Agricultural Meteorology
S. Shiukhy Soqanloo; M. Mousavi Baygi; B. Torabi; M. Raeini Sarjaz
Abstract
IntroductionWheat (Triticum aestivum L.) has become very important as a valuable strategic product with high energy level. The importance of investigating environmental stresses and their role in predicting and evaluating the growth and crops yield is essential. A wide range of plant response to stress ...
Read More
IntroductionWheat (Triticum aestivum L.) has become very important as a valuable strategic product with high energy level. The importance of investigating environmental stresses and their role in predicting and evaluating the growth and crops yield is essential. A wide range of plant response to stress is extended to morphological, physiological and biochemical responses. Considering the rapid advancement in computer model development, plant growth models have emerged as a valuable tool to predict changes in production yield. These growth simulation models effectively incorporate the intricate influences of various factors, such as climate, soil characteristics, and management practices on crop yield. By doing so, they offer a cost-effective and time-efficient alternative to traditional field research methods. Material and MethodsThis research was conducted in the research farm of Varamin province, which has a silty loam soil texture. The latitude and longitude of the region are 35º 32ʹ N and 51º 64ʹ E, respectively. Its height above sea level is 21 meters. According to Demarten classification, Varamin has a temperate humid climate. The long-term mean temperature of Varamin is 11.18 ° C and the total long-term rainfall is 780 mm. In this study, in order to simulate irrigated wheat cv. Mehregan growth under drought stress, an experimental based on completely randomized blocks (CRBD) including: non-stress as control (NS), water stress at booting stage (WSB), water stress at flowering stage (WSF), water stress at milking stage (WSM) and water stress at doughing stage (WSD) with three replications during growth season 2019-2020 was carried out in Varamin, Iran. Crop growth simulation was done using SSM-wheat model. This model simulates growth and yield on a daily basis as a function of weather conditions, soil characteristics and crop management (cultivar, planting date, plant density, irrigation regime). Results and DiscussionBased on the results, the simulation of the phenological stages of irrigated wheat cv. Mehregan under water stress condition using SSM-wheat model showed that there was no difference between observed and simulated values. Summary, the values of day to termination of seed growth (TSG) were observed under non- stress, stress in the booting stage, flowering, milking and doughing of the grains, 222, 219, 219, 221, 221 days, respectively andsimulation values with 224, 221, 220, 221, respectively. However, with their simulation values, there were slight differences with 224, 221, 220, 221, respectively. Acceptable values of RMSE (11.7 g.m-2) and CV (3.5) indexes showed the high ability of the SSM model in simulating the grain yield of irrigated wheat cv. Mehregan under water stress conditions. Grain yield values were observed in non-stress conditions of 5783, water stress in booting, flowering, milking and doughing of the grain stages in 5423, 5160, 5006 and 5100 kg. h-1, respectively. While the simulated values were 5630, 5220, 4920, 4680 and 4880 kg. h-1, respectively. Based on the findings, observed and simulated values of leaf area index (LAI) were observed under water stress condition in the booting, flowering, milking and doughing of the grain stages (4.3 and 4.47), (4.33) and 4.46), (4.4 and 4.57) and (4.4 and 4.58) cm-2, respectively. Evaluation of the 1000-grain weight of irrigated wheat cv. Mehregan under the water stress showed that the SSM model was highly accurate. RMSE (4.6 g.m-2) and CV (1.8) values indicate the ability of the SSM model to simulate the 1000-grain weight of irrigated wheat cv. Mehregan. Also, the simulated values of the harvest index were 34.7 % in non-stress conditions, which decreased by 6 % compared to the observed value. Harvest index values were observed under water stress conditions in the in the booting, flowering, milking and doughing of the grain stages in 30.2, 29.3, 29.9 and 29.5 %, respectively. Compared to its observed values, it was reduced by 3, 3.5, 5, and 5.5 %, respectively. ConclusionBased on the findings, the slight difference between the observed and simulated values demonstrates the SSM model's capability to accurately capture water stress impacts on the phenological stages, grain yield, and yield components of irrigated wheat cv. Mehregan during critical growth stages, including booting, flowering, milking, and doughing. The results indicate that the SSM model is effective in simulating wheat growth under water stress conditions, showcasing its potential as a valuable tool for modeling irrigated wheat growth. The model's ability to account for water stress and its effects on various growth parameters makes it a reliable and efficient tool for predicting crop performance in water-limited environments.
