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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Differences in the response of wheat, soybean and lettuce to reduced blue radiation

Although many fundamental blue light responses have been identified, blue light dose-response curves are not well characterized. We studied the growth and development of soybean, wheat and lettuce plants under high-pressure sodium (HPS) and metal halide (MH) lamps with yellow filters creating five fractions of blue light. The blue light fractions obtained were < 0.1, 2 and 6% under HPS lamps, and 6, 12 and 26% under MH lamps. Studies utilizing both lamp types were done at two photosynthetic photon flux levels, 200 and 500 mumol m-2 s-1 under a 16 h photoperiod. Phytochrome photoequilibria was nearly identical among treatments. The blue light effect on dry mass, stem length, leaf area, specific leaf area and tillering/branching was species dependent. For these parameters, wheat did not respond to blue light, but lettuce was highly sensitive to blue light fraction between 0 and 6% blue. Soybean stem length decreased and leaf area increased up to 6% blue, but total dry mass was unchanged. The blue light fraction determined the stem elongation response in soybean, whereas the absolute amount of blue light determined the stem elongation response in lettuce. The data indicate that lettuce growth and development requires blue light, but soybean and wheat may not.

NASA Discipline Life Support Systems↗
NASA NTRS2022

Estimating Species-Specific Leaf Area Index and Basal Area Using Optical and SAR Remote Sensing Data in Acadian Mixed Spruce-Fir Forests, USA

This study combined Sentinel-1 synthetic aperture radar (SAR), Sentinel-2 multispectral, and site variable datasets to model leaf area index (LAI) and basal area per ha (BAPH) of two economically important tree species in Northeast, USA; red spruce (Picea rubens Sarg.; RS), and balsam fir (Abies balsamea (L.) Mill.; BF). We used Random Forest (RF), and Multi-Layer Perceptron (MLP) algorithms for LAI and BAPH modeling. The results showed that RF outperformed MLP by reducing the normalized root mean square error (nRMSE) by 0.01 and 0.06 for LAI and BAPH, respectively. The final variables selected for modeling of both LAI and BAPH indicated the superiority of Sentinel-2 variables over the Sentinel-1 SAR with minor contributions of site variables (mainly elevation). The red-edge spectral vegetation indices played a significant role in both LAI and BAPH estimation. We attained the lowest nRMSEs of 0.12, and 0.16 for the final LAI model of RS, and BF, respectively using Sentinel-2 and site variables. The lowest nRMSE for both RS and BF BAPH models was 0.12. As RS and BF are the primary host species for a cyclically occurring and most destructive pest of the region, eastern spruce budworm (Choristoneura fumiferana; SBW), these estimations will be useful to evaluate SBW dynamics in the region.

Forest inventory↗
NASA NTRS2001

Evidence for yellow light suppression of lettuce growth

Researchers studying plant growth under different lamp types often attribute differences in growth to a blue light response. Lettuce plants were grown in six blue light treatments comprising five blue light fractions (0, 2, 6% from high-pressure sodium [HPS] lamps and 6, 12, 26% from metal halide [MH] lamps). Lettuce chlorophyll concentration, dry mass, leaf area and specific leaf area under the HPS and MH 6% blue were significantly different, suggesting wavelengths other than blue and red affected plant growth. Results were reproducible in two replicate studies at each of two photosynthetic photon fluxes, 200 and 500 mumol m-2 s-1. We graphed the data against absolute blue light, phytochrome photoequilibrium, phototropic blue, UV, red:far red, blue:red, blue: far red and 'yellow' light fraction. Only the 'yellow' wavelength range (580-600 nm) explained the differences between the two lamp types.

Non-NASA Center↗
NASA NTRS2004

Functional Groups Based on Leaf Physiology: Are they Spatially and Temporally Robust?

