierarchy process (FAHP). 8 main criteria including proper grouping of onions, machine capacity, mechanical damages, machine portability, member of outlet groups, adjustment of outlet group size range, initial price and after-sales services were considered for determining the priority of onion sorters. The results showed that among the 8 main criteria, the highest and lowest weights were allocated to mechanical damage and initial price, respectively. According to the results of the integration of different criteria and options, Both methods showing the same order determined that the expandable rollers with plate spacer with 0.317 (AHP) and 0.412 (FAHP) have the highest weight following by expandable roller with roller spacer with 0.315 (AHP) and 0.291 (FAHP), sieving screen with 0.218 (AHP) and 0.189 (FAHP) and fixed divergent rollers with 0.150 (AHP) and 0.106 (FAHP) respectively. In this way, expandable rollers with plate spacer, expandable roller with roller spacer, sieving screen and fixed divergent rollers were selected as the priority. These results showed that FAHP eliminating weak probabilities improved the decision-making ability.

Analysis of important energy indices in cotton cultivation is includes all stages in seed production of cotton seed from the stage of seed bed preparation until after harvest (cotton seed cracking). In Iran, up to harvesting studies have been done in conventional tillage method, and no research has been done from seed preparation till post harvest stage in different tillage methods. In this study was investigated the amount of energy consumed from seed bed stage to post harvest stage (seed cracking) in different tillage methods. Tillage treatments that were divided by reduction in energy consumption included conventional tillage (CT), low tillage(RT), minimum tillage (MT) and no tillage (direct planting) that were evaluated in a completely randomized block design. The results showed that conventional tillage with average yield of 3636.4 kg/ha had the highest yield and tillage treatment with average yield of 1753.3 kg/ha had the least amount of cotton yield. The results of this study showed that conventional tillage had the highest energy consumption (38942.44 MJ/ha) and no tillage treatment had the lowest energy consumption (32063.02 MJ/ha). The highest direct energy consumption were in conventional tillage method (19302.99 MJ/ha) and the no tillage method had the lowest direct energy consumption (12423.57 MJ/ha). The highest direct energy consumption was related to irrigation input and then fuel consumption respectively with 5850 and 4704.4 MJ/ha. The total amount of indirect energy consumed, including pesticides and fertilizers, was calculated to be 19639.45 MJ/ha. The highest Energy Ratio and energy Productivity were obtained in conventional tillage respectively values of 1.99 MJ/MJ and 0.09 kg/MJ and the lowest values were obtained in no tillage respectively with 1.17 MJ/MJ and 0.05 kg/MJ. According to the results of researches and the higher Energy Ratio and energy Productivity in conventional tillage method, this method can be recommended as a tillage method in this area.

Counting the number of objects using image processing is very important in many aspects from medical science and biology to agronomy, genetic study and plant breeding. Although many studies were implemented for detecting the objects in image processing but the counting objects is easier and faster than recognition, because in some cases, an object can be counted and not be detected. In this study, a new algorithm is presented to count the granular objects without detection and recognition. This method can work correctly in despite of some noise in image. Presented method is based on distance-transform and because of this, the results almost are independent on size and depend on shape of objects and in other hand this method is relatively simple and fast. The other strength of this method is to use from detected edges. Not only perfect edge is not needed but also even one pixel from edge in some cases can be effective for counting correctly. The sharper edges are more helpful in this method. This is a good combination of detecting edge and using shape and size to count correctly. The results showed that in all of conditions, ideal or natural, the proposed method was better than the other investigated methods. Some of investigated methods were implemented only in special condition or special shape of objects but results showed that our method is capable in all of the investigated conditions. Disadvantage of this method is that it does not work on star shape objects unless changes to convex shape with morphological transforms. In spite of the good results, sharp edges and a good binary image of objects guarantee an acceptable counting result. The presented segmented image as graphical output is a valuable instrument for object recognition in machine vision systems. This method is recommended for counting plant seeds, especially convex seeds.

