جستجوی مقالات مرتبط با کلیدواژه « Rainfed wheat » در نشریات گروه « کشاورزی »

Grain yield of rainfed wheat is very low in Iran. Therefore, it is necessary to investigate and develop crop management techniques for increasing of wheat yield in rainfed areas in Iran. The active compounds in the smoke are butenolide known as Karrikin and Cyanohydrin. Karrikins are small organic chemicals with known bioactive compounds related to the chemical 3-methyl-2H-furo [2,3-c]pyran-2-one. Karrikins are produced through pyrolysis of simple carbohydrates such as xylose, glucose or cellulose. There is evidence that karrikin has potential functions in mediating abiotic stress tolerance in plants. This experiment was carried out to study the effect of foliar application of smoke water derived from plant in different growth stages and identify the suitable time for application and its effect on some characteristics and grain yield of bread wheat in rainfed conditions in Iran.

To evaluate the effect of foliar application of plant derived smoke water on the growth characteristics, grain yield and its components of bread wheat a field experiment was carried out in the research field of the agricultural and natural resources campus, Razi University of Kermanshah, Kermansha, Iran in 2019-20 and 2020-21 cropping seasons as factorial arrangement in randomized complete block design with three replications. Experimental treatments included; rainfed bread wheat cultivars (Azer2 and Rijaw) and foliar application of smoke water with concentration of one milliliter per liter equivalent (1:1000 v/v) at eleven levels including no application (control), application in the stages of double ridge, second node detectable, heading, anthesis, double ridge + second node detectable, double ridge + heading, double ridge + anthesis, second node detectable + heading, second node detectable + anthesis and heading + anthesis. Plant height, leaf area index, grain yield, biological yield, number of grain.spike-1, 1000 grain weight were measured and recorded.

The results showed that the highest grain yield (2960 kg.ha-1), leaf area index (3.96), biological yield (8060 kg.ha-1), harvest index (36.1%) in foliar application of smoke water at double rige + second node detcteable stages. Foliar application of smoked water at double ridge+second node detectable stages improved grain yield in cv. Rijaw and cv. Azar2 by 30% and 34%, respectively, compared to control.

The results of this experiment showed that foliar application of smokewater in the reproductive growth stage was crop management technique to increase grain yield of bread wheat in rainfed growing areas in Iran.

Agriculture, especially rainfed agriculture, is one of the branches that is largely affected by the effects of climate change. The previous studies regarding the estimation of the length of the dry season wheat growth period in the country are mainly related to the length of the growth period of the past years or based on the growing degree day method, which is not very realistic. The purpose of this research is to estimate the length of the average growth period of rainfed wheat for the Tabriz Plain for the past 20 years (1993-2017) and the future conditions under the simulation of GCM models, for the next 50 years (1394-1444), using the meteorological parameters of temperature and rainfall. is. In the first step, the state of future conditions was evaluated under the GCM models of the sixth report of the Intergovernmental Panel on Climate Change (IPCC) and under the SSP1-2.6 and SSP5-8.6 scenarios, and then with the proposed method of the ecological zoning guidelines of the Food and Agriculture Organization of the United Nations (FAO), the length of the growth period of each period has been estimated and compared with each other. According to the FAO method, the length of the growth period is equivalent to the period of time when the rainfall is more than 50 percent of the potential evaporation and transpiration. It has been done. The results of comparing the length of the growth period of the base period and the state of future conditions under the simulation of GCM models showed that in the Tabriz Plain, the length of the wheat growth period has increased by an average of 16 days for the next 50 years, and the end of the growth period by an average of It will happen 12 days later.

In the present study, in order to evaluate the effect of stress periods on wheat yield gap in rainfed lands of Bostanabad, Tabriz, Sarab, Maragheh and Harris regions located in the east of Urmia Lake basin, in periods of 11 to 20 years, the water requirement satisfaction index has been used. The linear production function, which was provided by FAO, was also implemented to estimate the potential yield. According to the obtained results, in terms of water supply percentage of rainfed wheat or evapotranspiration ratio in rainfed to standard conditions, Harris with 42% has the best situation and Sarab with 23% has the worst situation. On average, the actual yield of rainfed wheat in the east of Urmia Lake basin is 976 kg/ha. The potential yield was estimated at 4216 kg/ha, indicating a significant gap between potential and actual yield in the study area. The highest regional yield coefficient equal to 0.41 was related to Harris and the lowest value was equal to 0.21 related to the Maragheh region, respectively. The results obtained from the water requirement satisfaction index indicate the existence of suitable conditions for the production of rainfed wheat in the region. However, the actual yield in the east of Lake Urmia basin is on average about 27.2% of the potential yield. This shows that the condition of rainfed lands in the east of Lake Urmia basin is not favorable in terms of the development of the production system and it is necessary to reduce the yield gap. Additionally, the evaluation of the results showed that the correlation of the water requirement satisfaction index with the regional yield coefficient is higher compared to the actual yield and this index can be used to evaluate the yield gap.

