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Siderophores are low molecular weight secondary metabolites produced by microorganisms under low iron stress as a specific iron chelator. In the present study, a rhizospheric bacterium was isolated from the rhizosphere of sesame plants from Salem district, Tamil Nadu, India and later identified as Bacillus subtilis LSBS2. It exhibited multiple plant-growth-promoting (PGP) traits such as hydrogen cyanide (HCN), ammonia, and indole acetic acid (IAA), and solubilized phosphate. The chrome azurol sulphonate (CAS) agar plate assay was used to screen the siderophore production of LSBS2 and quantitatively the isolate produced 296 mg/L of siderophores in succinic acid medium. Further characterization of the siderophore revealed that the isolate produced catecholate siderophore bacillibactin. A pot culture experiment was used to explore the effect of LSBS2 and its siderophore in promoting iron absorption and plant growth of Sesamum indicum L. Data from the present study revealed that the multifarious Bacillus sp. LSBS2 could be exploited as a potential bioinoculant for growth and yield improvement in S. indicum.

The effect of carbon source on efficacy of anaerobic soil disinfestation (ASD) toward suppression of apple root infection by Rhizoctonia solani AG-5 and Pratylenchus penetrans was examined. Orchard grass (GR), rice bran (RB), ethanol (ET), composted steer manure (CM), and Brassica juncea seed meal (SM) were used as ASD carbon inputs, with plant assays conducted in natural and pasteurized orchard soils. Subsequent studies investigated the effect of GR application rate used in ASD on control of these pathogens. In general, apple root infection by R. solani AG-5 was significantly lower in ET, GR, RB, and SM ASD treatments compared with the control. Among different ASD treatments, apple seedling growth was significantly greater when GR or SM was used as the carbon input relative to all other ASD treatments. R. solani AG-5 DNA abundance was significantly reduced in all ASD treatments, regardless of amendment type, compared with the control. In independent experiments, ASD-GR was consistently superior to ASD-CM for limiting pathogen activity in soils. ASD treatment with a grass input rate of 20 t ha−1provided superior suppression of P. penetrans but grass application rate did not affect ASD efficacy in control of R. solani AG-5. The soil microbiome from ASD-GR-treated soils was clearly distinct from the control and ASD-CM-treated soils. In contrast, composition of the microbiome from control and ASD-CM-treated soils could not be differentiated. Comparative results from pasteurized and nonpasteurized soils suggest that there is potential for GR based ASD treatment to recruit microbial elements that persist over the anaerobic phase of soil incubation, which may functionally contribute to disease suppression. When ASD was conducted with GR, microbial diversity was markedly reduced relative to the control or ASD-CM soil suggesting that this parameter, typically associated with system resilience, was not instrumental to the function of ASD-induced soil suppressiveness.

In resource-constrained settings, the recovery of nutrients and the production of energy from liquid and solid waste are important. We determined the range and magnitude of potential community health impacts of six solid and liquid waste recovery and reuse business models in Hanoi, Vietnam.We employed a health impact assessment (HIA) approach using secondary data obtained from various sources supplemented with primary data collection. For determining the direction (positive or negative) and magnitude of potential health impacts in the population, a semiquantitative impact assessment was pursued.From a public health perspective, wastewater reuse for inland fish farming, coupled with on-site water treatment has considerable potential for individual and community-level health benefits. One of the business models investigated (i.e. dry fuel manufacturing with agro-waste) resulted in net negative health impacts.In Hanoi, the reuse of liquid and solid waste-as a mean to recover water and nutrients and to produce energy-has considerable potential for health benefits if appropriately managed and tailored to local contexts. Our HIA methodology provides an evidence-based decision-support tool for identification and promotion of business models for implementation in Hanoi.

Abstract Background Environmental factors such as temperature, rainfall, and vegetation cover play a critical role in malaria transmission. However, quantifying the relationships between environmental factors and measures of disease burden relevant for public health can be complex as effects are often non-linear and subject to temporal lags between when changes in environmental factors lead to changes in malaria incidence. The study investigated the effect of environmental covariates on malaria incidence in high transmission settings of Uganda. Methods This study leveraged data from seven malaria reference centres (MRCs) located in high transmission settings of Uganda over a 24-month period. Estimates of monthly malaria incidence (MI) were derived from MRCs’ catchment areas. Environmental data including monthly temperature, rainfall, and normalized difference vegetation index (NDVI) were obtained from remote sensing sources. A distributed lag nonlinear model was used to investigate the effect of environmental covariates on malaria incidence. Results Overall, the median (range) monthly temperature was 30 °C (26–47), rainfall 133.0 mm (3.0–247), NDVI 0.66 (0.24–0.80) and MI was 790 per 1000 person-years (73–3973). Temperature of 35 °C was significantly associated with malaria incidence compared to the median observed temperature (30 °C) at month lag 2 (IRR: 2.00, 95% CI: 1.42–2.83) and the increased cumulative IRR of malaria at month lags 1–4, with the highest cumulative IRR of 8.16 (95% CI: 3.41–20.26) at lag-month 4. Rainfall of 200 mm significantly increased IRR of malaria compared to the median observed rainfall (133 mm) at lag-month 0 (IRR: 1.24, 95% CI: 1.01–1.52) and the increased cumulative IRR of malaria at month lags 1–4, with the highest cumulative IRR of 1.99(95% CI: 1.22–2.27) at lag-month 4. Average NVDI of 0.72 significantly increased the cumulative IRR of malaria compared to the median observed NDVI (0.66) at month lags 2–4, with the highest cumulative IRR of 1.57(95% CI: 1.09–2.25) at lag-month 4. Conclusions In high-malaria transmission settings, high values of environmental covariates were associated with increased cumulative IRR of malaria, with IRR peaks at variable lag times. The complex associations identified are valuable for designing strategies for early warning, prevention, and control of seasonal malaria surges and epidemics.