Soil science
F. Alizadehgan; M.A. Gholami; S. Shiukhy Soqanloo
Abstract
IntroductionIncreased agricultural activities, the occurrence of successive droughts, and limited freshwater resources, along with increasing population, have made a priority for the importance of protecting water resources in programs of developed and developing countries. Due to the climatic conditions ...
Read More
IntroductionIncreased agricultural activities, the occurrence of successive droughts, and limited freshwater resources, along with increasing population, have made a priority for the importance of protecting water resources in programs of developed and developing countries. Due to the climatic conditions in Iran, which has a wide range of arid and semi-arid characteristics, facing the challenge of water resources crisis, is inevitable. Therefore, the use of wastewater is very important.Materials and MethodsThis research was conducted in the research farm of Sari University of Agricultural Sciences and Natural Resources (SANRU), which has a silty clay soil texture. The latitude and longitude of the region are 36º 40ʹ N and 53º 04ʹ E, respectively. Its height above sea level is 21 meters. According to Demarten classification, Sari city has a temperate humid climate. The long-term average temperature of Sari is 11.18 °C and the total long-term rainfall is 780 mm. In order to evaluate the wastewater effects on soil chemical characteristics, microelements concentrations, heavy metals accumulation and Maize yield (Single Cross 704), an experiment was carried out as factorial based on a completely randomized design with treatments included; Water source factor (wastewater (A1), well water (A2)), Irrigation (subsurface method (I1) and (drip method (I2)) with three replication in 2018-2019 under lycimetric conditions, at the Sari Agriculture and Natural Resources University (SANRU), Iran.Results and DiscussionAccording to this study results, the effect of type of irrigation source on soil electrical conductivity, soil microelements and heavy metals accumulation of the soil was significantly different (P ≤ 0.01). The highest soil electrical conductivity with a value of 1.8 dS.m-1 was observed in the conditions of using treated wastewater. The highest amount of total nitrogen, phosphorus and potassium were related to the source of treated wastewater with values of 0.086, 24.2 and 222.2 mg.kg-1, respectively. The results showed that the accumulation of soil Pb (0.07) and Cd (0.014 mg.kg-1) in irrigation with treated wastewater increased compare to the well water source by 0.05 and 0.010 mg.kg-1, respectively. Also, the effect of irrigation method and the interaction effect of source and method irrigation on soil chemical characteristics, microelements concentration and heavy metals accumulation were not significant. The use of wastewater by increasing soil stability improves soil physical condition, increases soil fertility, increases photosynthetic products, increases the efficiency of plant photosynthetic system and ultimately improves plant growth. The use of subsurface irrigation resulted in a 67% increase in grain yield and 28% increase in biomass productivity compared to the drip method. Adequate nutrients during the reproductive growth stage of the plant play an important role in grain growth. Therefore, it can be said that the nutrients in the wastewater have increased the grain yield compared to using the well water source. Because the wastewater contains nutrients and micronutrients such as; nitrogen, phosphorus, potassium, calcium, zinc and iron were relative to the well water source and increased maize grain yield. The results showed that the use of effluent compared to well water, caused the absorption of more heavy metals lead and cadmium in the grain, leaf and stem of maize. Due to the use of wastewater water source, the amount of Pb uptake among different parts of the maize, with values of 27.2, 22.5 and 20.5 mg / g, respectively, related to the grain, leaf and stem. However, the uptake of Cd in the grains, leaves and stems was 2.32, 1.35 and 2.01 mg / g, respectively. According to the results, the high concentration of heavy metals Pb and Cd due to the use of wastewater in the grain sector directly threatens human health. Also, the concentration of heavy metals Pb and Cd in the leaf and stem parts of corn, by endangering the health of livestock and poultry, indirectly affects human health.ConclusionThe results showed that irrigation with treated wastewater due to its richness in nutrients and microelements, improves soil fertility and creates favorable conditions by increasing soil organic matter and mineral for plant growth. Also, according to the permissible threshold values of the concentration of heavy metals Pb and Cd in plants, the accumulation of heavy metals Pb and Cd in the grain, stem and leaf of single cross 704 corn, will not be a problem for consumers. Optimal use of wastewater can increase soil fertility and the ability of plants to absorb nutrients from the soil and ultimately increase plant yield.
