Background and objectives: Sowing date and irrigation are two constrain factors for MAIZE production, thus before sowing, it is necessary to know about crop yield responses to sowing date and water stress. These factors can be simulated using CERES-MAIZE model. This experiment was aimed to calibrate and evaluate the CERES-MAIZE model in Gorgan climatic conditions.Materials and methods: For this purpose, two experiments (each one at two years) were carried out at agricultural research station of Gorgan, Golestan Province. SC.704 as a commercial late-maturing hybrid (MO17×B73), is known as the best MAIZE hybrid is planting in different parts of Iran as well as Golestan province. The first experiment was performed within a three-replicated randomized complete block design during two years (2012 and 2013). The factors included three sowing dates (22 June, 6 July and 21 July) and four irrigation regimes based on maximum allowable depletion (MAD) of the total available soil water (TAW). Also the second experiment was conducted within a four-replicated randomized complete block design during two years (2007 and 2008). The factors included three sowing dates (7 April, 19 April, and 4 May) and two planting densities (6.5 and 8.5 plant m-2). The data from 6.5 plant m-2 was used in this experiment. The model was calibrated using three treatments of optimum irrigation and with nostress in 2012 and two treatments of the second experiment in 2007. Evaluation was done using planting date treatment (2008), planting date and deficit irrigation in 2012 and 2013.Results: The results of the model evaluation indicated that the model simulated phenological stages (anthesis day and maturity day) with high accuracy in different sowing dates and different irrigation regimes. The values of root mean square for anthesis and maturity dates were as 2.5 and 2.9 days, respectively. Therefore, this model could be used in field management planning. Also the results of evaluation base on spring sowing date (2008) and summer sowing dates (2012 and 2013) indicated that the model simulated dry matter and yield of MAIZE with high accuracy. On the other hand, the model simulated dry matter and leaf area index (LAI) trend in different irrigation levels, but hadn’t enough accuracy in terms of model statistical indices.Conclusion: Referring to results of this experiment, the CERES-MAIZE model can be used in Gorgan climatic conditions for simulating the growing stages and grain yield of MAIZE under favorable conditions.

Water deficit is one of the most common constraints to crop productivity in the world and Iran. In order to study effect of drought stress on morphologic traits, yield and yield components of 34 hybrids of corn, an experiment was carried out based of complete randomized block design with three replication under F.C. irrigation and drought stress in Khorasan Razavi Agricultural Research and Natural Resources Institute mashhad,Iran on 2010. Results of analysis of variance showed that in both conditions there are significant different between all hybrids for all traits. In these experiment drought tolerance indices as TOL, MP, GMP, SSI, STI, HARM and also Golden Mean (new index) were calculated. Results of hybrid means comparison showed that in F.C. Irrigation condition S.C500 hybrid and in stress condition N.11 hybrid was better than others in yield trait (13/79 and 5/69, respectively). It seems that Harm, STI, MP and GMP indices have a similar ability to separate drought sensitive and tolerant genotypes. According to cluster analysis (UPGMA method) based on stress tolerance and susceptibility indices and grain yield in both F.C. and stress conditions, hybrids were classified in three groups with low intra- and high extra-group similarities. In conclusion, it can be suggested that H11 and SC250 hybrids should be recommended in Mashhad Plain.

In order to investigate the effects of seed priming with plant growth promoting rhizobacteria (PGPR) on phyllochron and leaf appearance rate of corn, a factorial experiment based on randomized complete block design with three replications was conducted at the Research Farm of University of Mohaghegh Ardabili in 2008. Factors were: three corn cultivars (SC-404, SC-410 and SC-434) and seed priming with plant growth promoting rhizobacteria in four levels (without priming, seed priming with Azosprilium, seed priming with Azetobacter and seed priming with Azosprilium+Azetobacter). The results showed that phyllochron, time between the appearance of successive leaves on a shoot, was significantly affected by corn cultivar, seed priming with plant growth promoting rhizobacteria and interaction between of seed priming and corn cultivars. Seed priming with Azetobacter decreased the phyllochron but increased rate of leaf appearance. Response of corn cultivars was different to these characteristics.Leaf appearance rate in SC-404 was more than SC-410 and SC-434. The highest leaf appearance rate and the least of time for phyllochron were obtained with seed priming of SC-404 cultivar with Azetobacter. Leaf area index was increased due to seed priming with Azetobacter. In all of priming levels, process of variances leaf area index was similar until 37 days after sowing. From 44-65 days after sowing reached to a maximum level (4.96) and then decreased slowly till 79 days after sowing. This might be related to increasing aging of leaves, shadding and competition between plants for light and other resources. The highest leaf area index obtained in treatment combination of seed priming of SC-404 cultivar with Azetobacter and the least of it was in without priming.Number of leaf per plant and leaf dry matter increased in seed priming with Azetobacter.Thus, it is suggested that in order to increase leaf appearance rate, number of leaf per plant and leaf area index, seeds priming of SC-404 cultivar with Azetobacter be applied in conditions of Ardabil Plain.

