Research Article
F. Ahmadi
Abstract
Introduction: Surface water has always been one of the most essential pillars of water projects and, with modeling and predicting the river flow, in addition to the management and utilization of water resources, it is possible to inhibit the natural disasters such as drought and floods. Therefore, researchers ...
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Introduction: Surface water has always been one of the most essential pillars of water projects and, with modeling and predicting the river flow, in addition to the management and utilization of water resources, it is possible to inhibit the natural disasters such as drought and floods. Therefore, researchers have always tried to improve the accuracy of hydrological parameters estimation by using new tools and combining them. In this study, the effect of seasonal coefficients and mathematical methods of signal analysis and signal processing on wavelet transform to improve the performance of the Gene Expression Programming (GEP) model were discussed.
Materials and Methods: In the present study, for the prediction of the monthly flow of Ab Zal River, the information of Pol Zal hydrometric station in period 1972 to 2017 was used. In the next step, different input patterns need to be ready. To this purpose, the data are presented in three different modes: (a) the use of flow data and considering the role of memory up to four delays; (b) the involvement of the periodic term in both linear (?-GEP) and nonlinear (PT-GEP) states, and (c): data analysis using the Haar wavelet, Daubechies 4 (db4), Symlet (sym), Meyer (mey), and Coiflet (coif), was done in two subscales, prepared, and introduced to the GEP model. To better analyze the effect of mathematical functions used in the GEP method, two linear modes (using Boolean functions including addition, multiplication, division, and minus) and nonlinear (including quadratic functions, etc.) were considered. The wavelet transform is a powerful tool in decomposing and reconstructing the original time series. Wavelet function is a type of function that has an oscillating property and can be quickly attenuated to zero. Modeling was done based on 80% of recorded data (432 months) and the validation was done based on the remaining 20% (108 months). To evaluate the performance of each of models, statistical indices such as mean square error (RMSE), mean absolute error (MAE), and correlation coefficient (R) were used.
Results and Dissection: The results of linear and nonlinear GEP models showed that in both cases, the four-delay model achieved the most accuracy in river flow prediction. Still the performance of nonlinear GEP model according to RMSE (4.093 (m3/s)), MAE (2.782 (m3/s)) and R (0.660) were better than another, respectively. In the next step, the periodic term was added to the model inputs. Based on the results, the PT-GEP model with M4 pattern had the lowest error, the highest accuracy and was able to reduce the RMSE index by 8%. Then, in the third step, the river flow data were divided into approximate subdivisions and details using five wavelet functions. The most appropriate level of analysis based on the number of data was considered as number three. The results of the W-GEP modes showed an excellent performance of this method so that the model was able to reduce the RMSE statistics with 48.6%, 41.2%, and 31.1% compared to the L-GEP, NL-GEP and PT-GEP methods, respectively. Also, the best performance of the W-GEP model with the Symlet wavelet and the decomposition level of one had the highest accuracy (R=0.847) and the lowest error (RMSE =2.898 (m3/s) and MAE =1.745 (m3/s) among all models (35 models) such as linear and nonlinear, seasonal and non-seasonal and wavelet hybrid models.
Conclusion: Based on the results, it can be concluded that the overall use of data preprocessing methods (including seasonal coefficients and wavelet functions) has improved the performance of the GEP model. However, the combination of wavelet functions with the GEP model has significantly increased the accuracy of the modeling. Therefore, it is recommended as the most suitable tool for river flow forecasting.
Research Article
Irrigation
T. Khalili; M. Sarai Tabrizi; H. Babazadeh; H. Ramezani Etedali
Abstract
Introduction: Water resources management in arid and semi-arid regions is very important specially, in agricultural sector. The major share of water use is daily consumption by humans for drinking, washing and cooking. Furthermore, population growth increases agricultural production demand, and ...