M. R. Emdad; A. Tafteh
Abstract
Introduction: SALTMED model is one of the most practical tools for simulating soil salinity and crop production yield. Growth models are important and efficient tools for studying and evaluating the impact of different management conditions and scenarios on water, soil and plant relationships and can ...
Read More
Introduction: SALTMED model is one of the most practical tools for simulating soil salinity and crop production yield. Growth models are important and efficient tools for studying and evaluating the impact of different management conditions and scenarios on water, soil and plant relationships and can be used to make or predict appropriate management scenarios according to the region's conditions and to predict plant performance in the field. Since the performance of irrigation scenarios in field conditions are costly and time consuming, and due to the limited water resources in the country and the necessity of optimal water use in agriculture, using the efficient and generic models can be useful tool for simulating crop production and soil salinity variations. This research has been conducted in order to simulate soil salinity and yield production using SALTMED model in Azadegan Plain of Khuzestan province. Materials and Methods: This study was carried out in wheat fields of Azadegan plain in Khuzestan province during 2014-2015 in three regions including Ramseh (as saline soil), Atabieh (as very saline soil) and Hamidieh (as control, non-saline soil). Three 10-hectare plots were selected in each area and a pilot with area of 2000 m2 was used for evaluation and measurement in each plot. First year data were used to calibrate the SALTMED model and second year field data were used to validate the model and to achieve the results in three conditions. The dominant soil texture in the area was clay loam. The quality of used irrigation water with average salinity of 2 dSm-1 was classified as C3-S1(high salinity with low sodium absorption ratio) and had no effect on wheat yield loss. In this study, version 3-04-25(2018) of SALTMED model was used and after calibrating in the first year, the results of simulated wheat grain yield and soil salinity variation values were used for model validation in different regions and in soils with different degrees of salinity, in the second year. Results and Discussion: The average measured and simulated biomass yield in the first year were 6.6 and 6.1 t/ha, respectively. Furthermore, the average of measured and simulated of wheat grain yield was 2.9 and 2.6 t/ha, respectively. Some statistical indices including mean bias error, normalized root mean square error, and root mean square error for grain yield were 0.11, 0.04, and 0.12 t/ha, respectively. The values of the same statistical parameters for biomass were -0.49, 0.1, and 0.61t/ha, respectively. These results showed that the measured values of grain yield and wheat biomass were in good agreement with the simulated values using SALTMED model. The simulated and measured variations of soil salinity at three soil depths of 0-30, 30-60, and 60-90 cm, showed close agreement with each other in three layers. Root mean square error, normalized root mean square error, and mean bias error for soil salinity values were 1.3, 0.20, and -0.06, respectively. After calibrating the model in the first year, to validate this model in the second year, the results of three pilots locations in three regions of Ramseh (saline), Atabieh(very saline) and Hamidieh(non-saline) were used. Comparison of simulated and measured wheat grain yield and biomass values showed that there was no significant difference between simulated and measured values. The simulated values of grain yield and wheat biomass in the three non-saline, saline and very saline soils had high correlation with the measured values, indicating high accuracy and efficiency of this model in simulating grain and biomass yield in different degrees of soil salinity. Moreover, the trend of soil salinity changes simulated by the SALTMED model in three highly saline, saline and non-saline soils (for three soil layers) was close to the measured values. The SALTMED model with normalized root mean square error and mean bias error of 0.18 and -0.13, respectively, showed good accuracy in different salinity conditions. There was no significant difference (5% level) between the measured and simulated salinity values of the different soil layers. The mean standard error at the 0-30, 30-60, and 60-90 cm layers was 1.1, 1.05, and 0.81 dSm-1, respectively. Therefore, based on the results and statistical indices, it was found that SALTMED model had good accuracy and efficiency in simulating yield, biomass and soil salinity under different salinity conditions. Conclusion: According to the results and statistical indices, SALTMED model had good performance and accuracy in simulating grain yield, biomass and soil salinity variations in different soil salinity conditions and so it can be used to predict wheat yield, yield components and soil salinity in different soil condition with different degrees of soil salinity to sustain soil and water and improve water productivity in similar areas.
