نشریه مکانیزاسیون کشاورزی
سال پنجم شماره 1 (بهار 1399)

 Harvesting is one of the most difficult and important stages of crop production. In this regard, 49 combine harvesters including conventional combines JD 955, JD 1055, CLASS-S 68 and NEW Holland TC 5080 were investigated in wheat farms in 5 cities of Ardabil provinces, during 2018. The measured parameters were preharvesting yield losses  and the losses at different sections of combine harvester such as cutting unit, threshing and separation unit, and storage tank, and also MOG percentage. The results showed that there was a significant difference between the harvesters in terms of losses and field capacity at the level of 1%. The highest effective field capacity was for NEW Holland TC 5080 combine with 1.16 ha hr-1 where the lowest losses with 0.99 percent belonged to the same. Head grain losses in John Dear, CLASS-S 68 and NEW Holland TC 5080 combines were about 68.5, 65.2 and 90 percent, respectively. Cutting platform losses in John Dear, CLASS-S 68 Combine and NEW Holland TC 5080 were 1.41, 1.64 and 0.99 percent, respectively. Processing losses in John Dear and Class combines were 0.67% and 0.87%, respectively, where it was only 0.04% for New Holland 5080 TC. The highest total losses were 2.51 percent obtained for CLASS-S 68 combine with 0.78 ha hr-1 field capacity. Useful quality losses were 0.52, 1.03, and 1.14%, respectively, for New Holland 5080 TC, John Dear and Class combines, respectively. In overall, the natural preharvesting losses rate was 3.74% and the average total losses for all combine harvesters was 1.94%. According to the results, in general it is recommended to use JD955 and TC5080 combine harvesters due to their low losses, acceptable wheat grain purity percentage and suitable field capacity.

 Optimal energy management in agricultural systems and the emission of greenhouse gases from agricultural activities is one of the topics of interest for researchers around the world. This research has used the field method to collect and record data in the form of interviews and questionnaires. Optimization of energy consumption and modeling of energy consumption for the production of these products were performed using artificial neural networks and data envelopment analysis. DEA-SOLVER and EMS13 software were used for analysis and farms were evaluated in terms of energy consumption and production performance. The results showed that the average energy per hectare of rapeseed, wheat and coriander is about 984375, 1338762 and 626771 MJ per hectare, respectively. In rapeseed and wheat crops, respectively 57.66% and 72.92% of energy input, belonged to chemical fertilizers, especially nitrogen fertilizer, and in coriander, chemical toxins input had the highest share in energy input with 68.01%. Energy ratio index for products was 0.60, 0.91 and 0.50, respectively. As a result, the share of indirect energy was high in all products due to the use of chemical fertilizers and chemical toxins. The amount of technical efficiency, net technical efficiency and scale efficiency in rapeseed fields were estimated to be 0.89, 94 and 0.96, respectively. After chemical fertilizer, energy stored by fuel inputs with 15.98%, chemical toxins with 4.02% and seeds with 2.02% of total stored energy, after chemical fertilizer in the second to third ranks for they had the optimization of input energy.

 Chickpea is one of the legumes that have different nutritional uses. It is important to identify different chickpea varieties. For this reason, the aim of the present study was to develop a computer vision system to identify three similar chickpea varieties, namely, Adel, Arman and Azad using different artificial neural network hybrids including hybrid ANN- DE, hybrid ANN- CA, hybrid ANN-BA and hybrid ANN- ICA. In order to perform the segmentation, the image was first converted to YCbCr color space, and chickpeas were isolated from the background. Then, different properties were extracted in two color and texture areas based on gray surface co-occurrence matrix (GLCM). The YCBCR, YIQ, CMY, HSV and HSI color spaces were also extracted. Textural properties are extracted using the gray-area coherent matrix based on the position of the pixels of equal value. The multilayer perceptron artificial neural network divides the whole data into three categories data for training, the data for validation, and the third data for testing. Result showed that in all three classifications, the area under the curve for the correct class is lower than for the others, which means that the classifiers did not correctly identify the examples for this class and there is probably a high degree of sharing of selective affective properties between Adel, Arman and Azad classes. All classifiers have acceptable performance. Comparing the values of the classifier parameters, it can be seen that hybrid ANN-CA has higher values than the other classifiers, so it can be concluded that this classifier performs better than the other two classifiers. The results showed that the correct detection rates of hybrid ANN-CA, hybrid ANN-BA and hybrid ANN-ICA were 98.92, 99.46 and 92.92, respectively.

