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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Flow Development in Radial Plane of Rotating Detonation Engine Integrated with Aerospike

In this study, axial and radial velocity components are measured downstream of a rotating detonation engine (RDE) integrated with an aerospike by using particle image velocimetry (PIV) at 100 kHz. The RDE is operated at high pressures obtained by restricting the RDE exit with a converging nozzle, which also directs the flow radially toward the aerospike. Reactants, methane fuel, and enriched air (67% oxygen and 33% nitrogen) are supplied from separate plenums at ambient temperature. PIV data are presented to investigate how pressure ratios within the RDE channel affect the flow evolution across the aerospike. The RDE is shown to operate stably and consistently in a single wave mode for all six test runs. The study highlights large temporal and spatial variations in both axial and radial flow velocities at the nozzle throat that persist downstream across the aerospike. Each point in the flowfield oscillates at the frequency recorded inside the RDE channel. Overall, the temporally and spatially varying aerospike flowfield is far from the ideal case of a uniform flow at its exit, and it points toward the need to condition the flow within the RDE channel to produce more uniform conditions at the nozzle throat.

Engineering↗
DOE OSTI2023

Targeted Quantification of Protein Phosphorylation and Its Contributions towards Mathematical Modeling of Signaling Pathways

Post-translational modifications (PTMs) are key regulatory mechanisms that can control protein function. Of these, phosphorylation is the most common and widely studied. Because of its importance in regulating cell signaling, precise and accurate measurements of protein phosphorylation across wide dynamic ranges are crucial to understanding how signaling pathways function. Although immunological assays are commonly used to detect phosphoproteins, their lack of sensitivity, specificity, and selectivity often make them unreliable for quantitative measurements of complex biological samples. Recent advances in Mass Spectrometry (MS)-based targeted proteomics have made it a more useful approach than immunoassays for studying the dynamics of protein phosphorylation. Selected reaction monitoring (SRM)—also known as multiple reaction monitoring (MRM)—and parallel reaction monitoring (PRM) can quantify relative and absolute abundances of protein phosphorylation in multiplexed fashions targeting specific pathways. In addition, the refinement of these tools by enrichment and fractionation strategies has improved measurement of phosphorylation of low-abundance proteins. The quantitative data generated are particularly useful for building and parameterizing mathematical models of complex phospho-signaling pathways. Potentially, these models can provide a framework for linking analytical measurements of clinical samples to better diagnosis and treatment of disease.

mathematical modeling↗
NASA NTRS1995

Identification And Survival Of Bacteriohopanepolyol In A Hot Spring Microbial Mat

The polar lipids of a hot spring microbial mat located in Yellowstone National Park were examined for the presence of bacteriohopanepolvols (BHP). BHP are a group of molecules consisting of a hopanoid (peotacyclic triterpene) linked via a n-alkyl polyhydroxylated chain to a variety of polar end groups. BHP have been isolated in varying amounts from phylogenetically diverse eubacterial groups including cyanobacteria, methanotrophs and the Rhodospirillaceae. The hopanoids are excellent biomarkers and have been detected in sedimentary rocks as old as 1.7 bya. In order to interpret the ancient organic record, it is important to understand the abundance, source and fate of such biomarker compounds in microbial mats. A 40 sq cm mat section was taken from a 52 to 55 C site in the effluent channel of Octopus Spring and was sampled vertically over approximately 16 mm. The first 5-6 mm was sectioned into a top green layer (310 mg dry weight) and several subjacent, deep orange layers (240 and 250 mg, respectively). The lower 10 mm of the mat was sectioned into two gelatinous orange layers containing a siliceous gritty material (260 and 440 mg) which increased with depth, and a bottom layer composed almost exclusively of siliceous sinter (4.1 g). The progressive decrease in total organic carbon from 45% in the top green layer to only 4% in the bottom layer reflects the observed increase in siliceous deposition. GC-MS analysis of the phospholipid and glycolipid fatty acids yielded predominantly saturated normal chain acids, n-15 to n-18, and iso-branched acids, i-15 to i-17. Small amounts of unsaturated fatty acids (16:1, two positional isomers of 18:1, and two cyclopropyl acids, C(sub 17) and C(sub 19)) were present mainly in the top layer. Esterified fatty acid which is a good index for intact cellular membrane, i.e. viable organisms, was highest in the top two layers (203 and 231 micro g/mg total lipid, respectively) and gradually decreased to 66 micro g/mg total lipid in the bottom layer. Small amounts of BHP were present in all six layers, however in this case, BHP was lowest in the top green and subjacent deep-orange layers (118 and 172 micro g/mg total lipid, respectively) and increased with depth reaching almost 400 micro g/mg in the bottom two layers. This data suggest that BHP are survivina the initial phase of mat degradation and may be preferentially enriched in any organic record of such thermal environments. The relatively low level of BHP in the top layer also suggests that cyanobacteria may not be the major source of BHP in this mat. Since Chloroflexus a major component of the deep-orange layer has been reported to lack BHP, this material may prove a valuable biomarker for some other mat inhabitant. Further isotopic characterization of this BHP should help resolve this finding.

