نشریه مهندسی زراعی
سال چهل و ششم شماره 4 (زمستان 1402)

Nanotechnology involves nanomaterials that are less than 100 nm as an interdisciplinary and pioneering technology has solved many problems in the fields of agriculture. The use of iron nano-fertilizers in order to control the release of nutrients can achieve sustainable agriculture by reducing the consumption of chemical fertilizers. Nano CDs (carbon dots) are a new system or carbon material between molecule and condensed solid, which gathers the characteristics of nano effect, surface functional groups and carbon elements. Therefore, it shows three basic functions of optics, chemistry and biology, and has multiple functions and applications. In addition, the abundant hydrophilic functional groups on the surface of CDs, small size and other structural characteristics made it show great advantages in promoting crop growth and enhancing photosynthesis and stress resistance. The aim of this study was to investigate the effect of iron nano carbon dot fertilizer application on vegetative growth parameters of sorghum plant in a calcareous soil.

Iron nano carbon dots were synthesized with lemon juice (carbon source), ethylenediamine and iron sulfate (iron source) by hydrothermal method. Coating of nanoparticles with poly lactic acid was done by co-precipitation method. Characterization of iron nano carbon-dots to confirm the successful loading of iron on the surface of carbon dots and also successful coating was done by UV-VIS, EDAX, FTIR, TEM and SEM device analyses. Some chemical properties of nanocarbon dots such as pH, electrical conductivity and salinity index were measured. Sorghum cultivation was done in the greenhouse of Isfahan agricultural and natural resources research center with a factorial design in 3 replications. The first factor was foliar spraying in three levels (distilled water, iron sulfate and no coating iron carbon dot with a concentration of 3 per thousand) and the second factor was soil application of iron carbon dot (with and no coating) in 5 levels including iron carbon dot, no coating and coated each in two levels (5 and 10 mg Fe kg-1 soil). Foliar spraying of sorghum at the eight-leaf stage was carried out by iron carbon dot and iron sulfate with a concentration of 3 parts per thousand. After the plant growth period (4 months), growth parameters such as the number of leaves, stem height, stem diameter, and fresh and dry weight of stem and leaves were measured. Also, the concentration of iron in plants and soil was also measured.

No coating iron nano carbon dots had 4.98% total iron and polylactic acid coated carbon dots had 1% iron. According to the successful results on carbon dots, they were confirmed with UV-VIS and FTIR devices. Based on the results of leaf number (6/60), stem height (35.52cm), stem fresh weight (24.73 g plant-1), leaf fresh weight (24.39 g plant-1), leaf dry weight (5.37 g plant-1) and the dry weight of the stem (4.73 g plant-1) was related to the interaction effect of no coating iron carbon dot soil treatment with a level of mg Fe kg-1 soil 1 with carbon dot foliar spraying (concentration 3 per thousand). The highest amount of iron in the stem (211 mg kg-1) and leaf (186 mg kg-1) is related to the carbon dot iron soil treatment with a level of 10 mg Fe kg-1 soil and the highest amount in the soil (5.92 mg kg-1). It was related to the interaction effect of iron carbon dot soil treatment coated with polylactic acid polymer (level of 10 mg Fe kg-1 soil) with carbon dot foliar spraying (concentration 3 parts per thousand).

Among the foliar treatments with iron carbon dot and ferrous sulfate heptahydrate, the treatments that were in the group of foliar treatments with nano carbon dot iron had the most positive performance. The treatment of no coating iron carbon dot and then the treatment of iron carbon dot coated with polylactic acid, with level of 10 mg Fe kg-1 soil which simultaneously applied soil and foliar application with carbon dot with concentration 3 parts per thousand showed the best performance. Therefore, these two types of synthesized nano fertilizers are suitable for sorghum cultivation and can be used as a type of iron fertilizer for agricultural purposes.

Considering the essential role of the agricultural sector in Iran's economy, it is very important to investigate and identify optimal production methods from an economic point of view. The purpose of this study is to calculate the economic indicators of sugar beet production, use of the Data Envelopment Analysis (DEA) method to identify the efficient units, and use of the Adaptive Neuro-Fuzzy Inference System (ANFIS) method to predict the benefit-cost index based on the consumption of production inputs in Hamedan province.

