A field experiment was conducted at the experimental farm of Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Salna, Gazipur from November 2013 to May 2014 to determine the effect of nitrogen and herbicide on weed infestation and performance of Boro rice (cv. BRRIdhan28). Five nitrogen doses i.e. 0 , 50.6 , 101.2 , 151.8 and 202.4 kg ha-1 under selected pre-emergence and post-emergence herbicides along with one weed free and control (unweeded) treatment were imposed in the experiment. Nine weed species was found to dominate in the experimental plots where Scirpus maritimus L. showed the maximum visual abundance (58%) followed by Leersia hexandra sw., Paspalam distichum L. and Fimbristylis miliacea L. Post-emergence herbicide contributed to higher control efficiency than that in pre-emergence herbicide. Post-emergence herbicide without receiving nitrogen showed the highest weed control efficiency (97.39) at 60 days after transplanting. Treatment receiving N @ 200.4 kg ha-1 under post-emergence herbicide showed the highest number of tiller per hill (13.00), total dry matter (1568.6 g m-2), panicles per hill (10.60), filled grains per panicle (125.20) and grain yield (6.46 t/ha). N-dose 151.8 kg ha-1 under postemergence herbicide contributed to the second highest grain yield (6.41 t ha-1) with the highest benefit cost ratio of 1.60 but 50.6 kg N ha-1 under post-emergence herbicide showed the maximum Nitrogen use efficiency of 0.49. The study revealed that nitrogen dose up to 151.8 kg ha-1 might be increased above the recommended dose under coverage of a suitable post-emergence herbicide for profitable rice production.Bangladesh Agron. J. 2015, 18(2): 53-63

The experiment was conducted at the Agronomy farm of Sher-e-Bangla Agricultural University to identify the allelopathic effect of Brassica species along with their incorporation methods to control weeds in wheat field. The experiment was assigned in a split-plot design where three cultivated Brassica spp. were in the main plot and five different ways of green Brassica biomass inclusion were in the sub-plot. Brassica crops were uprooted at 30 days after sowing (DAS) and incorporated to the soil @ 0.5 kg m-2 as per treatment. Wheat seeds were sown on December 04, 2007 using 20 cm line to line distance. Weeds e.g., Amaranthus spinosus, A. viridis, Lindernia procumbens, Heliotropium indicum, Polygonum hydropiper, Celosis argentina, Ageratum conyzoides, Brassica kaber and Digitaria ischaemum were not found in the wheat field. Significantly the highest weed dry matter (1.72 g m-2) was found in Brassica juncea plots at 30 DAS but in Brassica napus field (1.44 g m-2) at 50 DAS. The lowest weed dry matter at 30 DAS (0.89 g m-2) was recorded with total incorporation of Brassica biomass to the soil but 50% incorporation and 50% spreading at 50 DAS. The Brassica biomass spreading above ground, mixed with soil and 50% spreading + 50% mixed with soil resulted positively compared to other ways of biomass incorporation. The highest grain yield (3.83 t ha-1) of wheat was given by Brassica juncea when spreaded on the above ground soil.Bangladesh Agron. J. 2014, 17(1): 73-80

Cardiovascular diseases are one of the common causes of high morbidity and mortality all over the world. Usually stroke occur in elderly, but stroke in younger group (age <45 years) are increasingly common now-a-days. The disease can occur in young patients without any apparent risk factors. It is therefore important to exclude all aetiological causes in order to reduce their chances for a subsequent event.Bangladesh Crit Care J September 2016; 4 (2): 123-124

Near Infrared (NIR) Spectroscopy leads a great opportunity to replace the expensive and time-consuming chemical conventional analysis for determination of the quality of meat products. This study was conducted aiming to evaluate the feasibility of NIRS and to establish a rapid assessment method to easily predict the quality of chicken meatball. Samples of meatball (n=123) were collected from Golden Harvest Company of Bangladesh. After collecting sample, spectra were obtained prior to analysis and a total of 369 NIRs were collected and stored in computer by DLP NIR scan Nano Software. To generate reference data 123 meatball samples were analyzed for proximate components, instrumental color CIE L*, a*, b*, and pH of meatball. After that a partial least square regression model for calibration and cross validation were developed for data analysis using The Unscrambler X software. Accuracies of the calibration models were evaluated using the root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), coefficient of calibration (R²C) and coefficient of cross validation (R2 CV). Calibration equations were developed from reference data using partial least squares regressions. The standard deviation is 2.41, 0.14, 2.1, 0.41, 1.31, 0.31, 1.26, 0.38, and 0.38 for L*, a*, b*, pH, DM, moisture, CP, EE and ash respectively which indicates that all values are adequate for analytical purposes. Predictive ability of the models was assessed by coefficient of determination of cross-validation (R2 CV) and root mean square error of cross-validation. Predictions were good (R2 CV=0.84) for lightness (L*), (R2 CV=0.72) for redness (a*), (R2 CV=0.77) for yellowness (b*), (R2 CV=0.78) for pH, (R2 CV=0.73) for CP, (R2 CV=0.83) for EE (R2 CV=0.72) for moisture, (R2 CV=0.72) for DM and (R2 CV=0.74) for ash. From the results, it can be concluded that NIRS can be used for the rapid assessment of physico-chemical traits of chicken meatball.