Search NASA⌕ Search

SEARCH · Search NASA

Results for “Leaf nitrogen”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Foliage plants for indoor removal of the primary combustion gases carbon monoxide and nitrogen dioxide

Foliage plants were evaluated for their ability to sorb carbon monoxide and nitrogen dioxide, the two primary gases produced during the combustion of fossil fuels and tobacco. The spider plant (Chlorophytum elatum var. vittatum) could sorb 2.86 micrograms CO/sq cm leaf surface in a 6 h photoperiod. The golden pothos (Scindapsus aureus) sorbed 0.98 micrograms CO/sq cm leaf surface in the same time period. In a system with the spider plant, greater than or equal to 99 percent of an initial concentration of 47 ppm NO2 could be removed in 6 h from a void volume of approximately 0.35 cu m. One spider plant potted in a 3.8 liter container can sorb 3300 micrograms CO and effect the removal of 8500 micrograms NO2/hour, recognizing the fact that a significant fraction of NO2 at high concentrations will be lost by surface sorption, dissolving in moisture, etc.

Wolverton, B. C.↗
DOE OSTI2026

Overcoming environmental constraints to high-yielding eastern cottonwood productivity in the southeastern United States

The global demand for biomass is rising, and Populus species are among the most productive temperate woody plants. This 6-year study, conducted in Sumter County, South Carolina, USA evaluated the effects of supplemental irrigation and fertilization on crown and leaf traits, dry weight productivity, and clonal variation in Populus deltoides. Eight commercially available clones (‘ST148’, ‘S2C20’, ‘3167’, ‘ST72’, ‘20WV’, ‘S7C1’, ‘ST70’, and ‘S7C15’) were assessed. Drip irrigation was applied to maintain soil tension at either 33 kPa (15% volumetric soil moisture) or 1500 kPa (10%). Nutrient treatments via weekly fertigation applications consisted of two levels: a high annual rate (initially 85 kg elemental nitrogen ha−1 year−1, increasing to 182 kg ha−1 year−1 at Year 3, then reduced to 135 kg ha−1 year−1 thereafter) and a low rate at 50% of the high treatment. Dry weight yields were estimated using standing tree measurements. Results revealed significant clonal differences in leaf area index (LAI) that peaked in Year 3, with the fastest-growing clones exhibiting lower LAI values. At Ages 2 and 3, these clones also showed higher concentrations of K, Ca, B, Cu, and Mn in leaves, along with lower Mg and Zn concentrations. Both annual height and diameter growth varied significantly by treatment and clone, with the largest height increases observed in the low fertilizer treatments from Year 3 onward. Biomass production in all irrigated plots exceeded that of non-irrigated plots across all biomass components at Ages 4, 5, and 6. Furthermore, stem-to-root dry weight ratios increased more rapidly in the best-performing treatment–clone combinations compared to non-irrigated plots. Notably, P. deltoides plots receiving fertilizer had higher soil carbon concentrations (i.e., percent C) compared to adjacent sweetgum, sycamore, and agricultural plots. These findings highlight the potential of targeted irrigation strategies to enhance biomass productivity in P. deltoides plantations.

Tuskan, Gerald [ORNL] (ORCID:0000000301061289)↗
NASA NTRS1991

Cyclic variations in nitrogen uptake rate of soybean plants: effects of pH and mixed nitrogen sources

