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At least 37 records · Page 2

Evaluating genetic and environmental controls on silicon accumulation in Populus trichocarpa leaves

Background and aims: Silicon (Si) accumulation and formation of non-crystalline silica particles (phytoliths) inside plant cells contribute to plant function, soil carbon storage, and Si reservoirs in soils. A better understanding of how genetic and environmental factors control Si accumulation may improve understanding of Si cycling between plants and soil and its impacts on other ecosystem processes. Methods: This study examined how genetic potential for Si uptake and silicification translated to Si concentrations and phytolith formation in Populus trichocarpa leaves. Leaves were collected from four different genotypes of cultivated poplar trees that were grown in a common garden and possess established differences in leaf-level gene expression related to Si transport and silicification. Scanning electron microscopy and subsequent image analysis were used to quantify Si concentrations and phytolith abundance and features. Results: Phytoliths were identified in nearly all leaves but were often absent at very low (< 0.5 wt.%) Si concentrations at the leaf surface. The proportion of leaf area occupied by phytoliths increased as Si content increased. Silicon content and phytolith abundance at the leaf surface did not vary across genotypes, but surface Si was weakly correlated with plant available Si in soil. Conclusion: Phytoliths were prevalent in P. trichocarpa leaves; however, the genetic potential for Si uptake and silicification at the leaf-level poorly predicted foliar Si and phytolith abundance. Uniformly low expression of Si uptake genes in the roots may have reduced differences across genotypes. Consequently, Si accumulation in leaves was likely more strongly influenced by soil Si bioavailability, phenology, or additional environmental factors.

Image analysis↗

A model of plant canopy polarization response

Sensors to remotely measure the linear polarization of ground scenes have been proposed for the Multispectral Resource Sampler (MRS), a satellite sensor system proposed to complement the Thematic Mapper. At present justification for a sensor on MRS to measure scene polarization is limited. This paper discusses a model for the amount of linearly polarized light reflected by the shiny leaves of such crops as wheat, corn, and sorghum. The theory demonstrates that, potentially, measurements of the linearly polarized light from a crop canopy may be used as an additional feature to discriminate between crops. Examination of the model suggests that, potentially, satellite polarization measurements may be used to monitor crop development stage, leaf water content, leaf area index, hail damage, and certain plant diseases. The model adds to the understanding of the potential information content of scene polarization measurements acquired by future satellite sensor systems such as MRS.

Vanderbilt, V. C.↗

A model of plant canopy polarization

A model for the amount of linearly polarized light reflected by the shiny leaves of grain crops is based on the morphological and phenological characteristics of the plant canopy and upon the Fresnel equations which describe the light reflection process at the smooth boundary separating two dielectrics. The theory used demonstrates that, potentially, measurements of the linearly polarized light from a crop canopy may be used as an additional feature to discriminate between crops such as wheat and barley, two crops which are so spectrally similar that they are misclassified with unacceptable frequency. Examination of the model suggests that, potentially, satellite polarization measurements may be used to monitor crop development stage, leaf water content, leaf area index, hail damage, and certain plant diseases. The information content of these measurements is needed to evaluate the proposed polarization sensor for the satellite-borne multispectral resource sampler.

Vanderbilt, V. C.↗

Prospect redux

The remote estimation of leaf biochemical content from spaceborne platforms has been the subject of many studies aimed at better understanding of terrestrial ecosystem functioning. The major ecological processes involved in exchange of matter and energy, like photosynthesis, primary production, evaportranspiration, respiration, and decomposition can be related to plant properties e.g., chlorophyll, water, protein, cellulose and lignin contents. As leaves represent the most important plant surfaces interacting with solar energy, a top priority has been to relate optical properties to biochemical constituents. Two different approaches have been considered: first, statistical correlations between the leaf reflectance (or transmittance) and biochemical content, and second, physically based models of leaf scattering and absorption developed using the laws of optics. Recently reviewed by Verdebout et al., the development of models of leaf optical properties has resulted in better understanding of the interaction of light with plant leaves. Present radiative transfer models mainly use chlorophyll and/or water contents as input parameters to calculate leaf reflectance. Inversion of these models allows to retrieve these constituents from spectrophotometric measurements. Conel et al. recently proposed a two-stream Kubelka-Munk model to analyze the influence of protein, cellulose, lignin, and starch on leaf reflectance, but in fact, the estimation of leaf biochemistry from remote sensing is still an open question. In order to clarify it, a laboratory experiment associating visible/infrared spectra of plan leaves both with physical measurements and biochemical analyses was conducted at the Joint Research Center during the summer of 1993. This unique data set has been used to upgrade the PROSPECT model, by including leaf biochemistry.

