Alternate wetting and drying (AWD) irrigation in lowland rice cultivation increases water use efficiency and could reduce greenhouse gas (GHG) emissions compared to the farmers' practice of continuous flooding (CF). However, there is a dearth of studies on the impacts of water management on methane (CH4) and nitrous oxide (N2O) emissions in Bangladesh. Multi-location field experiments were conducted during the dry seasons of 2018 and 2019 to determine the baseline emissions of CH4 and N2O from rice fields and compare the emissions from AWD irrigation and CF. CH4 and N2O emissions were measured using the closed chamber technique and their concentrations were determined using a gas chromatograph. CH4 and N2O emissions varied across water management schemes and sites. AWD irrigation significantly (p < 0.05) reduced cumulative CH4 emissions (37%, average across sites) without affecting grain yields compared to CF. The CH4 emission factor for AWD was lower (1.39 kg ha-1 day-1) compared to CF (2.21 kg ha-1 day-1). Although AWD irrigation increased seasonal cumulative N2O emissions by 46%, it did not offset reduced CH4 emissions. AWD reduced the total global warming potential (GWP) by 36% compared to CF. Similarly, GHG intensity (GHGI) in AWD was 34% smaller compared to that in CF. Emissions varied across sites and the magnitudes of seasonal cumulative CH4 and N2O emissions were higher at the Gazipur site compared to the Mymensingh site. AWD, which saves irrigation water without any yield penalty, could be considered a promising strategy to mitigate GHG emissions from rice fields in Bangladesh.

We examined the effects of zinc (Zn) fertilization on wheat, focusing on yield and biofortification in the grains of two wheat varieties. Five Zn rates, i.e., 0, 1.5, 3.0, 4.5, and 6.0 kg ha−1 applied as ZnSO4·7H2O (23% Zn), and two wheat varieties, i.e., ‘BARI Gom-25’ and ‘BARI Gom-26,’ were used in the study. All plant characteristics, except 1,000-grain weight and plant height, i.e., tillers plant−1, spikes m−2, spike length, spikelets spike−1, and grains spike−1, were significantly influenced by Zn fertilization. Treatment with 3.0 kg Zn ha−1 (Zn3.0) produced the highest grain yield (3.90 t ha−1), which was statistically similar to Zn4.5 and Zn6.0 treatments. The control treatment (Zn0) produced the lowest grain yield (2.99 t ha−1). The concentrations of N, Zn, and Fe were significantly and positively influenced by Zn treatment. The crop varieties did not differ significantly in terms of N and Zn concentrations. However, the grain Fe concentration was remarkably higher in ‘BARI Gom-26’ than in ‘BARI Gom-25.’ The grain N and protein concentrations increased linearly with the Zn application rate. The grain Zn concentration increased with Zn application rates in a quadratic line, indicating that the concentration of Zn in wheat grain increased with Zn fertilization; however, it attained a maximum value in the Zn4.5 treatment, after which it declined with higher rate of Zn application. The application of Zn at the rate of 4.5 kg ha−1 resulted in the highest Zn fortification (39.7 µg g−1) in wheat grains, which was 17.1% higher than in the control treatment. The response curve showed that 4.62 kg ha−1 for ‘BARI Gom-25’ and 3.94 kg ha−1 for ‘BARI Gom-26’ were the optimum Zn rates for achieving higher wheat grain yield. However, 5.5 kg ha−1 was the optimum Zn rate for obtaining higher Zn fortification in wheat grains.

Mahoni is a medical plant which have the potential as drug. The aims of this research were to analysis phytochemical content and to test the toxicity of ethanol extract of seed from Mahoni. The Phytochemicals that analyzed were total phenolic, total flavonoid and condensed tannin. Toxicity test was assessed using BSLT method. Extraction was done by maseration method using ethanol as the solvent. In BSLT method, the shrimp larvae were placed in a series of test solution of varied concentration. The value of LC50 were obtained based on calculation of shrimp larvae lethality percentage using probit analysis. LC50 values of ethanol extract were 0,95 ppm.

Major malnutrition in Bangladesh is zinc (Zn) and iron (Fe) deficiency as most people commonly depend on cereals, chiefly rice and wheat. The main objectives are to enhance Zn and Fe concentrations through the use of selected varieties and the application of respective fertilizers. Field experiments were conducted at Bangladesh Agricultural University (BAU) farm, Mymensingh (AEZ 9, non-calcareous soil) and at Bangladesh Institute of Nuclear Agriculture (BINA) substation, Ishwardi (AEZ 11, calcareous soil) for two consecutive wheat seasons (2014–15 and 2015–16) with 10 varieties and 15 advanced lines. Varieties BARI Gom 25, 27, 28 & 29 and breeding lines Vijay, HPYT-5, 15 & 21 and BL-1883 have been recognized as Zn-enriched wheat varieties (24–30 μg g⁻¹). Among the genotypes, Zn further increased by 4–8 μg g⁻¹ due to Zn fertilization. Concerning Fe-enriched wheat genotypes (24–30 μg g⁻¹), five varieties viz. Shatabdi, Prodip, BARI Gom 25 & 28 and Sufi, and four lines such as HPYT-12, BL-1883, BL-1040 and Fery-60 have been identified. The grain Fe concentration of wheat genotypes increased when Fe was added, the increment being 6–12 μg g⁻¹. A positive relationship between Zn and N is observed with increased protein content. The grain yield of wheat was increased by 3.8–25.7% due to Zn application over the varieties and locations but Fe addition had no effect. The result of the current study showed that a potential breeding line with appropriate fertilization can improve Zn and Fe levels in wheat grain, without incurring loss to wheat yield.

The main goal of this research is to the detection of spine tumors with the results provided by image processing of the patient’s MRI image. Especially, we focus on the methodology of image processing. We have also discussed the technique of detecting the fractional area of the spine tumor. A spine tumor is difficult to detect. For detecting tumors accurately Magnetic resonance imaging (MRI) is a common approach. It is a non-invasive technique for generating 3-dimensional topographic pictures of the human body. MRI is frequently utilized for the identification of various irregularities in soft tissues, for example, the Spine, lesions, and tumors. Nowadays clinical Image processing is the most difficult and arising field. It has already been mentioned that the main focus of this research is to develop a strategy to identify and extraction of Spine tumors from a patient"s MRI im-ages of the Spine. This technique incorporates segmentation and morphological operations and various noise reduction function which are the fundamental ideas of image processing. Our proposed method will take input from MRI images. Input image will convert to a grayscale image, then it will be adjusted based on the maximum intensity level, for avoiding extra data. For identifying the range of the spine cross-section images will be converted to binary data. It will also calculate the area of the spine cross-section. Then adjusted image will be converting to a binary im-age in order to eliminate the boundary and detect tumor affected area. Finally, we calculate the volume of the tumor with the help of MATLAB software.