The functional grouping hypothesis, which suggests that complexity in ecosystem function can be simplified by grouping species with similar responses, was tested in the Florida scrub habitat. Functional groups were identified based on how species in fire maintained Florida scrub regulate exchange of carbon and water with the atmosphere as indicated by both instantaneous gas exchange measurements and integrated measures of function (%N, delta C-13, delta N-15, C-N ratio). Using cluster analysis, five distinct physiologically-based functional groups were identified in the fire maintained scrub. These functional groups were tested to determine if they were robust spatially, temporally, and with management regime. Analysis of Similarities (ANOSIM), a non-parametric multivariate analysis, indicated that these five physiologically-based groupings were not altered by plot differences (R = -0.115, p = 0.893) or by the three different management regimes; prescribed burn, mechanically treated and burn, and fire-suppressed (R = 0.018, p = 0.349). The physiological groupings also remained robust between the two climatically different years 1999 and 2000 (R = -0.027, p = 0.725). Easy-to-measure morphological characteristics indicating functional groups would be more practical for scaling and modeling ecosystem processes than detailed gas-exchange measurements, therefore we tested a variety of morphological characteristics as functional indicators. A combination of non-parametric multivariate techniques (Hierarchical cluster analysis, non-metric Multi-Dimensional Scaling, and ANOSIM) were used to compare the ability of life form, leaf thickness, and specific leaf area classifications to identify the physiologically-based functional groups. Life form classifications (ANOSIM; R = 0.629, p 0.001) were able to depict the physiological groupings more adequately than either specific leaf area (ANOSIM; R = 0.426, p = 0.001) or leaf thickness (ANOSIM; R 0.344, p 0.001). The ability of life forms to depict the physiological groupings was improved by separating the parasitic Ximenia americana from the shrub category (ANOSIM; R = 0.794, p = 0.001). Therefore, a life form classification including parasites was determined to be a good indicator of the physiological processes of scrub species, and would be a useful method of grouping for scaling physiological processes to the ecosystem level.

Foster, Tammy E.↗
NASA NTRS2000

BOREAS TE-6 Multiband Vegetation Imager Data

The BOREAS TE-6 team collected data in support of its efforts to examine the influence of vegetation and climate on the major carbon fluxes in boreal tree species. A newly developed ground-based canopy imaging system called an MVI was tested and used by the BOREAS TE-06 team to collect measurements of the canopy crap fraction (sky fraction), canopy gap-size distribution (size and frequency of gaps between foliage in canopy), branch architecture, and leaf angle distribution (fraction of leaf area in specific leaf inclination classes assuming azimuthal symmetry). Measurements of the canopy gap-size distribution are used to derive canopy clumping indices that can be used to adjust indirect LAI measurements made in nonrandom forests. These clumping factors will also help to describe the radiation penetration in clumped canopies more accurately by allowing for simple adjustments to Beer's law. Measurements of the above quantities were obtained at BOREAS NSA-OJP site in IFC-2 in 1994, at the SSA-OA in July 1995, and at the SSA-OBS and SSA-OA sites in IFC-2 in 1996. Modeling studies were also performed to further validate MVI measurements and to gain a more complete understanding of boreal forest canopy architecture. By using MVI measurements and Monte Carlo simulations, clumping indices as a function of zenith angle were derived for the three main boreal species studied during BOREAS. The analyzed data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distrobuted Activity Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2002

Functional Groups Based on Leaf Physiology: Are they Spatially and Temporally Robust?

The functional grouping hypothesis, which suggests that complexity in function can be simplified by grouping species with similar responses, was tested in the Florida scrub habitat. Functional groups were identified based on how species in fire maintained FL scrub function in terms of carbon, water and nitrogen dynamics. The suite of physiologic parameters measured to determine function included both instantaneous gas exchange measurements obtained from photosynthetic light response curves and integrated measures of function. Using cluster analysis, five distinct physiologically-based functional groups were identified. Using non-parametric multivariate analyses, it was determined that these five groupings were not altered by plot differences or by the three different management regimes; prescribed burn, mechanically treated and burn, and fire-suppressed. The physiological groupings also remained robust between the two years 1999 and 2000. In order for these groupings to be of use for scaling ecosystem processes, there needs to be an easy-to-measure morphological indicator of function. Life form classifications were able to depict the physiological groupings more adequately than either specific leaf area or leaf thickness. THe ability of life forms to depict the groupings was improved by separating the parasitic Ximenia americana from the shrub category.

Foster, Tammy E.↗
NASA NTRS2000

Growth, pod, and seed yield, and gas exchange of hydroponically grown peanut in response to CO2 enrichment