Mohammad Jafar Malakouti; A. Majidi; x x
Abstract
Introduction: Among growth factors, proper nutrition plays an important role in increasing yield and the quality of wheat grain. Wheat in most human societies is a strategic product and the main supplier of protein and calories needed by communities. Among growth factors, proper nutrition plays ...
Read More
Introduction: Among growth factors, proper nutrition plays an important role in increasing yield and the quality of wheat grain. Wheat in most human societies is a strategic product and the main supplier of protein and calories needed by communities. Among growth factors, proper nutrition plays an important role in increasing yield and the quality of wheat grain. Potassium (K) is the most abundant cation in the cytoplasm of the plant and plays an important role in plant physiological functions. Its deficiency reduces the qualitative and quantitative yield of crops. It is an essential component in the basic stages of protein biosynthesis. Its deficiency results in a decrease in wheat protein. The results showed that a small amount of potassium was needed in the establishment and wintering stages of wheat and it was highly required at the later stages of plant growth and the plant requirement reached its maximum in flowering stage. This illustrates the importance of taking potassium partition. Among the low nutrient elements, Zinc (Zn) is the most important element that is clearly deficient in calcareous soils. Zinc is essential for enzymatic activities and increases the protein, carbohydrate and gluten of wheat grains.
Materials and Methods: In order to investigate the effect of different sources of potassium (K) fertilizers management on some qualitative and quantitative characteristics of wheat, two experiments were conducted in two fields with lower and higher critical level of K (Kava=125 and Kava= 412mg kg-1) in a randomized complete block design with five treatments and four replications in West Azarbayjan province in 2017-18. Treatments were as follows: T1 = control (use of all essential nutrients based on soil test except K-fertilizer) ; T2 = T1 + whole sulfate of potassium (SOP) before planting; T3 = T1 + consumption of 50% K from (SOP) before planting and 50% from muriate of potassium (MOP) in two topdressing; T4 = T1 + consumption of 50% K from SOP before planting and 50% from soluble sulfate of potassium (SSOP) in two topdressing; T5 = T1 + consumption of 50% K from SOP before planting and 50% from SSOP + Zn-EDTA in two topdressing periods during the first stem elongation and wheat heading. Basal elements based on soil analysis results were as follows: at site one, containing 250 kg ha-1 potassium fertilizer, 150 kg ha-1 triple superphosphate and 100 kg ha-1 pre-planting urea fertilizer, and at site two potassium and urea similar to site one and 75 kg ha-1 triple phosphate. Topdressing 120 kg urea ha-1 was used in two stages i.e. the first stem node and the emergence of cluster at both locations. The size of the plots was 4 m2 and the interval was 2 m. Mihan cultivar was planted at a density of 500 seeds m-2 and 180 kg ha-1 using a linear grain harvesting machine. After determination of yield parameters, soil and plant composite samples were prepared and taken to the laboratory. Physical and chemical analysis of soil was performed using conventional methods at the Soil and Water Research Institute. Statistical analysis of data for different traits at two locations was performed using SAS statistical software version 9.1. Mean comparisons were undertaken using Duncan's multiple range test at the 5% level of probability.
