Iranian Journal of Biosystems Engineering
Year:2018 | Volume:49 | Issue:3 |Papers Count:16

One of the important soil properties, which is related to the soil-plant relationship, is soil compaction. The aim of this study is to investigate the spatial variations of soil compaction using different Geostatistic methods, affected by conservation tillage. To evaluating the Geostatistic, soil samples were taken for regular grid of 10 × 10 meters in 117 points. The area of study was a 1. 2 hectare land in Agricultural Research Center located in the vicinity of Mashhad in Khorasan Razavi province, the soil cone index was measured at the depth of 0-35 cm. After Geostatistic analysis and semivariogram for estimating variables using the kriging methods (EBK) and Deterministic interpolation methods in GS + and Arc (GIS). Criteria for evaluation in this research are the values of root mean square error (RMSE), mean error (ME), using the cross-validation method. The results showed that the empirical Bayesian kriging methods (EBK) and Ordinary Kriging (OK) are the best model to estimate soil compaction region.

Simulation and Static and Fatigue Analysis of Cross Bar of Moldboard Plough by Finite Element Method (FEM)Frequent failures of mechanical components in machines and equipment due to exerted loads reveal the importance of optimizing or redesign the components. Practically, crossbar of moldboard plough is frequently failed in pin joints or deformed in support points. In this research, stress analysis of the crossbar was conducted by finite element method. After drawing the three-dimensional model in SolidWorks Software and transferring to ANSYS Software, the constraints and boundary conditions were applied on the model and the piece was loaded. Then the static and fatigue analyses were done on the model. To estimate the exerted forces on the crossbar, the maximum draft forces of Massey Ferguson 285 and 299 Tractors were considered. The results of static analysis showed the higher probability of failure at the left pin junction. The safety factor in fatigue analysis showed the higher probability of fatigue failure in left hole of crossbar. The safety factor in fatigue analysis of cross bar of moldboard plough during pulled by Massey Ferguson 285 and 299 Tractor was 1. 67 and 1. 677, respectively.

Nowadays, the growth of in-vehicle and off-road vehicle technology is significant and the need to develop its related infrastructure to maximize their capacity for land, sea and air transportation is essential and unavoidable. It is time consuming and costly to monitoring the environment in water, earth and air conditions for a safe operation, without the use of robots. With automatic monitoring, operations can be performed with the least error and 24 hours a day. So the purpose of this research is to develop and evaluate a composite algorithm for navigating an off-road vehicle (Surface Vehicle) and compare it with the results obtained from computer simulations, to check the accuracy of this algorithm. This robot boat is designed and developed for hydrographic construction could navigate and perform hydrographic operations around the clock and fully autonomous without any supervision. Comparison between experimental and simulation results showed that the simulated algorithm had acceptable accuracy and could navigate experimentally. The Standard Deviation (SD) for practical test was below 0. 5 m.

Reduction of tillage operations in conventional systems and its replacement with a reduced tillage and conservation systems is recommended in order to sustainable production in agriculture and preservation of soil and water resources. In this research, the effect of applying three types of conventional tillage machines with different geometry that have less rigidity of soil tillage than conventional tillage machines (Chisel packer, combined tiller and offset disc) on the performance parameters of tillage including Specific draft, specific tillage energy, and weighted average diameter of clods, roughness of soil surface and percent of crop residue on the soil surface. Tillage depth is fixed in 20 cm, forward speed was in three levels (2. 5, 4. 5 and 6 km/h) and tillage machinery type was in three levels. Double Split plot in Randomized Complete Block Design used in the study in which tillage depth (main factor), forward speed (secondary factor) and the tiller type (sub-secondary factor) were the independent variables. The results showed that the amount of residues remaining on the soil surface after soil tillage was negatively correlated with not only special draft but also with other indices (weighted average diameter of clods and roughness of soil surface), and crop residue after soil tillage was applied as a criterion for comparing soil tillage machinery. The results of the comparison of the ranking of treatments based on two methods (amount of crop residues after soil tillage and the Component Analysis method) showed that the combined tiller and the offset disc at low velocity and Chisel packer at high velocity is recommended for conservation systems of tillage.

