نشریه مهندسی بیوسیستم ایران
سال پنجاهم شماره 3 (پاییز 1398)

Hearing loss due to harmful sound is one of the most important occupational illnesses. Agricultural mechanization with the use of a variety of machinery causes problems in occupational safety and health for those working in this field. In this study, some of the factors affecting the noise generated by a garden tractor (H.938 Model) were evaluated and predicted. The tests were performed according to international standards of sound such as ISO 5131 and ISO 7216 at different engine speeds, gear positions, road type and microphone distance. The total number of treatment combinations for extracting sound signals released by the garden tractor reached 216 with 72 treatments and three repetitions. The obtained data were analyzed in the form of a factorial test based on a completely random plan. Besides, Artificial Neural Network and ANFIS model was created to predict the sound level in the aforementioned tractor with 216 patterns for training and assessment. The results of the research showed that the effect of the main factors on the level of sound emitted by the garden tractor were significant at probability level of 1%. The results of frequency analysis showed that noise pressure level decreases according to increase in frequency and the sound intensity that reaches the driver's ear is equal to 77.93 dB at the frequency of 4000 Hz. The results of Artificial Neural Network and ANFIS model for forecasting the Sound pressure level of the garden tractor with the highest coefficient of determination (R2) for this research were 99.73 and 99.91, respectively.

Agricultural production systems have a wide and varied range of energy consumption and environmental publications. Therefore, the study of environmental dimensions of any agricultural product is necessary. In this study, an integrated approach was used to assess and evaluate the greenhouse cucumber production process in East-Azarbaijan using life cycle assessment. The boundary of the system included all activities related to the production, transport and consumption of various inputs for the production of greenhouse cucumbers. Regarding the conditions of the study area, which has cold and dry air, information on spring cucumber cultivation was investigated. After collecting basic information, we calculated the life cycle log information (including three parts of consumption inputs, direct and indirect agricultural publications), and after obtaining indirect publications (Publication to Water, Publications to the Air and Publications to the Soil), the amount Pollutants were calculated in greenhouse cucumber production. According to the results of the study, the highest amount of contamination with 2914.81 kg of dichlorobenzene 861 was related to free water poisoning. The depletion of fossil resources with 1500 MJ was the second generation of pollutants, and the potential for global warming with a share of 183 Kg of carbon dioxide was the third largest pollutant.

In this study, a hot air- microwave dryer equipped to imaging system was used for modeling of drying kinetics of strawberry slice. The experiments were conducted at three levels of hot air temperature of 50, 60, and 70  C with 0.5 m/s air velocity as well as three levels of microwave power density of 2.7, 3.5 and 5 W/g with 40 C air temperature. In order to estimate the drying curve, seven different thin layer mathematical drying models were fitted to experimental data and according to the obtained results, Page’s model could satisfactorily describe the drying curve with highest R2 value (0.9945-0.9987) and lowest RMSE (0.0097-0.0213) of microwave data and Logarithmic model could describe the drying curve with highest R2 value (0.9945-0.9987) and lowest RMSE (0.0097-0.0213) of hot air drying data. Also ∆E color kinetic demonstrated that highest color changes were happened in the initial drying stage and remained constant in the other drying stage in microwave and finally the ∆E value changed in any power density near 10. But in hot air drying the color changes occurred progressively during drying process and reached upper than 15.

The automatic detection of plant diseases in the early stages of growth can increase the quality of the final product and prevent the occurrence of permanent damage in large part of farms. Therefore, in this research an intelligent system was designed and developed based on image processing in order to detect and eliminate the disease in the lilium plant leaf, as well as the classification of healthy plants from the unhealthy ones. Accordingly, 20 healthy flowers and 20 unhealthy were evaluated by machine vision system. In order to classify plants, 19 color and morphology parameters of the plant were extracted and the most effective ones (leaf L, leaf a, leaf b, stem L, and stem length) were selected by fuzzy entropy method and these suitable features were grouped by the similarity classifier. As result, the efficiency of the proposed algorithm to diagnose and classify the disease using fuzzy entropy H1, H2 / H3 fuzzy entropy and without applying selection of features method were 96.15, 93.18 and 84.3, respectively.

The highest yield of corn seed is obtained at the best uniformity of their placement distances and density in the field. So, in this study by changing the components of the parameters witch effect on grooved roller metering device designing, it could be able to present a new design of metering device in Solidworks software and built from PTFE material for row-crop corn planting. The laboratory evaluation was done on grease belt in eight level of distance between seeds (8, 9, 10, 11, 12, 13, 14 and 15 cm) which were resulted from number of grooves (three levels) and metering device rotational speeds (eight levels) in 3/5 Km.h-1 forward speed. The multiple index, quality of feed index, miss index, precision index and damaged seeds were considered to evaluate the performance of grooved roller metering device. . By using completely randomized design with three replications in SAS and SPSS software, the results were analyzed. With multiple linear regression, the optimum amount of distance between seeds (11cm) that arose in 105rpm rotational speed of metering devices with 5 grooves.