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Introduction: Water resources management in arid and semi-arid regions is very important specially, in agricultural sector. The major share of water use is daily consumption by humans for drinking, washing and cooking. Furthermore, population growth increases agricultural production demand, and this highlights the role of water resources management in the agricultural sector. The 1950’s studies showed 12 countries with a population of 20 million experienced water shortage. Virtual water is the volume of water which is consumed for a production from the beginning stage to the end. Scientists have shown that 96% of water footprints are related to crops, livestock and horticultural productions and only 4% it consumed as domestic water. Water balance data in Qom province shows that 90% of water resources are using in the agricultural sector. Investigation of water footprints in the agricultural sector is highly beneficial to improve water resources management in arid and semi-arid regions such as Qom. Materials and Methods: The research was conducted to find out the production and cultivation water needs in the agricultural sector for 10 years, via calculating the gray, blue and green water footprints using Mekonnen and Hoekstra models. In the livestock sector, water footprint’s information such as the number of livestock and poultry, production of red meat, chicken meat, egg and milk were also determined using the Mekonnen and Hoekstra. The water footprint in fertilizer was calculated using a questionnaire survey. Excel and SAS apps were used to analyze the collected data for all three study sections. Results and Discussion: The results showed that the water footprint in wheat, barley, cotton, onion, tomato, melon, watermelon, alfalfa, and corn were 3018, 2882, 10960, 1463, 1525, 960, 2504, 1683 and 416 m3/ton, respectively. The low irrigation efficiency led to a very high amount of white water footprint in the productions. Green water footprint was very low due to the lack of rainfall. In the livestock sector, the water footprint in red meat and milk were 39 m3/kg and 2.42 m3/lit, respectively which were much more than the global average. In the poultry sector, the water footprint in chicken meat and egg were 7.4 and 4.34 m3/kg, respectively, that were very high compared to the global average. The water footprint in fertilizer for wheat, barley, cotton and alfalfa productions were 2.62, 1.19, 1.07 and 2.54 m3/kg and this amount was higher under nitrogen fertilizer. The average virtual water footprint for chicken meat production in Qom province was 7.4 m3/kg. This amount in the world, USA, India, Russia, Mexico and the Netherlands is equal to 3.92, 2.39, 7.74, 5.76, 5.01 and 2.22 m3/kg respectively. In Netherlands, less water is in use in the agricultural sector than the other countries. In this country, the virtual water footprint in chicken meat is in the best position. India has the highest water consumption in poultry breeding with a consumption of 7.74 m3/kg. The average virtual water footprint in Iran for egg production is 4.34 m3/kg , while the average virtual water footprint for egg production in the world, USA, India, Russia, Mexico and the Netherlands is 3.34, 1.51, 7.53, 4.92, 4.28, and 1.4 m3/kg, respectively. India consumes the most water in the production of eggs such as chicken with a quantity of 7.53 m3/kg and the Netherlands has the least consumption with a value of 1.4 m3/kg . Conclusion: The concept of virtual water footprint in each region reduces the pressure on water resources. For better management in agricultural regions, it is possible to prevent the cultivation of high water demand crops. The most common cause of high water footprint in livestock and poultry is nutrition, so, internationally food import can be a good solution. Industrialization of poultry can also reduce water footprint. The implementation of this research can be a useful clue to the sustainable control and management of water resources and achieving an optimal cultivation pattern in our country and all provinces facing limited water resources.
Research Article
R. Chamani; M. Azari
Abstract
Introduction: Over the past decades, millions of hectares of high-quality lands have been converted to other uses and low-yielding agriculture, which have had some unpleasant consequences for watershed hydrology. Analysis of hydrological responses of different basins to land use change has shown that ...
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Introduction: Over the past decades, millions of hectares of high-quality lands have been converted to other uses and low-yielding agriculture, which have had some unpleasant consequences for watershed hydrology. Analysis of hydrological responses of different basins to land use change has shown that correct land use balances the hydrological status of the basin, so that land use and the type and density of vegetation play an effective role in permeability and runoff reduction by changing humidity, soil organic materials and soil structure. Dimensions of hydrological effects of land capability in Chehel chay watershed in Golestan province, which is affected by land use change and deforestation, are more important. Therefore, this study seeks to investigate different scenarios of land use change and its effect on the hydrological status of the basin.
Materials and Methods: The J2000 hydrology model was used to simulate the hydrology of the basin. To better investigate the spatial and temporal variations of the hydrological parameters of the study area, it is divided into 2013 hydrological response units. After calibrating the J2000 hydrological model, the model was fed by rainfall data (1992-2014) and land use potential.
Results and Discussion: To evaluate the performance of the model, the dataset obtained in the time period of 2002-2014 was used for selection simulation and the first nine-years was considered as the calibration period and the remaining was considered as the validation period. The R2 of 0.67 and 0.55, and NAS coefficients of 0.83 and 0.76 were found in the calibration and validation periods, respectively. According to the ranking of Moriasi et al., the model efficiency is "good" and can be used in the present study. Several studies with similar observational data have reported similar results. The results showed that in summer and in May and June, the emptiest space in LPS soil pores is 3.07 and 3.21%, respectively. Increasing the consumption of MPS soil pores has also increased, and from 0.5 to 1.69% of the empty pores in the average soil pores has increased in these months. Therefore, increasing water storage in LPS pores in the months of May to June, surface runoff (RD1) decreased within the range of 6.28-26.38%, and the range of subsurface runoff (RD2) reduction was 4.41-8.41%. The amount of water percolation into groundwater aquifers was positive, and the highest infiltration into groundwater ranged from 0.83 to 1.72% for fast section groundwater (RG1), and from 0.48 to 0.52% for groundwater. Large pores do not hold much water, and water is transferred vertically to medium pores under gravity. When medium pores are saturated with water, water does not penetrate into these pores and remains in large pores and moves horizontally, increasing the subsurface flow. The results indicate that deforestation in order to expand agricultural lands and inappropriate use of the lands are the most important problems. Moreover, population growth has exacerbated the condition, necessitating proper land use management and planning. The scholars have also stated that proper land use has important effects on the water balance of watersheds.