In this study, 88 farmers were studied. Data were collected from Hamadan province, Iran. Inputs included labor, machinery, diesel fuel, electricity, seeds, chemicals, farmyard manure, chemical fertilizers, and irrigation water. The indices of gross revenue, net income, gross income, economical productivity and benefit-cost ratio were calculated using information obtained from farmers. Then technical, pure technical, scale and cross efficiencies were calculated using CCR and BCC models for farmers. The benefit-to-cost ratio was considered as the economic index criterion in modeling with ANFIS. In this modeling, value of various inputs used for sugar beet production were selected as input variables. Various membership functions such as Triangular, Trapezoidal, Gaussian, Logarithmic and Gbell functions were tested. Also, different configurations were examined to provide the best configuration that predicts the model. In order to measure the accuracy of ANFIS models for estimating the observed values some quality parameters including the coefficient of determination (R2), root mean square error (RMSE) the mean relative error (RME) between the observed and the predicted values were applied to evaluate the performance of different models with different configurations.

The results showed that most of the production costs were in the category of variable costs. Variable costs account for 84% and fixed costs account for 16% of the total costs of sugar beet production. Cost of labor, water consumption, and land rent have the largest share of costs among all fixed and variable costs. The indexes of gross income, net income and benefit-cost ratio were obtained as 1188.99 $ha-1, 694.28 $ha-1 and 1.34, respectively.
The results of data envelopment analysis showed that from the total of 88 farmers, considered for the analysis, 19 and 55 farmers were found to be technically and pure technically efficient, respectively. In other words, the farmers who are identified with the BCC model are more efficient than the farmers who are identified with the CCR model. Average technical efficiency, net technical efficiency, and scale efficiency were calculated as 0.73, 0.94 and 0.77, respectively.
Data envelopment analysis indicates that farmers should focus on increasing the degree of mechanization of production by reducing the cost of human labor. The saving percentage of total input costs in the CCR model is higher than the BCC model. Optimization of input consumption in sugar beet production decreased the cost by 51.64% in the CCR model and by 28.27% in the BBC model. To predict the economic performance using inputs in sugar beet production, the three-layer arrangement with seven parameters obtained the best results. The modeled ANFIS is able to predict economic performance values with R2 of 0.96. This prediction is acceptable due to its high coefficient of determination and can be used in modeling.

Considering the high share of variable costs compared to fixed costs, it can be concluded that by applying appropriate management methods, the total costs of sugar beet production in Hamadan province can be significantly reduced. By mechanizing farms, the variable costs of farms can be reduced significantly. If the cultivated land does not have a problem with weeds, the use of conventional seeds can also reduce production costs. The DEA results showed that based on the CCR model, about 78.4% of farmers produce outside the efficiency and by providing management solutions taken from efficient DMUs (the recommendations of this study), they can reduce consumption costs by keeping product yield constant. The results of multi-level ANFIS implementation showed that the three-level ANFIS structure including four ANFIS models in the first level, two ANFIS models in the second level and a final model in the third level have the best performance for benefit-cost ratio prediction. It is proposed that implementation of multi-level ANFIS is a useful tool in helping to predict the economic indices of agricultural production systems.

Soil and water pollution, especially pollution by heavy metals such as cadmium,, has been noticed in many modern urban and industrial societies. If heavy metals accumulate in the soil, the capacity of the soil to keep the metals decreases, as a result, they enter the product and their bioavailability increases. Today, the use of biochar is suggested as a healthy method to control heavy metal pollution in the soil.In this research, in order to investigate the concentration of cadmium metals in soil and leaves in the exposure of cadmium stress and using biochar to investigate some physiological indicators of leaves and also to investigate the level of soil composition in 2 varieties of grapes in Malayer city, grape cuttings in plastic pots It was cultivated in the research greenhouse of Malayer University and Faculty of Agriculture.

In this experiment, the effect of biochar on two grape varieties (white Soltana and perlet) was investigated in the face of 100 mg/kg cadmium stress. After applying cadmium stress and using biochar (3% by weight) in the tested pots, The soils of the rhizosphere area were collected after 2 months of applying stress, and the cadmium concentration was done in the form of 5-stage classification in the research laboratory of Malayer University and finally analyzed by atomic absorption device. Leaf samples were also collected after about 2 months of applying stress and biochar, and physiological indicators such as ion leakage, chlorophyll, phosphorus and relative water content were measured.
The data related to each treatment (three replications) were carefully recorded and analyzed using SPSS software. EXCEL software was used to draw graphs. Duncan's test was used at a significance level of 1%.