To determine if the daily pattern of NO3- and NH4+ uptake is affected by acidity or NO3- : NH4+ ratio of the nutrient solution, non-nodulated soybean plants (Glycine max) were exposed for 21 days to replenished, complete nutrient solutions at pH 6.0, 5.5, 5.0, and 4.5 which contained either 1.0 mM NH4+, 1.0 mM NO3- [correction of NO3+], 0.67 mM NH4+ plus 0.33 mM NO3- (2:1 NH4+ : NO3-) [correction of (2:1 NH3+ : NO4-)], or 0.33 mM NH4+ plus 0.67 mM NO3- (1:2 NH4+ : NO3-). Net uptake rates of NH4+ and NO3- were measured daily by ion chromatography as depletion from the replenished solutions. When NH4+ and NO3- were supplied together, cumulative uptake of total nitrogen was not affected by pH or solution NH4+ : NO3- ratio. The cumulative proportion of nitrogen absorbed as NH4+ decreased with increasing acidity; however, the proportional uptake of NH4+ and NO3- was not constant, but varied day-to-day. This day-to-day variation in relative proportions of NH4+ and NO3- absorbed when NH4+ : NO3- ratio and pH of solution were constant indicates that the regulatory mechanism is not directly competitive. Regardless of the effect of pH on cumulative uptake of NH4+, the specific nitrogen uptake rates from mixed and from individual NH4+ and NO3- sources oscillated between maxima and minima at each pH with average periodicities similar to the expected interval of leaf emergence.

Non-NASA Center↗
DOE OSTI2024

Modeling Interactive Effects of Manganese Bioavailability, Nitrogen Deposition, and Warming on Soil Carbon Storage

Manganese (Mn) is a redox–active micronutrient that has been shown to accelerate plant litter decomposition; however, the effect of Mn–promoted decomposition on soil C storage is unclear. We present a novel biogeochemical model simulating how Mn bioavailability influences soil organic C (SOC) stocks in a soil profile (<50 cm) within a temperate forest. In our model, foliar Mn increased in response to increasing soluble Mn released through Mn–oxide (birnessite) dissolution in mineral soil layers. The ensuing Mn enrichment in leaf litter redistributed Mn to the surface forest floor layer, promoted enzymatic oxidation of lignin, and decreased SOC stocks. Total SOC loss was partially mitigated by accumulation of lignin–oxidation products as mineral–associated organic C. We also explored how Mn–driven changes to C storage interacted with effects of N deposition and warming. Nitrogen enrichment inhibited Mn–dependent lignin degradation, increasing SOC stocks and weakening their dependence on Mn bioavailability. Warming stimulated decomposition and reduced C stocks but was less effective at low Mn bioavailability. Our model results suggest that SOC stocks are sensitive to Mn bioavailability because increased plant uptake redistributes Mn to surface soils where it can enhance litter decomposition. Finally, based on our simulations, we predict that Mn becomes limiting to litter decomposition where Mn is poorly soluble. Depletion of bioavailable Mn or other cofactors that are critical to decomposition could limit the response of organic C stocks to warming over time, but quantitative projections of the role of Mn bioavailability in regulating decomposition requires additional measurements to constrain model uncertainties.

58 GEOSCIENCES↗
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 NTRS2020

Modelling climate change impacts on maize yields under low nitrogen input conditions in sub‐Saharan Africa

Smallholder farmers in sub‐Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low‐input systems is currently lacking. We evaluated the impact of varying [CO2], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi‐arid Rwanda, hot subhumid Ghana and hot semi‐arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in‐season soil water content from 2‐year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2], temperature and rainfall. Without N fertilizer input, maize (i) benefited less from an increase in atmospheric [CO2], (ii) was less affected by higher temperature or decreasing rainfall and (iii) was more affected by increased rainfall because N leaching was more critical. The model inter-comparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low-input systems. Climate change and N input interactions have strong implications for the design of robust adaptation practices across SSA, because the impact of climate change will be modified if farmers intensify maize production with more mineral fertilizer.

