Plant architecture is a key agronomic trait of peanut (Arachis hypogaea L.), which is closely associated with yield, stress resistance, and suitability for mechanical harvesting. However, research on the genetics and gene mining of peanut plant architecture remains relatively limited, thereby hindering the genetic improvement of peanut plant architecture. Most cultivated peanut varieties exhibit an erect or semi-prostrate growth habit, whereas wild peanut species predominantly display a trailing growth habit. In the present study, a recombinant inbred line (RIL) population, designated as the TI population was developed by crossing the female parent Tifrunner with the male parent IpaDur, a synthetic amphidiploid derived from cross of Arachis ipaënsis × Arachis duranensis. Traits related to plant architecture, including lateral branch angle (LBA), lateral branch length (LBL), main stem height (MSH), main stem thickness (MST), lateral branch thickness (LBT), internode length (IL), number of branches (NBS), and biomass (BIO), were evaluated across three environments. Based on a high-density genetic linkage map, 20 QTLs associated with these traits were identified, which explained 6.04%-18.68% of the phenotypic variance (PVE). A locus controlling LBA, LBL, and MST was mapped to an overlapping interval (122.57-137.18Mb) on chromosome 14. Phenotypic effect analysis revealed that this wild species-derived segment is crucial for controlling the typical morphogenesis of wild-type peanut species. In addition, we identified a set of genotypes derived from cultivated-wild hybrid population, which exhibited the convergence of one or more favorable agronomical traits. Using a cultivar-wild hybrid population, 20 QTLs for plant architecture were identified in peanut. A wild-derived genomic segment was found to control typical wild-type morphogenesis. Novel germplasm pyramiding multiple agronomic favorable traits were selected. This study provides key theoretical insights and valuable resources for utilizing wild species in peanut improvement.

Thermo-responsive hydrogels hold promise in various fields for their reversible phase transition behavior, but often at the expense of high energy consumption from external thermal inputs and volumetric swelling/shrinkage from phase transition. Herein, we present a water-driven phase transition strategy that circumvents thermal triggers while retaining upper critical solution temperature (UCST)-type thermo-responsiveness via enthalpy-entropy compensation. The UCST phase transition arises from entropy loss due to hydrophobic interactions within the hydrogel networks. By modulating the enthalpy/entropy balance, we achieve hydrogels with desired responsiveness, exemplified by a rapid (130s) and quasi-isovolumetric (volume change of 1.2) phase transition under mild conditions (water, 25°C). This strategy leverages water as a stimulus, enabling phase transitions that align with the compatibility requirements of biogenic materials, since the risks related to thermal triggers can be avoided. Our strategy thus offers a pathway to thermo-responsive hydrogels without thermal energy input, while mitigating volumetric instability challenges in practical applications, such as body temperature triggered information encryption and human brain mimic dynamic memory-forgetting.

Biomass ash-derived Fe self-doped zeolites for PMS mediated oxytetracycline degradation: Mechanism, pathways and toxicity evaluation.

Integrated biomass power with CCS and green hydrogen to methanol: A comprehensive thermodynamic, economic analysis and strategic assessment for China

The optimization of hydrodynamic conditions in microbial fuel cells (MFCs) is critical to enhancing both pollutant removal and electricity generation. This study evaluates the impact of impeller-driven mixing applied to anaerobic MFCs on biomass suspension, dye degradation, and power output. Activated sludge (100-300 g/L, equivalent to 2.0-6.0 g/L TS) was combined with a synthetic dye solution and operated under stirring speeds of 25, 75, and 125 rpm. A CFD framework based on the Eulerian multiphase approach and the RNG k-ε turbulence model was implemented in ANSYS Fluent to simulate liquid-solid interactions, predict biomass distribution, and compare the results with experimental measurements. CFD predictions aligned closely with measurements (error < 3%). At 125 rpm, a homogeneous sludge suspension was achieved, preventing sedimentation and promoting optimal substrate-biofilm contact. Under these conditions, dye removal reached 78% and power density increased to 0.951 W/m2. Reduced stirring (25 rpm) caused biomass accumulation at the bottom, lowering color removal to 35% and power density to 0.231 W/m2.

The threat of a global recession due to the global economic slowdown, rising energy prices, and geopolitical instability has prompted Indonesia to strengthen its economic resilience through energy diversification. One alternative being developed is wood-chip-based biomass as a co-firing fuel in coal-fired power plants to reduce dependence on coal. This study aims to analyze the role of Law No. 11 of 2020 on Job Creation in accelerating the development of biomass-fired power plants and its contribution to national economic resilience. The research method used is normative legal analysis with a legislative and conceptual approach. The results of the study indicate that the Job Creation Law accelerates biomass development through risk-based licensing reforms, simplified environmental approvals, and streamlined forestry permits, thereby enhancing legal certainty for renewable energy investments. These policies also support the acceleration of the biomass supply chain and the implementation of co-firing programs in coal-fired power plants. However, their implementation still faces technical challenges, infrastructure limitations, and the need for policy harmonization across sectors. This study concludes that wood-chip-based biomass power plants have the potential to serve as a strategic instrument in strengthening energy security and national economic stability amid the threat of a global recession.