Abstract We evaluated three Integrated Assessment Models (IAMs: IGSM, MERGE, MiniCAM) by: (i) comparing their global Primary Energy year-2000 initializations and projections for 2010 and 2015 to historical data; (ii) mapping their CO2 emissions projections against observations; and (iii) examining model-output diagnostics. The IAMs underestimated historical primary energy consumption and initial/projected CO2 emissions in both reference and stabilization scenarios (particularly for combustion fuels) but overestimated usage of non-biomass renewables, causing underestimates of future CO2 emissions that, for the stabilization scenarios, are wildly optimistic. Mitigation technology breakdowns in the policy scenarios vary enormously across IAMs, suggesting that confidence in their projections might be misplaced, or that options for mitigation have greater scope than is supposed. Most increases in carbon-free technologies in the stabilization scenarios are already captured in the reference cases. Energy-conversion efficiencies in electricity generation improve over time, but, (except for gas-powered generation in IGSM), efficiencies in the policy scenarios are less than in the reference. Electrification results diverge widely: IGSM has little change over the 21st century, while MiniCAM and MERGE have major electrification increases in their policy scenarios. We suggest: 1) comprehensive model output suitable for secondary analysis should be more readily available; 2) directly comparable reference and policy-driven mitigation scenarios are essential for assessing mitigation measures; 3) model validation using historical, source-specific energy data is crucial for assessing model credibility; 4) separation of mitigation contributions into no-policy and policy-driven amounts is needed to assess the effectiveness of mitigation policies; and 5) detailed inter-model comparisons can provide important insights into model credibility.

Water use efficiency (WUE) is a quantitative measurement which improvement is a major issue in the context of global warming and restrictions in water availability for agriculture. In this study, we aimed at studying the variation and genetic control of WUE and the respective role of its components (plant biomass and transpiration) in a perennial fruit crop. We explored an INRA apple core collection grown in a phenotyping platform to screen one-year-old scions for their accumulated biomass, transpiration and WUE under optimal growing conditions. Plant biomass was decompose into morphological components related to either growth or organ expansion. For each trait, nine mixed models were evaluated to account for the genetic effect and spatial heterogeneity inside the platform. The Best Linear Unbiased Predictors of genetic values were estimated after model selection. Mean broad-sense heritabilities were calculated from variance estimates. Heritability values indicated that biomass (0.76) and WUE (0.73) were under genetic control. This genetic control was lower in plant transpiration with an heritability of 0.54. Across the collection, biomass accounted for 70% of the WUE variability. A Hierarchical Ascendant Classification of the core collection indicated the existence of six groups of genotypes with contrasting morphology and WUE. Differences between morphotypes were interpreted as resulting from differences in the main processes responsible for plant growth: cell division leading to the generation of new organs and cell elongation leading to organ dimension. Although further studies will be necessary on mature trees with more complex architecture and multiple sinks such as fruits, this study is a first step for improving apple plant material for the use of water.

AbstractAlthough the process of microbial degradation of coal to produce biomethane has got much attention from many research works, the products profiles of coal at the initial stage of methanogenic bioconversion are not clear yet. In this study, five coal‐degrading bacterial strains (CD1, CD10, CD20, CD24, and CD25) from a methanogenic community were isolated and identified. Among them, CD1 and CD24 belong to Paenibacillus sp., CD10 and CD20 belong to Bacillus sp., and CD25 belongs to Stenotrophomonas sp. After biotreatment of lignite and bituminous coal, the kinds of newly produced compounds were 33 and 45, respectively. Metabolomics analysis showed that a large number of alkane compounds and heterocyclic aromatic compounds were produced after degradation of bituminous coal and lignite by isolated bacteria, and most of the compounds had been produced in a hydroxylated or acylated manner, indicating that the initial microbial treatment enhanced the bioavailability of coal. Some alkaloids and biosurfactants were also detected in the aforementioned products, such as glycerophosphocholine, proveratrol A, proveratrol B, surfactin, etc. These microbial metabolites may play an important role in solubilization during the degradation of coal. This study added to the understanding of the complicated metabolic process of methanogenic coal bioconversion and enabled effective production of biomethane with appropriate metabolic strategies.