Crop simulation model↗
NASA NTRS2000

BOREAS TE-10 Leaf Gas Exchange Data

The Boreal Ecosystem-Atmospheric Study (BOREAS) TE-10 (Terrestrial Ecology) team collected several data sets in support of its efforts to characterize and interpret information on the reflectance, transmittance, gas exchange, chlorophyll content, carbon content, hydrogen content, and nitrogen content of boreal vegetation. This data set contains measurements of assimilation, stomatal conductance, transpiration, internal CO2 concentration, and water use efficiency conducted in the Southern Study Area (SSA) during the growing seasons of 1994 and 1996 using a portable gas exchange system. The 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) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗
DOE OSTI2021

Validation of the Community Land Model Version 5 over the Contiguous United States (CONUS) using in situ and remote sensing data sets

The Community Land Model (CLM) is an effective tool to simulate the biophysical and biogeochemical processes and their interactions with the atmosphere. Although CLM Version 5 (CLM5) constitutes various updates in these processes, its performance in simulating energy, water and carbon cycles over the Contiguous United States (CONUS) at scales which land surface changes and hydrometeorological and hydroclimatological applications are more locally relevant is yet to be assessed. In this study, we conducted three simulations at 0.125? during 1979-2018 over the CONUS using different configurations of CLM, namely CLM5-biogeochemistry (CLM5BGC), CLM4.5BGC, and CLM5-satellite phenology (CLM5SP). We validated and compared their simulations against multiple remote-sensed and in-situ datasets. Overall, the parametric and structural updates (e.g., carbon cost for nitrogen uptake, variable soil thickness, dry surface layer) in CLM5 improve its ability in capturing terrestrial biogeochemical dynamics. The low evapotranspiration in CLM5BGC is associated with biases in simulating vegetation phenological characteristics rather than soil water limitations. The mismatch between CLM5BGC-simulated peak leaf area index and reference data can be attributed to CLM5BGC's inability in simulating phenology of trees and grasses. The differences between CLM-simulated irrigation and reference estimates can be attributed to differences between processes represented in models and in reality, and uncertainties in input and validation datasets. Evaluation against observations at small catchments suggest that hydrologic parameters needed to be calibrated to improve simulations of runoff, especially subsurface runoff. Additional efforts are needed to incorporate spatially-distributed plant phenology and physiology parameters and regional-specific agricultural management practices (e.g., planting, harvest).

Cheng, Yanyan↗
DOE OSTI2022

DEEPER: An Intergrated Platform for Deeper Roots

Crops with deeper roots would have multiple benefits, including better drought tolerance, reduced requirement for nitrogen fertilizer, and better sequestration of atmospheric CO 2 . DEEPER is an integrated platform of phenomic, genomic, and in silico technologies to generate maize lines with deeper roots. DEEPER is: LEADER (Leaf Elemental Accumulation from Deep Roots) is a breakthrough technology to nondestructively measure rooting depth by using the plant itself as a sensor. LEADER uses handheld X-ray Fluorescence spectrometry to quantify foliar accumulation of elements that are differentially distributed in the soil profile. LEADER is nondestructive and is orders of magnitude cheaper, faster, and more precise than any competing assay of rooting depth in the field. LEADER is able to distinguish deep-rooted from shallow-rooted maize lines in the field without the need for costly and noisy soil coring. RootRobot/DIRT3D, to automatically phenotype root architecture in any field, combining RootRobot, a mechatronics platform to excavate, clean, section, and image mature root crowns, with DIRT3D, software to quantify architectural traits in 3D. Anatomics, a high-throughput platform to phenotype root anatomy, combining LAT 2.0, a technology for 3D imaging of root anatomy and composition, with RootScan3D, software to automatically extract 3D anatomical and cell wall composition metrics from LAT 2.0 output. Using this platform we discovered two novel root traits, parenchyma cell wall thickness and multiseriate cortical sclerenchyma, that improve rooting depth and drought tolerance in maize and wheat. OpenSimRoot/Deep, software to simulate root interaction with hard subsoils. Using this platform we discovered novel concepts regarding how to increase crop rooting depth by modulating how individual root axes respond to hard soil. DeepGenes, a toolkit of genes, parent lines, and genomic selection strategies to enable breeding hybrids with deeper roots. We discovered 3 novel root genes that increase rooting depth in maize and wheat. DEEPER discovered novel root phenotypes for deeper rooting, and delivered validated ideotypes for deeper-rooted maize; novel technologies to rapidly assess root depth, root architecture and anatomy in field-grown plants; novel software tools for root modeling and 3D image analysis of root architecture and anatomy; and validated genes and genomic selection models to deploy traits for deeper rooting in maize breeding. Each DEEPER technology is transformative in its own right, and exceeds existing technologies. They are mutually synergistic, deployable for field-grown plants, and are ready for application. The phenotyping and modeling technologies are readily applicable to many crops, and genetic leads in maize may have utility in other grasses. Taken as a whole they represent a transformative platform to develop deeper-rooted crops, with greater drought tolerance, reduced fertilizer requirement, and greater carbon sequestration.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2007