Musculoskeletal disorders due to inappropriate conditions in sugarcane Agro-Industry in Khuzestan province today are the reason for many human labor injuries in sugarcane fields. The risk of exposure to harmful agents to the musculoskeletal system is evaluated in a variety of ways such as REBA, RULA, QEC and OWAS. The aim of this study was to determine the number of musculoskeletal injuries and ergonomic evaluation of work situation by sugarcane cuttings planting, and harvesting using OWAS method. In this descriptive-analytical study, the workplaces of 20 groups of 10 workers were planted and 100 workers were cutting and harvested. Situations of workers were recorded in different situations. Then they were coded into different parts of the body based on their status according to the method studied and these codes were entered into the table and the final scores were calculated using winOWAS software. The results showed that cuttings harvesting, planting, and harvesting sugarcane were 36.37, 41.67% and 33.33%, respectively, in the most critical situation. The prevalence of musculoskeletal disorders among sugarcane production workers is significant. Based on the results, the main problems of ergonomics are included inappropriate physical condition, lifting and carrying heavy loads and bending of the waist.

In this study, the energy consumption and environmental emissions for cake production were studied using life cycle assessment in Guilan Province. Necessary data using questionnaires and interviews was gathered from 21 factories of cake production. Equivalent energy of inputs and outputs was obtained using coefficients of energy. The results of this study showed that 62670.57 MJ of energy was consumed for the production of one ton of cake. The highest share of energy consumption allocated to natural gas with 30931 MJ. Evaluation of energy indices showed that energy efficiency in the production of cake in Guilan is 0.2872. The results of life cycle assessment showed that in cake production 13099.49 kg CO2 eq.  is released into the air that about 86 percent of that was related to activities outside of the factory and the rest was related to the combustion of natural gas for cooking cake.

The aim of the current study was to investigate the characteristics of sesame oils prepared by cold pressing method. 18 samples of sesame oil were collected and addition to qualitative characteristics, the amount of Cis and trans fatty acid, sterols, sterenes and tocopherols were determined. The results showed that 7 out of 18 samples (about 39%) did not match with the national standard at least for one of the investigated characteristics. The highest non-conformance of the samples related to the amount of tocopherols and sterols. The most important sterol in sesame oil was beta-sitosterol (between 57.7 and 61.9%).The current study showed that samples of sesame oil had the acceptable qualitative specifications, although some of them showed a decrease in tocopherol, which could be due to the use of thermal elements during oil extraction. Therefore, determining the amount of tocopherol is an important indicator to determine the quality of cold pressed oil.

Rice aroma is one of the important features of rice quality which affects its marketability. In this study, an electronic system consisting of six semiconductor metal oxide sensors was used as a non-destructive method for the separation of Iranian rice varieties and a frauded rice sample, which is a kind of common fraud in rice supply. Analysis of PCA with two main components covered 89% of the variance (variation) of the data for five original rice samples. Also, described 96% of the variance of data for four rice samples, which included two varieties of rice and two fraud samples using LDA method with the accuracy of 100%. The precision of the ANN method was obtained as 98.6% for separation of the two groups of Iranian varieties and the frauded samples.

In this research some water quality parameters in fish pond includes pH, Electrical Conductivity (EC), Total Dissolved Solids (TDS) and Turbidity (Turb) were determined by standard methods and predicted by image processing using smart phone and artificial neural network. All experiments carried out in Kappur ponds in Sonqor city, Kermanshah province. Samples collected from three different depths. The 12 parameters consisted of 6 color features (red, green, blue, black, gray and white), and 6 tissue features (mean, standard deviation, softness, third torque, uniformity and entropy) were extracted from image samples and were selected as inputs to the neural network model. Based on the results, network with structure of 12-15-4 (12 neurons in the input layer, 15 neurons in the hidden layer and 4 neurons in the output layer) was the best model for predicting the parameters with R2 of 0.913, 0.993, 0.994 and 0.958 for pH, TDS, EC and Turb, respectively. These values for RMSE were 0.054, 1.835, 3.766 and 0.262, respectively.