Janke, Linda L.↗
NASA NTRS2004

The mass and speed dependence of meteor air plasma temperatures

The speed and mass dependence of meteor air plasma temperatures is perhaps the most important data needed to understand how small meteoroids chemically change the ambient atmosphere in their path and enrich the ablated meteoric organic matter with oxygen. Such chemistry can play an important role in creating prebiotic compounds. The excitation conditions in various air plasma emissions were measured from high-resolution optical spectra of Leonid storm meteors during NASA's Leonid Multi-Instrument Aircraft Campaign. This was the first time a sufficient number and range of temperature measurements were obtained to search for meteoroid mass and speed dependencies. We found slight increases in temperature with decreasing altitude, but otherwise nearly constant values for meteoroids with speeds between 35 and 72 km/s and masses between 10(-5) g and 1 g. We conclude that faster and more massive meteoroids produce a larger emission volume, but not a higher air plasma temperature. We speculate that the meteoric plasma may be in multiphase equilibrium with the ambient atmosphere, which could mean lower plasma temperatures in a CO(2)-rich early Earth atmosphere.

Temperature↗
NASA NTRS1987

Local and exotic components of primitive meteorites, and their origin

The chemical and isotopic compositions of chondrites and their implications for chondrite origins are considered, reviewing the results of recent theoretical and experimental investigations. Numerical data are compiled in tables and graphs and discussed in detail. Consideration is given to the properties and classifications of chondrites; components of local origin in the matrix, chondrules, Ca-Al-rich inclusions, and carbon and organic matter; exotic components such as O-16-enriched dust, nucleosynthetic anomalies, and extinct radionuclides; and isotopic anomalies of volatiles such as C, N, and the noble gases. The implications of the chondrite data for the stony fraction of comet nuclei are briefly indicated.

Anders, E.↗
DOE OSTI2021

Resampling and data augmentation for short-term PV output prediction based on an imbalanced sky images dataset using convolutional neural networks

Integrating photovoltaics (PV) into electricity grids is challenged by potentially large fluctuations in power generation. In recent years, sky image-based PV output prediction using convolutional neural networks (CNNs) has emerged as a promising approach to forecasting fluctuations. A key challenge is imbalanced sky image datasets: because of the geography of solar PV system installations, sky image datasets are often rich in sunny condition data but deficient in cloudy condition data. This imbalance contrasts with the fact that model errors are dominated by cloudy condition performance. In this study, we attempt to remedy this by exploring the enrichment and augmentation of an imbalanced sky images dataset for two PV output prediction tasks: nowcasting (predicting concurrent PV output) and forecasting (predicting 15-minute-ahead future PV output). We empirically examine the efficacy of using different resampling and data augmentation approaches to create a rebalanced dataset for model development. A three-stage greedy search is used to determine the optimal resampling approach, data augmentation techniques and over-sampling rate. The results show that for the nowcast problem, resampling and data augmentation can effectively enhance the model performance, reducing overall root mean squared error (RMSE) by an average of 4%, or a 15 std. (standard deviation) of improvement compared to the variability of the baseline model. In contrast, the treatment RMSE for the forecast problem nearly always overlaps the baseline performance at the ± 2 std. level. The optimal resampling approach expands on the original dataset by over-sampling the minority cloudy data, with the best results from large over-sampling rate (e.g., 4 ~ 6 times over-sampling of cloudy images).