Optimal design for sourcing, grading and other post-harvest operations requires the availability of appropriate information about their physical properties. Also, achieving a high quality product requires the fight against weeds and impurities in the product. Therefore, in this research, some physical properties of wheat and barley were measured. A gravity separator was also used to separate the barley in the wheat mass. This machine has five customizable parameters includes air velocity, frequency of oscillation, amplitude of oscillation, longitudinal slope and latitudinal slope of the table. The effect of these parameters was investigated in the form of two factorial experiments in a completely randomized design to achieve maximum separation of barley from wheat mass. The results of experiments showed that in the conditions of air velocity of 6.75 m / s, the oscillation amplitudes of 5 mm, the longitudinal slope of 2.5 degree, the latitudinal slope 0.75 degree and the frequency of oscillation of 395 cycl / min, the maximum separation of barley from wheat mass to 20.6 % was achieved. In most cases, with increasing latitudinal slope from 0.75 degree to 2.52 degree , the longitudinal slope of the table from 2.5 degree to 4.5 degree and with the increase of the frequency up to 435 cycl / min, the separation of barley from the mass of wheat decreases. Also, the minimum amount of barley separation from wheat mass in condition of oscillation frequency of 455 cycl / min, l o n g i t u d i n a l slope of 4.5 degree, latitud in a l lope of 1.5 degree, oscillation a mplitude of 5 mm and air velocity of 6 m/s was obtained 9.417 %.

Camelina sativa L. is from the family of Brassicaceae, new oilseed crops, has desirable agronomic characteristics, adapted to temperate climates and as raw material for biodiesel production. In order to evaluate the effect of bio-fertilizer and chemical fertilizer on yield and some characteristics of biodiesel from Camelina sativa L., field experiment with three replications during 2017 in a field located in Kazeroun, a factorial in a randomized complete block design was applied. Treatments biofertilizerBarvar 2 containing phosphate solubilityenhancing bacteria (bacteria Pseudomonas putida Strain 13P and Strain 5P agglomerans Pantoea) as the first factor in 2 levels (consuming and not consuming) and chemical fertilizer as the second factor included control treatments, nitrogen fertilizers, phosphorus, sulfur alone and two values were recommended at the considered levels (200, 50 and 100 kg / ha, respectively) and 30% lower than recommended levels. Camelina sativa L. by creating conditions for plant nutrition, grain yield, oil percentage, oil yield and protein content lso, biodiesel characteristics including density, iodine number and saponification number and percentage of sulfur were studied. The results showed that grain yield and oil yield were higher in fertilizer phosphorus nitrogen than in other treatments. Sulfur chemical treatments had the highest increase in seed oil and protein content without using biofertilizers and nitrogen + phosphorous + sulfur without fertilizer application, respectively. The highest density, iodine number and saponification number and percentage of sulfur (0.9248 kg / m3, 26.94 mg iodine per 100 g oil and 227.1 mg sodium hydroxide per gram of oil and 0.027 % by weight) The production of biodiesel was carried out under nitrogen and phosphorus treatments, as well as bio fertilizer and sulfur treatment, and nitrogen + sulfur and phosphorus treatments were optimum without using bio fertilizer. In general, the results of this study showed that the application of biological fertilizers with chemical fertilizers improves the oil and biodiesel characteristics of whole grains is Camelina sativa L.

Dimensions, shape and mechanical properties for the design of agricultural machinery for separation, harvesting and classification are important. The neural network as one of the main components of computational intelligence has important properties and wavelet transformation improves the accuracy of the model. In Research, by horizontal position of almonds, power failure, static brain, three varieties of almond named Mamaee, Rabie and Shahrood 12, in three levels of moisture (5.5%, 15% and 25% wb) and three speed loading (5,15 and 25 millimeters per minute) were determined. In the neural network, input parameters including three levels of humidity and three levels of speed as an independent variable were introduced into the model. The variables of fracture force, energy consumption and modulus of elasticity were considered as dependent variables of the model output. For more precision, various wave-lets such as Haar, db4, Sym2, Coif4 were first applied to these data. The R-criteria was used to evaluate the accuracy of the model. The cross validation results indicated the superiority of the Coif4 wavelet. In this algorithm, a feed forward network with a Levenberg-Marquardt algorithm with a sigmoid tangent function in the hidden layer and a linear function in the output layer were used. The results show the high accuracy of the neural network-wavelet. For the mamaee Variaty neural network with an arrangement of 1-5-2 with R = 0.9523, the arrangement 1-7-2 with R = 0.9745 and the arrangement of 1-4-2 with R = 0.8374 the best prediction for the modulus Elasticity has the power of failure and energy consumption. The R-criteria was used to evaluate the accuracy of the model. The cross validation results indicated the superiority of the Coif4 wavelet. In this algorithm, a feed forward network with a Levenberg-Marquardt algorithm with a sigmoid tangent function in the hidden layer and a linear function in the output layer were used. The results show the high accuracy of the neural network-wavelet.