ABSTRACT Dimethyl sulfide (DMS) is a representative reduced sulfur compound that is difficult to oxidize and remove, particularly under the high-humidity conditions commonly encountered in waste-treatment and biomass power plants. In this study, a practical strategy for DMS removal under high-humidity conditions was investigated by combining ozone oxidation with a low-cost iodate-impregnated activated carbon catalyst with moderate catalyst heating. Ozone was generated using a xenon excimer lamp, enabling a compact system design without the need for a pressure-swing adsorption oxygen generator and thereby making the system suitable for small-scale and distributed applications. The DMS removal performance was evaluated using a dynamic adsorption method under relative humidity (RH) conditions of 45% and 90%. At 25 °C and 45% RH, the treatment capacity and reaction rate constant were 15 wt% and 6.9 s−1, respectively, whereas these values decreased to 1.5 wt% and 4.9 s−1 at 25 °C and 90% RH, indicating that water vapor significantly interfered with DMS treatment through preferential adsorption. However, when the catalyst temperature was increased by 10 °C (from 25 °C to 35 °C) under high-humidity conditions, the treatment capacity and reaction rate constant improved to 2.8 wt% and 5.8 s−1, respectively. This enhancement was attributed to the asymmetric adsorption behavior of DMS and water vapor, whereby moderate heating reduced water adsorption and restored sites available for DMS adsorption.

Tomato (Solanum lycopersicum) is a globally important high-value cash crop. However, long-term continuous cropping causes frequent soil-borne diseases and soil microecological imbalance, while overreliance on chemical pesticides leads to pesticide residues and water eutrophication. Plant growth-promoting rhizobacteria (PGPR) are key resources for addressing tomato cultivation challenges, with their functions partly depending on the rhizosphere microenvironment inherently shaped by seedling tray materials. Using rhizosphere soil and substrates of tomato at different growth stages under biomass (BM) and plastic (PM) seedling tray treatments, this study combined culture-independent and culture-dependent techniques to analyze microbial community characteristics and screen high-efficiency PGPR. Results showed that pH and available nitrogen drove microbial community assembly. BM significantly enriched beneficial taxa (e.g., Trichoderma and Bacillus) and enhanced culturable microbial abundance and genetic diversity, while PM enriched potential pathogens (e.g., Fusarium and Pyrenochaeta). The multifunctional strain S25095 from BM, with phosphate-solubilizing, potassium-solubilizing, and indole-3-acetic acid (IAA)-producing abilities, significantly promoted tomato shoot and root growth, outperforming single-functional strains and synthetic consortia. This study reveals the effects of growth stages and seedling tray treatments on tomato rhizosphere microorganisms, providing valuable PGPR resources for tomato cultivation.

Thermodynamic analysis of coconut shell biomass power generation system based on a combined supercritical CO2 Brayton and organic Rankine cycle

Exploratory modeling to estimate major elements contents of woody biomass ash from stokers, fluidized beds and gasification reactors.

Purpose This study aims to investigate the integration of circular economy (CE) within regenerative design (RD) practices, focusing on living-certified buildings under the Living Building Challenge (LBC) as an empirical lens. Given global climate challenges and the building sector's resource demands, it empirically assesses how CE strategies enhance RD to advance United Nations Sustainable Development Goals (SDGs), bridging the gap between theory and practice. It evaluates the extent, patterns and barriers of CE adoption in regenerative projects to identify opportunities for strengthening their coherence. Design/methodology/approach A mixed-method, multiple-case comparative analysis was conducted on 34 projects that achieved full living certification under the LBC as of mid-2025. Data were collected from the International Living Future Institute's project database and supplementary documentation. Qualitative content analysis and quantitative frequency mapping were applied to assess the adoption and co-occurrence of five literature-derived CE strategies, aligned with the Ellen MacArthur Foundation's three CE principles. Findings Material Transparency and closed-loop systems appear in 100% of projects, supporting SDG 12 (Responsible Consumption and Production). Biogenic materials (65%) advance SDG 13 (Climate Action) through carbon reduction and habitat restoration. While Design for Disassembly (15%) and Reverse Logistics (18%) show limited uptake, this constrains progress toward SDG 11 (Sustainable Cities and Communities). Research limitations/implications The limited number of available case studies, reliance on secondary data, variability in reporting detail across projects and potential coder bias may constrain the robustness and generalisability of the results. Practical implications Embedding disassembly requirements, incentivising formal take-back partnerships and expanding the use of regenerative materials are recommended to achieve comprehensive circularity and ecosystem restoration. Originality/value This study provides the first empirical, project-level mapping of CE integration within regenerative design practice with reference to living-certified buildings, offering a replicable analytical framework that bridges the gap between CE theory and regenerative implementation.