The effects of elevated CO2 on growth, pod, and seed yield, and gas exchange of 'Georgia Red' peanut (Arachis hypogaea L.) were evaluated under controlled environmental conditions. Plants were exposed to concentrations of 400 (ambient), 800, and 1200 micromoles mol-1 CO2 in reach-in growth chambers. Foliage fresh and dry weights increased with increased CO2 up to 800 micromoles mol-1, but declined at 1200 micromoles mol-1. The number and the fresh and dry weights of pods also increased with increasing CO2 concentration. However, the yield of immature pods was not significantly influenced by increased CO2. Total seed yield increased 33% from ambient to 800 micromoles mol-1 CO2, and 4% from 800 to 1200 micromoles mol-1 CO2. Harvest index increased with increasing CO2. Branch length increased while specific leaf area decreased linearly as CO2 increased from ambient to 1200 micromoles mol-1. Net photosynthetic rate was highest among plants grown at 800 micromoles mol-1. Stomatal conductance decreased with increased CO2. Carboxylation efficiency was similar among plants grown at 400 and 800 micromoles mol-1 and decreased at 1200 micromoles mol-1 CO2. These results suggest that CO2 enrichment from 400 to 800 micromoles mol-1 had positive effects on peanut growth and yield, but above 800 micromoles mol-1 enrichment seed yield increased only marginally.

NASA Discipline Life Support Systems↗
NASA NTRS1984

Tomato growth as affected by root-zone temperature and the addition of gibberellic acid and kinetin to nutrient solutions

The effect of root-zone temperature on young tomato plants (Lycopersicon esculentum Mill. cv. Heinz 1350) was evaluated in controlled environments using a recirculating solution culture system. Growth rates were measured at root-zone temperatures of 15 degrees, 20 degrees, 25 degrees, and 30 degrees C in a near optimum foliar environment. Optimum growth occurred at 25 degrees to 30 degrees during the first 4 weeks of growth and 20 degrees to 25 degrees during the 5th and 6th weeks. Growth was severely restricted at 15 degrees. Four concentrations of gibberellic acid (GA3) and kinetin were added to the nutrient solution in a separate trial; root-zone temperature was maintained at 15 degrees and 25 degrees. Addition of 15 micromoles GA3 to solutions increased specific leaf area, total leaf area, and dry weight production of plants in both temperature treatments. GA3-induced growth stimulation was greater at 15 degrees than at 25 degrees. GA3 may promote growth by increasing leaf area, enhancing photosynthesis per unit leaf area, or both. Kinetic was not useful in promoting growth at either temperature.

NASA Program CELSS↗
NASA NTRS2021

Cutting out the Middleman: Calibrating and Validating a Dynamic Vegetation Model (ED2-PROSPECT5) Using Remotely Sensed Surface Reflectance

Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types. Using a single common set of parameters across all sites, the calibrated model was able to accurately reproduce surface reflectance for sites with highly varied forest composition and structure. However, the calibrated model's predictions of leaf area index (LAI) were less robust, capturing only 46 % of the variability in the observations. Comparing the ED2 radiative transfer model with another two-stream soil–leaf–canopy radiative transfer model commonly used in remote sensing studies (PRO4SAIL) illustrated structural errors in the ED2 representation of direct radiation backscatter that resulted in systematic underestimation of reflectance. In addition, we also highlight that, to directly compare with a two-stream radiative transfer model like EDR, we had to perform an additional processing step to convert the directional reflectance estimates of AVIRIS to hemispherical reflectance (also known as “albedo”). In future work, we recommend that vegetation models add the capability to predict directional reflectance, to allow them to more directly assimilate a wide range of airborne and satellite reflectance products. We ultimately conclude that despite these challenges, using dynamic vegetation models to predict surface reflectance is a promising avenue for model calibration and validation using remote sensing data.

Alexey N Shiklomanov↗
NASA NTRS2018

Hydraulic Diversity of Forests Regulates Ecosystem Resilience During Drought

Plants influence the atmosphere through fluxes of carbon, water and energy, and can intensify drought through land–atmosphere feedback effects. The diversity of plant functional traits in forests, especially physiological traits related to water (hydraulic) transport, may have a critical role in land–atmosphere feedback, particularly during drought. Here we combine 352 site-years of eddy covariance measurements from 40 forest sites, remote-sensing observations of plant water content and plant functional-trait data to test whether the diversity in plant traits affects the response of the ecosystem to drought. We find evidence that higher hydraulic diversity buffers variation in ecosystem flux during dry periods across temperate and boreal forests. Hydraulic traits were the predominant significant predictors of cross-site patterns in drought response. By contrast, standard leaf and wood traits, such as specific leaf area and wood density, had little explanatory power. Our results demonstrate that diversity in the hydraulic traits of trees mediates ecosystem resilience to drought and is likely to have an important role in future ecosystem–atmosphere feedback effects in a changing climate.