Jacquemoud, S.↗

Seed-to-seed growth of superdwarf wheat and arabidopsis using red light-emitting diodes (LED's): A report on baseline tests conducted for NASA's proposed Plant Research Unit (PRU)

To determine the influence of narrow-spectrum red light-emitting diodes (LED's) on plant growth and seed production, wheat (Triticum aestivum L.cv Superdwarf) and Arabidopsis (Arabidopsis thaliana (L.) Heynh, race Columbia) plants were grown under red LED's (peak emission 660 nm) and compared to plants grown under daylight fluorescent (white) light and red LED's supplemented with either 1 percent or 10 percent blue fluorescent (BF) light. Wheat growth under red LED's alone appeared normal, whereas Arabidopsis under red LED's alone developed curled leaf margins and a spiraling growth pattern. Both wheat and Arabidopsis under red LED's alone or red LED's + 1 percent BF light had significantly lower seed yield than plants grown under white light. However, the addition of 10 percent BF light to red LED's partially alleviated the adverse effect of red LED's on yield. Irrespective of the light treatment, viable seeds were produced by wheat(75-92 percent germination rate) and Arabidopsis (85-100 percent germination rate). These results indicate that wheat, and to a lesser extent Arabidopsis, can be successfully grown under red LED's alone, but supplemental blue light is required with red LED's to sufficiently match the growth characteristics and seed yield associated with plants grown under white light.

Goins, G. D.↗

Incorporating the Acclimation of Photosynthesis and Leaf Respiration in the Noah‐MP Land Surface Model: Model Development and Evaluation

Abstract Realistic simulation of leaf photosynthetic and respiratory processes is needed for accurate prediction of the global carbon cycle. These two processes systematically acclimate to long‐term environmental changes by adjusting photosynthetic and respiratory traits (e.g., the maximum photosynthetic capacity at 25°C ( V cmax,25 ) and the leaf respiration rate at 25°C ( R 25 )) following increasingly well‐understood principles. While some land surface models (LSMs) now account for thermal acclimation, they do so by assigning empirical parameterizations for individual plant functional types (PFTs). Here, we have implemented an Eco‐Evolutionary Optimality (EEO)‐based scheme to represent the universal acclimation of photosynthesis and leaf respiration to multiple environmental effects, and that therefore requires no PFT‐specific parameterizations, in a standard version of the widely used LSM, Noah MP. We evaluated model performance with plant trait data from a 5‐year experiment and extensive global field measurements, and carbon flux measurements from FLUXNET2015. We show that observed R 25 and V cmax,25 vary substantially both temporally and spatially within the same PFT ( C.V. >20%). Our EEO‐based scheme captures 62% of the temporal and 70% of the spatial variations in V cmax,25 (73% and 54% of the variations in R 25 ). The standard scheme underestimates gross primary production by 10% versus 2% for the EEO‐based scheme and generates a larger spread in r (correlation coefficient) across flux sites (0.79 ± 0.16 vs. 0.84 ± 0.1, mean ± S.D.). The standard scheme greatly overestimates canopy respiration (bias: ∼200% vs. 8% for the EEO scheme), resulting in less CO 2 uptake by terrestrial ecosystems. Our approach thus simulates climate‐carbon coupling more realistically, with fewer parameters.

