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NASA NTRS2008

Potential Use of a Bayesian Network for Discriminating Flash Type from Future GOES-R Geostationary Lightning Mapper (GLM) data

Continuous monitoring of the ratio of cloud flashes to ground flashes may provide a better understanding of thunderstorm dynamics, intensification, and evolution, and it may be useful in severe weather warning. The National Lighting Detection Network TM (NLDN) senses ground flashes with exceptional detection efficiency and accuracy over most of the continental United States. A proposed Geostationary Lightning Mapper (GLM) aboard the Geostationary Operational Environmental Satellite (GOES-R) will look at the western hemisphere, and among the lightning data products to be made available will be the fundamental optical flash parameters for both cloud and ground flashes: radiance, area, duration, number of optical groups, and number of optical events. Previous studies have demonstrated that the optical flash parameter statistics of ground and cloud lightning, which are observable from space, are significantly different. This study investigates a Bayesian network methodology for discriminating lightning flash type (ground or cloud) using the lightning optical data and ancillary GOES-R data. A Directed Acyclic Graph (DAG) is set up with lightning as a "root" and data observed by GLM as the "leaves." This allows for a direct calculation of the joint probability distribution function for the lighting type and radiance, area, etc. Initially, the conditional probabilities that will be required can be estimated from the Lightning Imaging Sensor (LIS) and the Optical Transient Detector (OTD) together with NLDN data. Directly manipulating the joint distribution will yield the conditional probability that a lightning flash is a ground flash given the evidence, which consists of the observed lightning optical data [and possibly cloud data retrieved from the GOES-R Advanced Baseline Imager (ABI) in a more mature Bayesian network configuration]. Later, actual GLM and NLDN data can be used to refine the estimates of the conditional probabilities used in the model; i.e., the Bayesian network is a learning network. Methods for efficient calculation of the conditional probabilities (e.g., an algorithm using junction trees), finding data conflicts, goodness of fit, and dealing with missing data will also be addressed.

Solakiewiz, Richard↗

NASA NTRS2023

Fine particulate concentrations over East Asia derived from aerosols measured by the Advanced Himawari Imager using machine learning

Fine particulate matter with a diameter below 2.5 μm (PM 2.5 ) is deleterious to the cardiovascular and respiratory systems. It is often difficult to assess the effects of PM 2.5 on human health over regions with limited ground monitoring sites, especially in East Asia. As an alternative, we estimated near-surface PM 2.5 concentrations by analyzing Advanced Himawari Imager (AHI) Yonsei Aerosol Retrieval (YAER) products. This study incorporates daytime data for East Asia covering the Korean Peninsula, China, Japan, Southeast Asia, and southern Mongolia. We collocated AHI YAER product pixels with meteorological, land-cover, and other ancillary data for the period from March 2018 to February 2019. To estimate PM 2.5 concentrations over wide areas spanning many countries displaying various relationships between aerosol optical depth and PM 2.5 , monthly models were developed by considering both the spatial and temporal characteristics of ground-based PM 2.5 measurements. Random forest machine learning model estimated ground-level mass concentrations of PM 2.5 ; subsequent 10-fold cross validation (CV) yielded a CV R 2 value of 0.81 and a CV root mean squared error (RMSE) of 12.3 μg m -3 . We investigated the spatial pattern of PM 2.5 concentrations over multiple countries and seasonal variation in PM 2.5 concentrations. Diurnal variation of a severe PM 2.5 event in the Korean Peninsula was investigated as a case study. The model captured the extremely heterogeneous spatial distribution of PM 2.5 concentrations peaked around local noon. To measure the capability of the developed model to estimate PM 2.5 concentrations in areas with few in-situ data, its predictive performance was evaluated using a dataset independent of the training process with an R 2 of 0.60 and RMSE of 8.18 μg m −3 . This study demonstrates the potential for satellite-based PM 2.5 estimation for areas with insufficient measuring stations.

