Pyramiding of bacterial blight resistance genes into promising restorer BRRI31R line through marker-assisted backcross breeding and evaluation of agro-morphological and physiochemical characteristics of developed resistant restorer lines.

BRRI31R is one of the Bangladesh's most promising restorer lines due to its abundant pollen producing capacity, strong restoring ability, good combining ability, high outcrossing rate and genetically diverse from cytoplasmic male sterile (CMS) line. But the drawback of this line is that it is highly susceptible to bacterial blight (BB) disease of rice caused by Xanthomonas oryzae pv. oryzae. The present study highlighted the pyramiding of effective BB resistance genes (xa5, xa13 and Xa21) into the background of BRRI31R, through marker-assisted backcrossing (MABC). Backcross progenies were confirmed and advanced based on the foreground selection of target genes. Pyramided lines were used for pathogenicity test against five Bangladeshi Xanthomonas oryzae (BXo) races (BXo93, BXo220, BXo822, BXo826, BXo887) and confirmed the dominant fertility restore genes, Rf3 and Rf4 and further validated against SNP markers for more confirmation of target resistance genes. All pyramided restorer lines consisted of Xa4 (in built), xa5, xa13, Xa21, and Chalk5 with two fertility restorer genes, Rf3, Rf4. and these restorer lines showed intermediate amylose content (<25%). Restorer lines BRRI31R-MASP3 and BRRI31R-MASP4 showed high levels of resistance against five virulent BXo races and SNP genotyping revealed that these lines also contained a blast resistance gene Pita races. Gene pyramided restorer lines, BRRI31R-MASP3 and BRRI31R-MASP4 can directly be used as a male parent for the development of new BB resistant hybrid rice variety or could be used as a replacement of restorer line of BRRI hybrid dhan5 and 7 to enhance the quality of hybrid seeds as well as rice production in Bangladesh.

Green synthesis and characterization of silver nanoparticles and its efficacy against Rhizoctonia solani, a fungus causing sheath blight disease in rice.

Rice (Oryza sativa) stands as a crucial staple food worldwide, especially in Bangladesh, where it ranks as the third-largest producer. However, intensified cultivation has made high-yielding rice varieties susceptible to various biotic stresses, notably sheath blight caused by Rhizoctonia solani, which inflicts significant yield losses annually. Traditional fungicides, though effective, pose environmental and health risks. To address this, nanotechnology emerges as a promising avenue, leveraging the antimicrobial properties of nanoparticles like silver nanoparticles (AgNPs). This study explored the green synthesis of AgNPs using Ipomoea carnea leaf extract and silver nitrate (AgNO3), and also examined their efficacy against sheath blight disease in rice. The biosynthesized AgNPs were characterized through various analytical techniques such as UV-vis spectrophotometer, X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), Particle size analyzer, Zeta potential, Scanning Electron Microscope (SEM), Field Emission Scanning Electron Microscope (FESEM), Transmission Electron Microscope (TEM) for confirming their successful production and crystalline nature of nanoparticles. The results of UV-visible spectrophotometers revealed an absorption peak ranging from 421 to 434 nm, validated the synthesis of AgNPs in the solution. XRD, DLS, and TEM estimated AgNPs sizes were ~45 nm, 66.2nm, and 46.38 to 73.81 nm, respectively. SEM and FESEM demonstrated that the synthesized AgNPs were spherical in shape. In vitro assays demonstrated the significant inhibitory effects of AgNPs on mycelial growth of Rhizoctonia solani, particularly at higher concentrations and pH levels. Further greenhouse and field experiments validated the antifungal efficacy of AgNPs against sheath blight disease in rice, exhibiting comparable effectiveness to commercial fungicides. The findings highlight the potential of AgNPs as a sustainable and effective alternative for managing rice sheath blight disease, offering a safer solution amidst environmental concerns associated with conventional fungicides.

Salicylic Acid Priming Improves Cotton Seedling Heat Tolerance through Photosynthetic Pigment Preservation, Enhanced Antioxidant Activity, and Osmoprotectant Levels.

The escalating global temperatures associated with climate change are detrimental to plant growth and development, leading to significant reductions in crop yields worldwide. Our research demonstrates that salicylic acid (SA), a phytohormone known for its growth-promoting properties, is crucial in enhancing heat tolerance in cotton (Gossypium hirsutum). This enhancement is achieved through modifications in various biochemical, physiological, and growth parameters. Under heat stress, cotton plants typically show significant growth disturbances, including leaf wilting, stunted growth, and reduced biomass. However, priming cotton plants with 1 mM SA significantly mitigated these adverse effects, evidenced by increases in shoot dry mass, leaf-water content, and chlorophyll concentrations in the heat-stressed plants. Heat stress also prompted an increase in hydrogen peroxide levels-a key reactive oxygen species-resulting in heightened electrolyte leakage and elevated malondialdehyde concentrations, which indicate severe impacts on cellular membrane integrity and oxidative stress. Remarkably, SA treatment significantly reduced these oxidative stresses by enhancing the activities of critical antioxidant enzymes, such as catalase, glutathione S-transferase, and ascorbate peroxidase. Additionally, the elevated levels of total soluble sugars in SA-treated plants enhanced osmotic regulation under heat stress. Overall, our findings reveal that SA-triggered protective mechanisms not only preserve photosynthetic pigments but also ameliorate oxidative stress and boost plant resilience in the face of elevated temperatures. In conclusion, the application of 1 mM SA is highly effective in enhancing heat tolerance in cotton and is recommended for field trials before being commercially used to improve crop resilience under increasing global temperatures.