Adulteration, especially industrial type, is caused by the direct addition of natural or fermented syrups to honey. In this study, fennel honey was supplied from beekeepers located in Kangavar city.After ensuring the authenticity of honey, 39 samples of counterfeit honey were prepared by adding and stirring sucrose, fructose and a combination of 0.9 fructose-glucose syrups in natural honey at different levels of 0 to 100 wt%.Different samples were dissolved in water and their images were recorded using a camera.In order to process the images in each 33 monochrome channels, 15 parameters (495 parameters in total) were measured.  Few parameters were selected by sensitivity analysis using ANFIS fuzzy neural inference network, ANN artificial neural network and RSM response level. The explanation coefficient of the presented models for water-soluble samples was 0.9512, 0.9882 and 0.9904, respectively.Considering all the statistical error valuesof the RSM model, it was introduced as the best model to determine the amount of honey fraud in this method by the desirability function.

 Producing any dried product with acceptable quality is one of the main processes in the postharvest engineering. Several researchers reported the high quality of the product dried with new drying methods such as combined infrared-convectional drying methods compared with ones dried with convectional dryers. Evaluation of drying method and their effects on dried product could increase the quality of the final product and be used in designing and engineering of dryers. In this research, a constructed combined infrared-convectional dryer was evaluated at the various drying temperatures for banana slices with various thicknesses at the constant air temperature. The experiments were performed to calculate the values for effective moisture diffusivity, shrinkage percentage, and rehydration ability of banana slices. The drying duration of the slices with a thickness of 4 mm was 83 min at the infrared drying temperature of 75 °C, the air velocity of 0.7 ms-1 and the air temperature of 50°C. The effective moisture diffusivity was varied from 5.81×10-10 to 2.14×10-9 m2 s-1; as a function of drying temperature and slices thickness. The results indicated that the effect of slice thickness was significant on the rehydration ability of dried products. The drying temperature and the slice thickness had no significant effect on the shrinkage of the slices. This property was increased linearly as a function of moisture content. Therefore, it is not essential to consider the shrinkage as a function of temperature and thickness during the simulation process.

There are several factors affecting the combine harvester losses, the most important of which is the operation of the combine cutting bar, which affects the front and rear losses of the  harvester. The performance of a cutting bar is affected by the forward speed, reel speed, cutting height, product moisture, type of product, etc. In this study the effect of kinematic index and reel height was stutied on the combine header losses. The treatments was tested in the form of factorial experiment with a completely randomized design. The results showed that the effect of height and kinematic index on the total loss of the head at the level of 1 percent is significant. The highest loss was related to the highest kinematic index of 3.83 and about 8.3%. Regarding the total loss of the cluster, the main effects of reel height and kinematic index on the losses of the cluster and their interaction were significant at the level of 1 percent. Regard to grain loss, the results showed that the main effects were significant at the level of 1% probability and the interactions were significant only on the left side of the head and the total grain loss.

The use of thermo-compressors to increase the steam enthalpy in agricultural processing plants can improve productivity by upgrading the mechanization and also increase the value added of the final product. The simple construction, low cost, and simple mounting were enhanced using this equipment in relevant fields of industry and agriculture-mechanization. In this study, the various levels of motive steam pressure effect on the performance, vorticity development, and turbulent kinetic energy were investigated. Performance curves for various inlet flows were extracted and evaluated. Regarding the high potential of vorticity creation in the nozzle outlet, the suction section, and the wall vicinity were evaluated. In the following, the turbulent kinetic energy contours in the various motive pressures were assessed. Also, pressure and temperature diagrams along the longitudinal line of the thermo-compressor were presented to illustrate the increase in enthalpy. Finally, considering the results of the performance curve, turbulent energy contours, and vectors evaluation, P=15 bars present the best performance between the evaluated motive steams.

 In recent decades many studies have been conducted on the impact of magnetic waves on living organisms. The phenolic compounds are one of the largest groups of secondary metabolites that are widely distributed in plants, and the biologic activity and diverse pharmacology of these compounds have been reported in many studies. In this study, okra fruits were arranged in order to be exposed to the magnetic field. The samples were tested in three repetitions, three times (3, 6, 9 min) and three fields (0.2, 0.4, 0.6 mT). To measure total phenol and total flavonoids, 0.5 g of each sample was beaten with 5 ml of 80% methanol (1 to 10 ratio) and homogenized in a cold mortar. After assimilation, the material was placed on a shaker for 24 hours in a dark place and then centrifuged at 3000 rpm for 5 minutes. The results showed that the magnetic field had different effects on the quality of the two properties. Compared with the control treatment, increasing the magnetic field, increased the amount of phenol from 2.759 to 2.932 mgGUEg-1 significantly,  while the flavonoid content decreased significantly from 0.821 to 0.0895 mgGUE g -1.