This study was conducted to investigate the effective components in the fluctuations of the total factor productivity of rainfed wheat production with emphasizing the role of climate change in the important provinces that produce rainfed wheat in Iran.

For this purpose, a True Random Parameter Stochastic Production Frontier (TRP-SPF) Model was estimated using panel data and the obtained coefficients were used for calculating the proposed productivity index .

The results of estimation of True Random Parameter Stochastic Production Frontier (TRP-SPF) Model show that the variables of seed, pesticides, labor force, cultivated area, technological progress, square of air temperature, effective rainfall and square of effective rainfall have a significant and positive effect on the production of rainfed wheat while the air temperature has a negative and significant effect on the production of rainfed wheat. The results of calculating CATFP index of rainfed wheat show the existence of fluctuations in it. The analysis of the contribution of factors affecting changing the CATFP index showed that this index is mainly influenced by technological changes and then climate changes. After that, scale efficiency and technical efficiency are in the third and fourth places of influencing the CATFP index.

Food security has become one of the most important global issues due to rapid population growth and changing weather conditions, drought and heat stress. Cereals and especially wheat are among the strategic and important agricultural products and they have a special role in the food security of many countries of the world including Iran. Increasing mechanization, improving production methods and the widespread use of fertilizers during the 20th century have greatly helped to increase production and the production of agricultural products is the result of a complex interaction between various environmental factors such as soil properties and management operations. Different tillage systems have different effects on crop production in rainfed agriculture. Nitrogen is one of the most important nutrients in the production of crops, which affects the growth and performance of the plant. The purpose of this experiment was to determine the most appropriate method of seedded prepartion and the amount of nitrogen fertilizer on wheat grain yield and soil properties.

To investigate the effect of raised bed and flat planting methods and the amount of nitrogen fertilizer on soil characteristics, radiation efficiency, energy balance and grain yield of Kohdasht wheat cultivar, a factorial experiment was conducted in randomized complete block design layout with three replications in the cropping years of 2019-2020 and 2020-2021 were implemented in an experimental farm in the suburbs of Rostam Abad, Rudbar, Guilan, Iran. The experimental factors included the methods of raised bed and flat planting and nitrogen fertilizer at four levels of zero, 75, 150 and 225 kg.ha-1. Measured plant traits and other indices included plant height, 1000 grain weight, fruiting efficiency, radiation efficiency, grain protein content,  biological yield, grain yield, soil bulk density, soil porosity and energy balance.

Results showed that in the treatment of 225 kg.ha-1 of nitrogen in the method of raised bed and flat planting, the highest plant height (66.3 cm), grain yield (4908 kg.ha-1), 1000 grain weight (40 g), grain protein content (11%), fruiting efficiency (88 grain.g spike-1DW), radiation use efficiency (2.05 g.MJ-1) and biological yield (11349 kg.ha-1) were obtained. Raised bed planting methods increased the soil bulk density (1. 16 g.cm-3) and decreased soil porosity. The results showed that in terms of the total energy consumption for wheat production, the lowest and highest amounts were related to raised bed and flat methods, respectively (11681.1 and 13606.8 MJ.ha-1). The highest amount of energy consumed in the flat method was allocated to nitrogen fertilizer (51%) and fuel (19%), respectively.

Increasing nitrogen fertilizer application through the faster canopy closure and sooner maximum leaf area index caused an increase in the number of grain.spike-1, 1000 grain weight and the absorption of radiation, which ultimately increased the efficiency of radiation, biomass and grain yield. Due to the minimization of the traffic of machines on the soil by reducing the soil preparation operations, the tillage system of the raised bed planting method led to a decrease in the hours and energy required for the work of the machines per hectare compared to the flat planting method. Also, raised bed planting system along with nitrogen fertilizer increased the soil bulk density and decrease the porosity. According to the results of this experiment, it seems that the method of raised bed planting along with the consumption of 225 kg of nitrogen fertilizer.ha-1 is due to having favorable weather conditions in terms of grain yield and other studied traits for the production of Kohdasht wheat cultivar in the region, the subject of study seems to be more suitable.

The need for assessing the relationship between productivity and sustainability is being become more and more visible due to the key role of productivity improvement in development process. Conservation of production resources and paying attention to sustainable agriculture operations are the next important issues.