Conclusion: In this study, the hydrological effects of land uses on the hydrological situation in Chehel chay watershed have been evaluated by simulations of the hydrological model. Our results reveal that the unplanned land use changes, land clearing, and expansion of agricultural lands have intensified the hydrological situation of the basin. The peak discharge of surface and subsurface runoff in hydrological response units decreased and the rate of water infiltration into soil and groundwater increased. Reduction of surface and subsurface runoff has also decreased the discharge in the basin outlet.
Research Article
Irrigation
A,. Uossef gomrokchi; J. Baghani; F. Abbasi
Abstract
Introduction: One of the modeling methods researchers have considered in various sciences in recent years is artificial neural network modeling. In addition to the artificial neural network and regression models, today, the capabilities of data mining methods have been used to improve the output results ...
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Introduction: One of the modeling methods researchers have considered in various sciences in recent years is artificial neural network modeling. In addition to the artificial neural network and regression models, today, the capabilities of data mining methods have been used to improve the output results of prediction models and field information analysis. Tree models (decision trees) along with decision rules are one of the data mining methods. Tree models are a way of representing a set of rules that lead to a category or value. These models are made by sequentially separating data into separate groups, and the goal in this process is to increase the distance between groups in each separation. Research shows that plant yield is a function of various plant, climatic, and water, and soil management conditions. Therefore, calculating the amount of plant yield and related indices follows complex nonlinear relationships that also have special difficulty in modeling. Considering that the response of irrigated wheat to different inputs in different climates by field method is time-consuming, costly, and in some cases impossible, so the introduction of an efficient model that can predict yield and analyze yield sensitivity to various parameters is a great help. It will be to solve this problem. This study aimed to develop and evaluate the capability of three models of the neural network, tree, and multivariate linear regression in predicting wheat yield based on parameters affecting its yield in major wheat production hubs in the country. Materials and Methods: The information used in this study includes the volume of water consumption and yield of irrigated wheat and the committees related to these two indicators in irrigated wheat fields under the management of farmers (241 farms) in the provinces of Khuzestan, Fars, Golestan, Hamadan, Kermanshah, Khorasan Razavi, Ardabil, East Azerbaijan, West Azerbaijan, Semnan, south of Kerman and Qazvin, which were harvested in a field study in the 2016-17 growing season. According to the Ministry of Jihad for Agriculture statistics, these provinces have the highest area under irrigated wheat cultivation in the country and cover about 70% of the area under cultivation and production of this crop in the country. One of the most widely used monitored neural networks is the Perceptron multilayer network with error replication algorithm, which is suitable for a wide range of applications such as pattern recognition, interpolation, prediction, and process modeling. In the present study, in order to develop the neural network, the capabilities of R software with Neuralnet package have been used. After the normalization step, the data were randomized. This step aims to have a set of inputs and outputs in which the input-output categories do not have a special system. After the randomization of the data, the amount of information that should be used in the network training process is determined. This part of the data was considered for training (70%) and another part for network test (30%). Perceptron neural network activator functions in the implementation of network training and testing. The hyperbolic tangent activity function has been used to limit the range of output data from each neuron and the pattern-to-pattern training process. In the present study and the neural network modeling capability, the tree model method has been used to predict wheat yield. Tree modeling is one of the most powerful and common tools for classification and forecasting. The tree model, unlike the neural network model, produces the law. One of the advantages of the decision tree over the neural network is that it is resistant to input data noise. The tree model divides the data into different sections based on binary divisions. Each data partition can be re-subdivided into another binary, and a model fitted to each subdivision. In this research, the capabilities of WEKA software have been used to run a tree model. It is worth noting that after grouping, the prediction model is applied to the grouped data. Results and Discussion: In this study, the efficiency of three models of the artificial neural network, multivariate linear regression, and tree model to predict the performance of irrigated wheat in major production areas in the country was evaluated based on field information recorded in 241 farms. The results showed that the coefficient of explanation of the model in predicting the yield of wheat production in the model of artificial neural network and a multivariate linear regression model was 0.672 and 0.577, respectively, which was applied by grouping the data by tree method. The coefficient of explanation has been increased to 0.762. The output results of the tree model showed that the major wheat production areas in Iran in terms of water consumption could be divided into four independent groups. Finally, it can be concluded that the tree model, considering the purposeful grouping in the input data, can be used as a powerful tool in estimating irrigated wheat yield in major wheat production areas in Iran. Conclusion: In this study, the need to use data mining methods in analyzing field information and organizing large databases and the usefulness of data mining methods, especially the decision tree in estimating wheat crop yield, were investigated and compared with other forecasting methods. The general results of the research show that purposeful separation of input data into forecasting models can increase the output accuracy of forecasting models. However, it is not possible to provide a general approach to selecting or not selecting a forecasting model in different regions. In some studies, neural networks have shown a high ability to predict the performance of different products, but it is important to note that if there is sufficient data and correct understanding of the factors affecting the dependent variable, the accuracy of the models can be applied by data mining methods. It also improved the neural network. In a general approach, considering the accuracy of estimating the predicted models under study, these techniques can be used to estimate other late-finding characteristics of plants and soil.
