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At least 1,477 records · Page 82

Application of a Density Law via Python for Aqueous Plutonium Nitrate

A predictive density tool has been developed in Python to reduce bias and uncertainty in nuclear criticality safety calculations for plutonium nitrate systems. The Pitzer Method and an empirical method were implemented into the tool, allowing for plutonium nitrate density calculations. Additionally, the Python tool can generate atom densities for a MCNP6.2 material card using the density from the selected method and directly the densities into a prepared MCNP6 input text file. The material card and density are calculated based on customizable user inputs of plutonium content, nitric acid content, temperature, plutonium isotope weight percentages and impurity concentrations. The Python tool has been validated and verified against the International Handbook of Evaluated Criticality Safety Benchmark Experiments to predict densities within a root mean square error of 1.0% for the Pitzer method and 1.8% for the empirical method. These errors in density were shown to lead to a ±0.5% error in MCNP6.2 calculated k effective for the Pitzer method and a ±1.7% error for the Empirical method. Simultaneous work is also being done at the University of New Mexico and Los Alamos National Laboratory to create a similar tool for plutonium chloride solutions, which aims to provide the accreditation of the chlorine absorption. These capabilities will not only provide more accurate models but also lead the way towards a better understanding of solution systems and potential relaxation in the conservatism of the current aqueous plutonium processing limits.

97 MATHEMATICS AND COMPUTING↗

Incipient Failure Detection (IFD) of antifriction ball bearings

Two methods were investigated for retrieving the ball bearing signals buried by the overall signature of an operating large engine such as the main space shuttle engine. The signal averaging method averages n** signals over a time duration equaling the known period of the ball bearing defect frequency. With this method, the desired ball bearing defect signal will be enhanced over the noise by a factor of the square root of n. A second method is to perform a further frequency analysis on the logarithmic spectrum in order to detect and separate different families of harmonics and sidebands, thereby giving information about modulating frequencies. These two alternate IFD methods were carried out with a Norland 3001 waveform and data system. The obtained results are then compared with the power spectral density (PSD) of the overall machine signals and conclusions are made accordingly.

Wang, D. Y.↗

A reexamination of the laser supported combustion wave

Kantrowitz (1972) and Minovitch (1972) have proposed the use of laser sustained plasmas as a means to heat a rocket propellant. Recent studies of laser-powered propulsion have been directed toward the application of high-specific-impulse space propulsion systems for orbital transfer missions. Analyses of rocket performance relied heavily on the concept of the laser-supported combustion (LSC) wave. Raizer (1971) first drew the analogy between laser-sustained plasmas and combustion waves in an analysis. The Raizer model was later applied to hydrogen by Kemp and Root (1979). In connection with certain problems arising with the approach considered by Kemp and Root, the present investigation is concerned with a reexamination of the Raizer model. Attention is given to a numerical approach for the entire LSC wave in hydrogen, taking into account the incorporation of the proper boundary conditions far downstream of the wave.

Keefer, D.↗

A high speed data acquisition and analysis system for transonic velocity, density, and total temperature fluctuations

The high speed Dynamic Data Acquisition System (DDAS) is described which provides the capability for the simultaneous measurement of velocity, density, and total temperature fluctuations. The system of hardware and software is described in context of the wind tunnel environment. The DDAS replaces both a recording mechanism and a separate data processing system. The data acquisition and data reduction process has been combined within DDAS. DDAS receives input from hot wires and anemometers, amplifies and filters the signals with computer controlled modules, and converts the analog signals to digital with real-time simultaneous digitization followed by digital recording on disk or tape. Automatic acquisition (either from a computer link to an existing wind tunnel acquisition system, or from data acquisition facilities within DDAS) collects necessary calibration and environment data. The generation of hot wire sensitivities is done in DDAS, as is the application of sensitivities to the hot wire data to generate turbulence quantities. The presentation of the raw and processed data, in terms of root mean square values of velocity, density and temperature, and the processing of the spectral data is accomplished on demand in near-real-time- with DDAS. A comprehensive description of the interface to the DDAS and of the internal mechanisms will be prosented. A summary of operations relevant to the use of the DDAS will be provided.