To achieve the objective of this research, Kendrick Productivity Index and Senanayake approach were used for measuring the productivity and evaluating the sustainability of wheat cultivation operations, respectively. Finally, factors affecting on the agricultural sustainability were identified using a regression model. Furthermore, the required data and information were collected with filling the 271 questionnaire forms farmers Saqqez County during 2020-2021. .

The results revealed that the mean productivity of wheat production factors for the study area is 14.88. Also, application of Senanayake approach showed that the farmers were classified as: I) very unstable (1.84%); ii) unstable (15.13%), iii) moderately stable (65.31), iv) stable (16.24%), and v) very stable (1.48%). Further assessments using estimation by a regression model demonstrated that some variables e.g., level of education, cooperative memberships, the method of production, type of supplied seeds and total productivity have significant effect on sustainability of agricultural operations.

There is a positive relationship between total productivity factors and the index of agricultural operations sustainability. Thus, a set of action plans which will increase the productivity (including efficiency improvement and changes in scale as well as technology) due to economic efficiency, amplifies the motivation of wheat farmers to follow the principles of sustainable agriculture.

In order to plan and make correct policies in agricultural sector in terms of sustainable application of water resources and ensuring food security and self-sufficiency in the production of strategic products such as wheat, it is necessary to make an accurate prediction of dryland wheat yield. Recently, use of artificial intelligence methods for this purpose has increasingly attracted researchers' attention. In this study, the performance of three ANN algorithms, BR, GD, and LM were evaluated and compared to estimate dryland wheat yield. Meteorological data (2004-2018) from 10 meteorological stations, located in Kermanshah province, were used as input data in the proposed models. After determining the correlations between meteorological parameters and dryland wheat yield, relative humidity (RH) and precipitation (P) variables under three different input data combinations were used in the proposed models. Comparison of the predicted and observed data of dryland wheat yield showed acceptable performance of all three models. The R2 values of training step for the best combination of input data for the ANN algorithms (BR, GD and LM) were 0.85, 0.64 and 0.74, respectively, and the RMSE values were 0.09, 0.16 and 0.18 tons per hectare, respectively. Comparison of the results of different input data combinations showed that the P parameter has the most importance in predicting the yield of dryland Wheat, however, the use of P and RH data simultaneously as the third scenario leads to the highest accuracy. Finally, the BR algorithm by combining the inputs of P and RH with R2 and RMSE values for the test data equal to 0.85 and 0.09 ton/ha respectively, as the optimal model in estimating the drtyland Wheat Yield compared to other algorithms and input combinations were known.

Identifying the impact of consumption of different inputs on agricultural production helps to provide the right information to the policymaker. This study aimed at estimating the production function of two basic products (irrigated and rainfed wheat, and rice) using the three-dimensional spatial panel pattern (product, province and time). The required information was collected for the 30 provinces of Iran in the period from 2006 to 2018; and according to the selection criteria of the production functions, the translog function was selected as the superior function. Due to spatial effects and diagnostic tests, the spatial correlation model was evaluated as the optimal model. The study results showed that the elasticity of cultivated area, consumption of pesticides, tractors and combine harvesters to the production of irrigated wheat, rainfed wheat and rice products was positive and the elasticity of labor, consumption of seeds and fertilizers to the production of these products was negative; in addition, the elasticity of production inputs did not change significantly over time, and the trend of impacts of the production inputs on the production of the studied products was almost constant. Due to the surplus of labor in the production of these three products, the withdrawal of labor from production in this sector should be on the agenda and more investment should be made in investment factors such as combine harvesters and tractors to increase production so that the country can achieve self- sufficiency.

In order to evaluate the effects of Nitrogen and Potassium on Rainfed-wheat performance a factorial experiment based on RCBD with three replications was conducted at the Dryland Agricultural Research sub Institute for two years and in two crop rotation (wheat-wheat and chickpea-wheat) systems. Experimental factors includes 1- application of nitrogen at four levels N1: without nitrogen, N2: 80 kg/ha urea at planting + 3% urea foliar application, N3: 80 kg/ha urea at planting + 1 liter/ha foliar application of Royal Amine and N4: 80 kg/ha urea at planting time + 40 kg/haas top dressing, and 2- potassium application in four levels, K1: withoutpotassium, K2: 1 % potassium chloride ‌ K3: 1 liter/ha Royal Potassium and K4: ‌50 kg/ha of potassium sulfate. The results showed that in both wheat-wheat and chickpea-wheat rotations, the highest grain yield was obtained from Royal amin fertilizer treatment by 1554.5 and 1670.5 kg/harespectively which compared to the control, they increased by 17.3% and 14.53%, respectively. However, there was not significant differences with  urea top dressing treatment. The highest biological yield was recorded about 7105  kg/hafor Royal Amine and Royal Potassium treatments. Therefore, application of new nitrogen and potassium fertilizers forms such Royal Amine and Royal Potassium at the end of stem elongation stage could improve the wheat performance in cold temperate rainfed conditionswhile reducing environmental hazards.

