Journal of Researches in Mechanics of Agricultural Machinery

Abstract The use of medicinal plants has been considered these days due to fewer side effects than
chemical and combined drugs. Extraction is one of the most important stages of post-harvest
processing in medicinal plants. The first step in preparing the extract is the drying operation.
Therefore, choosing the best method and applying the most suitable conditions for drying a
product is important. Therefore, this study aims to use a new method of combined hotmicrowave air dryer in drying licorice root and its effect on the glycyrrhizic acid content of
the extract. The experiments were designed using the response surface method, and the
amount of glycyrrhizic acid was estimated using high-performance liquid chromatography
(HPLC). The results show that with increasing power from 180 to 360 watts, glycyrrhizic acid
has increased and reached 14.03 mg/g dry weight. Also, at 40 °C, the amount of glycyrrhizic
acid equals 12.81 mg/g dry weight; at 50 °C, this amount equals 14.03 mg/g dry weight; then
at 60 °C it equals 68. It reaches 14 mg/g dry weight. In other words, the amount of licorice
root active ingredient has increased with increasing microwave power intensity and increasing
temperature. However, after exceeding a threshold, increasing these two variables has reduced
the amount of glycyrrhizic acid. The study and modelling of licorice root drying kinetics
showed that the relation of Page's model, with a coefficient of determination of 0.99 and a
square value of 0.025, has the best agreement with the experimental data related to the drying
process. In this study, the amount of glycyrrhizic acid at the oven's drying temperature of 60
degrees Celsius has reached its maximum value equal to 15.54 mg/g.

Abstract In this research, the design, static analysis, and manufacturing of a platform for tractors with a power range of 40 to 60 hp and max weight of 2450 kg was performed. This platform includes the main chassis, steering column chassis, right and left fenders, rollover protection structure (ROPS), and other connecting parts. The main chassis was designed to include all the levers and control pedals, the driver's seat, the dashboard, and the steering system. The ROPS is mounted on the main chassis and is used to protect the driver in the event of a tractor overturning. The platform was designed with ST37 alloy steel for the chassis set and ST44 for ROPS using CATIA software, tested in accordance with ISO 5700 standard for static loading and mechanical strength. Maximum static stress obtained in ROPS compared to the final strength of ST44 steel (580 MPa, and with dimensions of 6×8 mm and thickness of 4 mm) for tractors RK404-A (Paddy/Garden model) and RK604-A (Garden/Farm model) was in the safe range and has sufficient strength. Also, ROPS in the maximum deflection during loadings did not enter the safe area of the driver. Technical knowledge of designed parts (2d and 3d drawings) was extracted and the parts were manufactured, assembled, and evaluated. The final results showed that the designed and manufactured platform with specific dimensions, material, and weight (209 kg) in terms of dimensions, mechanical strength, the place for installing pedals and control systems, and appearance is suitable to use in the production of tractors with a maximum weight of 2450 kg.

Abstract Manual harvesting bell peppers as a greenhouse product is time-consuming and has high labor costs. Various two-dimensional machine vision systems have been developed for the robotic harvest of this product. Due to the complex environment of the greenhouse, high density of branches and leaves, the presence of pests and diseases and sunburn, non-uniform and variable light conditions, and asynchronous maturation of the crop lead to non-uniformity in color. Therefore, harvesting colored sweet peppers are also associated with challenges in addition to green sweet peppers. The aim of this study is to recognize sweet peppers in the point cloud model based on the Fast Point Features Histogram (FPFH) descriptor, and machine learning. Kinect V2 sensor was used to record depth images. After creating a 3-D model, geometric features (FPFH) were used for classification, and H color channel was used to create supervision in 9 classification models on 15 3-D color peppers models supervised. According to the F1-Score criteria, the area under the roc curve, and the accuracy of the algorithm, the K-nearest neighbor classifier model was selected as the best model. To evaluate the KNN algorithm, 15 3D models of red, orange and yellow pepper were performed and finally, they were counted manually. The results showed that the value of F1-Score was higher than 0.7 in all cases, except for one case, the area under the roc curve was higher than 0.8 in all cases and the accuracy of the classification algorithm was higher than 0.9 in all cases. In addition, the human evaluation results showed that the minimum recognition accuracy is 71.42%, and the maximum is 100%.