Spatiotemporal mapping of rice acreage and productivity growth in Bangladesh.

Technological advancements have long played crucial roles in rice productivity and food security in Bangladesh. Seasonal variation over time and regional differences in rice production, however, pose a threat to agricultural sustainability but remain unexplored. We performed a spatial-temporal mapping of rice cultivation area, production, and yield from 2006-2007 to 2019-2020 using secondary data for disaggregating 64 districts in Bangladesh. Growth and multivariate approaches were employed to analyze time-series data. Results showed that Mymensingh had the highest rice cultivated area and production, while Bandarban had the lowest. The 14 years highest average rice yield was found in Gopalganj and Dhaka (3.63 tons/ha), while Patuakhali (1.73 tons/ha) had the lowest. For the Aus, Aman, and Boro, the rice cultivation area in 19 districts, 11 districts, and 13 districts declined significantly. The overall rice production increased significantly in most districts. For the Aus, Aman, and Boro seasons, the rice yield in 54, 50, and 37 districts demonstrated a significant upward trend, respectively. The adoption rate of modern varieties has risen dramatically. However, there are notable variances between regions and seasons. A significant increasing trend in Aus (0.007% to 0.521%), Aman (0.004% to 0.039%), and Boro (0.013% to 0.584%) were observed in 28, 34, and 36 districts, respectively, with an increase of 1% adaptation of HYV. Predictions revealed that rice cultivation area and production of Aus, Aman, and Boro seasons will be increased in most of the regions of Bangladesh by 2030. Based on spatiotemporal cluster analysis, the five identified cluster groupings illustrated that clusters lack spatial cohesion and vary greatly seasonally. This suggests increasing rice production by expanding cultivable land, adopting high-yielding varieties, and integrating faster technological advancement in research and extension. The findings will assist scientists in developing region-specific production technologies and policymakers in designing decentral region-specific policies to ensure the future sustainability of rice production.

Exploring the antioxidant and antimicrobial potential of three common seaweeds of Saint Martin's Island of Bangladesh.

Antioxidants, which have long been deemed an indispensable guardian of human health, play a pivotal role in bolstering the body's defense against a plethora of diseases. Three well-recognized seaweeds in Bangladesh, including Caulerpa racemosa, Padina tetrastromatica, and Hypnea musciformis, were subjected to meticulous analysis to reveal their phytochemical composition, antioxidant activity, and antimicrobial efficacy using advanced spectroscopic and disc diffusion methods. Intriguingly, we observed that C. racemosa emerges as frontrunners, possessing a substantial arsenal of phenol (143.08 ± 18.51 mg gallic acid equivalent g─1) and flavonoid (63.79 ± 2.16 mg rutin equivalent g─1). More fundamentally, C. racemosa exhibits a notable enrichment in the content of tannin (73.58 mg RE g─1) and chlorophyll (13.50 mg g─1), as well as, antioxidant capacity (4457.67 µg g─1). P. tetrastromatica, on the other hand, displayed commendable effectiveness in scavenging the DPPH radical, with percentages ranging from 53.98 to 62.17%. In terms of hydroxyl radical (OH•) scavenging activity, C. racemosa exhibited the highest efficacy at 400 g mL─1. Fascinatingly, C. racemosa exhibited an impressive antioxidant potential, as evidenced by its exceptionally low IC50 value of 5.58 µg mL-1 for OH• scavenging, whereas P. tetrastromatica showed impressively low value of 0.96 µg mL-1 for DPPH scavenging. Although the three seaweeds demonstrated limited efficacy against a spectrum of five human pathogenic bacteria, their potential as abundant sources of antioxidants remains unscathed. Notably, heatmap and PCA analysis revealed that C. racemosa and P. tetrastromatica emerge as the leading contender for studied antioxidant compounds, demonstrating their proclivity for antioxidant extraction, a trait that could be exploited for large-scale production of these valuable compounds.

Identification of influential weather parameters and seasonal drought prediction in Bangladesh using machine learning algorithm.

Droughts pose a severe environmental risk in countries that rely heavily on agriculture, resulting in heightened levels of concern regarding food security and livelihood enhancement. Bangladesh is highly susceptible to environmental hazards, with droughts further exacerbating the precarious situation for its 170 million inhabitants. Therefore, we are endeavouring to highlight the identification of the relative importance of climatic attributes and the estimation of the seasonal intensity and frequency of droughts in Bangladesh. With a period of forty years (1981-2020) of weather data, sophisticated machine learning (ML) methods were employed to classify 35 agroclimatic regions into dry or wet conditions using nine weather parameters, as determined by the Standardized Precipitation Evapotranspiration Index (SPEI). Out of 24 ML algorithms, the four best ML methods, ranger, bagEarth, support vector machine, and random forest (RF) have been identified for the prediction of multi-scale drought indices. The RF classifier and the Boruta algorithms shows that water balance, precipitation, maximum and minimum temperature have a higher influence on drought intensity and occurrence across Bangladesh. The trend of spatio-temporal analysis indicates, drought intensity has decreased over time, but return time has increased. There was significant variation in changing the spatial nature of drought intensity. Spatially, the drought intensity shifted from the northern to central and southern zones of Bangladesh, which had an adverse impact on crop production and the livelihood of rural and urban households. So, this precise study has important implications for the understanding of drought prediction and how to best mitigate its impacts. Additionally, the study emphasizes the need for better collaboration between relevant stakeholders, such as policymakers, researchers, communities, and local actors, to develop effective adaptation strategies and increase monitoring of weather conditions for the meticulous management of droughts in Bangladesh.