Pm2.5↗

DOE OSTI2024

Belowground plant allocation regulates rice methane emissions from degraded peat soils

Carbon-rich peat soils have been drained and used extensively for agriculture throughout human history, leading to significant losses of their soil carbon. One solution for rewetting degraded peat is wet crop cultivation. Crops such as rice, which can grow in water-saturated conditions, could enable agricultural production to be maintained whilst reducing CO 2 and N 2 O emissions from peat. However, wet rice cultivation can release considerable methane (CH 4 ). Water table and soil management strategies may enhance rice yield and minimize CH 4 emissions, but they also influence plant biomass allocation strategies. It remains unclear how water and soil management influences rice allocation strategies and how changing plant allocation and associated traits, particularly belowground, influence CH 4 -related processes. We examined belowground biomass (BGB), aboveground biomass (AGB), belowground:aboveground ratio (BGB:ABG), and a range of root traits (root length, root diameter, root volume, root area, and specific root length) under different soil and water treatments; and evaluated plant trait linkages to CH 4 . Rice (Oryza sativa L.) was grown for six months in field mesocosms under high (saturated) or low water table treatments, and in either degraded peat soil or degraded peat covered with mineral soil. We found that BGB and BGB:AGB were lowest in water saturated conditions where mineral soil had been added to the peat, and highest in low-water table peat soils. Furthermore, CH 4 and BGB were positively related, with BGB explaining 60% of the variation in CH 4 but only under low water table conditions. Our results suggest that a mix of low water table and mineral soil addition could minimize belowground plant allocation in rice, which could further lower CH 4 likely because root-derived carbon is a key substrate for methanogenesis. Minimizing root allocation, in conjunction with water and soil management, could be explored as a strategy for lowering CH 4 emissions from wet rice cultivation in degraded peatlands.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Miscanthus: An Environmental Choice for Marginal Lands

Miscanthus x giganteus, or Giant Miscanthus, is a tall, perennial grass originally from Asia. It is considered a sterile hybrid that has been bred to not produce viable seeds. Instead, rhizomes are planted to establish the crop. Here, the rhizome is an underground modified stem mass that puts out shoots and roots supporting new growth each year. This perennial crop takes two to three years to reach maturity, but established stands can reach upwards of 12 ft. tall with a very thick canopy (Pyter, 2007). Miscanthus has shown potential for high dry matter yields compared to other biomass crops, which could in turn lead to more efficient land use especially when applied to a bioenergy and bioproduct supply chain. In one study, switchgrass (Panicum virgatum) yielded 10.3 Mg/ha of biomass on average, while miscanthus yielded 22.4 Mg/ha (Heaton et al., 2004). Additionally, miscanthus production has been associated with many environmental benefits, including benefits to water quality, nutrient load removal, soil stabilization, and soil health (Bhardwaj et al., 2011; Hussain et al., 2019). Many of the possible practical and environmental benefits that are associated with miscanthus production may be attractive to stakeholders who are interested in alternative land use options, particularly in areas considered to be marginal in productivity.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2016

Assessment of the SMAP Passive Soil Moisture Product

The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational Level 2 soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 kilometer Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 cubic meter per cubic meter unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 cubic meter per cubic meter.

passive↗

NASA NTRS2000

Controlling Microbial Byproducts using Model-Based Substrate Monitoring and Control Strategies

We have developed a computer-controlled bioreactor system to study various aspects of microbially-mediated nitrogen cycling. The system has been used to investigate methods for controlling microbial denitrification (the dissimilatory reduction of nitrate to N2O and N2) in hydroponic plant growth chambers. Such chambers are key elements of advanced life support systems being designed for use on long duration space missions, but nitrogen use efficiency in them is reduced by denitrification. Control software architecture was designed which permits the heterogeneous control of system hardware using traditional feedback control, and quantitative and qualitative models of various system features. Model-based feed forward control entails prediction of future systems in states and automated regulation of system parameters to achieve desired and avoid undesirable system states. A bacterial growth rate model based on the classic Monod model of saturation kinetics was used to evaluate the response of several individual denitrifying species to varying environmental conditions. The system and models are now being applied to mixed microbial communities harvested from the root zone of a hydroponic growth chamber. The use of a modified Monod organism interaction model was evaluated as a means of achieving more accurate description of the dynamic behavior of the communities. A minimum variance parameter estimation routine was also' used to calibrate the constant parameters in the model by iterative evaluation of substrate (nitrate) uptake and growth kinetics. This representation of processes and interactions aids in the formulation of control laws. The feed forward control strategy being developed will increase system autonomy, reduce crew intervention and limit the accumulation of undesirable waste products (NOx).