Ren, Yanghang [Department of Earth System Science ↗

RSPECT: A PROSPECT-based model incorporating the real structure of rice leaves

Radiative transfer models (RTMs) describe how light is absorbed, scattered, and transmitted within leaves by simulating mechanistic light propagation processes. The PROSPECT model is based on measurable parameters (the leaf biochemical content) and a non-measurable parameter (the leaf anatomical structure represented by the leaf structure parameter (N)). The effect of N on the optical properties of leaves has been investigated through a number of local and global sensitivity analyses. Other studies have directly evaluated the effect of the leaf anatomical structure on spectral reflectance, particularly in the near infrared region. However, the relationship between N and the anatomical structure is unclear. Here, in this study, we leveraged eLeaf, a ray tracing-based 3D rice leaf simulator, to establish relationships between leaf anatomical features and spectral properties, enabling us to replace N in the PROSPECT-4 model with measurable leaf anatomical parameters and develop the RSPECT model. The leaf thickness at minor vein, leaf thickness at bulliform cells, mesophyll thickness at minor vein, and distance between two minor veins could be used to predict N effectively. The RSPECT model achieved spectral simulation accuracy comparable to PROSPECT-4 and was more suitable for parameter inversion of the physical and chemical properties of rice leaves, with relative root mean square errors of 7.4% for chlorophyll content, 5.6% for equivalent water thickness, and 7.5% for dry matter content. In conclusion, RSPECT improves radiative transfer modeling by integrating measurable anatomical features and provides a framework for extending this approach to other vegetation types.

hyperspectral↗

Using Landsat data to estimate evapotranspiration of winter wheat

Results obtained from an evapotranspiration model as applied to Kansas winter wheatfields were compared with results determined by a weighing lysimeter, and the standard deviation was found to be less than 0.5 mm/day (however, the 95% confidence interval was between plus and minus 0.2 mm/day). Model inputs are solar radiation, temperature, precipitation, and leaf area index; an equation was developed to estimate the leaf area index from Landsat data. The model provides estimates of transpiration, evaporation, and soil moisture.

Kanemasu, E. T.↗

Leveraging transfer learning and leaf spectroscopy for leaf trait prediction with broad spatial, species, and temporal applicability

Accurate and reliable prediction of leaf traits is crucial for understanding plant adaptations to environmental variation, monitoring terrestrial ecosystems, and enhancing comprehension of functional diversity and ecosystem functioning. Currently, various approaches (e.g., statistical, physical models) have been developed to estimate leaf traits through hyperspectral remote sensing and leaf spectroscopy. However, the absence of high-performing, transferable, and stable models across various domains of space, plant functional types (PFTs) and seasons hinder our ability to quantify and comprehend spatiotemporal variations in leaf traits. This study proposes robust and highly transferable models for better predicting leaf traits with hyperspectral reflectance. Initially, three datasets were assembled, pairing common leaf traits — chlorophyll (Chla+b), carotenoids (Ccar), leaf mass per area (LAM), equivalent water thickness (EWT) — with leaf spectra measurements collected across diverse geographic locations in the U.S. and Europe, PFTs, and seasons. Measurements were acquired using spectroradiometers (e.g., ASD FieldSpec 3/4/Pro and SVC HR-1024i) with integrating spheres, leaf clips, and contact probes. Here, we then developed transfer learning-based hybrid models that incorporated the domain knowledge of radiative transfer models (RTMs) through pretraining processes and were well-constrained by fine-tuning with field measurements. Through comparison with other state-of-the-art statistical models, including partial-least squares regression (PLSR) and Gaussian Process Regression (GPR), as well as pure physical models, we found that the proposed transfer learning models achieved better predictive performance and higher transferability. Specifically, compared to other statistical models and pure RTMs, the transfer learning model exhibited higher coefficient of determination (R 2 ) values with range of 0.01 to 0.79, lower normalized root mean square error (NRMSE) with range of 0.06 % to 33.25 % in model performance. Additionally, the models exhibited improved transferability, with higher R 2 values range from 0.04 to 0.32, lower NRMSE range from 0.08 % to 30.81 %. The findings underscore that transfer learning models through integrating domain knowledge from RTMs and limited observations, can harness the advantages of both RTMs and statistical models and serve as a promising approach for effectively predicting leaf traits.