The results showed that cadmium stress decreased the amount of chlorophyll and the relative content of water and also increased the amount of ion leakage. It was also observed that the application of biochar in both grape varieties increased the relative content of water, chlorophyll and phosphorus and reduced the amount of ion leakage to some extent. In the chemical forms of the soil, the use of biochar caused the reduction of exchange and carbonate forms and the increase of organic, oxide and residual forms. Biochar changed the easily replaceable parts of cadmium to those that are less available. In the conditions of cadmium stress, the use of biochar in soil can play a very important role in plant indicators such as relative water content, ion leakage, chlorophyll and phosphorus.The application of biochar decreased the fraction of exchangeable and carbonated cadmium, while the forms bound to Fe-Mn oxide, organic form and residual fractions increased.It was observed that the availability of heavy metals in the soil was significantly reduced with the addition of biochar compared to the control. Biochar significantly reduced ion leakage in both grape cultivars compared to untreated soil. In the organic form, the white Soltana variety in the presence of biochar and stress of 100 mg/kg of cadmium in the soil (6.57) compared to the samples without the presence of biochar (3.39) had an increase of 48.40% in the average concentration of cadmium. In Perlet cultivar, the percentage of increase was 21.45%, all of which showed an increase in organic form in the presence of biochar.Cadmium in soil in exchangeable and carbonate forms decreased after biochar application.In the residual form, the White Soltana variety in the presence of biochar and stress of 100 mg/kg of cadmium in the soil (20.88) compared to samples without the presence of biochar (15.47) had an increase of 34.97% in the average concentration of cadmium. In Perlet cultivar, the percentage of increase was 30.34%, which all showed the increase of residual form in the presence of biochar. Our results showed that the application of biochar can reduce the availability and toxicity of cadmium.

According to the results of this research, the application of biochar in the soil can be considered as an efficient management solution to control cadmium in areas contaminated with this heavy metal and can cause positive changes in plant leaf indices.Changes in the concentration of cadmium in different soil forms of grape cultivars as a result of the use of grape trunk biochar show that the use of biochar is a good strategy to reduce the risks of transferring cadmium to humans and the environment in metal-contaminated soils.

In sugar factories, control of sugar crystals growth in the granulation stages is very important to produce sugar grains with a special and required size. Machine vision systems can determine the size of sugar crystals. The main challenge of image processing systems is the lack of capable algorithms to separate contact and overlap crystals accurately. So far, various algorithms have been developed to detect crystals and remove their overlapping. However, these methods have not been able to fully detect and separate the overlap of crystals. The purpose of this study was to provide an appropriate image processing algorithm for determining the size of crystals in sugar baking solution (massecuite), which gives us the characteristics of size and shape for the particles in the baking pot instantly to evaluate and improve the quality of the final product. The massecuite samples were provided from Debal Khozaei Sugarcane Agro-industrial Company, Ahvaz, Iran. After preparation of the sugar crystals samples under lam and lamer (microscope slides), a digital camera with two Megapixel resolution, attached to a ZS9 Olympus microscope, was used for image capturing. Then, using MATLAB image processing toolbox, the color image (RGB) transferred to grey scale. A mixture of structural operations such as erosion and expansion with spatial filters including median filter were used to remove the image noises. The function of histogram local adjustment was used to improve image contrast. Three methods of segmentation including convexity, fuzzy clustering, and multiplicative intrinsic component optimization (MICO), along with their combination were used to segment the image of massecuite crystals. A reference image was used to determine accuracy of the image processing algorithms. To do this, the massecuite crystals image was manually segmented by Image J software. All segmentation algorithms were applied on the reference image, and seven geometrical parameters, including the mean aperture (MA), coefficient of variation (CV), and standard deviation (SD) were calculated for all the sugar particles in the image. Finally, the percent of MA measurement error was calculated for each sugar crystal to find the best algorithm. In manual segmentation, the number of sugar crystals in the selected image was 26. In the manually segmented image, the average of MA, SD and CV for sugar grains in the image were 0.422 mm, 0.157 mm and 37.18% respectively. The relatively large CV of the calculated geometrical parameters indicated the non-uniformity of the sugar particles size inside the massecuite. The convexity method was able to perform well in some areas of the image, and in some other areas, it could not detect the contact between the crystals. The value of the SD and CV of all the geometric parameters determined by the convexity method were greater than the reference values determined by the manual segmentation. This indicates the weaker performance of this method in determining the sugar crystals size compared to the manual method. The values of SD and CV of all geometric parameters determined by the combined fuzzy-convexity method were greater than the reference values, but lower than the values of the convexity method alone. So, the combination of the fuzzy clustering method with the convexity method improved the segmentation performance of crystal images. The SD and CV values of all geometric parameters determined by the combined MICO-convexity method were greater than the reference values, but lower than the values of convexity and fuzzy-convexity methods. This point shows the better performance of the combined MICO-convexity method in segmenting the images of sugar crystals compared to the other two methods. The average of MA, SD and CV for sugar crystals in the image were 0.382 mm, 0.150 mm and 39.23% respectively and had no significant difference with the reference method values in 5% probability level. The mean error of MA determined by the combined MICO-convexity algorithm was 13.24% and Pearson correlation factor was 0.88. As a result, the combined MICO-convexity method was proposed to determine the size of sugar crystals in massecuite. After applying different algorithms on the selected image of sugar crystals in massecuite, it was found that the combined MICO-convexity method can separate sugar crystals well. Also, the CV obtained for this image segmentation algorithm was not much different from the CV of the manual reference method, so this algorithm can be used in the image processing system of the massecuite crystals.