14 SOLAR ENERGY↗
DOE OSTI2023

Design and testing of an enriched uranium fueled molten salt irradiation vehicle

Molten salt reactors (MSRs) have garnered increasing attention recently with several demonstration efforts on the way. A key challenge to the licensing basis for these reactors is the lack of experimental data on fueled salts. This is expected to be crucial to the safety evaluation and licensing basis of reactors of this type deployed in the future. While capability for irradiating molten salts has started being reestablished in the recent decade, no enriched fuel irradiation capability has been developed and tested as of yet. A new experiment vehicle under development at Idaho National Laboratory (INL) is presented here. The Molten-salt Research Temperature-controlled Irradiation (MRTI) experiment was developed to host enriched-uranium bearing salt samples to be irradiated at a test reactor within the lab complex. One of the key scientific objectives is to provide irradiated salt samples for post irradiation examination (PIE) to study the impact of fission product generation and neutron/gamma radioactivity on the salt solution and salt-facing wall material. This paper provides a detailed overview of the mechanical design of the experiment, followed by an overview of the fabrication and assembly of an initial prototype vehicle (with non-fuel bearing salt). A summary of the key analyses conducted as a part of the performance and safety evaluation is then provided. Lastly, an overview of the test conducted in prototypic out-of-pile (non-neutron) environment are shown. These evaluations provide the foundation for a planned irradiation of and enriched uranium-bearing chloride salt sample in the near term. The upcoming irradiation will contain 13cm 3 of UCl 3 -NaCl salt (93% enrichment) generating around 20 W/cm 3 of fission energy during irradiation and a temperature range that can be contained between bounds of 525-900°C.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1987

Selective weathering of shocked minerals and chondritic enrichment of the Martian fines

In a recent paper, Boslough and Cygan reported the observation of shock-enhanced chemical weathering kinetics of three silicate minerals. Based on the experimental data and on those of Tyburczy and Ahrens for enhanced dehydration kinetics of shocked serpentine, a mechnaism is proposed by which shock-activated minerals are selectively weathered on the surface of Mars. The purpose of the present abstract is to argue on the basis of relative volumes of shocked materials that, as a direct consequence of selective weathering, the composition of the weathered surface units on Mars should be enriched in meteoritic material.

Boslough, M. B.↗
DOE OSTI2020

Liquid-Vapor Coexistence and Critical Point of Mg 2 SiO 4 From Ab Initio Simulations

Hypervelocity impact-driven vaporization is characteristic of late-stage planet formation. Yet the behavior and properties of liquid-vapor mixtures of planetary materials of interest are typically unknown. Multiphase equations of state used in hydrodynamic simulations of planet impacts therefore lack reliable data for this important phenomenon. Here, we present the first constraints on the liquid-vapor critical point and coexistence phase boundary of Mg2SiO4 computed from ab initio molecular dynamics simulations. We found that the vapor is depleted in magnesium and enriched in silica and oxygen, while the coexisting liquid is enriched in magnesium and depleted in oxygen, from which we infer vaporization is incongruent. The critical point was estimated from an equation of state fit to the data. The results are in line with recent calculations of MgSiO3 and together confirm that extant multiphase equation of state (EOS) models used in planetary accretion modeling significantly underestimate the amount of supercritical material postimpact.

58 GEOSCIENCES↗
DOE OSTI2024

Machine learning framework for predicting uranium enrichments from M400 CZT gamma spectra

A machine learning framework was developed for predicting uranium enrichments from M400 CZT gamma spectra. This framework leverages the availability of a large amount of measured M400 gamma spectra and uses a recently updated version of Gamma Detector Response and Analysis Software (GADRAS) for gamma spectrum analysis and generation. It also leverages the existing machine learning modules in Python for gamma spectrum data processing, curation, model training, benchmarking, and optimization of the deep machine learning models. The framework is used to develop a deep learning model to analyze gamma spectra from a set of U 3 O 8 samples with enrichments ranging from 0.31 to 93.17% and UF 6 cylinders with enrichments ranging from 0.2 to 4.95%, and the model performance is tested using a set of measured spectra and the respective declared enrichment values. Results show that the model can correctly classify 99.35% of the U 3 O 8 sample enrichments, and can predict the samples’ enrichments within an average absolute error of 0.099% (in percentage points of enrichment). For the UF 6 cylinders, the average absolute error was approximately 0.03%, with an accuracy of 98% in classifying discrete enrichment values of UF 6 samples. Finally, the results also show that the model has performed significantly better in terms of predicting enrichments in UF 6 cylinders based on measured gamma spectra than the GEM code, with a standard deviation (of the relative errors) of 2.23% (compared with the 11.51% value for the GEM code) based on results from a set of test data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Software Validation Work With The ZPPR-15 Data