Smernoff, David T.↗

NASA NTRS2019

An L-Band Brightness Temperature Disaggregation Method Using S-Band Radiometer Data for the Water Cycle Observation Mission (WCOM)

The Water Cycle Observation Mission (WCOM) will build upon previous L and C band passive microwave soil moisture satellite missions. WCOM will consist of a passive microwave synthetic aperture radiometer operating at L, S, and C bands. The WCOM requirements for passive soil moisture are to estimate soil moisture in the top 5 cm of soil layer with an error less than 0.04 cu m/cu m, at 15 km resolution and with a 3-day revisit. A new set of algorithms for these multi-frequency platforms will need to be developed for estimating the data products at the desired resolution. To accomplish this, a brightness temperature (TB) downscaling methodology is developed that uses passive S-band TB (30 km) to downscale L-band TB (50 km) and to estimate soil moisture at a 30 km resolution, based on the linear relationships between the passive signals of L-band and S-band. To test this downscaling method, analysis was performed using PALS data from the Soil Moisture Experiments in 2002 (SMEX02). For this study, 4 km L-band observations were downscaled to 800 m. The root mean square errors (RMSE) between the downscaled TBL at 800m with the observed TBL at 800m are 2.63 K and 1.60 K for H and V polarizations respectively. The results also showed that it was possible to use these disaggregated TB to estimate soil moisture to meet the mission requirement of 0.04 cu m/cu m. These results showed that we can obtain higher resolution soil moisture from L band passive TB with a high accuracy (<0.04 cu m/cu m) by using S-band information.

Disaggregation↗

DOE OSTI2026

A biosynthetic gene cluster for three post-chorismate pathways in Arabidopsis

Chorismate is a branch-point metabolite in the biosynthesis of aromatic amino acids, vitamins, antibiotics and various other aromatic products in bacteria, fungi and plants. Although 13 chorismate-utilizing enzymes have been identified in bacteria, only 6 have been described in plants, where an estimated 30% of all photosynthetically fixed carbon passes through chorismate. Here, in this study, we describe a biosynthetic gene cluster (BGC) consisting of five core genes, including two reductases, two methyltransferases and one glucosyltransferase. Genetic and biochemical evidence shows that these five enzymes collectively give rise to three biosynthetic pathways, each originating from chorismate: two parallel pathways produce a class of non-aromatic, isomeric compounds abundant in the roots of Arabidopsis thaliana, whereas the third pathway produces methylated and glucosylated chorismate derivatives that subsequently react non-enzymatically with glutathione. Genome analysis revealed that variants of this BGC are present in some but not all species in the Brassicaceae family. Taken together, our study uncovered a BGC, containing three chorismate-utilizing enzymes, that controls three distinct post-chorismate pathways in A. thaliana. This work not only advances our understanding of carbon flow in this model plant but also highlights that the biochemical complexity encoded by plant BGCs is greater than previously appreciated.

