Calibration and Evaluation of the CERES- Wheat of DSSA T V.4 model in Golestan Province

• Published in: a
• Main Authors: Asadi, Mohammad Esma`il, Kiyani, Ali Reza, Abu Mardani, Yahya, Rushan, Ashraf
• Format: Publication
• Language: Persian
• Published: Karaj (Iran) Agricultural Engineering Research Institute of Iran 2007
• Subjects: ADAPTATION DE LA PRODUCTION; ADJUSTMENT OF PRODUCTION; AGRICULTURAL RESEARCH; AJUSTE AGRARIO; APLICACIONES DEL ORDENADOR; APPLICATION DES ORDINATEURS; BLE; COMPUTER APPLICATIONS; COMPUTER SOFTWARE; DATA PROCESSING; ENSAYO DE MAQUINAS; ENVIRONMENTAL MANAGEMENT; EQUIPMENT TESTING; ESSAI DE MATERIEL; EVALUACION; EVALUATION; GESTION AMBIENTAL; GESTION DE L'ENVIRONNEMENT; INVESTIGACION AGRARIA; IRAN ISLAMIC REPUBLIC; IRAN REPUBLICA ISLAMICA; IRAN REPUBLIQUE ISLAMIQUE; Irrigation and Drainage Department; LOGICIEL; MODELE; MODELE VEGETAL; MODELOS; MODELOS VEGETALES; PLANT MODELS; PROCESAMIENTO DE DATOS; PROGRAMAS DE ORDENADOR; RECHERCHE AGRONOMIQUE; RENDEMENT; RENDIMIENTO; TRAITEMENT DES DONNEES; TRIGO; WHEATS; YIELDS

Recently, computer simulation models have turn out to be a helpful management tools to evaluate crop performance and its interactions with the environment. These models can be used efficiently to evaluate various water and fertilizers management practices to increase farm profitability and reduce degradation of groundwater quality. Modeling also may be used to predict crop yield without any additional fund. However, models must be properly constructed and used in order to describe the soil and plant response. Also, before models are used, they need to be calibrated and validated for the conditions under which they will be used. The CERES- Wheat is a yield simulation model and one of the main models that have been incorporated in DSSA T (Decision Support System for Agrotechnology Transfer). The CERES-Wheat model simulates the impacts of the main environmental factors, such as weather, soil type, and major soil characteristics, and crop management on wheat growth, development, and yield. Inputs requirements for CERES- Wheat include weather and soil conditions, plant characteristics, and crop management. The minimum weather input requirements of the model are daily solar radiation, maximum and minimum air temperature, and precipitation. Standard meteorological data were obtained using the nearest weather station. Required crop genetic inputs are coefficients resulted to photo period sensitivity, duration of grain filling, conversation of mass to grain number, grain-filling rates, verbalization requirements, stem size, and cold hardiness. The model simulates phonological developmentbiomass accumulation and partitioningleaf area index (LAI)root, stem, leaf, and grain growthand the soil and plant water and N balance from planting until harvest maturity based on daily time steps. The objective of this study was to calibration and evaluation of the dynamic simulation model CERES- Wheat of DSSA T 4 in Golestan province. Experimental data for two seasons were used for model calibration and evaluation. The experiment conducted during the 2001-02 growing season was used to calibrate the model, and the experiment conducted during the 2002-03 growing season was used for model evaluation. When using a crop model for any application, one first has to estimate the cultivar characteristics if they have not been previously determined. To calculate the used cultivar coefficients required by the CERES- Wheat model, we estimated the coefficients for genotypes by iteratively running the crop model with an approximate value of the coefficients concerned, comparing the simulated and measured data, and then altering the cultivar coefficient until the simulated and measured values match or are within predefined error limits. Crop coeffeients which were calculated were PIV, PID, PS, Gl, G2, G3 and PRINT. Then second year data were used to evaluate the model. Results showed that the model have simulated phenologycal process, leaf area index (LAI), biomass and grain yield reasonably well. The validation results showed that the discrepancies between observed and simulated values are generally small in both years. The statistical parameters of MPE, RMSD and MBE indicate that the model performed well. Predicting grain yield had a mean percentage error (MPE) equal to 5.78 percent which was 6 percent less than the observed value. Also predicting grain yield had a root mean square difference (RMSD) equal to 0.265 t ha-I. Validation results showed the reliability and good performance of the model. The study also showed that the CERES Wheat of DSSA T model may be applied with confidence to study effects of different crop management on wheat yield under golestan province conditions.