Comparison of Measurements and FluorMOD Simulations for Solar Induced Chlorophyll Fluorescence and Reflectance of a Corn Crop under Nitrogen Treatments [SIF and Reflectance for Corn]

The FLuorescence Explorer (FLEX) satellite concept is one of six semifinalist mission proposals selected in 2006 for pre-Phase studies by the European Space Agency (ESA). The FLEX concept proposes to measure passive solar induced chlorophyll fluorescence (SIF) of terrestrial ecosystems. A new spectral vegetation Fluorescence Model (FluorMOD) was developed to include the effects of steady state SIF on canopy reflectance. We used our laboratory and field measurements previously acquired from foliage and canopies of corn (Zea mays L.) under controlled nitrogen (N) fertilization to parameterize and evaluate FluorMOD. Our data included biophysical properties, fluorescence (F) and reflectance spectra for leaves; reflectance spectra of canopies and soil; solar irradiance; plot-level leaf area index; and canopy SIF emissions determined using the Fraunhofer Line Depth principal for the atmospheric telluric oxygen absorption features at 688 nm (O2-beta) and 760 nm (O2-alpha). FluorMOD simulations implemented in the default "look-up-table" mode did not reproduce the observed magnitudes of leaf F, canopy SIF, or canopy reflectance. However, simulations for all of these parameters agreed with observations when the default FluorMOD information was replaced with measurements, although N treatment responses were underestimated. Recommendations were provided to enhance FluorMOD's potential utility in support of SIF field experiments and studies of agriculture and ecosystems.

Middleton, Elizabeth M.↗
DOE OSTI2024

Programmable bionanocomposite coated fertilizers for prolonged controlled release of nitrogen

Controlled-release fertilizers (CRFs) present a promising solution for alleviating food and nutrient scarcity. However, their development has been mainly hindered by both rapid and unsynchronized nutrient release and unsustainable coating materials. In this study, we address this issue by developing a new coating layer for CRFs using a programmable biopolyurethane nanocomposite. This nanocomposite is prepared from diphenylmethane diisocyanate (MDI)-functionalized bentonite nanoclay (BNT-MDI) and a biopolyol from biomass waste. The results show that the BNT-MDI-doped CRFs (BCRFs) exhibit an impressive nitrogen (N)-release longevity of approximately 120 days at a 4 wt% coating ratio, surpassing previous CRF formulations. In a 30-day snap bean cultivation study, BCRF significantly improved root length (1000%), leaf length (257%), leaf width (400%), and plant height (1400%) compared to the control. The superior performance of BCRF is attributed to the PU-nanoclay biocomposite film, with full nano-exfoliation, controllable porosity, and high crosslinking density. Furthermore, we introduce a new dynamic release mechanism and establish a quantitative relationship between the nanostructure, property, and release performance of BCRF by combining the multiplicative and diffusion models for porous materials. Finally, this study provides a theoretical framework and a straightforward methodology for designing programmable nanocomposite structures for future biobased CRFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1980