Biomass power plants (BPPs) are expanding rapidly, yet the most toxicologically potent nanoscale fraction of its particulate emissions remains poorly quantified. Here, in vitro assays demonstrate that nanomagnetite particles (NMPs) constitute a disproportionately toxic subfraction of fine particles: despite contributing only 2.3% of particle mass, NMPs account for 59% of cytotoxicity. On this basis, we quantify NMP emissions from BPPs by integrating measured NMP concentrations with data-augmented machine-learning models and unit-level activities. The resulting global inventory shows strong spatial disparities, with national average concentrations ranging from 150 to over 2000 mg/kg and total global emissions reaching 230 (92-530) t in 2024. Asia contributes 45% of global emissions, followed by South America (26%) and Europe (20%), driven by differences in feedstock composition, installed capacity, and dust removal performance. Scenario projections further indicate that deployment of advanced dust removal technologies under a carbon-neutrality-oriented pathway could reduce global NMP emissions to 76 t by 2050. These results reveal a previously unrecognized source of nanoscale pollution and provide a quantitative framework for integrating NMPs into future bioenergy and air-quality strategies.

Abstract Background and aims Heavy metal/metalloid contamination in agriculture threatens food safety, with arsenic (As) and cadmium (Cd) commonly accumulating due to industrial activities and certain farming practices. Methods This study evaluated the ability of poultry litter incineration ash (PLIA) to reduce As and Cd uptake in radish. Characterization of PLIA was performed using FTIR, Raman, and XRD. The experiment was established under controlled conditions with the treatments as follows: control, As + Cd, As + Cd + 10 g kg −1 PLIA, As + Cd + 20 g kg −1 PLIA, and As + Cd + 40 g kg −1 PLIA. Results As + Cd treatment increased As from 0.30 to 12 mg kg −1 in leaves and from 0.68 to 132 mg kg −1 in tubers. Cd concentrations increased from 1.58 to 120 mg kg −1 in leaves and from 0.48 to 25.4 mg kg −1 in tubers. PLIA reduced both As and Cd accumulation: the 20 g kg⁻ 1 PLIA dose produced the lowest As concentration in leaves, while 10 g kg −1 resulted in the lowest As in tubers; for Cd, the lowest leaf concentrations occurred at 10–20 g kg −1 , and tuber Cd decreased to 17.6 mg kg −1 with 10 g kg −1 PLIA. Although As + Cd caused slight, non-significant reductions in plant-biomass, PLIA at 10 g kg −1 increased plant dry weight. PLIA improved P and K nutrition but decreased Ca and Mg in tubers, with Mg increasing in leaves. Conclusions PLIA demonstrated strong potential to immobilize As and Cd in soil and reduce their transfer to edible plant tissues. Graphical Abstract

ABSTRACT This study presents an integrated assessment of natural radioactivity and associated radiological hazards in coastal sediments and marine biogenic materials from St. Martin’s Island, the only coral island in Bangladesh. Activity concentrations of 226Ra, 232Th, and 40K (Bq/kg) showed clear matrix-dependent variations, with mean values of 19 ± 1, 31 ± 3, and 320 ± 22 in sands; 20 ± 1, 26 ± 2, and 273 ± 17 in rocks; 10 ± 1, 12 ± 1, and 150 ± 10 in coral skeletons; and 10 ± 1, 9 ± 1, and 110 ± 8 in seashells, respectively. Some of the sediment samples exhibited activity concentrations exceeding global average values, whereas all coral and seashell samples remained well below these reference levels. All evaluated radiological hazard indices were significantly lower than internationally recommended limits, indicating negligible radiological risk for residents, visitors, and associated personnel. This study provides the most comprehensive radiological baseline to date for St. Martin’s Island by offering the first integrated comparison of abiotic (sand and rock) and biogenic (coral skeletons and seashells) marine matrices in the coastal environment. These findings establish a comprehensive radiological baseline that will support future environmental monitoring programs and radiological safety assessments in Bangladesh, particularly for coastal regions where natural and anthropogenic influences may evolve over time.

