Bangladesh Agricultural University (Bengali: বাংলাদেশ কৃষি বিশ্ববিদ্যালয়, Bangladesh Krishi Bishshobiddalôe), abbreviated as BAU, was established as the only university of its kind in Bangladesh in 1961. The scheme for BAU was finalised on 8 June 1961 and its ordinance was promulgated on 18 August 1961. It started functioning with the College of Veterinary Science and Animal Husbandry at Mymensingh as its nucleus. The university has six faculties and 43 departments covering all aspects of agricultural education and research.BAU was the second highest budgeted public university in Bangladesh for the year 2013–2014. It is ranked number one university of Bangladesh according to the webmatrix university ranking 2017.
The Ganges Delta, largely situated in Bangladesh, is one of the world’s most densely populated and climate-exposed regions, where environmental vulnerability intersects with persistent poverty. Although national poverty trends are well documented, systematic evidence from designated climate hotspots remains limited. We address this knowledge gap by examining poverty trends and factors associated with poverty across seven climatic hotspots identified in the Bangladesh Delta Plan 2100, using 93,601 repeated cross-sectional household observations from 1995 to 2019. Results show a substantial decline in poverty across all hotspots over the past two decades; however, progress has been spatially uneven. Persistent deprivation remains pronounced in the Barind and drought-prone areas, followed by relatively less hazard-prone (RLHP), estuarine, coastal, haor and flood, hill, and urban regions. These disparities are associated with environmental stress, limited livelihood diversification, infrastructural deficits, restricted service access, and weak social capital. Extreme poverty in several hotspots remains both persistent and volatile, indicating continued structural vulnerability despite aggregate improvements. A dynamic within-cohort fixed-effects pseudo-panel regression reveals that human capital accumulation, economic transformation, improved living standards, digital access, gender equity, and social capital significantly reduce poverty risk, whereas adverse health conditions, demographic pressures, and exposure to climatic shocks exacerbate it. Across hotspots, we identify a structural climate–poverty paradox: environmental stressors heighten consumption volatility and erode welfare gains even amid economic progress. Robustness checks using a nonparametric two-stage copula control function to address endogeneity corroborate these findings. Overall, the study underscores the need for spatially differentiated, climate-responsive policies rather than centralized poverty reduction strategies.
Climate change puts Bangladeshi fish farming households at high risk for production. It poses serious impact on nutritional availability, livelihood, poverty, and income. The study aimed to assess the short and long run impacts on fish production in Bangladesh by utilizing climatic and non-climatic factors. Annual time series data spanning 45 years, from 1978 to 2022, were used in this study. The Autoregressive Distributed Lag (ARDL) technique and the Johansen cointegration test were used for validating short and long run relationships. The results of the bound test confirm that climate and non-climate variables and fish production have a long run association. The ARDL results indicate that pesticide use exerts a significant positive effect on fish production in both the short and long run, suggesting that its’ controlled application may enhance disease management and thereby improve overall productivity. The long run impacts of rainfall on fish production were also favorable, while the short and long run effects of temperature on fish production were negative. Our findings are confirmed to be robust by CUSUM and CUSUM squared tests, which showed that the model residuals show no signs of structural instability. Findings of the study highlight the importance of climate resilient fish production policies and practices to mitigate the effects. In order to guarantee a resilient aquaculture sub-sector and sustainable fish production, a comprehensive plan combining sustainable practices, technical advancements, and strong governmental frameworks is required.
The salt-tolerant genes (STGs) play important roles in protecting plants against salt stress. Although various types of STGs have been systematically characterized in plant species, the key genes (KGs) regulating salt stress tolerance in rice (Oryza sativa L.) remain elusive. This study focused on the identification and characterization of the members of STGs in rice through integrated bioinformatic and molecular approaches, including chromosomal location, physicochemical characteristics, protein–protein interaction, and expression profiles of the identified genes. A total of 164 differentially expressed genes (DEGs) were systematically identified as responsive to salt tolerance and sorted out potential 12 kg (OsHSP20.2, OsGFP2, OsBBTI2, OsEN20.6, OsUBC17, OsACD5, OsPEAB5, OsDP11, OsDFP5, OsWD40.7, OsEP11.1, and OsGRAM12) through the CytoHubba algorithms analysis. Physicochemical characterization indicated substantial variation among KGs, including genomic sequences (824–4051 bp), amino acid length (148–659 aa), molecular weight (16.39–71.35 kDa), and isoelectric point (4.66–10.37). Protein–protein interaction (PPI) network prediction indicated intricate functional associations among key STGs. Gene Ontology (GO) enrichment analysis revealed that the KGs are involved in numerous biological processes and molecular functions. Moreover, gene homology results revealed that KGs have multiple relationships with other plant species. Co-expression network analysis revealed that 12 kg are potentially involved in the regulatory mechanisms underlying the biological process. Relative gene expression through the comparative threshold (ΔΔCT) of qRT-PCR revealed that the KGs are salt-induced and may play crucial roles in rice responses to salt stress. Tissue-specific expression patterns revealed that the KGs significantly altered expression levels across different tissues and under stress. This systematic investigation demonstrated that the 12 identified genes may play roles in the development of salt-tolerant rice varieties.
Zinc deficiency is major constraint in lentil (Lens culinaris Medik.) production, affecting crop yields and nutritional quality. This study aimed to evaluate the efficacy of diverse zinc application strategies on productivity, seed quality, profitability, and zinc use efficiency of diverse lentil genotypes. Factorial experiment was conducted in pot and field settings to evaluate 18 treatment combinations, comprised three lentil genotypes (BARI Masur-3, BARI Masur-5, BARI Masur-8) and six zinc application strategies (soil, foliar, seed priming and their combinations). Treatment T4 (50
Environmental decision-makers increasingly confront non-stationary systems where predictive models fail, yet management actions remain urgent. Conventional approaches assume sufficient data and stability for forecasting, but these assumptions are often violated in data-limited contexts of the Global South. We present a diagnostic forecasting framework that acknowledges irreducible uncertainty and provides decision-support tools for adaptive governance. Rather than pursuing complex models that may produce misleading precision under irreducible uncertainty, our framework emphasizes diagnostic capacity: understanding system state, identifying stressors, decomposing uncertainty, and preparing for plausible futures. Applied to a 35-year wetland fisheries dataset from Bangladesh, model selection uncertainty contributed 40