Supplemental irrigation is effective in reducing the risk and increasing the stability and sustainability of rainfed crop production. In fact, supplemental irrigation is a temporary intervention and is designed to increase the natural transpiration of the plant when water is provided. On the other hand, it is inappropriate when rainfall is sufficient for crop growth. Under supplementary irrigation conditions, once or twice irrigation at sensitive stages of growth can prevent the drought stress in a significant area of rainfed land. In this paper, the conditions of supplementary irrigation of rainfed wheat in autumn and spring, suitable cultivars for supplementary irrigation, as well as applied extension recommendations in cold and temperate climates including North Khorasan, Zanjan, Kurdistan, Kermanshah, Lorestan, Fars, and East Azerbaijan provinces are presented.

The climate potential of agricultural lands for crop production is mainly influenced by the amount and distribution of rainfall and crop water requirement. Evaluation of environmental variables and predict climate phenomena can be help to determine suitable areas for rainfed agriculture. In dryland farming, there is a significant correlation between grain yield and soil moisture, that the soil moisture content can be affected on all phenological processes in crop especially grain filling and it leads a reduce in economic yield. In order to estimate the occurrence probability of climatic factors in agricultural lands of Aq-Qala, Kalale and Gonbad Kavous townships, were used the statistical distribution analysis of Smada software program and spatial analysis of Geographic Information System (GIS).

This research was carry out in the agricultural lands of Aq-Qala, Kalale and Gonbad Kavous townships in Golestan province, during 2015. Studied environmental variables were as annual, autumn, spring and May precipitations, optimum temperature of germination, suitable temperature in heading stage and suitable temperature in grain filling stage. In this research, the occurrence possibility of these climate variables were predicted in the return period of 25 years and at 95% probability level, using Distrib 2.0 of Smada software. Then map the spatial distribution of each of the climatic variables in the 95% probability level was prepared using various methods of geostatistical and interpolation methods and classified in GIS media. The performance criteria for evaluation were Mean Absolute Error (MAE), Mean Bias Error (MBE), Root Mean Square Error (RMSE) and Cross Validation method.

The results of occurrences probability of climatic variables such as annual, spring and May precipitations, and temperatures showed that these variables are suitable for rainfed cultivation of wheat and barley in these townships. But, the autumn precipitation can be a limiting factor for some studied areas, in the return period of 25 years and at the 95% probability level.

Despite supplying water requirements of wheat and barley in autumn season in the extensive areas of studied region, there is limitation in the north and northeast lands of Gonbad Kavous township. This zone covers about 7.40 % of the total area with 68.76-80 mm rainfall that it is classified to semi-suitable zone. The results of this research can be used in agricultural planning and future management of dryland farming in Golestan province. Keywords: Occurrence possibility, Geostatistical methods, rainfed wheat and barley, Smada.

Weather-based crop insurance is one of the best insurance systems in which it is required to simulate production yield with respect to weather variables and explaining of dependence structure to compute premium. The evaluation of dependence structure with consideration of simultaneous impact of variables using vine copula can provide more appropriate results. Therefore, in this study, the dependence structure between weather variables and rainfed wheat yield with utilization of canonical vine copula functions (C-vine) was measured and then yield of rainfed wheat in Miyaneh County has simulated. The result showed that most of the investigated variables have dependency in lower tail; in the other word, they are more impressible in small amounts than big amounts. Hence, the mean amount of simulated rainfed wheat yield was 871.6839 kg per hectare so that these results can be used in expected loss and premium calculation.