Clukey, Steven J.↗

A Summary of NASA and USAF Hypergolic Propellant Related Spills and Fires

Several unintentional hypergolic fluid related spills, fires, and explosions from the Apollo Program, the Space Shuttle Program, the Titan Program, and a few others have occurred over the past several decades. Spill sites include the following government facilities: Kennedy Space Center (KSC), Johnson Space Center (JSC), White Sands Test Facility (WSTF), Vandenberg Air Force Base (VAFB), Cape Canaveral Air Force Station (CCAFS), Edwards Air Force Base (EAFB), Little Rock AFB, and McConnell AFB. Until now, the only method of capturing the lessons learned from these incidents has been "word of mouth" or by studying each individual incident report. The root causes and consequences of the incidents vary drastically; however, certain "themes" can be deduced and utilized for future hypergolic propellant handling. Some of those common "themes" are summarized below: (1) Improper configuration control and internal or external human performance shaping factors can lead to being falsely comfortable with a system (2) Communication breakdown can escalate an incident to a level where injuries occur and/or hardware is damaged (3) Improper propulsion system and ground support system designs can destine a system for failure (4) Improper training of technicians, engineers, and safety personnel can put lives in danger (5) Improper PPE, spill protection, and staging of fire extinguishing equipment can result in unnecessary injuries or hardware damage if an incident occurs (6) Improper procedural oversight, development, and adherence to the procedure can be detrimental and quickly lead to an undesirable incident (7) Improper materials cleanliness or compatibility and chemical reactivity can result in fires or explosions (8) Improper established "back-out" and/or emergency safing procedures can escalate an event The items listed above are only a short list of the issues that should be recognized prior to handling hypergolic fluids or processing vehicles containing hypergolic propellants. The summary of incidents in this report is intended to cover many more issues than those listed above.

Nufer, Brian M.↗

Asymmetry in Subseasonal Surface Air Temperature Forecast Error with Respect to Soil Moisture Initialization

Soil moisture (W) helps control evapotranspiration (ET), and ET variations can in turn have a distinct impact on 2-m air temperature (T2M), given that increases in evaporative cooling encourage reduced temperatures. Soil moisture is accordingly linked to T2M, and realistic soil moisture initialization has, in previous studies, been shown to improve the skill of subseasonal T2M forecasts. The relationship between soil moisture and evapotranspiration, however, is distinctly nonlinear, with ET tending to increase with soil moisture in drier conditions and to be insensitive to soil moisture variations in wetter conditions. Here, through an extensive analysis of subseasonal forecasts produced with a state-of-the-art seasonal forecast system, this nonlinearity is shown to imprint itself on T2M forecast error in the conterminous United States in two unique ways: (i) the T2M forecast bias (relative to independent observations) induced by a negative precipitation bias tends to be larger for dry initializations, and (ii) on average, the unbiased root-mean-square error (ubRMSE) tends to be larger for dry initializations. Such findings can aid in the identification of forecasts of opportunity; taken a step further, they suggest a pathway for improving bias correction and uncertainty estimation in subseasonal T2M forecasts by conditioning each on initial soil moisture state.

Air Temperature↗

T2M Forecasts at Subseasonal Leads: Do Different Soil Moisture Initial States Have Different Impacts?