As the most important source of calories and protein, bread has a special role and importance in the nutrition of the country, and its cheapness has caused it to replace other food items in the diet in recent years. The increase in bread consumption in the low-income and vulnerable groups has been more intense due to the low volume of supply of other food products and the excessive and continuous increase in the price of other alternative products. Flat bread has the highest consumption statistics among other breads in Iran. One of their types is Barbari bread, which is the second most consumed bread after lavash bread in Iran. Therefore, the health and quality of consumed Barbari bread is of particular importance. For this purpose, this study was conducted with the aim of the effect of storage time of Barbari bread based on the characteristic of smell using the olfactory machine system based on eight metal oxide semiconductor sensors.

An odor machine system based on eight MOS sensors was carried out in order to investigate the effect of bread storage time based on odor characteristics. Designed system includes data acquisition system, sensors, shield of sensors, sample container, power supply, connections, electric valves, air pump and air filter. The sensor array was consisted of the 8 MOS sensors that each one reacts to specific volatile compounds. These sensors are widely used in olfactory machines because of their high chemical stability, high durability, low response to moisture and affordable prices. These are the most commonly used sensors in electronic nose system. Sensors are the main components of an electronic nose system therefor it is necessary to select the able sensors to detect differences among samples. In order to carry out the test, the sample was placed in sample container and in the baseline correction step (150 seconds), clean air was passed through the sensors to transmit the response of sensor array to steady state. At the injection step (180 seconds), the sample headspace was transmitted and passed through sensors chamber. Output voltage of each sensor depends on the type of sensor and its sensitivity. At the cleaning step (150 seconds) the clean air was passed through sensors to get the sensor array responsive to a stable state. Also, at this step the pump removed the odor remaining inside the sample container and system is prepared for the next test. The signals obtained from the sensors were recorded and then pre-processed.

The olfactory machine system based on eight metal oxide semiconductor (MOS) sensors was investigated with the PCA pattern recognition method due to the storage time of Barbari bread at four different temperatures. The data obtained from the signals processing with fractional method were used as input of PCA. The results of principal component analysis with two components PC1 and PC2 are 95, 90, 86 and 85%, respectively, for Barbari bread that is stored at room temperature (in the table), refrigerator temperature (4°C), room temperature (in foil) And the temperature of the freezer was placed, it showed. The results obtained from the QDA analysis to determine the quality of Barbari bread at 4 °C for 9 days, at room temperature (in foil) and (on the table) for 5 days and Barbari bread at the freezer temperature of the refrigerator (-18 °C) for 15 days of storage with classification accuracy of 98.52, 96, 100 and 97.35% respectively. The results of LDA analysis for the signals obtained from the olfactory machine, in the classification of the duration of storage of Barbari bread at refrigerator temperature, room temperature (in the table), room temperature (in foil) and refrigerator freezer temperature, respectively, with classification accuracy of 79.26 and 85.33, 78.67 and 75.22 percent were obtained. Also, according to the output obtained from the loading linear graphs and the radar graph, the smell of Barbari bread has the most and the least effect on the MQ9 sensor and the TGS813 sensor, respectively