Introduction: Wheat is one of the key cereals that provides a nutrition source to millions of people around the world. By conducting applied studies, the limitations of soil and climate that reduce the yield per unit area must be understood and solutions should be provided to address these limitations. One of these strategies is a detailed study and spatial prediction of yield at points with different soil and climate characteristics. Models that predict crop yield can estimate the yield regarding climate, landscape, soil and management constraints. Considering the arid and semi-arid climate of Iran, the shortage of yield per unit area and the growing population, the country needs new research and strategies to increase yield per unit area. For this purpose, the first step is to examine the spatial variations of the yield. In the present study, the factors affecting the rainfed wheat yield in order of importance and efficiency of different methods of estimating spatial variations were investigated and the predicted yield of this crop was mapped digitally. Materials and Methods: The study area, with an area of 6700 hectares is located in Badr watershed, around Ghorveh city, Kurdistan province, west of Iran. The mean annual air temperature is 12.1oC and the average annual precipitation is 345.8 mm. The soils of the area were classified in the orders of Entisols, Inceptisols and Mollisols and in 32 soil families, according to the last version of Keys to Soil Taxonomy. Based on hypercube technique, 125 observation points were selected, soil profiles were dug and described at these points and soil samples were collected from horizons of the profiles. Some physical and chemical characteristics of the soils were determined according to the standard laboratory methods. Rainfed wheat yield was measured at each side of one soil profile in a 1m×1m quadrangle. In the present study, in addition to geomorphological data, different types of auxiliary variables such as some of the primary and secondary derivatives of digital elevation model (DEM) and Landsat satellite image data were used. To find out the affecting auxiliary topographic and plantcover data on rainfed wheat yield prediction in order of importance,ReliefAttributeEval algorithm of WEKA software was used. Artificial neural network, decision tree Analysis, discriminant analysis, and averaging k-nearest neighbors are the models that were used in this research for prediction of rainfed wheat yield. Results and Discussion: Calcium carbonate, organic carbon and coarse fragments, respectively with variability coefficients of 174.4, 62.4 and 61.3%, had the highest variation and pH, CEC and sand, respectively with 3.6, 16.9 and 20.3% variability coefficients showed the least variability in the soils of the studied area. In addition to geomorphological data, the parameters that were taken from the digital elevation model include elevation, slope percentage, slope aspect, slope curvature, slope surface curvature, longitudinal curvature, slope relative position, wetness index, multiresolution valley bottom flatness index, multiresolution ridge top flatness index, valley depth, channel network base level, modified catchment area, catchment slope, catchment slope aspect and catchment height. The environmental parameters that were taken from the Landsat 8 satellite imagery, include the normalized differential vegetation and the soil-adjusted vegetation indices. The ReliefAttributeEval algorithm in Weka software, in order of decreasing importance, identified geomorphology, relative slope position, longitudinal curvature, multi-resolution ridge top flatness index, slope, normalized differential vegetation index and soil-adjusted vegetation index as the most important factors affecting rainfed wheat production in the studied area. The amount of rainfed wheat yield was predicted by the models of artificial neural network, decision tree analysis, discriminant analysis, and averaging k-nearest neighbors. The error criteria for this prediction and a significant correlation between measured and estimated values of the rainfed wheat yield, indicate a higher accuracy for the averaging k-nearest neighbors model, compared to other models. The spatial distribution of the rainfed wheat yield, predicted by the averaging k-nearest neighbors model, was mapped. In the Badr watershed, the yields are continuously reduced towards the mountains. In this landscape, as the slope increases, depth and water storage capacity of the soil decrease mainly in the presence of Entisols. These soils are seen in the eastern, southern and western parts of the watershed. At lower elevations, the soils are deeper and are mainly Inceptisols. Rainfed wheat yield increases in the piedmont landscape, including hill, glacie and alluvial fan. Conclusion: In order of decreasing importance, geomorphology, relative slope position, longitudinal curvature, multi-resolution ridge top flatness index, slope, normalized differential vegetation index and soil-adjusted vegetation index are the most important factors affecting rainfed wheat production in the studied area. The averaging k-nearest neighbors model has a higher accuracy for rainfed wheat yield prediction, compared to other models. In the Badr watershed, the rainfed wheat yield is continuously reduced towards the mountains in the eastern, southern and western parts, where mainly Entisols are present. The yield increases in the Inceptisols, located on the piedmont landscape.