According to the water crisis in the country and watermelon traditional irrigation process, it is possible to reduce planting and consequently increase the price of this product in the coming years, which highlights the necessity of indices for choosing high-quality watermelons. The purpose of this study is classification of the Charleston Gray watermelon variety into unripe, ripe and overripe classes, in this regard acoustic signals processing, data mining algorithms, and artificial intelligence techniques have been used for this purpose. After preparing the samples, firs through a capacitive microphone, signals acquired from different positions of watermelon using a solenoid and then, samples classes were determined by performing sensory evaluations. Signal processing techniques in time, frequency, processing domains and wavelet transformation were used for extraction of important features from acoustic signals of the watermelons, then some of the features that were significant in classification were selected using the t-test. Support Vector Machines and K Nearest Neighbor algorithms were used for sample classification. Totally 52% of the samples were classified correctly by experts. For metal ball, SVM algorithm with cubic kernel function resulted 78% correctly classification for acoustic signals obtained from middle position and Gaussian kernel function resulted 75% correctly classification for signals obtained from stem side position. K Nearest Neighbor algorithm equipped with the cosine distance resulted highest samples classification with a precision of 79% for the metal ball and the position of the stem side.

Managing the production of greenhouse products requires knowledge of controlling many environmental factors and plant nutrition and fight against pests and plant diseases. Recognition pests and fight against them is one of the most important activities in the process of production of greenhouse products. Pre-knowledge of the demographic density of insect pests is one of the effective methods of pesticides and reduce their levels of use, especially for insect pest control toxins. Wireless Sensor Networking Technologies (WSN) is one of the new technologies used to sense the environment and collect and transmit information to the user or the central station to view and respond appropriately to an occurrence or phenomenon. In this study, the use of WSN in monitoring, timely diagnosis of greenhouse white flies, design and mapping of greenhouse contamination was investigated. For this goal, 3750 images of 15 sticky traps with white flies that attached to Melon greenhouse in Isfahan Agricultural Jihad Research Center were provide and transmitted online using a WSN to a computer located at a distance of 900 meters from the greenhouse. The color images of the sticky traps are acquired by using 15 digital cameras were converted to gray colored images using MATLAB software, then after image classification with Support Vector Machine (SVM) classifier based on their features, are divided into two categories of images: whiteflies affected image and whiteflies unaffected image. After identification of the white flies, number of pests was counted and infection maps of Greenhouse with ArcMap10. 2 software was drawn up. Assessment of the system showed that accuracy of SVM algorithm for categorizing images of sticky traps was 97. 73%, and the average values of statistic parameters of the Confusion matrix for 15 traps including sensitivity, accuracy, specificity and classification accuracy were 98. 46%, 83. 31%, 99. 08% and 97. 72% respectively. The overall accuracy of the system for detection and counting Greenhouse whitefly pests is 97. 71%. The average root mean square error (RMSE) in estimating of the number of white flight by image processing and direct counting was between 1 and 5. 03. Therefore, the system is suitable for detecting and tracing and counting the number of trapped white flies, and it is possible to design appropriate greenhouse poisoning plans to fight this pest.

This study was conducted to investigate and model the energy consumption and greenhouse gas emissions of irrigated chickpea cultivation in Isfahan province using multilayer perceptron artificial neural network (ANN). The amount of each consumed inputs in production were collected from 110 producers of chickpea randomly by a questionnaire. The total energy consumption, product yield and energy ratio in chickpea production were calculated as 33211. 18 MJ/ha, 2276. 36 kg/ha, and 1. 02, respectively. Nitrogen fertilizer with 9808 MJ/ha had the highest amount of consumed energy. Total greenhouse gas (GHG) emissions were calculated 965. 20 kg CO2eq. ha-, in which, electricity and diesel fuel had the highest amount of total GHG emissions with 36% and 34%, respectively. An ANN model with 13-7-2 topology was recognized as the best model for prediction of yield and total GHG emissions. Based on this ANN model, the values of determination coefficient in prediction of yield and total GHG emissions were determined as 0. 929 and 0. 979, respectively. The results of sensitivity analysis of the model showed that agricultural machinery inputs had the highest impact on yield and total GHG emissions.