59 BASIC BIOLOGICAL SCIENCES↗

Effect of curvature on the backscattering from a leaf

Using a model previously developed for the backscattering cross section of a planar leaf at X-band frequencies and above, the effect of leaf curvature is examined. For normal incidence on a rectangular section of a leaf curved in one and two dimensions, an integral expression for the backscattered field is evaluated numerically and by a stationary phase approximation, leading to a simple analytical expression for the cross-section reduction produced by the curvature. Numerical results based on the two methods are virtually identical, and in excellent agreement with measured data for rectangular sections of coleus leaves applied to the surfaces of styrofoam cylinders and spheres of different radii.

Sarabandi, K.↗

Competency for graviresponse in the leaf-sheath pulvinus of Avena sativa: onset to loss

The development of the leaf-sheath pulvinus of oat (Avena sativa L. cv. Victory) was studied in terms of its competency to respond to gravistimulation. Stages of onset of competency, maximum competency and loss of competency were identified, using the length of the supertending internode as a developmental marker. During the early phases in the onset of competency, the latency period between stimulus and graviresponse decreased and the steady state response rate increased significantly. When fully competent, the latency period remained constant as the plant continued to develop, suggesting that the latency period is relatively insensitive to quantitative changes (e.g., in carbohydrate or nutrient availability) at the cell level within the plant. In contrast, the response rate was found to increase with plant development, indicating that graviresponse rate is more strongly influenced by quantitative cellular changes. The total possible graviresponse of a single oat pulvinus was confirmed to be significantly less than the original presentation angle. This was shown to not result from a loss of competency, since the graviresponse could be reinitiated by increasing the presentation angle. As a result of the low overall graviresponse of individual pulvini, two or more pulvini are required to bring the plant apex to the vertical. This was determined to occur though the sequential, rather than simultaneous, action of successive pulvini, since a given pulvinus lost competency to gravirespond shortly after the next pulvinus became fully competent.

Non-NASA Center↗

Influence of atmospheric oxygen on leaf structure and starch deposition in Arabidopsis thaliana

Plant culture in oxygen concentrations below ambient is known to stimulate vegetative growth, but apart from reports on increased leaf number and weight, little is known about development at subambient oxygen concentrations. Arabidopsis thaliana (L.) Heynh. (cv. Columbia) plants were grown full term in pre-mixed atmospheres with oxygen partial pressures of 2.5, 5.1, 10.1, 16.2, and 21.3 kPa O2, 0.035 kPa CO2 and the balance nitrogen under continuous light. Fully expanded leaves were harvested and processed for light and transmission electron microscopy or for starch quantification. Growth in subambient oxygen concentrations caused changes in leaf anatomy (increased thickness, stomatal density and starch content) that have also been described for plants grown under carbon dioxide enrichment. However, at the lowest oxygen treatment (2.5 kPa), developmental changes occurred that could not be explained by changes in carbon budget caused by suppressed photorespiration, resulting in very thick leaves and a dwarf morphology. This study establishes the leaf parameters that change during growth under low O2, and identifies the lower concentration at which O2 limitation on transport and biosynthetic pathways detrimentally affects leaf development. Grant numbers: NAG5-3756, NAG2-1020, NAG2-1375.

Non-NASA Center↗

The reflection for dense plant canopies from the one-angle radiative transfer equation

An essential component of remote sensing of vegetation canopies from satellites is fundamental understanding. Since passive remote is driven by photons, the modeling of photon interactions with vegetation is a basic building block in that understanding. Several such photon transport models have been developed during the past two decades and continue to be developed. Different approaches have been followed including monte carlo, radiosity methods, geometric shadowing, and radiative transfer. In general, each approach has application for canopies with specific attributes. This presentation concerns the application of radiative transfer to dense vegetation canopies in which the soil does not participate. The approach taken here is novel in that a consistent theory for photon transport for non-rotationally invariant leaf scattering is developed in a canopy with a general leaf angle distribution (LAD). The theory is limited to the one-angle approximation (azimuthally averaged radiance) and is based on Chandrasekhar's analytical theory. While such a model is admittedly only approximate, it does fulfill a unique function in our search for understanding. In particular, the model is simple in its construct yet contains the essential features of canopy architecture that are mainly responsible for observed responses. Thus, this model will not only be a predictive tool but also an educational one. The mathematical setting is the radiative transfer equation in a dense (semiinfinite) canopy. The leaf scattering phase function is assumed to be Lambertian with different reflectance and transmittance. In addition, abaxial and adaxial differentiation is allowed which effectively destroys optical reciprocity. The analytical solution for the canopy BRDF is obtained by manipulation of the integral transport equation (a la Chandrasekhar) for a general LAD. With discretization of the. leaf angle, the resulting set of integral equations are solved iteratively including an acceleration procedure when the single scatter albedo is near one (in the NIR). Results will be compared to the LARS soybean canopy radiances as well as to broadleaf results from a recent Ames experiment.