Peng, Meng [Ghent Univ. (Belgium); Flemish Institu↗

NASA NTRS1996

Effect of CO2 levels on nutrient content of lettuce and radish

Atmospheric carbon-dioxide enrichment is known to affect the yield of lettuce and radish grown in controlled environments, but little is known about CO2 enrichment effects on the chemical composition of lettuce and radish. These crops are useful model systems for a Controlled Ecological Life-Support System (CELSS), largely because of their relatively short production cycles. Lettuce (Lactuca sativa L.) cultivar 'Waldmann's Green' and radish (Raphanus sativus L.) cultivar 'Giant White Globe' were grown both in the field and in controlled environments, where hydroponic nutrient solution, light, and temperature were regulated, and where CO2 levels were controlled at 400, 1000, 5000, or 10,000 ppm. Plants were harvested at maturity, dried, and analyzed for proximate composition (protein, fat, ash, and carbohydrate), total nitrogen (N), nitrate N, free sugars, starch, total dietary fiber, and minerals. Total N, protein N, nonprotein N (NPN), and nitrate N generally increased for radish roots and lettuce leaves when grown under growth chamber conditions compared to field conditions. The nitrate-N level of lettuce leaves, as a percentage of total NPN, decreased with increasing levels of CO2 enrichment. The ash content of radish roots and of radish and lettuce leaves decreased with increasing levels of CO2 enrichment. The levels of certain minerals differed between field- and chamber-grown materials, including changes in the calcium (Ca) and phosphorus (P) contents of radish and lettuce leaves, resulting in reduced Ca/P ratio for chamber-grown materials. The free-sugar contents were similar between the field and chamber-grown lettuce leaves, but total dietary fiber content was much higher in the field-grown plant material. The starch content of growth-chamber lettuce increased with CO2 level.

NASA Discipline Life Support Systems↗

NASA NTRS2012

Improving the Accuracy of the AFWA-NASA (ANSA) Blended Snow-Cover Product over the Lower Great Lakes Region

The Air Force Weather Agency (AFWA) -- NASA blended snow-cover product, called ANSA, utilizes Earth Observing System standard snow products from the Moderate- Resolution Imaging Spectroradiometer (MODIS) and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) to map daily snow cover and snow-water equivalent (SWE) globally. We have compared ANSA-derived SWE with SWE values calculated from snow depths reported at ~1500 National Climatic Data Center (NCDC) co-op stations in the Lower Great Lakes Basin. Compared to station data, the ANSA significantly underestimates SWE in densely-forested areas. We use two methods to remove some of the bias observed in forested areas to reduce the root-mean-square error (RMSE) between the ANSA- and station-derived SWE. First, we calculated a 5- year mean ANSA-derived SWE for the winters of 2005-06 through 2009-10, and developed a five-year mean bias-corrected SWE map for each month. For most of the months studied during the five-year period, the 5-year bias correction improved the agreement between the ANSA-derived and station-derived SWE. However, anomalous months such as when there was very little snow on the ground compared to the 5-year mean, or months in which the snow was much greater than the 5-year mean, showed poorer results (as expected). We also used a 7-day running mean (7DRM) bias correction method using days just prior to the day in question to correct the ANSA data. This method was more effective in reducing the RMSE between the ANSA- and co-op-derived SWE values, and in capturing the effects of anomalous snow conditions.

Hall, Dorothy K.↗

NASA NTRSDate not supplied

Plant Water Management in Microgravity

The NASA Plant Water Management (PWM) technology demonstrations aboard ISS apply recent advances in microgravity capillary fluidics research towards the mundane yet problematic challenges of simply watering plants in space. Plant growth in a low-g environment is often hampered by inadequate aeration and oversaturation of the root zone. The present effort aims to exploit the passive capillary forces of poorly wetting liquids (i.e., contaminated water) within unique system geometries that effectively replace the role of gravity in providing sufficient aeration and hydration for simulated plants. Several flight demonstrations have been completed on ISS, including soil and hydroponic models in single and parallel channel networks. The results demonstrate proof-of-concept, system stability, limits of operation, more. The implications are discussed in relation to plant growth facilities for further near-term microgravity plant science research as well as automated food production for long duration human exploration missions.