A practical model including a parameter as a function of drying condition were introduced to predict the effect of far-infrared radiation (FIR) in a combined rough rice drying process. Tests were conducted in three replication for four levels of FIR (0, 0. 1, 0. 2 and 0. 3 Wcm-2) and three levels of inlet air temperature (30, 40 and 500C). The results obtained from the simulation of the proposed model demonstrated that the models were capable satisfactorily express the characteristics of drying rough rice in combined dryer. Also due to the effects of combination of hot air and FIR drying technique on drying rates, cracking enhancement ratio (CER), required breaking energy for grain, specific energy consumption (SEC) and optimal method was presented. Combination of hot air at temperature of 40 0C and FIR at intensity of 1000 W. m-2 is the best way to have lowest SEC and highest grain quality point of view.

In addition to harmful effects on the physical health of people, noise pollution can also create annoyance conditions for those who are exposed to it. Therefore, in addition to evaluating the sound quantity parameters, it is absolutely essential to examine the sound qualitative parameters in the work environment. In this research, the sound qualitative metrics of the HEPCO backhoe loader were evaluated. The acoustic annoyance model of the tested machine was determined using loudness, sharpness and fluctuation strength. The coefficient of determination of acoustic annoyance model and jury test was 0. 93. Also, the acoustic annoyance model from this study was compared with two unbiased and psychoacoustic annoyance models. The results of this comparison showed that the proposed model changes in the gear ratios are not identical with the other two models. Therefore, by measuring the sound of the machine and extracting its quality metrics, it can calculate the acoustic annoyance inside the cabin.

In this study, a two-ring capacitive sensor mountable on multiple-tip horizontal penetrometers has been developed. The size and shape of the electric field around the sensor was estimated to ensure that the sensor fields are not interfered with the adjacent probes of the multiple-tip penetrometer using finite element. The sensor function was then evaluated at different levels of volumetric moisture. The maximum radius of the soil located in the sensor’ s electric field is 30 mm in the wetted soil. So the usage of the sensor in combination with the penetrometers at distance of 10 cm from each other would not cause the interference of the electric fields of the sensors. Increasing volumetric moisture reduces the output voltage of sensor (R2=0. 91). The developed capacitive sensor is a suitable devise for measuring soil moisture in the range of 0-PL which can be used to measure simultaneously resistance and soil moisture in several depths independently in combination with multiple-tip horizontal penetrometers.

The aim of this study was to produce Persian shallot essential oil nano-emulsion containing omega-3 fatty acids by spontaneous emulsification method and obtain the optimum conditions by head space-solid phase microextraction/gas chromatography (HS-SPME/GC) technique and polyaniline (PANI) nano fiber. The effects of four factors including omega 3 percent, surfactant type (TWEEN 20, 80 and caseinate sodium), surfactant-to-oil ratio (SOR 10-300%), and storage time on the encapsulation efficiency and chromatographic characteristics (including total peak area and total peak height) were studied. The Central Composite Design (CCD) was used to design 32 experiments. The effects of factors was considered on the emulsion, and P-value of <0. 05 statistically significant. Desirability function (D) was used for determination of optimum conditions. Results showed that all four factors affected GC chromatogram characteristics, essential oil release and encapsulation efficiency. According to the results at the optimum conditions, the emulsion has the maximum amount of encapsulation and the best release power: Omega 3(75%), Storage Time (57 days), SOR (238%) and Surfactant type (T20). Values of dependent variables at the optimum conditions were obtained: total peak area (534. 9), total peak height (15) and encapsulation efficiency (78. 3 %).

