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Molecular determinants of host specificity of maize-, rice- and mango-pathogenic species of the genus Fusarium

Fusarium species of the Gibberella fujikuroi species complex cause serious diseases on different crops such as rice, wheat and maize. An important group of plant pathogens is the Gibberella fujikuroi species complex (GFC) of closely related Fusarium species which are associated with specific hosts; F. verticillioides and F. proliferatum are particularly associated with maize where they can cause serious ear-, root-, and stalk rot diseases. Two other closely related species of the GFC, F. mangiferae and F. fujikuroi, which share about 90Prozent sequence identity with F. verticillioides, are pathogens on mango and rice, respectively. All of these species produce a broad spectrum of secondary metabolites such as phytohormones (gibberellins, auxins, and cytokinins), and harmful mycotoxins, such as fumonisin, fusarin C, or fusaric acid in large quantities. However, the spectrum of those mycotoxins might differ between closely related species suggesting that secondary metabolites might be determinants for host specificity. In this project, we will study the potential impact of secondary metabolites (i.e. phytohormones and certain mycotoxins) and some other species-specific factors (e.g. species-specific transcription factors) on host specificity. The recently sequenced genomes of F. mangiferae and F. fujikuroi by our groups and the planned sequencing of F. proliferatum will help to identify such determinants by genetic manipulation of the appropriate metabolic pathway(s).

Greenhouse Gas Emission of Different Crop Rotations of Rice (flooded and non-flooded) and Maize

This subproject will assess net-fluxes of CH4 and N2O as well as soil CO2 emissions from flooded and non-flooded rice as well as maize grown in different rotations and under different management practices. SP5 will encompass two research tasks, (i) automated chamber measurements and (ii) soil gas concentration measurements of different crop rotations. In total 36 automated chambers will be placed in two large field blocks (18 chambers each) divided into fields representing three crop-rotations: R-WET (rice flooded - rice flooded), R-MIX (rice flooded - rice non-flooded), M-MIX (maize - rice flooded) experiencing three differ-ent crop management practices: a control with no fertilizer application (zero-N), site specific nutrient management (site-spec) and conventional fertilizer application (conv). In the fields of conventional fertilization SP5 will also conduct soil concentration measurements of CO2, N2O and CH4 for identification of the main production and/ or consumption horizons which may differ between the three crop rotation systems which will allow identification of the dominating processes responsible for GHG exchange with the atmosphere. Emissions of different greenhouse gases together with data on biomass production/ yields (conducted by IRRI) will be aggregated to compile the total GHG exchange of different crop rotations and management practices. Thus, the data obtained in SP5 will create a sound basis for projecting the environmental consequences of different land use options in rice-based systems with respect to the net GHG exchange. Moreover, data obtained in SP5 will be linked in particular with results from C and N process studies of SP1-SP4 and will form a sound base for further development, testing and valida-tion of the process based model applied in SP6/ 7.

Energieeffiziente Wärmepumpen durch die Kombination aktiver und passiver Anti-Eis Strategien, Teilvorhaben: Steuerung der piezoelektrischen Wandler zur Aktorik und Sensorik zur Eisdetektion und Entfernung

Demonstration einer Kaelteanlage mit 'Wasser als Kaeltemittel' zur Erzeugung von Kaltwasser und binaerem Eis ('Vakuumeis)

Immobilisation of arsenic in paddy soil by iron(II)-oxidizing bacteria

Arsenic-contaminated ground- and drinking water is a global environmental problem with about 1-2Prozent of the world's population being affected. The upper drinking water limit for arsenic (10 Micro g/l) recommended by the WHO is often exceeded, even in industrial nations in Europe and the USA. Chronic intake of arsenic causes severe health problems like skin diseases (e.g. blackfoot disease) and cancer. In addition to drinking water, seafood and rice are the main reservoirs for arsenic uptake. Arsenic is oftentimes of geogenic origin and in the environment it is mainly bound to iron(III) minerals. Iron(III)-reducing bacteria are able to dissolve these iron minerals and therefore release the arsenic to the environment. In turn, iron(II)-oxidizing bacteria have the potential to co-precipitate or sorb arsenic during iron(II)- oxidation at neutral pH followed by iron(III) mineral precipitation. This process may reduce arsenic concentrations in the environment drastically, lowering the potential risk for humans dramatically.The main goal of this study therefore is to quantify, identify and isolate anaerobic and aerobic Fe(II)-oxidizing microorganisms in arsenic-containing paddy soil. The co-precipitation and thus removal of arsenic by iron mineral producing bacteria will be determined in batch and microcosm experiments. Finally the influence of rhizosphere redox status on microbial Fe oxidation and arsenic uptake into rice plants will be evaluated in microcosm experiments. The long-term goal of this research is to better understand arsenic-co-precipitation and thus arsenic-immobilization by iron(II)-oxidizing bacteria in rice paddy soil. Potentially these results can lead to an improvement of living conditions in affected countries, e.g. in China or Bangladesh.

GTS Bulletin: FCSN33 ESSA - Forecast (details are described in the abstract)

The FCSN33 TTAAii Data Designators decode as: T1 (F): Forecast T1T2 (FC): Aerodrome (VT < 12 hours) A1A2 (SN): Sweden (Remarks from Volume-C: NilReason)

GTS Bulletin: FCSN32 ESIA - Forecast (details are described in the abstract)

The FCSN32 TTAAii Data Designators decode as: T1 (F): Forecast T1T2 (FC): Aerodrome (VT < 12 hours) A1A2 (SN): Sweden (Remarks from Volume-C: NilReason)

GTS Bulletin: FCSN31 ESIA - Forecast (details are described in the abstract)

The FCSN31 TTAAii Data Designators decode as: T1 (F): Forecast T1T2 (FC): Aerodrome (VT < 12 hours) A1A2 (SN): Sweden (Remarks from Volume-C: NilReason)

GTS Bulletin: FTSN32 ESSA - Forecast (details are described in the abstract)

The FTSN32 TTAAii Data Designators decode as: T1 (F): Forecast T1T2 (FT): Aerodrome (VT >= 12 hours) A1A2 (SN): Sweden (Remarks from Volume-C: NilReason)

GTS Bulletin: SRLV40 UMRR - Surface data (details are described in the abstract)

The SRLV40 TTAAii Data Designators decode as: T1 (S): Surface data T1T2 (SR): Hydrological (river) reports A1A2 (LV): Latvia (Remarks from Volume-C: NilReason)

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