Food waste has a high content of decomposable material. This material is very good source for fertilizer or compost has a better quality than commercial mineral fertilizers. This research investigated the effect of bulking agents on the maturity and greenhouse gaseous emissions of composting food waste. Food waste with biochar product sewage agriculture with three different treatments (sugercan baggas (FWSB) –bread (FWBB) - sawdust (FWGB) were used. The parameters of temperature, humidity, percentage of material, C/N ratio, pH, EC, carbon losses and nitrogen were measured compared and evaluated. In this study, the decomposition of food waste occurred at a temperature of 60-65 ° C, and this high degree of healing could significantly improve the response time. After 60 hours of the production process, the C/N ratio in the FW from 23.13 to 16.35 and in the FWSB from 24.5 to 21 and in the FWBB from 28.82 To 23.61 and in FWGB from 26.26 to 21.5. The organic matter of FW was from 81% to 52% and in FWGB from 86% to 53.61% and in FWSB from 87.3% to 59% and in FWBB ranged from 83.7% to 57%. The EC level in each of the treatments was incremental and its rate was evaluated in all treatments. At the end, the composting process led to improved fertility indices in each of the treatments and reached a maturity very quickly. This process there is a significant competitive advantage in reducing fertility production times compared with other previous studies.

The aim of this study was to evaluate the protein quality of complementary baby food produced from germinated beans and mung bean and to assess the health and safety of the product in terms of storage and toxic metal content. The results showed that energy levels of this product were higher than the daily energy requirements recommended by WHO for infants in 2009. Copper content was higher in the control compared to that in GCBF. Chromium content was at 0.22 mg/kg in both formula (GCBF and the control). These levels are below the safety limits of trace elements recorded by specialized organizations. GCBF exhibited high levels of energy and quality of digestibility of proteins and possessed the highest amounts of amino acids. Therefore, the developed formula is suitable for children suffering from nutritional problems and nutrient deficiencies.

The scope of this research was to model and optimize the electrospun parameters for the production of nanofiber membrane from polysulfone (PSF) polymer using the response surface methodology (RSM) with application in membrane systems. For this purpose, the influence of applied voltage (12-18 KV), flow rate (0.3-0.6 mL/h), the distance between needle and collector (10.5-17.5 cm) and effect of non-ionic surfactant Triton x-100 (TR-100) on the morphology and structure of nanofibers membrane was investigated. The optimal conditions for the fabrication of nanofibers were found to be as follow: the voltage 16.31 kV, the flow rate 0.39 mL/h, and the spinning distance 15.45 cm. The results of SEM demonstrated that with the addition of the surfactant, the fiber diameter reduced about 20% and the morphological properties of PSF nanofiber improved and homogeneous nanofibers have been produced. The contact angle of the developed nanofibers demonstrated that their surfaces were hydrophobic (PSF and PSF/TR-100).

Celiac Disease (CD) is a type of autoimmune gastrointestinal disorder that develops as a patient's inability to digest gluten in food. The only treatment of this disease is a gluten-free diet throughout one's life. Therefore, considering the production of high quality gluten-free food production for these patients is important. The aim of this study was to investigate the effect of sugar replacement with stevia at (0, 0.5 and 1 levels) and Chia Seed Flour (CSF) (0 and 8 % levels) and Chickpea Protein Isolated (CPI) (0 and 3 % levels) on specific gravity, batter flow properties, moisture content, specific volume, porosity, hardness, browning index, water activity and sensory properties of gluten-free muffin prepared from rice flour. The results indicated stevia, sugar and CSF especially combination of them  are able to increase moisture content, water activity, specific volume, porosity and browning index (BI) and decrease specific gravity. Also sugar-CSF sample had lower hardness, higher sensory properties and got highest acceptance rate (score5) in sensory assessment comparison with other samples.

Creating a map of the greenhouse environment and determine the position of the pots on this map, which are the main obstacles in agricultural environments, especially greenhouses, is an essential step in automating agricultural operations. In this research, using stereovision, the map from the greenhouse environment was extracted and the pots in this map were detected and segmented. To reach this goal, ROS framework, nodes and network connections in this framework, was used. To evaluate the designed algorithm, the error rate is calculated using Euclidean distance between estimated locations and actual locations of pots. The results of this study showed that 100% of the pots were identified and positioned. The evaluation results showed that the mean errors in estimating the position of the pots was 0.056 and Root mean squared error (RMSE) was 0.0006. Also, the maximum error in estimating the position of the pots was 0.137m and the minimum error was 0.005m. The results showed that the designed algorithm has a high accuracy in estimating the position of the pots

Nowadays, the vertical cultivation method is considered because of its high productivity per unit area and improvement of greenhouse products quality Conventional and manual methods are currently being used to produce a variety of plant support forms in vertical planting for greenhouse products. Therefore, construction of the various plant supporting forms using computer numerical control (CNC) technology is very important. In this study, design, construction and evaluation of an automatic wire bending machine is provided to create various plant supporting forms. This machine is including three units such as mechanical, electrical and control-programing units. In the mechanical unit, the rotational-to-linear wire conversion mechanism along with stepper motor and eccentric offset vertical shaft mounted gear were used for transferring and bending of the wires, respectively. Also, the new coordinates were created in the bending process by holding of wire and rotating working plate around the transferring axis for 3-D wire bending. In the electronic unit were used an Arduino board, three stepper motors, three drivers and a DC motor. Subsequently, the machine was controlled by an operator through connecting the electronic unit to a computer followed by sending a move command which this process carried out in Arduino medium. The machine parameters such as frequency at four levels (31, 42, 50 and 61 Hz), the distance of bender to plant support at two levels (1.7 and 2.3 mm), and process time at four levels (5, 7, 8 and 10 second) as independent variables were evaluated on linear and angular displacement as the dependent variables and the performance of constructed machine was compared with a software models. The results showed that in the modeling of various plant supporting forms there was not a significant difference between constructed machine and software models through variation of independent parameters. In general, in this study, the constructed automatic wire bending machine was created the high-precision, high-speed and applicable of the different plant supporting forms, and thereby, it provided optimizing the complex designs for plant growth.