An olfactory machine system based on eight metal oxide semiconductor (MOS) sensors was investigated for the Barbari bread time retention effect at four different temperatures. The results of principal component analysis with two components PC1 and PC2, for Barbari bread at room temperature (the table), refrigerator temperature, room temperature (in foil) and It showed that they were exposed to freezing temperatures. The results obtained from QDA analysis to detect the quality of Barbari bread at 4°C in room temperature (in foil) and (in the table) and refrigerator freezer temperature respectively. The results of LDA analysis for the classification of Barbari bread at refrigerator temperature, room temperature (in the table), room temperature (in foil) and freezer temperature of the refrigerator. The was obtained. Also, according to the output obtained from the loading linear graphs and the radar graph, the smell of Barbari bread has the most and the least effect on the MQ9 sensor and the TGS813 sensor, respectively.

In recent years, due to its availability and low environmental pollution, the use of Earth-Air Heat Exchanger (EAHE) has been developed as an efficient energy system in heating and cooling residential buildings and agricultural greenhouses. In this system, air is circulated by a fan through a pipe buried deep in the ground. Depending on the geographical location and soil type, the soil temperature at a depth of 2-3 meters remains unchanged throughout the season. Of course, this depth varies throughout the year and according to climatic changes. The heat exchange between the soil and the air inside the pipe depends on the type of soil and its moisture content, the length and diameter of the air transmission pipe, the depth of burial and the velocity of the air flow (air velocity). Air circulation can be done in an open-loop or closed-loop circuit.

A factorial experiment was conducted in the form of a completely randomized block design with two factors (pipe length at three levels (34, 17 and 52 meters) and air velocity at two levels (5 and 10 m/s)) in three replications, to investigate the effect of these factors on the coefficient of performance (COP), system efficiency and outlet air temperature. The experiment was conducted in a greenhouse in Arak city, Iran, in Joune 2022. This 150 square meter greenhouse was equipped with geothermal equipment. Air was circulated through a 200 mm diameter PVC pipe buried three meters deep in the ground. Air was circulating through an open loop circuit. Dependent variables were measured during the hot hours of the day (from 12:00 to 18:00) for one week at the end of July. The air temperature at the fan inlet and at 17, 34 and 52 meters along the pipe was measured by a single-channel data logger. Hourly changes in outlet air temperature, COP and efficiency were measured in a 24-hour period and plotted using Excel software.

The outlet air temperature for the pipe length of 34 and 52 m did not change when the air velocity decreased from 10 m/s to 5 m/s. But for the pipe length of 17 m, the maximum temperature, COP and efficiency were observed at an air velocity of 5 m/s. Regardless the air velocity, the average temperature of the outlet air for the three levels of the pipe length was 28.5, 25.5 and 25.3°C, respectively. The outlet air temperature was almost the same for the 34 and 52 m pipe lengths. In other words, the optimal length of the pipe is about 34 meters. The mean efficiencies for these two pipe length levels were 0.69 and 0.66, but the COP depended on the air velocity. The average COP for air velocity of 5 and 10 m/s was obtained 1.4 and 2.5, respectively. Based on these results, the best performance of the system in terms of output temperature reduction, cooling efficiency and COP is obtained in situation that the length of the pipe is 34 m and the air velocity is 10 m/s. when the length of the pipe is 17 meters, the temperature of the air outlet at two velocities of 10 and 5 m/s was 29.9 and 27 °C, respectively. The cooling efficiency and COP at two velocity of 10 and 5 m/s, were 0.34, 0.54; and 2.1, 1.7 respectively. If the desired temperature is 28-30 °C, pipe length of 17 m and the air velocity of 5 m/s is recommended. The results of hourly performance analysis showed that the highest difference between inlet and outlet air temperatures, is obtained at middle hours of the day. The higher the ambient temperature, the higher the efficiency of the EAHE system.

This system successfully met the cooling needs of a model greenhouse in the weather conditions of Markazi Province in June. Based on the results, the optimal pipe length and air velocity were obtained as 34 m and 10 m/s, respectively. The average air outlet temperature and cooling efficiency were 25.5, 0.66 and 2.5 respectively. The higher the ambient temperature, the higher the EAHE efficiency. This is mainly due to the higher temperature difference between the outgoing and incoming air during the hottest hours of the day. As a result, system efficiency and COP increase at the hottest hours of the day.