Soil moisture (W) helps control evapotranspiration (ET), and ET variations can in turn have a distinct impact on 2-m air temperature (T2M), given that increases in evaporative cooling encourage reduced temperatures. Soil moisture is accordingly linked to T2M, and realistic soil moisture initialization has, in previous studies, been shown to improve the skill of subseasonal T2M forecasts. The relationship between soil moisture and evapotranspiration, however, is distinctly nonlinear, with ET tending to increase with soil moisture in drier conditions and to be insensitive to soil moisture variations in wetter conditions. Here, through an extensive analysis of subseasonal forecasts produced with a state-of-the-art seasonal forecast system, this nonlinearity is shown to imprint itself on T2M forecast error in the conterminous United States in two unique ways: (i) the T2M forecast bias (relative to independent observations) induced by a negative precipitation bias tends to be larger for dry initializations, and (ii) on average, the unbiased root-mean-square error (ubRMSE) tends to be larger for dry initializations. Such findings can aid in the identification of forecasts of opportunity; taken a step further, they suggest a pathway for improving bias correction and uncertainty estimation in subseasonal T2M forecasts by conditioning each on initial soil moisture state.

2-meter Temperature↗

Examination of L-Band Brightness Temperature Forecasts in the SMAP Level-4 Soil Moisture Analysis

The NASA Soil Moisture Active Passive (SMAP) mission [4] has been providing L-band (1.4 GHz) passive microwave brightness temperature (Tb) observations since April 2015. By assimilating the Tb observations into the NASA Catchment land surface model [5] using a spatially distributed ensemble Kalman filter, the NASA Global Modeling and Assimilation Office generates the SMAP Level-4 Soil Moisture (L4_SM) product, which provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with ~2.5-day latency for use in research and applications [6]. The L4_SM product also includes estimates of soil temperature, land surface fluxes, and assimilation diagnostics such as the model forecast and observed Tb values [7]. The output from the L4_SM system is routinely monitored by the L4_SM team. Such monitoring provides valuable information; instances of unusually large Tb observation-minus-forecast (O-F) residuals can indicate events during which soil moisture conditions are poorly described in the land modeling system [7,8]. For example, repeated occurrences of very large Tb O-F values in central Australia were traced back to deficiencies in the gauge-based precipitation product used in the land modeling system through L4_SM Version 5; this discovery prompted the use, beginning in Version 6, of satellite- and gauge-based precipitation observations outside of North America [9]. Recently, a statistical analysis of the Tb O-F residuals revealed systematic errors in the “tau-omega” L-band radiative transfer model that converts the land-model simulated soil moisture and temperature into the forecast Tb prior to the L4_SM analysis. The L4_SM analysis is built on the ensemble Kalman filter and assumes unbiased forecast errors. The presence of systematic Tb forecast errors could thus adversely impact the quality of the analyzed soil moisture. In this paper, we examine the Tb O-F residuals of the latest Version 7 L4_SM data (Science Version ID Vv7030 and Vv7032) [10,11,12]. In the L4_SM Version 7 algorithm, key parameters of the L-band radiative transfer model, including soil roughness, scattering albedo, and a (seasonally varying) climatology of vegetation opacity, are obtained from the SMAP Level-2 Radiometer retrieval product (Version 5) [1]. Additionally, we also use ground measurements of surface soil moisture and soil temperature from the SMAP core validation sites as in situ reference of soil conditions [2,3]. As part of the L4_SM system calibration, the seasonally-varying bias between the model forecast Tb and the observed values is removed prior to the assimilation of the SMAP Tb observations [7]. That is, the L4_SM system is designed to only correct errors in synoptic-scale and interannual variations from the long-term mean seasonal cycle while maintaining the model’s (potentially erroneous) climatology. The Tb O-F residuals examined here are thus computed using SMAP Tb observations after they are rescaled to the mean seasonal cycle of Tb from the modeling system without SMAP data assimilation. Consequently, the long-term average of the Tb O-F residuals has a global mean of only 0.13 K and locally small values, ranging from -1 to 3 K. Despite the small time-average values of the Tb O-F residuals, the model forecast Tb was nevertheless found to exhibit undesirable systematic errors. At some locations, the time-average Tb O-F values strongly depend on surface soil moisture (SM). At the Yanco SMAP core validation site, for example, the Tb O-F residuals typically range from 5 to 15 K under dry soil moisture conditions (SM < 0.15 m3 m-3) yet are predominantly negative under wet soil moisture conditions (SM > 0.25 m3 m-3), with values ranging from 0 to -40 K. This results in soil moisture analysis increments that persistently make the soil drier under dry SM conditions and persistently make the soil wetter under wet SM conditions, suggesting an error in the dynamic range of the simulated Tb, soil moisture or soil temperature. In this paper, we describe the higher-order systematic Tb forecast errors in more detail, examine their impact on the L4_SM product quality, and explore potential avenues to further improve the L4_SM algorithm.