In this paper the effect of different milling processes (high shear blender, ceramic mill and ball mill, and stone mill) on the structure and size distribution of sesame paste particles was investigated and rheological properties of the resulting paste samples were analyzed. Sesame paste was a fluid suspension of protein–oil. The results indicated that the stone mill for 10 min in comparison to other mill processing can significantly affect on size reduction of the particles in sesame paste, improving the rheological properties and stability of the product. The results indicated that the colloidal stability of sesame paste was improved by decreasing the median particle size to values below 5 µm. Shear thinning behaviors were observed for different sesame paste samples. Creep test showed that the elastic structure of sesame paste changed to a viscous behavior with decreasing particle size that was also related to the milling method. Whiteness (L-values) of sesame paste decreased with the reduction of particle size.

Drying is one of the most widely used methods for preserving fruits and vegetables. In the drying process, to reach final water activity, the water content of the food has reduced. This guarantees microbial resistance of the products and minimizes the physical and chemical changes. In this study, the effect of osmotic and ultrasonic pre-treatment on strawberries has investigated. Strawberries after cutting, they were submerged in a sucrose osmotic solution by 60% concentration and also distilled water. In the following, a sample in sucrose solution under ultrasonic process (UOD), one sample in a sucrose solution without ultrasound (OD) and one sample of distilled water with ultrasound (UDW) After 10, 20, and 30 minutes in an oven at 60 ° C, were are placed to complete the drying process. After that, the effect of osmotic and ultrasonic pre-treatments on the level of water loss, absorption of soluble solids, weight loss, water re-absorption, shrinking percentage, tissue, color index and sensory acceptability were evaluated. The results showed that osmotic-ultrasonic pre-process led to an increase in absorption of soluble solids, water loss, weight loss and tissue loss. Shrinking Percentage (down to 21.44%) and redness and yellowness index also decreased during sonication. Osmotic pre-treated samples were more acceptable among consumers in terms of taste, color, tissue and general acceptance. Total drying time reduce 5 up to 25% with applying pretreatment types. As a result, osmotic-ultrasound pretreated method of drying is more cost-effective in terms of time.

In recent years, life cycle assessment (LCA) approach is turned to be a useful tool for investigating and determining the environmental impacts of agricultural products and food industry, so that in most countries, it is used as a tool for decision-making in agricultural production planning. Considering the fish as an important part of the human protein required, an investigation was carried out on the environmental indicators (impact categories) in the system of warm water production in Guilan province. Data related to the production value of inputs (indirect emissions) and their’s consumption (direct emissions) in ponds were collected using sampled questionnaire and Ecoinvent database. The results of normalization showed that marine aquatic ecotoxicity (MAET), acidification (AC) and Freshwater Aquatic Ecotoxicity (FAET) have the highest amount of environmental pollutants as 5.17×10-7, 1.95×10-7 and 0.98×10-7, respectively. Emissions resulting from the production of electricity (direct emissions) and pollutants released from the use of electricity, chemical fertilizers and manure (indirect emissions) have the highest share of pollution on these indicators. Also, the comparison of the results of ANFIS design methods showed that the fuzzy C-means method with 8 clusters, with higher accuracy and less error, was able to predict the values of environmental impact categories.

In this study, edible films based on gelatin - russian olive flour (Elaeagnus angustifolia L.) incorporated with ZnO nanoparticles (2, 4 and 6% w/w) were investigated. The thickness, solubility, water vapor permeability, elongation to breakpoint of films with ZnO were higher than control ones. Color measurement of the edible films indicated that increasing the percent of ZnO nanoparticles, decreased the brightness(L*) and transparency and increased the a* and b* parameters of films (P < 0.05). In general, adding nanoparticles up to 4% increased the antioxidant capacity of the films compared to the control sample. Morphology images of the films showed that with the addition of ZnO the surface of the films was roughercompared to the control sample. Moreover, ZnO nanoparticles decreased the biodegradability of films. In general, films based on gelatin and russian olive flour with 2% ZnO are suitable films with good physical and chemical properties for food packaging.