Research Article
Irrigation
M.H. Naderi; N. Arab; O. Jahandideh; Meysam Salarijazi; A. Aarb
Abstract
Introduction: Hydrological variability is of great importance for water resources management. Analyzing the instream environmental flow demand by coupling the hydrological cycle and the hydrodynamic process with aquatic ecological processes at a watershed scale remains one of the most important yet most ...
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Introduction: Hydrological variability is of great importance for water resources management. Analyzing the instream environmental flow demand by coupling the hydrological cycle and the hydrodynamic process with aquatic ecological processes at a watershed scale remains one of the most important yet most difficult issues. Ecological water demand (environmental flow) refers to the typical—intra-annual and inter-annual natural flow regime variability—which describes the quality, quantity, and timing of flow discharge required to preserve the ecosystem and sustain essential services upon which human livelihoods and well-being depend. Therefore, ecological water demand (EWD) should be considered as a constraint in water resource planning and management.
Materials and Methods: Numerous methods and frameworks have been developed for establishing ecological water demand at regulated rivers. Hydrologically-based ecological water demand methods, because of their simplicity, data availability, and other economic and social aspects, remain the most applied ones. A suitable range of discharges environmental flow Dinavar River was estimated using advocate statistical analysis of hydrological methods Tennant, Annual Distribution Method, and Texas, coupled with habitat suitability model using the program River2D to natural flow variability need. River2D is a two-dimensional, depth-averaged hydrodynamic and fish habitat model widely used in environmental flow assessment studies. A detailed digital model of the river channel and its surrounding area was developed, including all the morphological characteristics of the river channel and its various sandy islets. Data collection was performed through GIS/GPS mapping surveys, hydro-morphological measurements (water depth, flow, substratum type, etc.), and electrofishing samplings at a microhabitat scale under different discharge conditions. Several different steady-state hydraulic simulations were conducted under typical low flow conditions, producing water depth and water velocity (direction and magnitude) maps for each discharge scenario, while results were verified with the use of field measurements. In the next step, River2D was used for the fish habitat modeling of the study area, with the application of fish preference curves developed specifically for the study area. Finally, the fish habitat modeling was conducted for the Capoeta trutta (Heckel, 1843) species, divided into two life groups, forced under the flow conditions. Also, the suitable level of ecological water demand and crucial values with different flow frequencies were analyzed, including water level, water surface width, and Weighted Usable Area.
Results and Discussion: Results show that high environmental flow releases did not necessarily provide the highest habitat availability and suitability at all seasons and fish life-stages. The adult life stage resulted in being more vulnerable to water diversion, particularly during the spring season. Shallow-water hydromorphological units suffered the highest habitat loss. Some of the environmental flow methods demonstrated inconsistent results over seasons and fish life-stages by either allowing for higher environmental flow releases. Also, the Weighted Usable Area -Discharge curve was calculated with the suitability index in medium flow conditions. From the result, the Weighted Usable Area is changed according to flowrate. In the flowrate- Weighted Usable Area/A graph, ecological flow can be determined at 1.38 m3/s for Capoeta trutta (Heckel, 1843) species. Ecological flows were calculated in the range 0.17–3.71 m3/s as the required discharge, which assures the welfare and sustainability of protected fish species populations. It was also noticed that low flow months (June to November) required more proportions of mean monthly flow than high flow months (December to May). When compared with flow-duration analysis, it is demonstrative that simulation results fitted EWD considering the quantity of available habitat for fish species. Also, the results of the study indicated that monthly EWD had an increasing trend during the flood season and a decreasing trend during the non-flood season in three sections at different suitable levels. With the increase of suitable levels, the range of EWD in the three sections also increased. The EWD and crucial values were the lowest in April with the smallest range and were the highest from June to October.
Conclusion: The major finding of this research is that the estimated Suitable Range of Discharges could better address environmental water requirements, rather than simply allocating single value minimum ecological flows. Results reveal that the ecohydraulic modeling of river basins should be considered as an indispensable component in sustainable water resources.
Research Article
Irrigation
M. Emadi; M. Noshadi; A.A. Ghaemi
Abstract
Introduction: According to expantion of urbanization, it is necessary to create green space as the most important environmental factor in moderate cities. However in recent decades, shortage of water resources is one of the problems facing the expansion of green space especially grass type. Therefore, ...
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Introduction: According to expantion of urbanization, it is necessary to create green space as the most important environmental factor in moderate cities. However in recent decades, shortage of water resources is one of the problems facing the expansion of green space especially grass type. Therefore, the application of management methods such as deficit irrigation is very important. Development of green space requires sufficient water supply and according to the climatic conditions of our country, finding alternative methods and resources for effective irrigation and utilizing all available capacities is one of the main goals of municipalities and water organizations.
