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 cr...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.展开更多
Soil quality assessment methods, based on different attributes, are available but not well calibrated/validated for subsequent operational applications. We have developed a method for soil quality index assessment by ...Soil quality assessment methods, based on different attributes, are available but not well calibrated/validated for subsequent operational applications. We have developed a method for soil quality index assessment by considering soil texture, organic carbon, pH, available water, cation exchange capacity, bulk density, total porosity, saturated hydraulic conductivity, salinity, aggregate stability, slope and soil depth. The scoring was done on 0 - 100 scale and the lowest score was assigned to the most limiting factor of crop growth and development. Attribute-wise rating was made by using Macros developed in MS-Excel and IDRISI3.2 was used to delineate the rating maps. About 64.6% soils scored more than 60 and the best soil group (score > 70) was only about 15%. Soil health score, as determined through our method, showed good relationship with wheat yield. Multiplicative response function was more sensitive than simple regression model. The correlation analyses with one or two attributes with most severe stress and relatively with lower rating values showed better predictability of wheat yields. The soil quality index as estimated from principal component analysis having strongly loaded (>0.75) factors showed inferior correlation with grain yields of wheat than geometric mean approach. It is concluded that geometric mean approach for soil health scoring can be utilized in similar environments around the globe with or without further improvement.展开更多
文摘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.
文摘Soil quality assessment methods, based on different attributes, are available but not well calibrated/validated for subsequent operational applications. We have developed a method for soil quality index assessment by considering soil texture, organic carbon, pH, available water, cation exchange capacity, bulk density, total porosity, saturated hydraulic conductivity, salinity, aggregate stability, slope and soil depth. The scoring was done on 0 - 100 scale and the lowest score was assigned to the most limiting factor of crop growth and development. Attribute-wise rating was made by using Macros developed in MS-Excel and IDRISI3.2 was used to delineate the rating maps. About 64.6% soils scored more than 60 and the best soil group (score > 70) was only about 15%. Soil health score, as determined through our method, showed good relationship with wheat yield. Multiplicative response function was more sensitive than simple regression model. The correlation analyses with one or two attributes with most severe stress and relatively with lower rating values showed better predictability of wheat yields. The soil quality index as estimated from principal component analysis having strongly loaded (>0.75) factors showed inferior correlation with grain yields of wheat than geometric mean approach. It is concluded that geometric mean approach for soil health scoring can be utilized in similar environments around the globe with or without further improvement.