Abstract The main objective of this study is the economic analysis of using transplanting machines in rice fields. For this purpose, the technical efficiency and the technological gap ratio of farmers who have performed transplanting operation with the traditional method were compared with farmers who have used modern methods for transplanting. The stochastic nonparametric envelopment of data (StoNED) was used to calculate the technical efficiency. The required data were obtained from 531 farmers by using cluster sampling method proportional to the size of the population and by completing a questionnaire. The results of estimating the technical efficiency of the frontier function showed that it is possible to increase production by using the current amount of input and the available level of technology. This is a point of hope for agricultural policymakers. Because by intragroup transferring the correct patterns and techniques of using inputs, rice production can be increased. The results of technical efficiency based on metafrontier function showed that paddy farmers who used the modern planting system had better technical performance. The results of technical efficiency based on the metafrontier function showed that the paddy farmers who used the modern planting system had better technical performance. In addition, the results of the technological gap ratio showed that in all the surveyed farms, farmers who used modern methods for rice transplanting also had a higher technological gap ratio. According to the results, farmers can increase their production by buying modern machinery cooperatively. The government can also take steps to increase production and move towards self-sufficiency through incentive mechanisms such as low-interest facilities for farmers or cooperatives to purchase modern machinery.

Abstract In the present study, in order to improve the planting quality of the corn planter, a new multi-slot rotor metering device was manufactured and evaluated in the field. The corn planter was tested in the farm after fabricating and assembling the metering device parts. The planter was contained two planting units, one of which was equipped with a pneumatic metering device as a control unit and the other unit was equipped with a new multi-slot rotor metering device. Experiments were performed as a randomized complete block design and experimental treatments were three levels of forward speed (3, 4 and 5 km h-1) and three levels of slot’s mouth angle of this metering device (23°, 25° and 27°) each with three replications. The traits measured in this study were miss-planting index, multi-planting index, precision index, index of feed quality and coefficient of variation which were measured and compared for both planting units. The results showed that the multi-slot rotor metering device could improve the miss-planting index, so that using a multi-slot rotor metering device in comparison with the pneumatic metering device reduced the miss-planting index by 26.28%. However, the difference between the measured values for other traits was not significant at the 5% probability level for the two metering device. Finally, the optimal value of the mouth angle of the new multi-slot rotor metering device was determined using the response surface methodology as 25°. In this study, a model with determination coefficient of 0.94 was also presented to predict the solids volumetric flow rate of metering device based on slot’s mouth angle and the angular velocity of metering device feed shaft. The model prediction error was in the range of ±12% and the root mean square error of model was obtained as 140 mm3 min-1.

Abstract The precision agriculture is one of the best ways to carry out mechanized operations to conserve natural and economic resources. By achieving to this important issue, utilizing a variety of sensors, various hydraulic, electronic and mechanical technologies in agricultural machinery. Control and planning to apply the variable rate application (VRA) 1, especially by solving the problem of required power supply will be provided, on the other hand, the expansion of supplying electricity energy due to easier transmission, high efficiency and intelligent planning capabilities in various industries, especially automotive industry, during a few recent decades show the necessity of its entrance to tractors and agricultural machineries, but the type and amount of electrical power avaliable in tractors is the main limiting factor. In this research, with an overview of the methods of supplying electricity to agricultural tools agricultural equipment, a new method was tested to supply the vibration of an electric vibrating subsoiler. which is based on the design of a DC inverter is with a power input from the tractor battery, which according to it, a pulse width modulation and a potentiometer are responsible for applying the appropriate speed for electromotor and variable vibration frequency, and the subsoiler vibration system frequencies (zero frequency: F1 frequency +18: F2, -18: F3, +36: F4 and -36: F5) was provided with required power up to 1 kW. The results of tillage indicators of a rotary vibrating subsoiler with electricity energy showed that the effect of vibration frequency levels on the draft force and the reduction of the clod mean weight diameter has significant at the level of 5%, so electrifying the agricultural equipment can improve their performance and power supply with inverter design in addition to simplicity and cost reduction, the power supply feature independent of tractor engine speed is very important and efficient for precision agriculture.