Materials and Methods: This research was performed in a greenhouse with an area of 120 square meters located in the college of Agriculture of Shiraz university with longitude 52032’, latitude 29036’,1810 height above sea level, and in flower pots with dimensions of 30 * 30*30 in order to investigate the effect of water stress in the traditional irrigation method on morpho-physiological factors and water productivity in two variety long grass. The research was in the form of split plots based on a random full canton with three replication and three levels (%100 per) (w1), (%75 per) (w2), (%50 per)(w3) of water requirement. The grass used in this design is Festuca, arundinacea Schreb with two variety named Asterix and Talladega which are considered as cold grasses and has a root depth of 15-20 cm. The first 3 cm of sand (to create drain conditions) was placed in the bottom of the flower pot, and then 24 cm of soil was poured on it and compacted until it reached the required density. On April 10, two variety of grass seeds were poured manually on the pots (10 grams of seeds per pot). Then, 100 gr of rotten and screened animal dung was poured on the seeds in each flower pot and irrigated with a hose by a traditional (manual) system. Early cultivation was done manually due to the application of more water and the establishment of grass. In this way, every day for a week, two to three times irrigation and after the seeds germinate (10 days after cultivation), once-daily irrigation and until the seeds germinate completely (20 days after cultivation), the irrigation period was once between 7 until 15 days, and then water stress was imposed. The first grass mowing was done after the grass was completely established (30 days after cultivation). Also, in order to compensate for the shortage of nutrients in the soil after two months (July) 6 gr /m2 of urea fertilizer (0.54 gr/ m2 to each flower pot) was applied. The onset of stress was two months after cultivation (July 10), and the duration of stress was 45 days. To determine the water requirement a separate flowerpot among the other flowerpots was located, and provide the moisture to FC level. Every other day, the water lost by this flower pot compared to the initial weight (FC), the same amount of water was given to the flowerpots with 20% more as for the leaching requirement.
Results and Discussion: Analysis of experimental data was performed by SAS 9.4 statistical software, and Duncan’s multiple range experiments at 5% level were used to compare the means, at the level of 5% probability. Results and data analysis was investigated under water stress in two varieties.
Dryness stress and water use efficiency: Water productivity in both varieties of grass and in different irrigation treatments did not change significantly at 95%. So decline in the amount of irrigation water has not affected water productivity.
Interaction of dryness and grass quality: The results showed that water stress and the interaction of water stress and grass variety on the appearance quality of grass were not significantly different at 95% and in the second ten days of August, the appearance quality was more desirable than in the first half.
Interaction of dryness and relative leaf water content of leaf: The relative water content of the leaf was weekly measured during the stress period. The results of comparing the mean relative water content (RWC) of leaf under water stress in two types of Festuca grass showed that the effect of water stress interaction was significant in Asterix grass variety on the relative water content of leaf at 95% level. The relative water content of the leaves is a good index of the water situation of the leaves, and its reduction in the leaves causes wilting and reduces the freshness and appearance quality of the grass and reducing the relative water content of the leaf has not affected the appearance quality of the grass.
Interaction of dryness and leaf growth rate: The leaf growth rate was measured during the stress period (monthly) in three ten-day periods (August). The results of comparing the means showed that the effect of water stress interaction and two variety of grasses on leaf growth rate was not significant during the first ten days. In the second ten days, the effect of water stress was significant in both Asterix and Talladega grass and growth rate in irrigation treatments of 75 and 50% (percentage) of full irrigation was significantly different from full irrigation.
Conclusion: The results of this study showed that deficit irrigation could increase water use efficiency without reducing the quality of green cover. With less water consumption (half full irrigation), the appearance quality of the grass will be well maintained. The relative water content of the leaf decreased as dryness stress progresses and causing changes in the cell membrane and thus increasing electrolyte permeation from the cell. Considering that dryness stress has not reduced the appearance quality of the grass, reducing the relative water content of the leaf has not affected the appearance quality of the grass. Generally, the growth rate in all three decades was maximum in dryness stress 75% (percentage), which indicates the high photosynthesis of the plant in this stress.
Research Article
Soil science
M. Gheitasi; Sh. Kiani; A. Hosseinpur
Abstract
Introduction: Large amounts of nitrogen (N) fertilizers are being applied to optimize yield in vegetable production. Nitrogen use efficiency in vegetable fields is low due to high application of N fertilizers in frequent cultivation, short growth cycles and their shallow rooting system. Nitrification ...
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Introduction: Large amounts of nitrogen (N) fertilizers are being applied to optimize yield in vegetable production. Nitrogen use efficiency in vegetable fields is low due to high application of N fertilizers in frequent cultivation, short growth cycles and their shallow rooting system. Nitrification inhibitors (NI) are compounds that retard the biological oxidation of ammonium to nitrite by depressing the activity of Nitrosomonas bacteria in soil. In different studies, the positive effects of these compounds on the reduction of N losses from soil and increase of N use efficiency and crop yield have been demonstrated. The 3,4-dimethylpyrazole phosphate (DMPP) is a very popular nitrification inhibitor around the world. The efficacy of this molecule depends on climatic conditions and soil properties including of texture, pH, organic matter, moisture, temperature and mineral nitrogen. In this experiment, the effects of NI 3, 4-dimethylpyrazole phosphate on the N use efficiency of two spinach varieties were investigated in different soils.