The CSM-CERES-MAIZE model was calibrated and evaluated by using the field and weather data set of a two-year field experiment previously carried out on silage corn at the Agricultural Research Center in Varamin. The data set included soil, crop, and weather data of a two-year corn experiment with four irrigation levels and three N fertilization levels. Twelve treatments were arranged in a strip-plot design in a randomized complete block with three replications during the 2003 and 2004 growing season. Data collected in the field included weight of biomass, leaf area index, and important physiological dates such as silking, anthesis, grain filling, and harvest maturity during the growing period. The maximum leaf area index and weight of biomass at physiological harvest, along with anthesis and maturity dates were used in the calibration process. The biomass weight during the growing season was used for the model evaluation. The results indicated that GENCALC tool is capable enough to be applied for determining genetic coefficients of MAIZE with acceptable accuracy. The result of calibration of the model produced the following statistics, root mean square errors (RMSE) for anthesis and maturity dates were 1 and 2 days, 980 and 1313 kg ha-1 for weight of biomass and 0.75 and 0.44 for maximum LAI in the years of 2003 and 2004, respectively. Genetic coefficient required by the CSM-CERES MAIZE model including P1, P2, P5, G2, G3, and PHINT were found to be 236 (oC), 0.4 (days/hr), 790 (oC), 833, 8.5 (mg/day), and 55 (oC), respectively. The evaluation of the CSM-CERES-MAIZE showed that the model was able to simulate weight of biomass for the silage MAIZE accurately with root mean square errors (RMSE) ranging from 9 to 1483 kg ha-1 and coefficient of determinations (r2) ranging from 0.86 to 0.99 for all of the 12 treatments for two years. It is concluded that the GENCALC tool was capable of successfully determining the cultivar parameters required by the CSM-CERES-MAIZE model and that the model itself was well calibrated for the data set used in this study.

A successful hybrid MAIZE (Zea mays L. ) seed production program depends on conformity and synchrony of growth and developmental stages of the parental inbred lines with environmental conditions. Crop simulation models plays a key role in managing such synchrony by providing the simulation of the growth stages occurrence time. To evaluate the power of the DSSAT-CSM-CERESMAIZE model to simulate the growth and developmental stages of B73 MAIZE inbred line, an experiment was performed as split plot in randomized complete block design with four replications in Karaj, Iran, in 2013. The experimental factors were including planting date and plant densities in five and four levels, respectively. Time to reach any of the developmental stages of B73 MAIZE inbred line including emergence (VE), tassel initiation (TI), silk appearance as the crop flowering (R1), completion of fertilization or beginning of the seed filling (R2) and physiological maturity (R6) were recorded. Then, the genetic coefficients used in the model including P1, P2, P5 and PHINT were determined based on generalized likelihood uncertainty estimation using GLUE software. These genetic coefficients were 307, 0. 33, 970 and 70, respectively. The normalized root of error mean square (nRMSE) values for the recorded five growth stages were calculated as 7. 857, 14. 0, 7. 141, 3, 607 2. 687, respectively, which show the model can simulate the growth stages of B73 MAIZE inbred line using the new specific genetic coefficients. Overall, the results of current research showed that the CERES-MAIZE model which already developed to simulate the growth and development of MAIZE hybrid cultivars can be efficient and accurate to simulate the production of MAIZE hybrid seed only if the specific genetic coefficient of each parental inbred line is used.

In order to study the effect of light quality and quantity on morphological and physiological characteristics of two late and early MAIZE (Zea MAIZE L.) S.C., an experiment was conducted in greenhouse conditions, Ferdowsi University of Mashhad, Iran, during 2008. The experiment was carried out factorial based on randomized complete block design with six treatments and three replications. Different light conditions including natural light, additional two hours lighting after sunset, and reduction of the quality and quantity of light conditions during plants growth, were investigated. The results indicated that leaf area in both MAIZE hybrids increased by light measured until 28 days, and then decreased compared to the natural lighting conditions. In comparison with natural light conditions the dry mater of leaf and stem was increased by adding light until flowering stage. Leaf area and dry weight was reduced in both hybrids with decreasing lighting conditions. Leaf length to width ratio increased by adding the lighting measure till the seventh leaf appearance and later on reduced. This ratio increased with reduction of light duration. Chlorophyll content increased by adding light duration till the sixth leaf appearance. The chlorophyll content of two hybrids in screen conditions decreased compared to other conditions. In general, leaf area, stem and leaf dry weights, height and lodging index of short season hybrid was lower than long season hybrids. The present study showed that extending light duration resulted in increasing of the dry weight and development stage of MAIZE.

Field capacity (FC) is one of the important parameters of soil-water-crop-atmosphere models which the accurate measurement of this parameter is very expensive and time consuming. In this study the sensitivity of the CSM-CERES-MAIZE model to FC for simulating soil nitrate and ammonium concentration in different soil layers, and plant N uptake was evaluated. The study was performed using the experimental data obtained from the field study conducted on silage MAIZE in 2003 and 2004 at south Tehran, Iran. The treatments were consisted of four irrigation levels (0.7, 0.85, 1 and 1.13 soil moisture depletion) with three fertilizer levels (0, 150, and 200 kg N ha-1). The results indicated that the change of simulated soil nitrate concentration was between 7.17 and 96.75 due to 25% changes in FC (either increase or decrease). This value for simulated soil ammonium concentration was between 33.31 and 139.01. The CERES model was sensitive to FC changes in simulation of soil nitrate and ammonium concentrations and its sensitivity was different in soil layers. This model was less sensitive to FC changes in simulating mineralization, nitrification, and plant N concentration. It can be then calculated that an exact determination of FC can reduce uncertainty in simulating soil nitrate and ammonium concentrations using the CERES model.