Effects of management practices on reflectance of spring wheat canopies

The effects of available soil moisture, planting date, nitrogen fertilization, and cultivar on reflectance of spring wheat (Triticum aestivum L.) canopies were investigated. Spectral measurements were acquired on eight dates throughout the growing season, along with measurements of crop maturity stage, leaf area index, biomass, plant height, percent soil cover, and soil moisture. Planting date and available soil moisture were the primary agronomic factors which affected reflectance of spring wheat canopies from tillering to maturity. Comparisons of treatments indicated that during the seedling and tillering stages planting date was associated with 36 percent and 85 percent of variation in red and near infrared reflectances, respectively. As the wheat headed and matured, less of the variation in reflectance was associated with planting date and more with available soil moisture. By mid July, soil moisture accounted for 73 percent and 69 percent of the variation in reflectance in red and near infrared bands, respectively. Differences in spectral reflectance among treatments were attributed to changes in leaf area index, biomass, and percent soil cover. Cultivar and N fertilization rate were associated with very little of the variation in the reflectance of these canopies.

Daughtry, C. S. T.↗
DOE OSTI2023

A functional trait framework for integrating nitrogen‐fixing cover crops into short‐rotation woody crop systems

Abstract Developing approaches to simultaneously maximize short‐rotation woody crop (SRWC) productivity while minimizing footprints associated with intensive management is imperative to profitable and sustainable bioenergy production systems. Intercropping nitrogen (N)‐fixing cover crops in SRWC systems is an overlooked approach to sustainably intensify SRWC production by increasing N availability using less environmentally costly inputs. Here, we discuss how functional traits (e.g., seasonal activity, lifespan, leaf habit, soil exploration) of cover crops and SRWCs may interact through space and time influencing access to light, water, and nutrients to provide a framework for successful integration of cover crops into SRWCs. Next, we summarize the literature on intercropping forest plantations with N‐fixing cover crops to identity research gaps and outline future research needs and opportunities. And then, using empirical N demand and productivity data from SRWCs and cover crop N inputs from the literature, we illustrate how SRWC leaf habit (conifer evergreens and deciduous hardwoods) would influence successful integration of cover crops and potential N fixation. We estimate that integrating cover crops into SRWCs could supply 27% and 72% of the N demand across a 10‐year rotation for an evergreen and a deciduous hardwood, respectively. These figures suggest these integrated SRWC systems may approach a virtual minimal external N input when other biogeochemical cycles are considered. The guiding principles presented here are grounded in ecological theory and provide a framework for sustainable intensification of forest production.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1988

Prediction of leaf chemistry by the use of visible and near infrared reflectance spectroscopy

The chemical content of dry, ground leaf material sampled from deciduous and conifer tree species from sites in Alaska, Wisconsin, and California was estimated using visible and shortwave IR spectroscopy. Seven chemical components - sugar, starch, protein, cellulose, total chlorophyll, lignin, and total nitrogen - were analyzed by wet chemical methods and their concentrations regressed against log 1/rho and first and second differences of log 1/rho (where rho is measured reflectance) at wavelengths selected by stepwise regression. Predictions of chemical concentrations based on cross validation suggest that this technique may be useful for extracting vegetation canopy biochemical information by remote sensing.

Card, Don H.↗
DOE OSTI2020

Parameterizing Perennial Bioenergy Crops in Version 5 of the Community Land Model Based on Site‐Level Observations in the Central Midwestern United States

Abstract With projected expansion of biofuel production at a global scale, there is a pressing need to develop adequate representation of bioenergy crops in land surface models to help effectively quantify the biogeophysical and biogeochemical effects of its associated land use changes. This study implements two new perennial bioenergy crops, Miscanthus and switchgrass, into the Community Land Model Version 5 based on site‐level observations from the midwestern United States by modifying parameters associated with photosynthesis, phenology, allocation, decomposition, and carbon cost of nitrogen uptake and integrating concomitantly land management practices. Sensitivity analyses indicate that carbon and energy fluxes of the perennial crops are most sensitive to photosynthesis and phenology parameters. Validation of simulated fluxes against site‐level measurements demonstrates that the model is capable of capturing the overall patterns of energy and carbon fluxes, as well as physiological transitions from leaf emergence to senescence. Compared to annual crops, perennial crops feature longer growing season, greater leaf areas, and higher productivity, leading to increased transpiration, lower annual runoff, and larger carbon uptake. The model simulations suggest that with higher CO 2 assimilation rates and lower demands for nutrients and water, high‐yielding perennial crops are promising alternatives of bioenergy feedstocks compared to traditional annual crops not only for mitigating climate change but also for environmental conservation purposes by reducing fertilizer application and therefore alleviating surface‐ and ground‐water contaminations. Although the local‐scale simulations shed light on potential benefits of using perennial grasses as bioenergy feedstocks, quantifying consequences of their plantations at larger scales warrants additional investigation.

