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Article citations


Sarkar, R. and Kar, S. (2006) Evaluation of Management Strategies for Sustainable Rice-Wheat Cropping System, Using DSSAT Seasonal Analysis. Journal of Agricultural Science, 144, 421-434.

has been cited by the following article:

  • TITLE: Calibration and Validation of Decision Support System for Agro-Technology Transfer Model for Simulating Growth and Yield of Maize in Bangladesh

    AUTHORS: F. Ahmed, Apurba K. Choudhury, S. Akhter, M. A. Aziz, Jatish C. Biswas, M. Maniruzzaman, M. Main Uddin Miah, M. M. Rahman, M. A. H. S. Jahan, Imrul Mosaddek Ahmed, R. Sen, S. Ishtiaque, A. F. M. Tariqul Islam, M. M. Haque, M. Belal Hossain, Naveen Kalra, M. Hafijur Rahman

    KEYWORDS: Calibration, Validation, DSSAT Model and Maize

    JOURNAL NAME: American Journal of Plant Sciences, Vol.8 No.7, June 23, 2017

    ABSTRACT: Maize is an emerging important crop in Bangladesh because of its high yield potential and economic profitability compared to rice and wheat crops. There is a need to understand the growth and yield behavior of this crop in varying production environments of Bangladesh. Crop model such as Decision Support System For Agro-technology Transfer (DSSAT) version 4.6 (DSSAT hereafter) can be utilized cost effectively to study the performances of maize under different production environments. It needs to calibrate and validate DSSAT model for commonly cultivated maize cultivars in Bangladesh and subsequently take the model to various applications, including inputs and agronomic management options and climate change that impacts analyses. So, the present study was undertaken to firstly calibrate DSSAT model for popular four hybrid maize cultivars (BARI Hybrid Maize-7, BARI Hybrid Maize-9, Pioneer 30B07 and NK-40). Subsequently, it proceeded with the validation with independent field data sets for evaluating their growth performances. The genetic coefficients for these cultivars were evaluated by using Genotype coefficient calculator (GENCALC) and Generalized likelihood uncertainty estimation (GLUE) module of DSSAT on the basis of first season experiment. The performance of the model was satisfactory and within the significant limits. After calibration, the model was tested for its performance through validation procedure by using second season data. The model performed satisfactorily through phenology, biomass, leaf area index (LAI) and grain yield. Phenology, as estimated through days to flower initiation and maturity, was in good agreement, although simulated results were slightly over predicted compared to observed values but within the statistical significance limit...when compared with observed values at specific growth stages of the crop. The final yield values (10.12 to 10.59 t·ha-1) were in close agreement with the observed values (10.16 to 10.94 t·ha-1), as the percentage error was within tolerable limit (0.39% to 6.81%). The model has been successfully calibrated and validated for Gazipur environment and now can be used for climate change impact studies for similar environments in Bangladesh.