Wheat is grown worldwide in agricultural lands under different cropping systems. About 66% of cultivated area of wheat in Iran was belonged to rainfed cropping. Current estimation show that Iran needs to approximately 25 billions ton of wheat in 2021. Land suitability determination for a particular agricultural crop such as wheat requires consideration of many criteria. Evaluation of the environmental components and understanding of local biophysical restraints can help determine the areas suitable for agriculture. Topographic characteristics, climatic conditions and the soil quality of an area are the most important parameters to evaluate land suitability. The objective of this research was agroecological evaluation of Gonbad–e-Kavous township for rainfed wheat cultivation by potential and spatial analysis of geographic information system (GIS). For this purpose, agroecological requirements of crop firstly, identified according to scientific resources. Thematic requirement maps were then provided. In this research, studied environmental variables were as annual, autumn, spring and May precipitations, average, minimum and maximum temperatures, germination temperature, the maximum temperature in heding and grain filling stages, slope percent, elevation, slope aspect, OM, pH, and EC. Then, each layer was classified into four classes (high suitable, suitable, less suitable and non-suitable). The analytical hierarchy process (AHP) was used to determine the weight of criteria by using the questrationnaires analysis sheet. In final, by weighted overlay technique in geographic information system (GIS) media, land suitability map was generated in 4 classes. In this study, the results showed that about 9.20% and 24.73% of agricultural lands in Gonbad–e-Kavous township were located in the high suitable and suitable zones for rainfed wheat cultivation, respectively. These regions were identified in the south of this township. In these zones, there are not limiting factors for wheat cultivation according to precipitation and temperatures variables, slope percent, elevation and soil characteristics. In this evaluation, the less suitable (39.92%) and non-suitable (26.15%) regions were located in the some areas of central, north, and northeast of Gonbad–e-Kavous. In addition, these areas were faced by at least one limitation factors from environmental variable. In this research, it was identified that almost of total studied areas were suitable for wheat cultivation according to topography and climatic conditions. Results showed that the limiting factors in less suitable and non-suitable regions were including: non-suitable annual and spring precipitations, low content of organic matter and high EC.

Climate is one of the basic factors in nature that its change is one of the most important challenges in current century. Increasing emissions of greenhouse gases, as the most important affecting factor on climate change, lead to change of temperature, precipitation and other climatic parameters. Unlike the other sectors, agricultural sector is more vulnerable to damages caused by climate change, so that the atmosphere precipitation and temperature average patterns changing damages the horticultural and agricultural production which are the main food sources in society. Both amount and quality of production reduction arises from climate change, consequently put farmer's income at risk. In the group of cereals, wheat was the most important crop in the country during the 2013-2014 crop year with the highest cropping area of 51.22%. East Azerbaijan province with the cultivated area of 40.6% of the country's total wheat has ranked sixth among producers of this crop. Ahar, one of the largest producers of wheat, has 95.5% of the province's cultivated area. Rainfall and temperature variations show climate risks for wheat, which are the most important indicators of climate change. Usually, the highest correlation is found between wheat yield and rainfall, so that the correlation coefficient between wheat yield of Ahar and rainfall in wheat growing season (October to July) was 45%, which indicates that most of the variation of yield is explained by rainfall. Therefore, risk management in agricultural sector, particularly weather risk, is highly important; however, risk management strategy cannot be implemented properly without identifying and measuring it. Hence, with attention to the importance of weather risk measurement, in this present study we tried to measure the rainfed wheat yield risk caused by climate change in Ahar County in two base (1986-2015) and future periods (2016-2045).
We applied weather Value at Risk (VaR) and weather conditional value at risk (CVaR), aquacrop, HadCM3 general circulation models under A2 emission scenarios and downscaling Lars-wg application. For this purpose, we collected weather information between 1986 and 2015 from East Azerbaijan Province Meteorological Organization, yield and soil feature data of 1991-2015 crop years from Management of Agriculture of the city of Ahar. The concept of ‘Weather Value at Risk’ represents a method to measure non-catastrophic economic weather risks. It captures both a socio-economic indicator’s sensitivity and exposure towards weather variability. Weather-VaR (α) denotes the Value at Risk resulting from adverse weather conditions, and represents–for a given level of confidence [α] over a given period of time–the maximum expected losses. Conditional Value at Risk (CVaR) attempts to address the shortcomings of VaR model, which is a statistical technique used to measure the level of risk within a firm. Conditional Value at Risk (CVaR) also known as the expected shortfall is a risk assessment measure that quantifies the amount of tail risk an investment portfolio has. CVaR is derived by taking a weighted average of the “extreme” losses in the tail of the distribution of possible returns, beyond the value at risk (VaR) cutoff point.. AquaCrop was chosen because it is a crop water productivity model that simulates yield response to water of herbaceous crops, and can be used specifically in situations where water is a key limiting factor in crop production. AquaCrop has the additional advantage that it is relatively simple and robust and uses “a relatively small number of explicit and mostly-intuitive parameters and input variables requiring simple methods for their determination”. AquaCrop was specifically designed for “assessing water-limited, attainable crop yields at a given geographical location” and “carrying out future climate scenario analyses.
The results show that in the future period, precipitation, maximum and minimum temperature, solar radiation, maximum and minimum relative humidity, wind speed and evapotranspiration variables will shift 9.15 millimeters, 0.63 and 0.56 Celsius degrees, 0.06 MJ/m2/d, -0.61 and -0.29 percent, 0.03 m/s and 18.48 millimeters per year, respectively. Based on the weather variables change, the yield average will increase from 0.954 in the base period to 0.999 t/ha in the future period, and beta and wakeby distribution were selected for yield as the best distributions to measure risk. Compared to base period, yield risk is reduced. In three probability levels, that is 1, 5 and 10 percent, and based on VaR method the amounts of risk reduction were obtained 0.139, 0.83 and 0.61 for beta distribution, and 0.297, 0.81 and 0.31 tons per hectare, respectively for wakeby distribution, while in CVaR method for beta distribution were 0.158, 0.115 and 0.93, and for wakeby distribution were 0.403, 0.148 and 0.77 tons per hectare, respectively.
According to the results, evapotranspiration is one of the variables that increase the yield risk; therefore, it is recommended that farmers use the natural and artificial mulch to reduce evaporation from the soil surface.