Cheng, Yanyan↗
DOE OSTI2025

A global dataset of terrestrial biological nitrogen fixation

Biological nitrogen fixation (BNF) is the main natural source of new nitrogen inputs in terrestrial ecosystems, supporting terrestrial productivity, carbon uptake, and other Earth system processes. We assembled a comprehensive global dataset of field measurements of BNF in all major N-fixing niches across natural terrestrial biomes derived from the analysis of 376 BNF studies. The dataset comprises 32 variables, including site location, biome type, N-fixing niche, sampling year, quantification method, BNF rate (kg N ha −1 y −1 ), the percentage of nitrogen derived from the atmosphere (%N dfa ), N fixer or N-fixing substrate abundance, BNF rate per unit of N fixer abundance, and species identity. Overall, the dataset combines 1,207 BNF rates for trees, shrubs, herbs, soil, leaf litter, woody litter, dead wood, mosses, lichens, and biocrusts, 152 herb %N dfa values, 1,005 measurements of N fixer or N-fixing substrate abundance, and 762 BNF rates per unit of N fixer abundance for a total of 424 species across 66 countries. This dataset facilitates synthesis, meta-analysis, upscaling, and model benchmarking of BNF fluxes at multiple spatial scales.

Reis Ely, Carla R. [Oregon State Univ., Corvallis,↗
NASA NTRS2002

Contribution of Chlorophyll Fluorescence to the Reflectance of Corn Foliage

To assess the contribution of chlorophyll fluorescence (ChlF) to apparent reflectance (Ra) in the red/far-red, spectra were collected on a C4 agricultural species (corn, Zea Mays L.) under conditions ranging from nitrogen deficiency to excess. A significant contribution of ChlF to Ra was observed, with on average 10-25% at 685nm and 2-6% at 740nm of Ra being due to ChlF. Higher ChlF was consistently measured from the abaxial leaf surface as compared to the adaxial. Using 350-665nm excitation, the study confirms the trends in three ChlF ratios established previously by active F technology, suggesting that the ChlF utility this technology has developed for monitoring vegetation physiological status is likely applicable also under natural solar illumination.

Campbell, Petya K. Entcheva↗
NASA NTRS1992

Scientific issues and potential remote-sensing requirements for plant biochemical content

Application of developments in imaging spectrometry to the study of terrestrial ecosystems, which began in 1983, demonstrate the potential to estimate lignin and nitrogen concentrations of plant canopies by remote-sensing techniques. Estimation of these parameters from the first principles of radiative transfer and the interactions of light with plant materials is not presently possible, principally because of lack of knowledge about internal leaf scattering and specific absorption involving biochemical compounds. From the perspective of remote-sensing instrumentation, sensors are needed to support derivative imaging spectroscopy. Biochemical absorption features tend to occur in functional groupings throughout the 1100- to 2500-nm region. Derivative spectroscopy improves the information associated with the weaker, narrower absorption features of biochemical absorption that are superimposed on the strong absolute variations due to foliar biomass, pigments, and leaf water content of plant canopies. Preliminary sensor specifications call for 8-nm bandwidths at 2-nm centers in four spectral regions (about 400 bands total) and a signal-to-noise performance of at least 1000:1 for 20 percent albedo targets in the 2000-nm region.

Peterson, David L.↗