Materials and Methods: A pot experiment was conducted in a completely randomized design with a factorial arrangement with three replications at Shahrekord University. Experimental factors were different N fertilizer sources, soil types and spinach varieties. Three N fertilizer sources consisted of urea, ammonium sulfate nitrate (ASN) and ASN plus DMPP (0.8 %). A no added N fertilizer treatment was considered as the control. The soil factor contained three different soils with different physical and chemical characteristics. The textures of the soils No. 1, 2 and 3 were loamy sand, loam and silty clay, respectively. Three selected soils were non-saline (EC1:2=0.14-0.31 dS m-1) and alkaline (pH1:2=7.9-8.0). Organic carbon and calcium carbonate equivalent (CCE) ranged from 0.26 to 0.35%, and 28.5 to 36.2%, respectively. Two spinach varieties were smooth-leaf (Giant Santos) and wrinkled-leaf (Viking). The used soils were mixed homogenously with 100 mg P kg−1 soil as triple super phosphate, 5 mg Fe kg−1 soil as Fe-EDDHA, 15 mg Zn kg−1 soil as ZnSO4.7H2O, 5 mg Mn kg−1 soil as MnSO4.H2O and 2.5 mg Cu kg−1 soil as CuSO4.5H2O. Nitrogen was applied at the rate of 150 mg kg-1 soil in two split doses before sowing and after one month. Twelve seeds were sown in 7 kg soil in plastic pots, and then placed in a greenhouse. The pots were thinned to 7 seedlings per pot after plant establishment. One week before harvesting, 10 measurements were done using a chlorophyll content meter to determine chlorophyll content index of leaves. At the end of the experiment, shoot dry weight was determined and plants were mixed and dried to measure N concentration. Finally, shoot N uptake and N use efficiency were calculated in different treatments.
Results and Discussion: In the present study, spinach plants fertilized with ASN+DMPP had a better appearance (dark green color) than those grown without DMPP. The results indicated that application of ASN with DMPP led to significant increase of leaf chlorophyll content index in comparison of ASN and urea fertilizers in all studied soils. Application of DMPP slowed down the process of ammonium oxidation to nitrite. Thus, this increase may be due to the role of ammonium in N nutrition of spinach plants treated with DMPP. This may be explained by the fact that ammonium has a positive effect on the synthesis of polyamines, cytokinins and gibberellins. The presence of these two phytohormones retarded senescence and chlorophyll degradation in plants. However, adding ASN to DMPP resulted in a significant decrease of shoot dry weight as compared with the ASN and urea fertilizers in soils No. 1 (loamy sand) and 2 (loam). In soil No. 3, shoot dry weight was not affected in plants fertilized with ASN+DMPP. Also, agronomic and physiological efficiencies of N significantly decreased by applying ASN+DMPP in comparison with ASN. It seems that application of DMPP strongly delayed the ammonium nitrification to nitrate, and consequently the soil nitrate availability appears not to be synchronized with spinach N needs. Due to short growth cycle of spinach, low availability of nitrate resulted in decreased shoot dry weight of spinach. The highest N use efficiency was observed is soil No. 2 (loam) and Giant Santos had more N use efficiency than Viking.
Conclusion: The results demonstrated that using ASN+DMPP led to yield loss, and we cannot recommend its application as a nitrogen fertilizer for spinach. However, application of ASN+DMPP is an effective strategy for improving qualitative appearance (dark green color) of spinach. Also, all studied indices were not affected in plants fertilized with ASN and urea. Therefore, application of both fertilizers is recommended for spinach production under similar conditions of the present study.
Research Article
K. Kamali; Gh. Zehtabian; tayybe Mesbahzadeh; M. Arabkhedri; Hossain Shohab Arkhazloo; A. Moghadamnia
Abstract
Introduction: Soil quality is an essential indicator for sustainable land management that generally depends on soil physical, chemical and biological properties. Due to the multiplicity of soil properties, the number of variables is usually reduced to a minimum set by statistical methods, which reduces ...
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Introduction: Soil quality is an essential indicator for sustainable land management that generally depends on soil physical, chemical and biological properties. Due to the multiplicity of soil properties, the number of variables is usually reduced to a minimum set by statistical methods, which reduces study time, decreases monitoring cost for sustainable use of agricultural lands. The aim of this study was to introduce the most effective soil characteristics of agricultural lands in Mohammadshahr plain, Karaj, to prevent the descending trend of soil quality.
Materials and Methods: In this study, four farms and orchards which were different in terms of crop type and irrigation system were selected and evaluated with Integrated Quality Index (IQI) and Nemero Quality Index (NQI). In both indicators, the characteristics affecting soil quality are combined in the form of a mathematical model and presented as a numerical quantity. For this purpose, first 12 soil profiles were described, followed by sampling from topsoil (surface layer) and sublayers (weighting average for the depths) and testing 17 soil characteristics affecting its quality. In the next step, both indicators were calculated using two different sets of soil properties. The first category, the Total Data Set (TDS), included all measured soil characteristics, and the second group, the Minimum Data Set (MDS), included the most important properties affecting soil quality. The Principle Component Analysis was implemented to select the MDS. Soil properties were scored to calculate IQI and NQI. For this purpose, a function was defined for each soil feature to standardize all scores between zero and one. Weighting various soil quality properties was also performed by calculating the common variance of the variables, which was obtained by factor analysis method.