Wheat (Triticum aestivum L.) as the most strategic crop for human nutrition is cultivated in many countries under rainfed conditions in semiarid regions. To be vital importance to predict rainfed wheat yield and determine the important factors which affect this crop. Modeling is one of the approaches to predict the response of land to land use. Artificial neural networks (ANN) are considered as one of the modeling approaches to yield prediction and determination of the most important parameters in crop productions. In rainfed wheat hilly land of central Zagros of Iran, there are various parameters that influence this crop production. Therefore, the objective of this study was to identify these important factors.
This study was conducted for two years and at two sites under rainfed conditions in Koohrang and Ardal districts in Chaharmahal and Bakhtiari provinces, central Zagros of Iran. At both sites, the study was made on farmer–operated winter wheat fields. At the Koohrang and Ardal sites, 102 and 100 sampling points were selected, respectively. 202 sampling points were chosen on the landscape covering summit, shoulder, backslope, footslope, and toeslope at two sites with varying climatic conditions. Four parameter groups including terrain attributes, soil physical and chemical properties, precipitation, and weed biomass, including 54 factors were used as the inputs, and wheat grain and biomass yield as the targets for ANN models. A feed-forward back-propagating ANN structure was used to develop yield prediction models. The data set was randomly shuffled; 60%, 20% and 20% of them were used for the learning network, testing and verification, respectively. After determination of the best structure of ANN model, crop yields were predicted by the ANN models. By the Hill sensitivity analysis method (Hill, 1998), response of each factor was studied and determined the most effective parameters on grain and biomass yield. This method calculates relative sensitivity coefficient by dividing the sensitivity coefficient of every variable when the variable is reduced 10% by the maximum sensitivity coefficient, therefore the maximum relative sensitivity coefficient is 1.
The descriptive statistics for various soil characteristics showed that, soil chemical and physical parameters can be classified into three orders. Sand, TN, Kava., Pava., SOM, CCE, and gravel showed high variability (CV>35); clay, silt, and CEC had moderate variability (3515); and SP and pH indicated low variability (CV

The aim of this study was to investigate the climate change impacts on some factors affecting rainfed wheat growth such as effective rainfall, planting date and length of growing season in four stations located in Chaharmahal and Bakhtiari province. Firstly, it is necessary to predict future (2046-2065) climatic conditions. For this purpose, the output of HADCM3 general circulation model was used under three scenarios of A1B, A2 and B1. The data were downscaled by LARS-WG model. After simulating the climatic parameters in mention period, the effective rainfall during the wheat growing season was calculated by Food and Agriculture Organization method. Also, the optimum planting date was defined according to the date of the first rain (at least 10 mm in case of continuing for next days). The wheat's growth stages were determined by Growing Degree Days method. The results indicated a rise in temperature for four stations. On average, it is expected that the annual temperature increase by 1.8°C compared with the baseline period (2010-1990). Total annual precipitation in Shahrekord, Koohrang and Borujen will decrease 2.2, 7.8 and 3.6 per cent respectively. About Lordegan it will increase by 2.7 per cent. Also, the results showed that in three stations of Shahrekord, Koohrang and Borujen, the amount of effective rainfall in November will increase compared to baseline, but in Lordegan it will reduce. So, in the first three stations, in most years, planting date was obtained earlier than baseline, but in Lordegan it was later than baseline. The Length of growing season will reduce in Shahrekord, Borujen and Lordegan stations, 12 days on average and in Koohrang about 13 days.