Rolf Reichle↗

A Comparison of RESRAD and GoldSim Models for Assessing Radiological Dose for a RCRA Landfill - 20418

US Ecology Idaho (USEI) operates a Resource Conservation and Recovery Act (RCRA) Subtitle C, Hazardous Waste Treatment, Storage, and Disposal (TSD) Facility on a 640-acre property in Owyhee County, Idaho. USEI accepts a wide variety of RCRA-exempt low activity radioactive wastes, including naturally occurring radioactive material (NORM) and technologically enhanced NORM (TENORM) (USEI 2009). The performance of the landfill with regard to radiological operating permit requirements was previously assessed using a model constructed with the residual radioactivity (RESRAD) computer program, developed by Argonne National Laboratory for the U.S. Department of Energy (DOE). RESRAD supports the evaluation of several environmental transport pathways related to a radionuclide-contaminated soil source term, but it was not conceived as a model for the evaluation of landfill radiological performance. A more comprehensive and realistic model is desired in order to better support submissions to both the State of Idaho's Department of Environmental Quality as well as the U.S. Nuclear Regulatory Commission. A Performance Assessment (PA) computer model was developed using GoldSim software for the USEI RCRA Subtitle C landfill. The RESRAD computer model was specifically developed for calculating soil cleanup criteria and radiological dose and cancer risk from residual radioactive material in soil. To evaluate site-specific conditions, users may select from among a number of available environmental transport and exposure pathways and modify 'default' parameter values. In GoldSim, a user must construct the model 'from scratch.' However, this modeling is facilitated by a number of specialized elements available in GoldSim to support a radiological mass transport model. These include elements for defining radiological decay and ingrowth, container failure and radiological release, advective and diffusive transport, and other processes. Advantages afforded by the use of RESRAD for modeling radiological dose for a RCRA Subtitle C landfill include ease of use and reasonable flexibility in specifying site-specific conditions. GoldSim allows for considerably more flexibility and site-specificity than RESRAD, including evaluation of potentially relevant environmental transport processes not supported in RESRAD. The probabilistic modeling capabilities of GoldSim also far exceed those of RESRAD. The pros and cons of RESRAD and GoldSim for this modeling problem are explored with a focus on identifying approaches and critical factors in identifying the appropriate platform. The capabilities of RESRAD and GoldSim for mathematically modeling the disposal system will be contrasted and compared. For example, the existing RESRAD radiological safety assessment evaluated potentially complete exposure pathways related to infiltration to groundwater and upwards diffusion of radon. Additional transport pathways identified in the USEI Idaho facility Conceptual Site Model include deposition of radon decay products in cover material, root uptake of radionuclides in disposed wastes by native plants, and mixing of cover material by burrowing animals. Results of the two models and how the different transport and dose pathways affect results will be discussed. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Contrasting Carbon–Water–Energy Dynamics in Perennial and Annual Bioenergy Agroecosystems Using Eddy Covariance and Interpretable Machine Learning