Climate and Earth system modelling↗
NASA NTRS1986

Penetration of sunlight into a canopy - Explicit models based on vertical and horizontal leaf projections

The projections of leaf areas onto a horizontal plane and onto a vertical plane are examined for their utility in characterizing canopies for sunlight penetration (direct beam only) models. These projections exactly specify the penetration if the projections on the principal plane of the normals to the top surfaces of the leaves are in the same quadrant as the sun. Inferring the total leaf area from these projections (and therefore the penetration as a function of the total leaf area) is possible only with a large uncertainty (up to + or - 32 percent) because the projections are a specific measure of the total leaf area only if the leaf angle distribution is known. It is expected that this uncertainty could be reduced to more acceptable levels by making an approximate assessment of whether the zenith angle distribution is that of an extremophile canopy.

Otterman, J.↗
NASA NTRS1991

A hotspot model for leaf canopies

The hotspot effect, which provides important information about canopy structure, is modeled using general principles of environmental physics as driven by parameters of interest in remote sensing, such as leaf size, leaf shape, leaf area index, and leaf angle distribution. Specific examples are derived for canopies of horizontal leaves. The hotspot effect is implemented within the framework of the model developed by Suits (1972) for a canopy of leaves to illustrate what might occur in an agricultural crop. Because the hotspot effect arises from very basic geometrical principles and is scale-free, it occurs similarly in woodlands, forests, crops, rough soil surfaces, and clouds. The scaling principles advanced are also significant factors in the production of image spatial and angular variance and covariance which can be used to assess land cover structure through remote sensing.

Jupp, David L. B.↗
NASA NTRS1989

A growth analysis of waterlogging damage in mung bean (Phaseolus aureus)

Mung beans (Phaseolus aureus Roxb.) were grown for 2 weeks in gravel-vermiculite soilless mix in a growth chamber and subjected to a 1-week waterlogging period followed by a 1-week recovery period. Sequential harvests were made to determine the time course of effects of waterlogging and subsequent recovery on growth parameters by techniques of growth analysis. Root dry matter was the first to be affected, along with an increase in leaf dry matter and specific leaf weight. After a 1-week waterlogging period, specific leaf weight had more than doubled in the stressed plants. Leaf area declined in relation to the control plants as did the ratio of root dry matter to shoot dry matter. During the recovery period there was an increase in the dry matter allocation to the roots relative to the shoot. Specific leaf weight fell to control levels although the rate of leaf area elaboration did not increase during this time, suggesting a redistribution of stored assimilates from the leaves. Net assimilation rate increased during the waterlogging period, probably due to a restriction in root metabolism and reduced translocation out of the leaf rather than to an increase in photosynthesis. Net assimilation rate of waterlogged plants was severely reduced compared with control plants during the recovery period. Both relative growth rate and leaf area duration declined during the waterlogging period and declined further subsequent to the waterlogging treatment. The results illustrate the interrelationships between root and shoot carbon budgets in mung bean during response to the stress of waterlogging.

Non-NASA Center↗
NASA NTRS1974

Vegetation density as deduced from ERTS-1 MSS response

Reflectance from vegetation increases with increasing vegetation density in the 0.75- to 1.35 micron wavelength interval. Therefore, ERTS-1 bands 6 (0.7 to 0.8 micron) and 7 (0.8 to 1.1 micron) contain information that should relate to the probable yield of crops and the animal carrying capacity of rangeland. The results of an experiment designed specifically to test the relations among leaf area index (LAI), plant population, plant cover and plant height, and the ERTS-1 MSS responses for 3 corn, 10 sorghum, and 10 cotton fields are given. Plant population was as useful as LAI for characterizing the sorghum and corn fields, and plant height was as good as LAI for characterizing cotton fields. These findings generally support the utility of ERTS-1 data for explaining variability in green biomass, harvestable forage and other indicators of productivity.

Wiegand, C. L.↗
NASA NTRS2016

Simulation of Satellite, Airborne and Terrestrial LiDAR with DART (I):Waveform Simulation with Quasi-Monte Carlo Ray Tracing