 Fruit packaging is an essential factor in reducing the mechanical damages caused by transportation. Accurate information on the transportation status of any region helps packaging designers to reproduce a more precise simulation of the existing conditions. This study was aimed to analyze the vibration acceleration of truck beds during transportation on local roads. For this, a wireless sensor network combined of three sensor nodes with a tri-axial accelerometer was used to measure the instant acceleration on the front and rear bed of the trucks equipped with leaf-spring suspensions. Acceleration values were three-dimensionally received by the sink node and recorded in a laptop. The average power spectral density (PSD) levels were computed for the local roads. Increasing the speed from 70 to 90 km/h increased the maximum PSD from 0.193 to 0.340 G2/Hz. Compared to the ASTM 4728 standard, the PSD levels of the trucks with spring suspension on local roads were higher in 1 to 35 Hz and lower in 35 to 200 Hz. The highest PSD values ​​occurred at frequencies below 6 Hz and the frequency range of 3-4 Hz was determined as the predominant frequency on local roads. The average RMSG values in the vertical direction were 0.654 G for heavy trucks. In this study, the effects of road type, speed, direction, and location of package on vibration level were also discussed in detail. The findings can be applied to simulate the realistic transportation modes of the packaged fruit in lab-programmable-vibration tables.

Disposal of agricultural waste and livestock manure in the environment can cause pollution. Annually, a very large volume of animal waste and various types of agricultural wastes is produced, which could be considered as a potential for biogas production. Such an energy production causes proper disposal of waste and reduce pollution. Therefore, in this study, biogas production from the combination of livestock manure and pumpkin waste was investigated. Pumpkin is produced solely to extract its seeds and most of the product is useless and disposed of as waste. The experiments were performed using three ratios of pumpkin waste to cow manure (10:90, 20:80, 30:70) at two different concentrations (1:1 and 1:2 combination of the waste with water) in 1 liter batch reactors. To optimize the process, the response surface methodology (RSM) and full factorial experiment in three replications were used. Design Expert 12 software was used to analyze the experimental data. The results showed that the effect of waste concentration on the amount of produced biogas and the effect of composition ratio are significant at the level of 1% and 5% probability, respectively, but their interaction is not significant. The relationship between biogas production with feed concentration variables and composition ratios was presented in the form of a regression equation. The ratio of 10:90 and the feed concentration with the ratio of 1:2 were determined as the optimal feed, which lead to the maximum production of biogas at the amount of 93.5267 ml/day.

 The soil compaction is one of the main reasons of destructing the soil which caused in changing the soil structure, limitation of air and water penetration and lower level of penetration of the root in the soil. The purpose of this study is to determine the suitable soil compaction for melon, watermelon and cucumber. The independent factor including the cultivation type in two levels of Confined Compression Test (CCT), Plate Sinkage Test and Uniaxial confined compression Test (CCT + PST) for three mentioned agricultural was considered. There were two moisture content levels of 15% and 17.5% and four levels of density including 1.3, 1.4, 1.5 and 1.6 (gr/ cm–3) used for these products. Some parameters such as germination timing (day), stem length (mm), root length (mm) and seedling weight with the regular root in the soil (gram) were measured and investigated. The results revealed that the root lengths at the cultivation type of (CCT) in every three products were more than the root length of the cultivation type of (PST + CCT). Also there were better results for cultivation type of (PST + CCT) for some variables such as stem length and germination day for all studied products by his special cultivation type.

One of the most time-consuming and difficult stages of crop production is the harvesting stage, that almost more product losses occur at this stage. Adjustments are very important in increasing the efficiency of grain combine harvesters and subsequently decreasing product loss. However, good adjustments require the identification of the components of the harvester, quantifying the losses in these components. In this research, a model has been developed to measure the rear losses of combine harvester (total threshing and separation losses) based on machine parameters. In this research, the effects of different levels of forward speed (3, 4 and 5 km/h), cylinder rotating speed (1100, 1200 and 1300 rpm) and fan speed (600, 700 and 800 rpm) on rear losses of combine harvester in three replications were investigated. A factorial experiment based on a randomized complete block design generally results of ANOVA showed that the travel speed, cylinder rotating speed and fan speed had significant effect on rear loss. Multivariate linear regression was used to make model and determine the relationship between rear loss and investigated parameters. The results of the regression model analysis showed that there was a good fitting between the rear loss and the parameters at the probability level of 1 or 5%. In other words, this model can be used for prediction of combine harvester rear loss under different operational conditions. The coefficient determination of model was obtained 0.85, which shows that a significant part of the rear loss of combine harvester is justified by the three parameters examined in this study.