Understanding how agroecosystems respond to environmental variability is fundamental to predicting productivity and sustainability under a changing climate. We analyzed 55 site-years of high-frequency eddy covariance observations from five agroecosystems—two perennial grasses (miscanthus and switchgrass), two annual rotation systems (maize–soybean and sorghum–soybean), and a restored native prairie—to examine ecosystem-scale carbon, water, and energy fluxes. Using an interpretable machine-learning framework with regression tree ensembles, Shapley Additive Explanations, and Accumulated Local Effects, we quantified how environmental and temporal factors regulate gross primary productivity (GPP), evapotranspiration (ET), water-use efficiency, and the Bowen ratio. Perennials exhibited stronger physiological buffering and maintained fluxes across a broader range of temperature and moisture conditions, reflecting deeper rooting and persistent canopy cover. Annuals, in contrast, showed greater short-term variability and stronger coupling to atmospheric demand, with GPP and ET declining rapidly under low humidity or soil moisture. Differences in temperature sensitivity of Bowen ratio further revealed that perennials sustained proportionally greater sensible heat flux under cool conditions, whereas annuals exhibited constrained energy exchange when evaporative demand was low. Together, these results demonstrate that crop life cycle and canopy structure are fundamental determinants of ecosystem-scale carbon–water–energy coupling. By integrating long-term flux observations with interpretable machine learning, this study identifies the environmental drivers that shape agroecosystem function and highlights how conversion from annual to perennial feedstocks can enhance climatic resilience and alter land–atmosphere energy feedbacks. These findings provide a data-driven basis for improving crop and Earth-system models and for guiding bioenergy landscape design under future climate scenarios.

Accumulated Local Effects↗

Arbuscular mycorrhizal fungal community responses to drought and nitrogen fertilization in switchgrass stands

Anthropogenic global change is increasing the severity and frequency of abiotic stresses such as drought that are likely to affect soil communities. Arbuscular mycorrhizal fungi (AMF) play important roles in many soil processes, so it is important to understand how drought affects AMF biodiversity. This is especially relevant in agricultural systems where crops rely on AMF associations for water and nutrient uptake, and where management decisions such as crop selection and fertilizer application may influence how the AMF community responds to drought. In this study, we examined the effects of reduced precipitation and nitrogen fertilization on AMF richness, community composition, and root and soil colonization in monocultures of two cultivars of switchgrass (Panicum virgatum) grown for bioenergy feedstock. We conducted a two-year field experiment using rain-out shelters to manipulate precipitation in mature stands of switchgrass growing in a long-term nitrogen fertilization (0 or 56 kg N ha –1 ) experiment at the W.K. Kellogg Biological Station Long-Term Ecological Research site in Michigan, USA. We expected that AMF richness and colonization would decrease due to drought, as predicted by the stress exclusion hypothesis. Contrary to our expectations, we found that drought stress increased AMF species richness in fertilized plots by 15%; there was no effect of drought on AMF richness in unfertilized plots. Drought also significantly altered AMF community composition, primarily due to increases in Rhizophagus taxa abundance, and reduced AMF root colonization in switchgrass by 6%. We also found variation in AMF richness and colonization across switchgrass cultivars as well as sampling dates. Furthermore, the changes in AMF richness and composition that we observed in this study may have implications for perennial bioenergy feedstock selection and management as changes in AMF communities may feedback to affect host plants.

54 ENVIRONMENTAL SCIENCES↗

Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability

Snow plays a critical role in carbon cycling, vegetation dynamics, and permafrost hydrology at high latitudes by influencing surface energy exchange. Predicting snow distribution patterns is essential for understanding the evolution of Arctic ecosystems, yet scaling process-level knowledge to landscape predictions remains challenging. Here, we analyze snow depth (2019 and 2022), terrain elevation, and vegetation height from a watershed on the Seward Peninsula, Alaska, to examine how topography and shrubs shape snow redistribution across spatial scales. We find that snow depth is strongly coupled to terrain at scales below ∼60 m but becomes increasingly decoupled at larger scales. The topographic model of snow depth variation, which transforms terrain data to align with these scale-dependent snow patterns, is well correlated with local snow depth variations (linear fit R 2 > 0.5 for 85% of 100-m patches). A machine learning reconstruction of shrub canopy snow trapping reveals a simple exponential relationship between canopy structure and snow accumulation ( R 2 = 0.59), highlighting the combined influence of topography and vegetation on snow distribution. Together, these empirical relationships capture much of the observed snow variability in the watershed ( R 2 = 0.49, root mean square error (RMSE) = 30 cm), though systematic limitations persist in areas of strong scour and at coarser scales where wind-terrain interactions are more complex. These findings provide a framework for more efficient snow depth prediction and offer insights to improve snow-vegetation feedback representation in Earth System Models.