The analysis activities for fast reactors involve using many different pieces of software that are relied upon for their predictive capabilities. For this software to be considered reliable, documented proof that the predictions of the software are accurate is required. In this manuscript, the validation work that covers some of the Argonne software used in fast reactor design activities is discussed and displayed. This validation work includes neutron and gamma flux distributions, reaction rate distributions, and reactivity worth. In an ideal world, a reactor development program would have access to a comprehensive set of experimental facilities to help inform the design aspects of the reactor itself. While thermal-hydraulics experiments, and to a limited degree mechanical experiments, can be carried out today for validation needs, neutronics related experimental facilities are rather impractical because of the lack of experimental facilities. Given the desired time table for construction of new reactors, the reconstitution or creation of new neutronic experimental facilities is untenable and thus those reactor development programs must rely upon any available experimental measurements that are qualitatively similar to the design. While a methodology has been proposed to assess the similarity between the past experimental measurements and the reactor itself, that aspect is beyond the scope of this manuscript. In this manuscript, the focus is entirely placed on the analysis results for a series of experiments carried out at the ZPPR facility in Idaho in the mid-1980s. In this regard, this manuscript only shows the validation of the stated neutronics software for specific loadings of the ZPPR reactor. Because of the fuel form, its proposed enrichment, and the material content of the reactor core, the ZPPR-15 experiments were identified as potential validation data for the reactor. The ZPPR-15 experiments were intended as mockups of a 330 MWe Integral Fast Reactor program which was a follow on program to the Clinch River Breeder Reactor. In the ZPPR-15 series of experiments, measurements of the neutron spectrum, control rod worth, sodium void worth, foil reaction rate distributions, Doppler worth of heated samples, gamma dose, and axial expansion worth were all carried out and published. In many cases, these reactivity coefficients are good candidates to validate the reactivity coefficient calculation scheme used by the analysis software and included in the safety analysis activities of fast reactor development projects today. This manuscript discusses the modeling methodology and accuracy of the calculated experimental results using the LANL software MCNP and the ANL software package ARC (Argonne Reactor Codes). As will be shown, for many of the experimental measurements, the two software packages are found to be good predictive analysis tools for those experiments. In other cases, problems with the analysis methodology or underlying cross section data are exposed which indicates where predictive analysis is not as reliable. Finally, in some of the measurements the conclusion is reached that the experimental measurement cannot be reproduced with the analysis software as it is simply too difficult.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Software Validation Work With The ZPPR-15 Data

The analysis activities for fast reactors involve using many different pieces of software that are relied upon for their predictive capabilities. For this software to be considered reliable, documented proof that the predictions of the software are accurate is required. In this manuscript, the validation work that covers some of the Argonne software used in fast reactor design activities is discussed and displayed. This validation work includes neutron and gamma flux distributions, reaction rate distributions, and reactivity worth. In an ideal world, a reactor development program would have access to a comprehensive set of experimental facilities to help inform the design aspects of the reactor itself. While thermal-hydraulics experiments, and to a limited degree mechanical experiments, can be carried out today for validation needs, neutronics related experimental facilities are rather impractical because of the lack of experimental facilities. Given the desired time table for construction of new reactors, the reconstitution or creation of new neutronic experimental facilities is untenable and thus those reactor development programs must rely upon any available experimental measurements that are qualitatively similar to the design. While a methodology has been proposed to assess the similarity between the past experimental measurements and the reactor itself, that aspect is beyond the scope of this manuscript. In this manuscript, the focus is entirely placed on the analysis results for a series of experiments carried out at the ZPPR facility in Idaho in the mid-1980s. In this regard, this manuscript only shows the validation of the stated neutronics software for specific loadings of the ZPPR reactor. Because of the fuel form, its proposed enrichment, and the material content of the reactor core, the ZPPR-15 experiments were identified as potential validation data for the reactor. The ZPPR-15 experiments were intended as mockups of a 330 MWe Integral Fast Reactor program which was a follow on program to the Clinch River Breeder Reactor. In the ZPPR-15 series of experiments, measurements of the neutron spectrum, control rod worth, sodium void worth, foil reaction rate distributions, Doppler worth of heated samples, gamma dose, and axial expansion worth were all carried out and published. In many cases, these reactivity coefficients are good candidates to validate the reactivity coefficient calculation scheme used by the analysis software and included in the safety analysis activities of fast reactor development projects today. This manuscript discusses the modeling methodology and accuracy of the calculated experimental results using the LANL software MCNP and the ANL software package ARC (Argonne Reactor Codes). As will be shown, for many of the experimental measurements, the two software packages are found to be good predictive analysis tools for those experiments. In other cases, problems with the analysis methodology or underlying cross section data are exposed which indicates where predictive analysis is not as reliable. Finally, in some of the measurements the conclusion is reached that the experimental measurement cannot be reproduced with the analysis software as it is simply too difficult.

