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Calibration and Validation of Decision Support System for Agro-technology Transfer Model for Simulating Growth and Yield of Maize in Bangladesh

F. Ahmed
Bangladesh Agricultural Research Institute, Gazipur, Bangladesh

Apurba K. Choudhury
Bangladesh Agricultural Research Institute, Gazipur, Bangladesh

S. Akhter
Bangladesh Agricultural Research Institute, Gazipur, Bangladesh

M. A. Aziz
Bangladesh Agricultural Research Institute, Gazipur, Bangladesh

Jatish C. Biswas
Bangladesh Rice Research Institute, Gazipur, Bangladesh

M. Maniruzzaman
Bangladesh Rice Research Institute, Gazipur, Bangladesh

M. Main Uddin Miah
Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh

M. M. Rahman
Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh

M. A. H. S. Jahan
Bangladesh Agricultural Research Institute, Gazipur, Bangladesh

Imrul Mosaddek Ahmed
Bangladesh Agricultural Research Institute, Gazipur, Bangladesh

R. Sen
Bangladesh Agricultural Research Institute, Gazipur, Bangladesh

S. Ishtiaque
Bangladesh Agricultural Research Institute, Gazipur, Bangladesh

A. F. M. Tariqul Islam
Bangladesh Agricultural Research Institute, Gazipur, Bangladesh

M. M. Haque
Bangladesh Rice Research Institute, Gazipur, Bangladesh

M. Belal Hossain
Bangladesh Rice Research Institute, Gazipur, Bangladesh

Naveen Kalra
Consultant CRP-II Project, KGF, Dhaka, Bangladesh

M. Hafijur Rahman
Bangladesh Agricultural Research Institute, Gazipur, Bangladesh

Abstract/ Executive Summary:

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 the Genotype coefficient calculator (GENCALC) and the Generalized likelihood uncertainty estimation (GLUE) module of DSSAT on the basis of first season experiment. The performance of the model was satisfactory and within 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.

Keywords: Calibration, Validation, DSSAT Model and Maize

Location: Bangladesh

Start Date:

End Date:

Program Area: Knowledge Management

Non-commodity: Modeling

Objectives:

The present study was undertaken to evaluate the coefficients of four maize cultivars adapted in Bangladesh. Specific objectives were to determine maize crop growth and development indices under optimum growing conditions, to compute maize cultivars coefficients and calibrate DSSAT model for assessing growth and yield of maize under various biotic and abiotic stresses.

Methodology:

2.1. Field Experiments Site description: 8 m above mean sea level. The study area experiences a sub-tropical monsoon climate. Seventy percent of the total rainfall is received during July to September, with average annual rainfall of 2148 mm. April is the hottest month, with average minimum and maximum temperatures of 23.6⁰C and 33.7⁰C, respectively. The coldest month is December where the average minimum and maximum temperatures are 14.1⁰C and 26.4⁰C, respectively. Average sunshine hours are 6.52 hr^-1day⁻¹ . The soils of the study site were characterized as silt clay loam with moderate drainage. 2.2. DSSAT (CERES-Maize) Model DSSAT was developed by an international network of scientists, cooperating in the International Benchmark Sites Network for Agrotechnology Transfer project (IBSNAT Project). DSSAT version 4.6 was utilized for the study. The DSSAT simulate crop growth, development and yield using a defined data set on crop management, minimum weather data and soil profile parameters. Some of the crop management data required to simulate DSSAT include crop, cultivar, planting date, row and plant spacing, fertilizer-N levels, tillage practices and organic amendments. 2.3. Field Experiments for Model Calibration and Validation Two field experiments were carried out at the research field of Plant Physiology Division, BARI, Gazipur during rabi seasons of 2014-15 and 2015-16. The crops were grown under no stress condition. First year’s data were s used to calibrate genetic coefficients and second year’s data were used for the validation of model. 2.4. Data Collection Soil characterization: Before conducting experiments, soil samples from 0 - 15, 15 - 30, 30 - 60, 60 - 90 and 90 - 120 cm depths were collected. The soil samples were analyzed for texture, bulk density, soil moisture, pH, organic matter, total N, field capacity, wilting point, bulk density, nitrate (NO_{3 −} ) and ammonium (NH_{4 +} ) concentrations. Results of various physico-chemical properties of soil have been summarized. Hydraulic conductivity, bulk density and saturated moisture content were derived from the in-built pedotransfer functions module of SOIL of DSSAT. 2.5. Weather Information Daily weather data for both the growing seasons, including precipitation (mm), minimum and maximum air temperatures (?C), and sunshine hours were collated from the weather observatory. Solar radiation (MJm−2 d−1 ) was calculated from daily sunshine hours by using Weatherman of DSSAT. The weather files were created by using WEATHERMAN module of DSSAT for running of the model. 2.6. Growth, Yield and Yield Attributes Recording Phenology: Every day we visited the crop field and recorded phonological information in terms of number of days required for attaining a particular growth stage. Ten plants from each plot were tagged at two-leaf stage which was used for destructive sampling to determine tassel initiation stage. Three randomly located plants of each cultivar from each replication were removed at regular intervals (every 2 - 3 day) starting from 12 days after emergence. The apex was dissected under a stereoscopic microscope and observed carefully. When the tip of tassel was visible under microscope data was recorded. Fifty percentage tasseling date was recorded when tasseling was noticed in 50% of tagged plants. For observing physiological maturity we collected grains from different parts of the selected cobs like base, middle and tip when the cob became straw color at 2 - 3 days interval. We recorded physiological maturity date when 50% of the grains showed black layer which indicate that no further accumulation of assimilates in grain is possible.

Source of Information: American Journal of Plant Sciences, 2017, 8, 1632-1645 http://www.scirp.org/journal/ajps ISSN Online: 2158-2750 ISSN Print: 2158-2742

Article Link (Online Journal):

Funding Source:

1.

Budget:

Total Budget (Tk.) :

Achievement/Findings:

Maize has taken an important place among cereal crops of Bangladesh after the introduction of hybrid genotypes. It is necessary to understand the growth behavior of hybrid maize in different production environment, especially to address future climate change impacts. Since crop growth model plays an important role in delineating variability study performances, The DSSAT was calibrated and validated for Gazipur environment using field experimental data. The performance of the model was evaluated through phenology, biomass at harvest, leaf area index and grain yield. The simulated results were in close agreement with the observed values and these were within the statistical significance limit. Biomass, to some extent, was over predicted by the simulation but within significant limit. Simulated and observed phenology and yields were in close agreement with the observed values. It can be inferred that the DSSAT version 4.6 can be successfully employed for simulating the growth and yield of maize hybrids grown under various biotic and abiotic stresses, including evaluation of the climate change impact analysis in Bangladesh.

Knowledge Management: Journal