54 ENVIRONMENTAL SCIENCES↗

Conserved and reproducible bacterial communities associate with extraradical hyphae of arbuscular mycorrhizal fungi

Abstract Extraradical hyphae (ERH) of arbuscular mycorrhizal fungi (AMF) extend from plant roots into the soil environment and interact with soil microbial communities. Evidence of positive and negative interactions between AMF and soil bacteria point to functionally important ERH-associated communities. To characterize communities associated with ERH and test controls on their establishment and composition, we utilized an in-growth core system containing a live soil–sand mixture that allowed manual extraction of ERH for 16S rRNA gene amplicon profiling. Across experiments and soils, consistent enrichment of members of the Betaproteobacteriales, Myxococcales, Fibrobacterales, Cytophagales, Chloroflexales, and Cellvibrionales was observed on ERH samples, while variation among samples from different soils was observed primarily at lower taxonomic ranks. The ERH-associated community was conserved between two fungal species assayed, Glomus versiforme and Rhizophagus irregularis, though R. irregularis exerted a stronger selection and showed greater enrichment for taxa in the Alphaproteobacteria and Gammaproteobacteria. A distinct community established within 14 days of hyphal access to the soil, while temporal patterns of establishment and turnover varied between taxonomic groups. Identification of a conserved ERH-associated community is consistent with the concept of an AMF microbiome and can aid the characterization of facilitative and antagonistic interactions influencing the plant-fungal symbiosis.

59 BASIC BIOLOGICAL SCIENCES↗

Recursive least squares estimation and Kalman filtering by systolic arrays

One of the most promising new directions for high-throughput-rate problems is that based on systolic arrays. In this paper, using the matrix-decomposition approach, a systolic Kalman filter is formulated as a modified square-root information filter consisting of a whitening filter followed by a simple least-squares operation based on the systolic QR algorithm. By proper skewing of the input data, a fully pipelined time and measurement update systolic Kalman filter can be achieved with O(n squared) processing cells, resulting in a system throughput rate of O (n).

Chen, M. J.↗

Control structural interaction testbed: A model for multiple flexible body verification

Conventional end-to-end ground tests for verification of control system performance become increasingly complicated with the development of large, multiple flexible body spacecraft structures. The expense of accurately reproducing the on-orbit dynamic environment and the attendant difficulties in reducing and accounting for ground test effects limits the value of these tests. TRW has developed a building block approach whereby a combination of analysis, simulation, and test has replaced end-to-end performance verification by ground test. Tests are performed at the component, subsystem, and system level on engineering testbeds. These tests are aimed at authenticating models to be used in end-to-end performance verification simulations: component and subassembly engineering tests and analyses establish models and critical parameters, unit level engineering and acceptance tests refine models, and subsystem level tests confirm the models' overall behavior. The Precision Control of Agile Spacecraft (PCAS) project has developed a control structural interaction testbed with a multibody flexible structure to investigate new methods of precision control. This testbed is a model for TRW's approach to verifying control system performance. This approach has several advantages: (1) no allocation for test measurement errors is required, increasing flight hardware design allocations; (2) the approach permits greater latitude in investigating off-nominal conditions and parametric sensitivities; and (3) the simulation approach is cost effective, because the investment is in understanding the root behavior of the flight hardware and not in the ground test equipment and environment.