Results and Discussion: Calculation of IQI and NQI indices showed that the topsoil samples were in grade III and sublayer samples belonged to grade IV with major limitations due to lack of profile development, organic carbon deficiency, salinity and high gravel. Four and six items out of 16 variables were identified effective for topsoil and sublayers, respectively. The IQI index based on TDS was more accurate and sensitive than the NQI index for soil quality assessment, as more features are considered for TDS. In the IQI index, both the weight of attributes and their scores are effective, while in the NQI index, only the attribute score is considered. On the other hand, the coefficient of determination between the TDS and MDS for topsoil and sublayer samples was 0.55 and 0.56% for IQI model, respectively, and 0.48 and 0.16% for NQI model, respectively. In other words, the determination coefficients showed the reliability of using the MDS instead of TDS in both IQI and NQI models. In the MDS, mean weight diameter (MWD) showed the highest effect on the surface layer and percentage of gravel had the greatest impact on the soil quality of the sublayer.
Conclusion: Although TDS took into account all soil properties and showed a slightly higher coefficient of determinations with both soil quality indicators, the MDS obtained similar results to the TDS with only about half of the properties. In the MDS, the features with an internal correlation is eliminated rendering it more cost effective. The results of this study assist decision-makers to choose better quality management and soil sustainability strategies while decreasing the monitoring cost.
Research Article
Soil science
R. Naseri; A. Mirzeai; A. Abbasi
Abstract
Introduction: Biofertilizers play a crucial role in soil fertility by dissolving stabilized phosphates and producing the nutrients needed for plant growth in the soil. One of the most important soil microorganisms is mycorrhizal fungi. Mycorrhizal fungi, with their extensive hyphae network and increasing ...
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Introduction: Biofertilizers play a crucial role in soil fertility by dissolving stabilized phosphates and producing the nutrients needed for plant growth in the soil. One of the most important soil microorganisms is mycorrhizal fungi. Mycorrhizal fungi, with their extensive hyphae network and increasing the level and speed of root uptake, increases the plant efficiency in nutrients, especially inactive elements such as phosphorus, and improves plant growth. Mycorrhiza fungi increase nutrient uptake of plants due to stimulation of root formation and subsequent increase in root level through the production of auxin and gibberellin hormones. By extending the root system, mycorrhizal fungi increase the total absorption surface of inoculated plants and thus improves crop plant access to water absorption. Considering the important and critical role of roots in crops, having sufficient information and understanding the morphological characteristics of the root system is important. Therefore, this study was conducted to investigate the role of the root system in the presence of mycorrhizal fungi in new barley cultivars in the Ilam region in rainfed conditions. Materials and Methods: In order to investigate the effect of inoculation with mycorrhiza fungi on the root system of barley cultivars in rainfed conditions, a factorial field experiment was carried out based on a randomized complete block design with three replications in the farm station of Sarablah Agricultural Research Center during 2019-2020 cropping season. Experimental treatments were including barley cultivars (Mahali, Mahour, Khorram, and Fardan) and fertilizer sources treatment including control (without fertilizer), 50% P fertilizer, mycorrhizal fungi (Glomus mosseae, Glomus etunicatum, and Rhizophagus irregularis), mycorrhizal fungi+50% P chemical fertilizer and 100% P chemical fertilizer. Root-related characteristics were measured inside the field at the pollination stage using a metal cylinder with dimensions of 30 cm in length and 2 cm in width, which had been pre-designed by hand. To measure grain yield after removing the marginal effects (50 cm from the beginning and end) were recorded for each plot. Statistical analysis of the data of this research project was done by SAS software, means were compared by Duncan’s multiple range test method, and graphs were prepared by Excel software Results and Discussion: This study showed that the interaction between cultivar× fertilizer sources was significant on the characteristics of rainfed barley roots. So that the maximum root length (76.6%), root volume (75.7%), root area (73.3%), root length density (76.8%), root tissue density (89.9%), root-specific mass (65.7%), and root surface area density (70.6%) was obtained from Fardan cultivar×mycorrhizal fungi+50% P chemical fertilizer compared to control treatment (without fertilizer source). It seems that the presence of mycorrhizal fungi has caused changes in root morphology so that the spread of mycorrhizal mycelium related to the internal tissues of the root has increased root length. Conclusion: The results of this study showed that the use of mycorrhizal fungi increased root system and root morphological changes in new barley cultivars. What is clear and has been mentioned in the reports of other researchers is that the mycorrhizal fungi can gain maximum use of moisture and nutrient uptake by creating a strong rooting system in the host plant from the rhizosphere. Recent research has shown that Fardan cultivar in the presence of mycorrhiza fungi had maximum root length, root volume, root area, root length density, root tissue density, and finally, root surface area density, and when no fertilizer source was used, a large reduction in the rooting system was observed in all cultivars. Therefore, among the cultivars used, Fardan cultivar with co-consumption of mycorrhizal fungi and 50% of P fertilizer can cause the development of root system and ultimately increase grain yield in the region under dryland conditions.