Aliberti, Gerardo↗
NASA NTRS2018

NASA GIBS and Worldview: Visualizing NASA's Earth Science Data for All to Explore

For more than 20 years, the NASA Earth Observing System (EOS) has operated dozens of remote sensing satellites collecting nearly 15 Petabytes of data that span thousands of science parameters. Within these observations are keys the Earth Scientists have used to unlock many discoveries that we now understand about our planet. Also contained within these observations are a myriad of opportunities for learning and education. The challenge is making them accessible to educators and students in intuitive and simple ways so that effort can be spent on lesson enrichment and not overcoming technical hurdles. The NASA Global Imagery Browse Services (GIBS) system and NASA Worldview website provide a unique view into EOS data through daily full resolution visualizations of hundreds of earth science parameters. For many of these parameters, visualizations are available within hours of acquisition from the satellite. For others, visualizations are available for the entire mission of the satellite. Accompanying the visualizations are visual aids such as color legends, place names, and orbit tracks. By using these visualizations, educators and students can observe natural phenomena that enrich a scientific education.

Cechini, Matthew↗
NASA NTRS1984

Ge abundances in the lunar mantle and implications for the origin of the Moon

Regardless of the origin of the Moon, metal segregation must have occurred within the moon in order to account for its low siderophile element abundances relative to the Earth or chondrites. Germanium is a strongly siderophile element whose bulk distribution coefficient indicates that it is not fractionated during igneous processes on the Moon. The variability in absolute Ge abundances in mare basalts and pristine highland rocks, rather than elemental ratios, can be used to infer lunar mantle abundances and processes. Literature data have been compiled for Ge abundances in mare basalts and pristine highland rocks. For some landing sites, samples with 12 ppb Ge were considered to be extreme outliers and are not included. The Apollo 15 samples are enriched in Ge by a factor of 2.5 over the Apollo 12, 16 and 17 samples. Other siderophile element variations have been found in the Moon. Based on this data, best estimate of the average Ge abundance in the silicate portion of the Moon is 3.52 ppb. The Moon is depleted, relative to chondritic abundances, by a factor of 38,000 normalized to Si. Two possible explanations for the observed variations in Ge abundance in the Moon are: (1) more metal may have segregated from some regions of the Moon than from others; or Ge-bearing material may been been added later in the evolution of the Moon.

Dickinson, T.↗
DOE OSTI2024

Californium-252 production at the High Flux Isotope Reactor - I: Validation study using campaign data

This paper presents a series of 252 Cf production validation and code-to-code comparison studies performed based on data from the production campaigns at the High Flux Isotope Reactor (HFIR). These studies support efforts to convert HFIR from using highly enriched uranium (HEU) fuel to low-enriched uranium (LEU) fuel. HFIR must maintain its world-class performance and missions following this conversion, and because 252 Cf is a vital neutron-emitting radioisotope used for a variety of high-impact applications (e.g., reactor startup, cancer treatment), the ability to efficiently produce 252 Cf must be preserved. In this work, the HFIRCON, Shift, ORIGEN, and TCOMP codes were deployed, and several sets of data libraries were investigated to better understand the calculation codes and the data biases. As-loaded target composition data, as-run irradiation history data, and post-irradiation measurements from recent multi-cycle irradiation campaigns of the HEU core were used to validate and determine methodology biases. Further, the findings demonstrated a good agreement, with results falling within 3 standard deviations of measurements. This paper lays the ground work for the second paper, which evaluates and compares 252 Cf production and safety metrics with the HEU core and a proposed LEU core.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

Estimating the Timing of Early Simian-Human Immunodeficiency Virus Infections: a Comparison between Poisson Fitter and BEAST

