Abdullah Al Mahmud

Soil salinity is a major abiotic stressor that inhibits plant growth. Arbuscular mycorrhizal fungi (AMF) form symbiotic relationships with plants that can enhance their tolerance to such stresses. This study evaluated the efficacy of AMF in mitigating salt stress in three plant species. Sorghum bicolor, Sesbania sesban, and Cassia tora were cultivated under greenhouse conditions for five months. Plants were subjected to four salinity levels (0, 2.5, 5.0, and 7.5 dS m^-1) with or without AMF inoculation. Growth parameters (plant height, leaf number, fresh and dry weight of shoots and roots, relative growth rate (RGR), and root-to-shoot ratio (RSR)) were measured. The percentage of root colonization by AMF structures (mycelium, vesicles, arbuscules) was also assessed. AMF colonization rates were highest at the lowest salinity level (2.5 dS m^-1) and declined significantly at 7.5 dS m^-1. Sesbania sesban showed the highest colonization rate (90%), followed by Sorghum bicolor and Cassia tora. Inoculation with AMF significantly improved all growth parameters under salt stress, particularly at 2.5 dS m^-1. Sorghum bicolor demonstrated the highest tolerance, with AMF-inoculated plants showing remarkable improvements in RGR and biomass even at 7.5 dS m^-1. AMF symbiosis significantly enhances salt stress tolerance in the studied species, with the effectiveness being species-dependent and inversely correlated with salinity levels. Sorghum bicolor exhibited the greatest potential for AMF-assisted cultivation in saline soils.

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.

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.

Spine tumor, a severe disease, has affected and destroyed many lives. This disease has been the center of attraction of thousands of researchers for many decades, around the world. Researchers have combined their knowledge and efforts from many areas ranging from medical to mathematical sciences, to better understand the disease and to find more effective treatments. The key objective of this paper is to form a methodology for detection and extraction of spine tumor from a patient’s MRI. This method incorporates with some noise removal functions, segmentation and morphological operations which are the basic needs of image processing. Proposed methodology will detect tumor and finally the fractional area of spine tumor will be calculated. All of this processing will be done by MATLAB software.