Light Detection And Ranging (LiDAR) provides unique data on the 3-D structure of atmosphere constituents and the Earth's surface. Simulating LiDAR returns for different laser technologies and Earth scenes is fundamental for evaluating and interpreting signal and noise in LiDAR data. Different types of models are capable of simulating LiDAR waveforms of Earth surfaces. Semi-empirical and geometric models can be imprecise because they rely on simplified simulations of Earth surfaces and light interaction mechanisms. On the other hand, Monte Carlo ray tracing (MCRT) models are potentially accurate but require long computational time. Here, we present a new LiDAR waveform simulation tool that is based on the introduction of a quasi-Monte Carlo ray tracing approach in the Discrete Anisotropic Radiative Transfer (DART) model. Two new approaches, the so-called "box method" and "Ray Carlo method", are implemented to provide robust and accurate simulations of LiDAR waveforms for any landscape, atmosphere and LiDAR sensor configuration (view direction, footprint size, pulse characteristics, etc.). The box method accelerates the selection of the scattering direction of a photon in the presence of scatterers with non-invertible phase function. The Ray Carlo method brings traditional ray-tracking into MCRT simulation, which makes computational time independent of LiDAR field of view (FOV) and reception solid angle. Both methods are fast enough for simulating multi-pulse acquisition. Sensitivity studies with various landscapes and atmosphere constituents are presented, and the simulated LiDAR signals compare favorably with their associated reflectance images and Laser Vegetation Imaging Sensor (LVIS) waveforms. The LiDAR module is fully integrated into DART, enabling more detailed simulations of LiDAR sensitivity to specific scene elements (e.g., atmospheric aerosols, leaf area, branches, or topography) and sensor configuration for airborne or satellite LiDAR sensors.

Gastellu-Etchegorry, Jean-Philippe↗
NASA NTRS1974

Predicting soil moisture and wheat vegetative growth from ERTS-1 imagery

The author has identified the following significant results. Study results indicate: (1) Vegetative growth was best predicted by a linear relationship between leaf area index and the radio of band 4 to band 5. All significant soil moisture effects were cancelled by the ratio. (2) Soil moisture at a depth of 0 to 15 cm, with specific soil factors, was predicted by band 4 and leaf area index with a high regression coefficient. (3) Vegetative growth, measured by leaf area index, was one of the necessary inputs in evaluating the winter wheat crop coefficient from March to maturity.

Krupp, J. W.↗
NASA NTRS2021

Assessing impacts of canopy 3D structure on chlorophyll fluorescence radiance and radiative budget of deciduous forest stands using DART

Although remote sensing (RS) of solar-induced chlorophyll fluorescence (SIF) is increasingly used as a valuable source of information about vegetation photosynthetic activity, the RS SIF observations are significantly influenced by canopy-specific structural features (i.e., canopy architecture including leaf area index and presence of woody components), atmospheric conditions during their acquisition (e.g., proportion of direct and diffuse irradiance) and observational geometric configurations (e.g., sun and viewing directions). Radiative transfer (RT) models have the potential to provide a better understanding of the canopy structural effects on the SIF emission and RS signals. Here, we used the DART model to assess the daily influence, from morning to evening, of forest 3D architecture on SIF nadir radiance, emission, escape factor and nadir yield of eight 100 m × 100 m forest study plots established in a temperate deciduous forest of the Smithsonian Environmental Research Center (Edgewater, MD, USA). The 3D architecture of each plot was derived from airborne LiDAR. DART simulations of these 3D forest plots and their 1D (i.e., vertical profile of sun-adapted and shade-adapted leaves) and 0D (i.e., homogeneous layer of sun-adapted leaves above an homogeneous layer of shade-adapted leaves) abstractions were compared to assess the relative errors (ε1D−3D and ε0D−3D) associated with horizontal and vertical structural heterogeneity, respectively. Forest 3D structure, especially horizontal heterogeneity, had a great influence on forest nadir SIF radiance, resulting in ε1D−3D up to 55% at 8:00 and 18:00 (i.e., for oblique sun directions). The key indicators of this impact, in the descending order of importance, were the SIF escape factor (ε1D−3D up to 40%), the attenuation of incident photosynthetically active radiation (ε1D−3D less than 5%), and the SIF emission yield (ε1D−3D less than 2%). The influence of forest architecture on the nadir SIF escape factor and SIF yield (ε1D−3D up to 40%) varied over time, with differences in forest stand structure, and per spectral domain, being always larger between 640 and 700 nm than between 700 and 850 nm. In addition, woody elements demonstrated a large influence on forest SIF radiance due to their “shading” effect (ε up to 17%) and their “blocking” effect (ε ≈ 10%), both of them higher for far-red than for red SIF. These results underline the importance of 3D forest canopy architecture, especially 2D heterogeneity, and inclusion of woody elements in RT modeling used for interpretation of the RS SIF signal, and subsequently for the estimation of gross primary production and detection of vegetation stress.

Omar Regaieg↗