Chory, M. A.↗

TDRSS Onboard Navigation System (TONS) flight qualification experiment

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) is currently developing an operational Tracking and Data Relay Satellite (TDRS) System (TDRSS) Onboard Navigation System (TONS) to provide realtime, autonomous, high-accuracy navigation products to users of TDRSS. A TONS experiment was implemented on the Explorer Platform/Extreme Ultraviolet Explorer (EP/EUVE) spacecraft, launched June 7, 1992, to flight qualify the TONS operational system using TDRSS forward-link communications services. This paper provides a detailed evaluation of the flight hardware, an ultrastable oscillator (USO) and Doppler extractor (DE) card in one of the TDRSS user transponders and the ground-based prototype flight software performance, based on the 1 year of TONS experiment operation. The TONS experiment results are used to project the expected performance of the TONS 1 operational system. TONS 1 processes Doppler data derived from scheduled forward-link S-band services using a sequential estimation algorithm enhanced by a sophisticated process noise model to provide onboard orbit and frequency determination and time maintenance. TONS 1 will be the prime navigation system on the Earth Observing System (EOS)-AM1 spacecraft, currently scheduled for launch in 1998. Inflight evaluation of the USO and DE short-term and long-term stability indicates that the performance is excellent. Analysis of the TONS prototype flight software performance indicates that realtime onboard position accuracies of better than 25 meters root-mean-square are achievable with one tracking contact every one to two orbits for the EP/EUVE 525-kilometer altitude, 28.5 degree inclination orbit. The success of the TONS experiment demonstrates the flight readiness of TONS to support the EOS-AM1 mission.

Gramling, C. J.↗

Temperature cycling periods affect growth and tuberization in potatoes under continuous irradiation

Plants of the potato (Solanum tuberosum L.) cultivars Denali, Norland, Haig and Kennebec were grown for 42 days under three temperature cycling periods (thermoperiods) with continuous irradiation in two repeated experiments to help determine if temperature cycling might be varied to optimize tuber development of potatoes in controlled environments. Thermoperiods of 6/6 hours, 12/12 hours and 24/24 hours were established with the same temperature change of 22/14C and same controlled vapor pressure deficit of 0.60 kPa. The thermoperiod of 24/24 hours significantly promoted tuber initiation but slowed tuber enlargement in all four cultivars, compared to the thermoperiods of 6/6 hours and 12/12 hours. Denali' produced the highest tuber and total dry weights under the 6/6 hours thermoperiod. Kennebec' produced the highest tuber dry weight under the 12/12 hours thermoperiod. Thermoperiods had no significant effect on shoot and root dry weights of any cultivars. The major effect of thermoperiods was on initiation and enlargement of tubers.

NASA Program CELSS↗

Effect of ammonium sulfate, ammonium chloride and root-zone acidity on inorganic ion content of tobacco

Tobacco plants (Nicotiana tabacum L. cv NC82) were supplied with (NH4)2SO4 or NH4Cl at root-zone pH of 6.0 and 4.5 in hydroponic culture for 28 days. Dry matter accumulation, total N and C content, and leaf area and number were not affected by the NH4+ source or root-zone pH. Plants supplied with NH4Cl accumulated up to 1.2 mM Cl g DW-1, but accumulated 37% less inorganic H2PO4- and 47% less SO4(2-) than plants supplied with (NH4)2SO4. The large Cl- accumulation resulted in NH4Cl- supplied plants having a 31% higher inorganic anion (NO3-, H2, PO4-, SO4(2-), and Cl-) charge. This higher inorganic anion charge in the NH4Cl-supplied plants was balanced by a similar increase in K+ charge. Plants supplied with NH4Cl accumulated greater concentrations of Cl- in leaves (up to 5.1% of DW) than plants supplied with (NH4)2SO4 (less than -% DW). Despite the high Cl- concentration of leaves in NH4Cl supplied plants, these plants showed no symptoms of Cl- toxicity. This demonstrates that toxicity symptoms are not due solely to an interaction between high Cl- concentration in tissue and NH4+ nutrition. The increase in root-zone acidity to pH 4.5 from 6.0 did not induce toxicity symptoms.

NASA Program CELSS↗