Results and Discussion: The results of this study revealed that in the field (1), K-fertilizers increased grain yield and protein content. In this field, T5 was the best treatment in comparison with the other treatments. Split application of SSOP+Zn-EDTA was the best treatment and increased potassium fertilizer efficiency (KUE). Topdressing of SSOP+Zn-EDTA compared to other K-fertilizers, due to having available K and Zn, increased the kernel, grain yield, grain protein, straw weight and Zn content. While KUE in T2 was 5 kg kg-1, it became 6 kg kg-1 in T3 and T4 , and increased up to 8 kg kg-1 in T5. However, in the field (2) due to its higher content of available K, application of K-fertilizers had no significant effects in all treatments. In the field (1), applying the optimum amount of fertilizer (T3), increased wheat yield by 1300 kg ha-1 compared to the control treatment. However, T5 increased the yield and fertilizer efficiency by 11% and 60%, respectively, even with respect to T3. Therefore, split application of K-fertilizers should be conducted based on the soil analysis result.
Conclusion: Topdressing of soluble sulfate potassium +Zn-EDTA compared to other K-fertilizers, due to having available K, Zn and SO4, increased grain yield, protein, straw weight and Zn content, and fertilizer efficiency.
F. Mondani; B. Gholami; A.R. Bagheri; Gh.R. Mohammadi
Abstract
Introduction: The DSSAT model is one of the most general and extensively used process-based crop growth simulation models. This model has been used worldwide to simulate crop biomass, yield, and soil nitrogenleaching under different management practices and various climatic conditions. Among management ...
Read More
Introduction: The DSSAT model is one of the most general and extensively used process-based crop growth simulation models. This model has been used worldwide to simulate crop biomass, yield, and soil nitrogenleaching under different management practices and various climatic conditions. Among management agronomic factors, nitrogen fertilizer has a major effect on crops production. However, nitrogen fertilizer limiting causes to decrease crops production, but, high application rates of nitrogen would led to strong environmental consequences. Thus, management of nitrogen fertilizer consumption causes to decrease environmental pollution in the agroecosystems. Therefore, the objectives of the present study were: (1) determination of genetic coefficients and calibration of the CERES-Wheat modelof DSSAT-CSM, (2) evaluation the performances of model forsimulating wheat growth, development and grain yield and (3) simulationof changesof soil and plant nitrogen in different fertilizer nitrogen application rates under Kermanshah climate condition.
Materials and Methods: Two experiments were established based on the randomized complete block design with three replications during 2015-2016. The treatments were included 4 levels of nitrogen fertilizer application (90, 180, 300 and 360 kg ha-1 urea). The required model inputs describe field management, daily weather condition, soil profile characteristics, and cultivar characteristics. The cultivar coefficients calibrated under optimum conditions (i.e., minimum stress in weather and nutrients). The genetic coefficients (P1V, P1D, P5, G1, G2, G3 and PHINT) of the Pishtaz wheat cultivar were derived using the GenCal software of DSSAT v 4.6 for 300 kg Urea ha-1 treatment (optimum condition of nitrogen fertilizer based on the results of soil library). After model calibration process, the CERES-Wheat model validated by comparing simulated and measured values of wheat cultivars phenologicaldevelopment stages (DVS), leaf area index, total dry weight and grain yield for treatments of 90, 180, 300 and 360 kg Urea ha-1 fertilizer by root mean square error (RMSE), normalized RMSE (nRMSE) and index of agreement (d) by results ofan independent experiment from calibration experiment.