Many HIV prevention strategies are currently under consideration where it is highly informative to know the study participants’ times of infection. These can be estimated using viral sequence data sampled early in infection. However, there are several scenarios that, if not addressed, can skew timing estimates. These include multiple transmitted/founder (TF) viruses, APOBEC (apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like)-mediated mutational enrichment, and recombination. Here, we suggest a pipeline to identify these problems and resolve the biases that they introduce. We then compare two modeling strategies to obtain timing estimates from sequence data. The first, Poisson Fitter (PF), is based on a Poisson model of random accumulation of mutations relative to the TF virus (or viruses) that established the infection. The second uses a coalescence-based phylogenetic strategy as implemented in BEAST. The comparison is based on timing predictions using plasma viral RNA (cDNA) sequence data from 28 simian-human immunodeficiency virus (SHIV)-infected animals for which the exact day of infection is known. In this particular setting, based on nucleotide sequences from samples obtained in early infection, the Poisson method yielded more accurate, more precise, and unbiased estimates for the time of infection than did the explored implementations of BEAST. The inference of the time of infection is a critical parameter in testing the efficacy of clinical interventions in protecting against HIV-1 infection. For example, in clinical trials evaluating the efficacy of passively delivered antibodies (Abs) for preventing infections, accurate time of infection data are essential for discerning levels of the Abs required to confer protection, given the natural Ab decay rate in the human body. In such trials, genetic sequences from early in the infection are regularly sampled from study participants, generally prior to immune selection, when the viral population is still expanding and genetic diversity is low. In this particular setting of early viral growth, the Poisson method is superior to the alternative approach based on coalescent methods. This approach can also be applied in human vaccine trials, where accurate estimates of infection times help ascertain if vaccine-elicited immune protection wanes over time.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1986

Carbon-13 NMR studies of salt shock-induced carbohydrate turnover in the marine cyanobacterium Agmenellum quadruplicatum

Carbon turnover in response to abrupt changes in salinity, including the mobilization of glycogen for use in osmoregulation was studied with pulse-chase strategies utilizing nuclear magnetic resonance (NMR)-silent and NMR-detectable 12C and 13C isotopes, respectively. Growth of Agmenellum quadruplicatum in 30%-enriched 13C bicarbonate provided sufficient NMR-detectability of intracellular organic osmoregulants for these studies. A comparison of NMR spectra of intact cells and their ethanol extracts showed that the intact cell data were suitable for quantitative work, and, when combined with ESR measurements of cell volumes, yielded intracellular glucosylglycerol concentrations without disrupting the cells. NMR pulse-chase experiments were used to show that 13C-enriched glycogen, which had previously been accumulated by the cells under nitrogen-limited growth at low salinities, could be utilized for the synthesis of glucosylglycerol when the cells were abruptly transferred to hypersaline media, but only in the light. It was also shown that the accumulation of glucosylglycerol in the light occurred on a time scale similar to that of cell doubling. Depletion of glucosylglycerol when cells abruptly transferred to lower salinities appeared to be rapid--the intracellular pool of this osmoregulant was decreased 2-fold within 2 hours of hypotonic shock.

NASA Discipline Life Support Systems↗
DOE OSTI2020

Distinct Preflowering Drought Tolerance Strategies of Sorghum bicolor Genotype RTx430 Revealed by Subcellular Protein Profiling

Drought is the largest stress affecting agricultural crops, resulting in substantial reductions in yield. Plant adaptation to water stress is a complex trait involving changes in hormone signaling, physiology, and morphology. Sorghum (Sorghum bicolor (L.) Moench) is a C4 cereal grass; it is an agricultural staple, and it is particularly drought-tolerant. To better understand drought adaptation strategies, we compared the cytosolic- and organelle-enriched protein profiles of leaves from two Sorghum bicolor genotypes, RTx430 and BTx642, with differing preflowering drought tolerances after 8 weeks of growth under water limitation in the field. In agreement with previous findings, we observed significant drought-induced changes in the abundance of multiple heat shock proteins and dehydrins in both genotypes. Interestingly, our data suggest a larger genotype-specific drought response in protein profiles of organelles, while cytosolic responses are largely similar between genotypes. Organelle-enriched proteins whose abundance significantly changed exclusively in the preflowering drought-tolerant genotype RTx430 upon drought stress suggest multiple mechanisms of drought tolerance. These include an RTx430-specific change in proteins associated with ABA metabolism and signal transduction, Rubisco activation, reactive oxygen species scavenging, flowering time regulation, and epicuticular wax production. We discuss the current understanding of these processes in relation to drought tolerance and their potential implications.

59 BASIC BIOLOGICAL SCIENCES↗