The use of photovoltaic (PV) systems is a useful solution for providing the required pumping power for irrigation of farms and gardens away from the grid (detached from the grid). The design of photovoltaic systems for water pumping completely depends on estimating the plant's water requirement. Because the water needs vary with time during the different irrigation season and solar radiation, performing accurate simulations is essential in order to achieve a successful and desirable design. The purpose of this paper is to provide a method for designing photovoltaic water pumping systems by combination water estimation relations and solar power models. In this study, Karaj station meteorological data during the ten year period (2005-2014) was used to estimate water demand and solar power. The water requirement of different months was estimated using the Penman-Monteith evapotranspiration model. The results showed that the highest water requirement was in July with 70 m3/day. It was estimated that in order to provide the necessary energy for daily pumping of up to 70 m3/day with a height of 30 m and taking into account the pump hydraulic efficiency and the efficiency of other components of the system, the pump with a power of 2200 W, the solar panel capacity of about 3222 W with 22 square meters area would be enough.

Electrohydrodynamic drying as a non-thermal method of drying increases the quality of dried products at ambient temperature. Considering the importance of using advanced methods in date fruit drying, in this study, an electrohydrodynamic-convective dryer equipped with temperature control system was developed to model the drying process of date fruit (cv. Shahani) slices based on changes in moisture ratio per drying time in electrohydrodynamic (EHD), hot air (HA) and the hybrid (EHD-HA) drying methods. Results showed as the air velocity increased, the drying time in 25 and 35 ° C of EHD drying increased while increasing in air velocity, decrease the drying time in both HA and EHD-HA drying methods.

Sugarcane is an important industrial-agricultural crop in country. Considering the high cultivation level of this product in Khuzestan province and the high volume of data stored in these mechanized agricultural units, it is necessary to have a tool to process stored data. The data mining technique is well equipped to provide sugarcane manufacturers with the necessary information and patterns in modeling the yield of sugarcane. One of the most practical of these algorithms is decision trees. The main objective of this research is to predict yield sugarcane and to evaluate the factors affecting it using decision trees CART and CHAID. The present work was an analytical study conducted on a database containing 13211 records. Data were obtained from farms of Amir Kabir Agro-Industry, during 2013-2016. Data analysis was performed using IBM modeler software version 14. 2 by CRISP methodology. The accuracy of decision tree (CART and CHAID) on the training data and test data were 90, 81, 85 and 79 percent, respectively. The results of this research can be used for sugarcane production and cultivation industries in Khuzestan Province in order to evaluate and optimize the sugarcane production process and predict the yield of sugarcane.

Using Combine is the common method to harvest wheat in Iran. Since harvesting operations as the most sensitive stage of production affected by combine harvester performance, therefore investigating the combine harvester performance has a special importance and it’ s necessary to evaluate. In this study, the effect of field and crop conditions on combine harvester performance in wheat harvesting has been investigated. For this purpose, an experiment was conducted in a completely randomized experimental with an unbalanced 2 x 3 factorial designs and covariance analysis using a New Holland combine harvester (TC 5070 model 2014) in Shahid Beheshti’ s agro industry company farms in the town of Dezful, in 2016. Independent factors included three planting patterns (uniform row planting and furrow planting) and three levels of grain moisture contents (6-8, 8-10, 10 12 %), and dependent factors involved field capacity, field efficiency and the losses by combine. Furthermore, yield, percent of lodging and farm length were defined as covariant. The results indicated the effect of planting pattern on combine field capacity, combine field efficiency and combine losses have been significant (p value ≤ 0. 01). The combine field capacity in the farms with uniform row planting pattern was 7. 26 ton ha− 1, while in farms with furrow planting pattern was 6. 73 ton ha− 1. The combine field efficiency in the farms with uniform row planting pattern was 83. 70%, while in farms with furrow planting pattern was 82. 42%. The losses by combine in the farms with uniform row planting pattern was 24. 2 ton ha− 1, while in farms with furrow planting pattern was 23. 7 ton ha− 1.