Results and Discussion: The results indicated that the coefficient P1V was 54.45 °C day, the coefficient P1D was set 90.75 days hr-1, the value for P5 was 720 °C day, the value for G1 was 25, the values for G2 was 30 mg day-1, the value for G3 2 g, and the PHINT was 95°C day. The calibration results showed that the CERES-Wheat model was able to simulate growth, development stages and yield correctly, which indicate high accuracy in calculated genetic coefficients derived using the GenCal software of DSSAT v 4.6. In the simulated and measured conditions, leaf area index, total dry weight and grain yield improved by increasing of nitrogen fertilizer application. In the simulated and observed conditions, the highest grain yields were 7048 and 7874 kg ha-1 in the treatment of 360 kgnitrogen ha-1 and the lowest grain yields were 4006 and 4217 kg ha-1 in the treatment of 360 kgnitrogen ha-1, respectively. The validation results also indicated that the CERES-Wheat model had high ability to predictg growth, development stages and grain yield in the different fertilizer nitrogen application rates. So that, the RMSE fordevelopment stages were about 3 to 4 days and the nRMSEwere about 7 to 8% of measured average, respectively. The index of agreement (d) for development stages was about 0.99. The RMSE for total dry weight were about 360 to 720 kg ha-1 and the nRMSE were about 5% to 9% of measured average, respectively. The index of agreement (d) for total dry weight were about 0.94 to 0.99. The amount RMSE for grain yield were 304 to 630 kg ha-1 and the nRMSE were 11% to 17% of measured average, respectively. The index of agreement (d) for grain yield ranged from 0.98 to 0.99. The simulation result also indicated that amount of soil NO3 and NH4 increased with nitrogen fertilizer application. The highestsoil NO3 were 41.3, 54.5, 72.1 and 80.9 kg ha-1 in the treatments of 90, 180, 300 and 360 kg Urea ha-1, respectively. The amount of nitrogen leaching increased with rising of nitrogen fertilizer. The nitrogen leaching were 259.3, 276.2, 310.4 and 335.5 kg ha-1 in the treatments of 90, 180, 300 and 360 kg Urea ha-1, respectively. The amount of nitrogen in the wheat biomass improved by increasing nitrogen fertilizer application.
Conclusion: The results indicated that the CERES-Wheat calibrated correctly that confirm calculated genetic coefficient for Pishtaz cultivar under Kermanshah climate conditions. The results of validation also showed that the CERES-Wheat model was able to simulate all studied traits wheat cultivars except leaf area index accurately in different fertilizer nitrogen application rates. Excessive nitrogen consumption led to nitrogen leaching and groundwater pollution. Therefore, it is important to know the distribution of various forms of nitrogen and how they move in the soil.
Farzad Mondani
Abstract
Introduction: The DSSAT consists of a series of popular and widely used process-based crop growth simulation models. The models have been used worldwide to simulate crop biomass and yield, and soil nitrogen leaching under different management practices and various climatic conditions. The DSSAT has also ...
Read More
Introduction: The DSSAT consists of a series of popular and widely used process-based crop growth simulation models. The models have been used worldwide to simulate crop biomass and yield, and soil nitrogen leaching under different management practices and various climatic conditions. The DSSAT has also proven to be a useful tool for selecting improved agricultural practices. Among all management agronomic factors, nitrogen fertilizer and crop species are major effective aspects impacting crops production. Although limited use of nitrogen fertilizer seems likely to reduce crop yield, high application rates of nitrogen causes serious adverse environmental effects. Thus, management of nitrogen fertilizer consumption decreases production costs and environmental pollution in agroecosystems. Therefore, the objectives of the present study were: (1) to determine the genetic coefficients and calibrate the CERES-Maize model (2) to evaluate the performances of the CERES-Maize model in simulating maize cultivars growth, development and grain yield for different fertilizer nitrogen application rates under Kermanshah climate condition.
Materials and Methods: This experiment was carried out in a split-plot design with 5 levels of nitrogen fertilizer application (0, 138, 238, 350 and 483 kg ha-1 urea) as main plots, 3 current maize cultivars SC-704, BC-678 and Simon as sub plots, and 4 replications in 2014. The required model inputs describe field management, daily weather condition, soil profile characteristics, and cultivar characteristics. The cultivar coefficients were obtained under optimum conditions (i.e., minimum stress in weather and nutrients). The genetic coefficients (P1, P2, P5, G2, G3 and PHINT) of the maize cultivars i.e. SC-704, BC-78 and Simon were determined using the GenCal software of DSSAT v 4.6 for 350 kg Urea ha-1 treatment (optimum nitrogen fertilizer amount based on the results of soil library). Model performance was evaluated by comparing simulated and measured values of maize cultivars phonological development stages (DVS), leaf area index, total dry weight and grain yield for independent nitrogen fertilizer treatment (0, 138, 238 and 483 kg Urea ha-1) by root mean square error (RMSE), normalized RMSE (nRMSE) and index of agreement (d).