Abstract Efficient detection of estrus is a permanent challenge for successful reproductive performance in dairy cattle. At present, in most parts of the world, estrus detection is done with observational basis, which has low productivity and causes great losses to this industry. Among the methods used to automatically detect estrus the electronic nose can be used to detect estrus from milk based on its odor due to advantages such as high speed, low operating cost and low manufacturing cost. In this study, an electronic nose system consisting of 7 metal oxide semiconductor (MOS) sensors was used to detect and predict the time of estrus. In this study, milk of 34 cows was sampled for 30 days in the Livestock of the University of Tehran in Karaj-Mohammadshahr and was tested on the same day, 26 of them showed signs of estrus and thus were examined for analysis. The system was analyzed along with pattern recognition methods such as Principal component analysis (PCA), Linear discriminant analysis (LDA), and Artificial neural network (ANN). At first, the feature vector was extracted from the response signal of the sensors and after sorting and classification, it was used as the input of pattern recognition methods. The results of pattern recognition methods were obtained as (94%) for principal component analysis, (86.33%) for Linear discriminant analysis, and (91.80%) for artificial neural network. The results showed well that the electronic nose system is a very efficient and fast way to classify and separate the different stages of the estrous cycle, particularly estrus stage.

Abstract The agricultural industry produces about 10-12% of the world's greenhouse gases. studying the energy use in agriculture systems can be effective in optimizing energy consumption and reducing environmental pollution. This study was performed to evaluate the environmental indicators of okra production by the ReCiPe 2016 method in Monoculture, intercropping with cucumber and date palm agroforestry systems in Khuzestan province. This research was carried out in the cropping seasons 2020-2021. The system boundary of the research is from planting to harvesting okra in its cultivation systems. Collected information included all inputs used such as fertilizers, pesticides, Agricultural machinery, human labor, and fuel consumption. The studied method is ReCiPe 2016 environmental indicators. This method includes the end point of damage to human health, ecosystems, and resources, as well as midpoint indicators such as global warming and ozone depletion. The results showed that intercropping of okra and cucumber has higher environmental destructive effects due to the use of higher chemical and plastic inputs than monoculture and agroforestry (17.15 and 79.10 respectively). Nitrogen fertilizer, phosphate, and fuel consumption along with plastic are the most effective inputs in environmental indicators. Eco-efficiency index also showed that okra and date agroforestry have a significant advantage over monoculture and intercropping. Therefore, considering the higher performance of intercropping system compared to monoculture, it is recommended to optimize its high-use inputs. Also in areas of Khuzestan province where there is a possibility of agroforestry, this type of cultivation is recommended due to its lower environmental pollution.

Abstract Biodiesel is known as a chemically modified and environmentally friendly, renewable, non-toxic, biodegradable and safe fuel that is mainly used in compression combustion engines. The aim of this study is the feasibility of producing biodiesel from waste kitchen oil using the ultrasonic system and finally evaluating the produced fuel. In this study, the effect of molar ratio of alcohol to oil, weight percentage of catalyst and reaction time on methyl ester production efficiency was investigated. Optimum conditions using response surface method for biodiesel production included molar ratio of 8.30, catalyst percentage of 5.32 and reaction time of 33.23 minutes. Also, the results obtained from the evaluation of biodiesel fuel produced in a diesel generator engine ,showed that by increasing the amount of biodiesel in the fuel input to the engine, CO emissions have decreased by 0.026%, and the level of engine exhaust smoke has decreased by 22%, and NOx has increased to 513 ppm. The increase in the percentage of biodiesel also increased the specific braking power by 46.5 kW and led to an increase of 91 g/kWh in the specific consumption of brake fuel and on the other hand, it led to a decrease of 87 Nm in braking torque.

Abstract Eggs are a widely consumed material that can endanger people's health due to their high perishability. Therefore, detecting its freshness is very important for the food industry. Several nondestructive methods have been proposed to measure the internal quality of eggs, and in this research, an acoustic system was used to detect egg freshness. The samples were kept at room temperature for 16 days. A 45 cm long inclined surface with a 4 mm high step in the middle was used in the mentioned system. The sound resulting from the rolling of the samples and the impact caused by passing the step were recorded by a microphone. Then, the fractal dimension of sound signals was calculated using Higuchi and Katz methods. A destructive test was also done considering the Haugh unit and the eggs were divided into two groups AA and A+B in terms of freshness. The results of the three classification methods of artificial neural network (ANN), support vector machine (SVM) and linear diagnostic analysis (LDA) showed that the SVM method has better efficiency compared to the other two methods. The average classification accuracy of test data in the SVM method for Katz fractal dimension and window length of 25 milliseconds was obtained as 78.07%.