Prediction of woody biomass ash potential for utilization as fertilizer and cement material

The excessive usage of plastics has resulted in serious environmental challenges along with evidences of distinct imprint on Earth’s geological record. In this study, a plastic-rock formation- plastistone has been identified for the first time from west coast of India in the state of Maharashtra. A plastistone sample was collected from the coastal rocky shore of Diveagar beach and analyzed using microscopic and spectroscopic techniques. The identified plastistone also contained integrated microplastics along with a substantial portion of biogenic materials, such as barnacles, shells of molluscs, and foraminifera. The plastic materials identified in the plastistone were polyamide (nylon 6), polypropylene, polyethylene, and PET (polyethylene terephthalate) based on Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) and Micro-Raman spectroscopy. The source of these plastic materials was identified as fishing gear thereby highlighting concern about plastic waste generated from discarded fishing gears. The findings provide the first evidence of plastistone formations along the Maharashtra coast and emphasize the need to incorporate occurrence of such plastic-rock composites as part of coastal ecological health monitoring protocols.

Although biomass power plants are cleaner than fossil-fuel-based plants, they emit nitrogen dioxide (NO₂), which can degrade urban air quality and pose respiratory health risks. Therefore, reliable estimation (nowcasting) of NO₂ levels around these facilities is crucial for public health and air quality management. This study proposes an adaptive network-based neutrosophic hesitant fuzzy inference system optimized by particle swarm optimization (ANNHFIS-PSO) to estimate NO₂ concentrations near biomass plants in Istanbul. To our knowledge, this is the first adaptive neuro-fuzzy inference system (ANFIS)-based framework that incorporates neutrosophic hesitant fuzzy sets to represent environmental uncertainty. The proposed model integrates a neural network with neutrosophic hesitant fuzzy membership functions and employs a hybrid learning scheme that combines PSO-based global optimization with Adam-based fine-tuning to capture nonlinear relationships. Its performance was benchmarked against multilayer perceptron artificial neural network (MLP-ANN), ANFIS-PSO, grid-search-tuned ANFIS (ANFIS-GS), long short-term memory (LSTM) network and ANNHFIS-GS. Model accuracy was evaluated using metrics including root mean square error (RMSE) and coefficient of determination (R²). On the test dataset, ANNHFIS-PSO achieved an RMSE of 3.6488 µg/m³ and an R² of 0.8938, yielding the lowest RMSE and a high R² among the evaluated models. These results suggest that the proposed approach may support decision-making for air quality management near biomass plants.

Heat stress negatively impacts key yield-contributing physiological traits in wheat, leading to a decrease in grain yield. Scanning of genomic regions linked to these traits, along with the identification of the most relevant candidate genes (CGs), is an effective strategy for developing heat-tolerant wheat cultivars in the near future. In this context, a genome-wide association mapping approach has been employed to identify chromosomal regions associated with these traits, along with to identify the putative CGs for heat tolerance in wheat. Genotyping was performed using the 35K Axiom Wheat Breeder Array. From our study, principal component analysis (PCA) revealed that biomass (BM), canopy temperature (CT), and seed weight per pot (SWPP) explained a higher cumulative variance. Population structure and diversity analysis filtered 13,947 markers and revealed three subpopulations with sufficient diversity. A large whole-genome LD block size of 7.15MB was obtained at a half LD decay value. We have mapped 14 significant MTAs linked to these traits with - log10(p) value > 5.44 after Bonferroni correction and also identified 14 high-confidence CGs. Our study also identified four haplotype groups, suggesting the potential for a haplotype-based breeding program under heat stress. Promoter analysis revealed 174 cis-regulatory elements (CREs). Phylogenetic analysis of the pleiotropic gene TraesCS7A02G200200 revealed three major clades of closely related species. We have also reported several orthologous genes related to our 14 major CGs. Untranslated regions (UTRs) analysis found several upstream Open Reading Frames (uORFs) in few identified genes, which can be employed to understand the stringent mechanism of gene regulation under heat stress. By using the Multitrait-genotype ideotype index (MGIDI), we have selected 13 high-performance genotypes for their use as donor parent for heat tolerance. Henceforth, after successful validation, these SNPs can be utilized for marker-assisted transfer of genes/QTLs to develop heat-tolerant wheat cultivars.

This article explores the renewable energy development in Ukraine, taking into account military risks through an economic-mathematical assessment of its investment attractiveness. To evaluate the investment priorities of renewable energy in Ukraine, two strategies have been considered – traditional and the one taking into account ESG factors. Using the Fuzzy TOPSIS approach, the main priorities of renewable energy in Ukraine have been determined: solar power plants for the traditional strategy, and for the ESG strategy – biomass power plants. For further evaluation of the investment attractiveness of the identified priorities, a multifactor model for assessing investment attractiveness using the method of integral assessment was constructed. The model is based on four primary indicators: development prospects, return on equity of enterprises, level of inflation stability in industry prices, and industry-specific risks. First published online 3 March 2026

Carbon monoxide formation during the co-firing of coal and biomass waste fuels in a 10 kWth bubbling fluidized bed rig under oxy-fuel combustion conditions