Results and Discussion: The coefficients of P1, P2, P5, G2, G3 and PHINT ranged between 275 to 286 °C day, 0.576 to 1.80 days hr-1, 910 to 950 °C day, 940 to 990 number per plant, 7.0 to 7.9 mg day-1 and 51.70 to 51.97 °C day , respectively, for all cultivars. The CERES-Maize model was able to accurately simulate growth, development stages and yield for maize cultivars. For both simulated and measured conditions, leaf area index, total dry weight and grain yield were improved by increasing the application of nitrogen fertilizer. Simon cultivar had higher simulated (9925 kg.ha-1) and measured (10467 kg.ha-1) grain yield in respect to other cultivars. The validation results also indicated that the CERES-Maize model gave a reliable estimate of growth, development stages and grain yield for maize cultivars in the different fertilizer nitrogen application rates. The value of RMSE and nRMSE for leaf area index of SC-704, BC-78 and Simon cultivars were 0.56, 0.46 and 0.36 and 25.5%, 21.8% and 16.3%, respectively. The index of agreement (d) for leaf area index ranged from 0.94 to 0.98. The RMSE and nRMSE magnitudes for total dry weight of SC-704, BC-78 and Simon cultivars were 440.1, 569.6 and 419.7 and 6.2%, 8.2% and 5.8%, respectively. The index of agreement (d) for total dry weight ranged from 0.94 to 0.95. The RMSE and nRMSE values for SC-704, BC-78 and Simon grain yield were equal to 163.7, 345.2 and 314.4 and 4.3%, 11.4% and 8.1%, respectively. The index of agreement (d) for grain yield ranged from 0.93 to 0.98.
Conclusion: The results indicated that the CERES-Maize was parameterized reliably for three maize cultivars under Kermanshah climate conditions. The results of validation also showed that the CERES-Maize model was able to give an accurate simulation of all studied traits of maize cultivars except leaf area index in different fertilizer nitrogen application rates.
A Rezaei Estakhroeih; S. Khoshghadam; M. Ebrahimi Serizi; A. Badiehneshin
Abstract
Water shortage is the most important factors on crop production in the world. Several methods of deficit irrigation are solutions for reduction of irrigation water. To understand the effects of conventional deficit irrigation and partial root zone drying treatments on yield, yield components and water ...
Read More
Water shortage is the most important factors on crop production in the world. Several methods of deficit irrigation are solutions for reduction of irrigation water. To understand the effects of conventional deficit irrigation and partial root zone drying treatments on yield, yield components and water use efficiency of sunflower (Farrokh cultivar), one study was carried out. The research was conducted on Shahid Bahonar University of Kerman in the spring of 2011. A factorial experiment in a randomized complete block design with one control (full irrigation) and 18 deficit irrigation treatments in three replications was considered. Deficit irrigation treatments were: conventional deficit irrigation (irrigation with %80, %60 and %40 ETP) and partial root zone drying (irrigation with %80, %60 and %40 ETP). Every deficit irrigation treatment was conducted in three growth stage of sunflower (all periods of growth, vegetative growth stage and reproductive growth stage).The results showed that the conventional deficit irrigation treatments (irrigation with 80% ETP) in vegetative growth had the highest plant height, leaf area, leaf area index and head diameter. Also, the maximum biological yield equal to49054, maximum grain yield is equal to 9934/3 and maximum oil yield is equal to 2441/2 kg per hectare in the conventional deficit irrigation treatments (irrigation with 80% ETP) in vegetative growth occurred.The highest water use efficiency for grain yield is equal to 1/46,forbiological yield equal to7/21 and for dry forage yield is equal 5/7 kilograms per cubic meter of water. According to results,conventional deficit irrigation (irrigation with %80, %60 and %40 ETP) is recommended on based.