microgravity↗

NASA NTRSDate not supplied

Thermal Model of Ice Growth in Vacuum for Lunar Water Production

To support NASA’s goal of sustained lunar presence, the use of in-situ resource utilization will reduce launch weight and frequency of resupply missions. With the discovery of water in the permanently shadowed regions of the moon, the prospect of harvesting water has generated particular interest. A more fundamental understanding of water storage and capture in lunar conditions is necessary for effective and efficient water capture and transport. The present study derives a thermal model for ice height, heat flux, chamber pressure, and mass flow rate in sub-atmospheric pressures below the triple point. The thermal model compares ice layer height against the results of the experiment at two pressures (300 Pa and 500 Pa) and temperatures from -18°C to -3°C. The thermal model predicts the trends seen experimentally with an overall root mean square error of 0.1135 cm and coefficient of efficiency of 0.994, indicating the model predicts the experimental results. The thermal model can be utilized to examine the impacts of varying pressure, temperature, and cold plate area to determine the most effective ice growth conditions for efficient capture of water on the lunar surface. The thermal model will provide a useful tool for NASA in the design of the lunar ice tanker and shows the promise of effective capture water on the lunar surface.

Ice growth↗

NASA NTRSDate not supplied

Thermal Model of Ice Growth in Vacuum for Lunar Water Production

Ice growth↗

DOE OSTI2026

Making an s1G Self-Preserving Environmental DNA (eDNA) Filter from Sustainable Materials

Environmental DNA (eDNA) sampling of aquatic environments is a powerful new tool for resource managers to use in detecting the presence of rare and endangered species. The use of eDNA for species detection is quickly becoming an industry-standard methodology in environmental science, and the technology sector is moving quickly to create purpose-built tools for eDNA sampling. Smith-Root, Inc. pioneered the new technology of self-preserving eDNA filters that automatically preserve the DNA captured on filters by desiccating the internal filter membrane. This capability saves the sampling technician significant time in the field and drastically reduces the potential for sample contamination. One main constraint of this new technology, however, is the necessity of single-use plastics for eDNA sampling. Single-use designs are employed because sampling equipment must be devoid of potential contaminating DNA, and the time required to sterilize equipment is often not cost-effective for practitioners. Thus, this technology is creating a significant new source of plastic waste—something that eDNA practitioners, and society, would like to avoid. This project explores the use of alternative bio based polymers and composites as replacements for incumbent industrial standards for eDNA filtration systems, with an emphasis on ease of processing and biodegradable options. 8 candidate materials, 3 for the top filter housing and 5 for the bottom filter housing, were investigated to replace incumbent housing materials. Of the 8 candidates, 2 materials were identified for future investigation which met performance requirements, were bio-based and could potentially offer better disposal options like soil degradation or composting, features sought by the customers of these products. The top housing candidate, material 1, has comparable performance to the incumbent material and equally manufacturable. The bottom housing candidate, material 6, improved desiccation performance by 81% after 1 hour in comparison to the incumbent material, is 100% bio-based, compostable and can be sourced domestically throughout the U.S.A.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Morphophysiological Plant Phenotyping for the Development of Plant Breeding Under Drought and Heat Conditions: A Practical Approach

ABSTRACT Currently, the breeding programs focus their efforts on identifying and developing tolerant genotypes to adverse conditions, such as drought and high temperatures. In this context, the physiological approach, which involves phenotyping several traits, is useful for breeding programs. Leaf photosynthetic traits have become one of the main objectives to be evaluated for breeders due to their relationship with improving grain yield and biomass production. Gas exchange ( Ge ) and chlorophyll “a” fluorescence ( Chf ) are the main tools to characterize the photosynthetic activity in real time at the leaf level. Consequently, several association studies using proximal and nonproximal sensing (e.g., RGB, thermography) have been developed. However, for the correct application of this breeding approach, it is essential to have a basic knowledge of both the physiological principles involved in the readings and the limitations of phenotyping due to the characteristics of the devices available on the market. This revision also covers other traits, such as the morphological and anatomical characteristics of leaves and roots, and the use of isotopes complementing Ge and Chf measurements.