Ganapol, B. D.↗

Measurement of leaf relative water content by infrared reflectance

From basic considerations and Beer's law, a leaf water content index incorporating reflectances of wavelengths from 0.76 to 0.90 microns and from 1.55 to 1.75 microns was developed that relates leaf reflectance to leaf relative water content. For the leaf succulent, Agave deserti, the leaf water content index was not significantly different from the relative water content for either individual leaves or an entire plant. Also, the relative water contents of intact plants of Encelia farinosa and Hilaria rigida in the field were estimated by the leaf water content index; variations in the proportion of living to dead leaf area could cause large errors in the estimate of relative water content. Thus, the leaf water content index may be able to estimate average relative water content of canopies when TM4 and TM5 are measured at a known relative water content and fraction of dead leaf material.

Hunt, E. Raymond, Jr.↗

Remote sensing of the leaf area index of temperate coniferous forests

To estimate the one-sided leaf area index (LAI) of temperate coniferous forests using data acquired from the Daedalus Airborne Thematic Mapper, an empirical model is developed. The study area follows an environmental gradient across west-central Oregon, where leaf development varies in response to temperature and moisture. The relationship between the ratio of thematic-mapper simulator channels four and three and the leaf area index for selected closed canopy or fully stocked forest stands along the gradient is analyzed. Results show that a good relationship exists between the LAI and the IR/red ratio for conifers and that a conifer species-independent asymptotic relationship is observed between LAI and near IR/red reflectance, with near radiometric saturation occurring at an LAI of about 7-8.

Spanner, M. A.↗

Brachypodium SPEECHLESS2 Promoter Drives Expression of a Synthetic EPF to Reduce Stomatal Density in Sugarcane Without Pleiotropic Effects

Stomata are microscopic pores that regulate the exchange of CO 2 and water vapour, making them a major target for engineering plants with improved intrinsic water use efficiency (iWUE). Proof-of-concept studies have demonstrated the potential to increase iWUE by reducing stomatal density (SD) and stomatal conductance (g sw ) by ubiquitously expressing EPIDERMAL PATTERNING FACTOR (EPF) family genes. However, unwanted effects on leaf, stem and reproductive traits are often observed when EPFs are misexpressed in this fashion. We sought to test if these effects result from pleiotropy and to identify a targeted promoter that can circumvent the side effects while retaining the desired reduction in SD. A previously reported synthetic EPF (EPF syn ) was expressed in sugarcane ( Saccharum spp.) using two putatively tissue-specific promoters from Brachypodium distachyon (BdCESA7p and BdSPCH2p) and a ubiquitous control from Zea mays (ZmUBI4p). BdSPCH2p control reduced SD to statistically equivalent levels as ZmUBI4p on the abaxial (23%) and adaxial (23%) leaf surfaces. ZmUB4p and BdCESA7p induce expression in four tissue types often associated with pleiotropic effects in EPF-expressing low SD plants. Transgenic plants carrying either the BdCESA7p or ZmUBI4p EPF syn cassettes displayed leaf chlorosis, reduced leaf nitrogen and chlorophyll content, and altered stem architecture. However, transgenic events harboring the BdSPCH2p EPF syn cassette restricted EPF syn expression to the stomatal development zone and leaf nodal tissues and produced transgenic plants without the associated pleiotropic effects. These results represent an important step toward engineering low-SD crops since they show that targeted gene expression can engineer stomatal patterning without impairing agronomically important traits.

59 BASIC BIOLOGICAL SCIENCES↗