A timely and reliable system of maize yield forecasting well in advance is prime emphasis to farmers and other people who are dependent on cereal crop. The best model was generated using maize field experiment trial which was conducted at Dorbasta union of Gobindagonj upazila, Gaibandha during two consecutive Rabi crops growing season 2018-19 and 2019-20. Randomized Complete Block Design (RCBD) along with five treatments (or varieties) and three replications were considered for maize yield performance. The agronomical and weather parameters and also, satellite data (Landsat 8 OLI) were used for the required maize field experiment. We found that Normalized Difference Vegetation Index (NDVI) was strongly positively correlated with the weather variables in this study. Stepwise regression method was applied for generating best estimated model. Best estimated model (Backward elimination) showed that only five controlled variables which were variety 5 (BHM 13), 1000 grain weight, diameter of cob, plant height and NDVI that were factors to the yield of maize. The developed maize yield forecast model (ideal model) including agronomical, weather and satellite data give the better results of yield estimation at regional level on the basis of best model criterion. Therefore, the ideal model used in specific region including all types of data that gives more precise result on maize yield or production that should be more significant and reliable in national level. So, the researcher, policymaker can use this maize yield prediction model forty to fifty days earlier of harvesting time.
Bangladesh J. Agril. Res. 48(4): 433-449, December 2023
N. Mohammad, MA Islam, MM Rahman et al.· Bangladesh Journal of Agricu...· 0 citations
The present study was conducted to evaluate sixteen cauliflower (Brassica oleracea var. botrytis L.) genotypes under the agro-climatic conditions of Gazipur, Bangladesh during 07 November 2024 to 24 February2025, to find out their variability, character association and path coefficient of curd yield and its related traits at the Research Field of Olericulture Division of Horticulture Research Center, Bangladesh Agriculture Research Institute. The experiment was laid out in a randomized complete block design with three replications. Significant variation (p ≤ 0.001) was observed among genotypes for all traits, indicating ample genetic diversity suitable for selection and improvement of cauliflower. Early maturing genotypes such as CL-1, CL-2, and CL-4 showed the shortest duration for curd initiation and harvest but produced smaller curds and lower yields. In contrast, Cl-5, CL-7, CL-9, CL-12 and CL-13 recorded superior vegetative growth, larger curd size and the highest curd yield per hectare (58.56-67.07 t/ha). High heritability coupled with high genetic advance as percent of mean for traits such as whole plant weight, marketable curd weight, days to first curd initiation, days to fifty percent curd initiation and net curd weight indicated that additive gene effects play a major role and simple selection methods would be successful. However, the less deviations between phenotypic coefficient of variation and genotypic coefficient of variation suggested low influence of growing environment for all traits and these traits are mostly controlled by gene. Correlation and path coefficient analyses revealed that days to first curd initiation, whole plant weight, marketable curd weight, curd breadth, and leaf length had strong positive associations and direct effects on curd yield, identifying them as major selection indices, suggesting these traits as key selection criteria for curd yield improvement in cauliflower genotypes.
Bangladesh J. Agril. Res. 50(4): 407-421, December 2025
MA Islam, S. Akter, Mh Islam et al.· Bangladesh Journal of Agricu...· 0 citations
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