Estrada, Félix [Instituto de Investigaciones Agrop↗

DOE OSTI2025

Variation in Flooding Tolerance in Populus deltoides ‘D-124’ and P. trichocarpa x P. deltoides Hybrid ‘52–225’

Flooding poses a substantial challenge to plant survival and productivity, particularly in riparian genus like Populus. This study examines the physiological, morphological, metabolic, and molecular responses of Populus deltoides ‘D-124’ and P. trichocarpa x P. deltoides hybrid clone ‘52–225’ under control and inundated conditions to identify differences in flooding tolerance. Under flooding conditions, physiological and cellular stress was more pronounced in P. deltoides ‘D-124’ than in the hybrid clone ‘52–225,’ as evidenced by lower transpiration (E), photosynthesis (A), and chlorophyll content. In contrast, ‘52–225’ showed reduced ROS accumulation suggesting better cellular function under stress. Morphologically, ‘52–225’ produced more shoot-born roots, which likely enhance oxygen transport and metabolic activity during flooding. Metabolite profiling revealed both overlapping and distinct patterns of sugar and amino acid accumulation between genotypes. Gene expression analysis revealed that flooding-responsive genes, including ALCOHOL DEHYDROGENASE 1 and HYPOXIA RESPONSIVE ERF 2, were activated in both genotypes, with a more pronounced response noted in ‘52–225.’ These findings extend our understanding of flooding tolerance mechanisms in Populus by connecting physiological traits, stress responses, and genetic regulation. This research contributes to the development of more flooding-resilient poplar varieties, with potential applications in breeding and restoration programs for flooding-prone environments.

Flooding stress↗

NASA NTRS1990

Preparatory space experiments for development of a CELSS

The goal of Closed Ecological Life Support System (CELSS) studies is to examine the effects of microgravity on yield and quality of plant products and on the interactions between irradiance and crop area. Measuring yield and quality of crops as a function of irradiance in microgravity is virtually unique to the CELSS program, as is the emphasis on canopies rather than individual plants. The first step for space experiments is to develop a relatively stress free environment for plant growth, something that has so far never been achieved. High light levels are essential, and there must be time enough to complete a significant portion of the life cycle. Optimal atmosphere and nutrients must be provided. Such responses as germination, orientation of roots and shoots, photosynthesis and respiration, floral initiation and development, and seed maturation and viability will be studied.

Salisbury, Frank B.↗

NASA NTRS2004

Response of graywater recycling systems based on hydroponic plant growth to three classes of surfactants

Anionic (sodium laureth sulfate, SLES), amphoteric (cocamidopropyl betaine, CAPB) and nonionic (alcohol polyethoxylate, AE) surfactants were added to separate nutrient film technique (NFT) hydroponic systems containing dwarf wheat (Triticum aestivum cv. USU Apogee) in a series of 21 day trials. Surfactant was added either in a (1). temporally dynamic mode (1-3 g surfactant m(-2) growing area d(-1)) as effected by automatic addition of a 300 ppm surfactant solution to meet plant water demand, or (2). continuous mode (2 g surfactant m(-2) growing area d(-1)) as effected by slow addition (10 mLh(-1)) of a 2000 ppm surfactant solution beginning at 4d after planting. SLES showed rapid primary degradation in both experiments, with no accumulation 24 h after initial addition. CAPB and AE were degraded less rapidly, with 30-50% remaining 24 h after initial addition, but CAPB and AE levels were below detection limit for the remainder of the study. No reductions in vegetative growth of wheat were observed in response to SLES, but biomass was reduced 20-25% with CAPB and AE. Microbial communities associated with both the plant roots and wetted hardware surfaces actively degraded the surfactants, as determined by monitoring surfactant levels following pulse additions at day 20 (with plants) and day 21 (after plant removal). In order to test whether the biofilm communities could ameliorate phytotoxicity by providing a microbial community acclimated for CAPB and AE decay, the continuous exposure systems were planted with wheat seeds after crop removal at day 21. Acclimation resulted in faster primary degradation (>90% within 24h) and reduced phytotoxicity. Overall, the studies indicate that relatively small areas (3-5m(2)) of hydroponic plant systems can process per capita production of mixed surfactants (5-10 g x person(-1)d(-1)) with minimal effects on plant growth.

Hydroponics↗