Research Article
Agricultural Meteorology
A,.A,. Sabziparvar; A.R. Seifzadeh Momensaraei
Abstract
Introduction: Although the contribution of Ultra-violet (UV) radiation is about 5-7% of the whole solar energy; nevertheless, it plays an important role in regulating the biological and photochemical processes within the Earth-atmospheric system. Ultra-violet radiation is well-known for its significant ...
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Introduction: Although the contribution of Ultra-violet (UV) radiation is about 5-7% of the whole solar energy; nevertheless, it plays an important role in regulating the biological and photochemical processes within the Earth-atmospheric system. Ultra-violet radiation is well-known for its significant influence on human health and the environment. High UV doses have negative effects on the skin (erythema (sunburn), skin cancer) and cause eye diseases and immune suppression. However, moderate UV doses have positive effects causing vitamin D production. Apart from the solar elevation, ozone and cloudiness are the main factors affecting UV level and providing significant year-to-year variability of UV radiation. The effect of clouds on UV radiation is as varied as the clouds change. Fully overcast skies lead to reductions in surface UV irradiance. On average, scattered or broken clouds also cause reductions, but short-term or localized UV levels can be larger than for cloud-free skies if direct sunlight is also present. It is noted that long-term cloud type and amount trends are largely unknown due to the relatively short data record of comprehensive cloud observations and the high variability of clouds on interannual and longer time scales. So far, most studies have focused on in-vitro impacts of UV radiation on human health and plant physiology. Unfortunately, not much research has addressed the effect of ozone and clouds distribution on total daily UVB irradiances in central arid deserts of Iran. Meanwhile, these limited investigations have used Tropospheric Ultraviolet-Visible (TUV5) radiation. The present work is aimed to evaluate the influence of clouds and ozone on daily UVB in different sky conditions.
Materials and Methods: To estimate the total daily UVB irradiances (280-315 nm), 13-year (2005-2017) historical data from 22 meteorological sites (9 provinces) were applied as the input of the TUV5 multilayer radiative transfer model. The Tropospheric Ultraviolet-Visible (TUV) model is used widely by the scientific community for applications including atmospheric photochemistry, solar radiometry, and environmental photobiology. The model calculates spectral radiance, irradiance, and actinic flux over 120-750 nm at an underlying resolution of 0.01 nm, as well as weighted spectral integrals including wavelength bands (visible, UVA, UVB, UVC), photolysis coefficients (112 reactions), and biologically active irradiances (UV index, DNA damage, vitamin D production, etc.). Atmospheric inputs include vertical profiles of N2, O2, O3, NO2, SO2, clouds, and aerosols. The propagation of radiation through multiple atmospheric layers (concentric spherical shells for direct solar beam, plane-parallel for diffuse radiation) is computed using a fast 2-stream approximation or a multi-stream discrete ordinates scheme. Version 5.3 provides updated spectroscopic data for a number of photolysis reactions (7). The aforesaid dataset includes Total column ozone (TCO), Cloud optical depth (COD), Aerosol optical depth (AOD), and Surface albedo (SALB), which were freely extracted from ://disc.gsfc.nasa.gov satellite-based images.
Results and Discussion: TUV5 Model estimated total daily UVB radiation for three different sky conditions (Clear-sky, whole sky cover, real sky) and the results compare to each other. The maximum daily UVB for clear-sky and overcast conditions (whole cloud cover) was found in summer and for the south and south-east of the region (Kerman, Fars, and Yazd provinces). The observed decline in daily UVB due to the clouds varied from 33% in summer to 67% in autumn, which highlights the importance of total cloud cover (overcast) in reducing the UVB radiation in the study sites. For the real sky condition (all-sky), the maximum daily UVB irradiances were found in southern parts of the region for most of the seasons. However, as the Indian summer Monsoon result, the maximum UVB has slightly moved toward the northwest of the region. Meanwhile, the inter-comparison of daily UVB maps with total column ozone (TCO), cloud optical depth (COD), aerosol optical depth (AOD), and surface albedo (SALB) maps show that the geographical position of maximum UVB radiation in southern provinces is in good agreement with the total column ozone and cloud optical depth. In this regard, variations of monthly SALB and AOD have less influence on the determination of displacing the maximum UVB.
Conclusion: Results of the present work highlight the high biological risk of solar UVB irradiances during clear-sky days over the study region. For full cloud cover (overcast condition), the maximum and minimum UVB are observed in the south and northeast of the region, respectively. A relative comparison of total daily UVB in clear-sky conditions versus the UVB of overcast conditions highlights the fact that clouds can significantly reduce the biological risk from 33% in summer to 67% in autumn. The UVB reduction by clouds is more pronounced during cold seasons due to the combined interaction of larger solar zenith angle (lower sun angle) with clouds and ozone.