Regions Annual precipitation is one of the important factors for successful rainfed agriculture. Generally, cold and moderate climate regions with annual precipitation of 300 mm or more are suitable for rainfed wheat cultivation. Wherever, this amount is averagely 248.5 mm in Tabriz region over the last 30 years. In this research the possibility of rainfed wheat cultivation in the Tabriz plain based on precipitation amount and air temperature factors was investigated. For this purpose a set of 30 years data (1985-2015) was applied. The studied period was devided into 6 sub-perids of 5 years and the probability of success in wheat cultivation was evaluated in the rainfed condition. Results clarified that the supplemental irrigation was inevitable in the studied area. In order to determine the suitable time for supplemental irrigation practice, the autumn and spring precipitation amounts were calculated and subsequently these values were compared with corresponding crop water requirements. Finally, with investigation of wheat sensitive stages to water stress and comparison with seasonal rains, the suitable time of supplemental irrigation was proposed for June during filling stage. Over the recent 29 years the precipitation amounts of June have been less than minimum crop water requirement. Furthermore, the accurate management of the planting time can improve autumn precipitation utilization, as the autumn precipitations have been satisfactory in 3.8 years of each 5 years sub-period, averagely. The Growing-Degree-Days (GDD) index was applied for calculating the date of different growing stages of wheat. Also regarding to the importance of temperature in rainfed wheat growing process, the different phenological stages of the wheat from temperature view were investigated and the results were compared with required values.

Marls are the most susceptible geological formation of erosion and keeping a permanent crop cover on the soil of this formation is difficult due to some limitations such as the instability of soil
structure, poor soil productivity and low soil moisture storage. Polymers can be investigated as one of options to protect soil resources in these formations. This study was conducted to compare the effects of polyacrylamide (PAM) and polyvinyle acetate (PVAc) on improving soil properties and germination rate in the marl formations. PAM and PVAc were sprayed on the soil surface with 0.0, 33.3, 66.6, 100.0 kg ha-1 amounts in three splits. In total 32 boxes of polymerized soil were provided and wheat seeds were planted in them. The soil physical properties along with the wheat germination percentage were evaluated in the polymerized soils after five rainfall simulations (40 mm h-1 for 30 min). The experiment was conducted as factorial using a completely randomized design with three replications. With an increase in the two polymers rates, aggregate size, aggregate stability and saturated hydraulic conductivity were significantly improved whereas bulk density and soil surface resistance were strongly decreased in the prepared marl soil. Water holding capacity and available water of the soil decreased after the application of PAM while no significant differences were found after treating with the PVAc. This study revealed that the PVAc had the same role with the PAM in improvement of soil physical properties and in contrast it had no negative effect on the water holding capacity. Therefore, the PVAc can be successfully considered as a replacement for the PAM in the marl areas.

Changing in planting date causes changing in plant phenology such as grain filling in wheat. In order to evaluate the effect of planting dates on grain filling trend of some bread wheat genotypes under rainfed condition, an experiment was conducted at agricultural research station of Gonbad-e Kavous, Iran, in 2012-13 growing season. Five planting times i.e.: Dec. 2nd, Dec. 21st, Jan. 9th, Jan. 28th and Feb. 17th were considered as first and five wheat genotypes i.e.: line 16, Gonbad, Koohdasht, Karim and line 7 as second factor, respectively. The effect of planting date × wheat genotypes was highly significant for grain filling rate and final grain weight and significant for effective grain filling period, whereas it was not significant for grain yield. With a delay in planting dates, grain yield of the wheat genotypes decreased. The highest and lowest grain yield were produced at the first and fifth planting dates, respectively. The highest grain yield was produced by Karim and the lowest yield was produced by Line 16. With a delay in planting, grain filling rate of the wheat genotypes increased. The highest grain filling rate (1.76 mg.day-1) was obtained with Koohdasht at fourth planting date and the lowest rate (1.44 mg.day-1) was observed in Line 16 at first planting date. The highest variation among genotypes for this trait throughout different planting dates was 0.46 mg.day-1 for Koohdasht and the least variation was for Gonbad cultivar with 0.14 mg.day-1 increase. The effective grain filling period of wheat genotypes decreased from 35.33 days to 18.37 days with a delay in planting dates. The highest final grain weight of the wheat genotypes at various planting dates decreased from 54.14 mg to 29.5 mg and the highest (19.4 mg) and the lowest (13.28 mg) reduction were for Gonbad and Karim cultivars, respectively. With an each 1o C increase in environment temperature from fifth to first planting date, grain filling duration reduced by 4.1 day and for each day delaying in planting date grain yield decreased by 51 kg.ha-1. The results of evaluation showed that the responsible of wheat genotypes on grain filling trend under unusual environmental conditions were different, thus it can be infer that such as studies will be use to identifying and selection of suitable wheat germplasms on wheat breeding programs under rainfed condition at Gonbad region.