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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

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↗
DOE OSTI2023

Similar photosynthetic but different yield responses of C 3 and C 4 crops to elevated O 3

The deleterious effects of ozone (O 3 ) pollution on crop physiology, yield, and productivity are widely acknowledged. It has also been assumed that C 4 crops with a carbon concentrating mechanism and greater water use efficiency are less sensitive to O 3 pollution than C 3 crops. This assumption has not been widely tested. Therefore, we compiled 46 journal articles and unpublished datasets that reported leaf photosynthetic and biochemical traits, plant biomass, and yield in five C 3 crops (chickpea, rice, snap bean, soybean, and wheat) and four C 4 crops (sorghum, maize, Miscanthus × giganteus , and switchgrass) grown under ambient and elevated O 3 concentration ([O 3 ]) in the field at free-air O 3 concentration enrichment (O 3 -FACE) facilities over the past 20 y. When normalized by O 3 exposure, C 3 and C 4 crops showed a similar response of leaf photosynthesis, but the reduction in chlorophyll content, fluorescence, and yield was greater in C 3 crops compared with C 4 crops. Additionally, inbred and hybrid lines of rice and maize showed different sensitivities to O 3 exposure. This study quantitatively demonstrates that C 4 crops respond less to elevated [O 3 ] than C 3 crops. This understanding could help maintain cropland productivity in an increasingly polluted atmosphere.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Annual Herbaceous Plants Exhibit Altered Morphological Traits in Response to Altered Precipitation and Drought Patterns in Semiarid Sandy Grassland, Northern China

The frequency and intensity of extreme precipitation events and severe drought are predicted to increase in semiarid areas due to global climate change. Plant morphological traits can reflect plant responses to a changing environment, such as altered precipitation or drought patterns. In this study, we examined the response of morphological traits of root, stem, leaf and reproduction meristems of annual herbaceous species to altered precipitation and drought patterns in a semiarid sandy grassland. The study involved a control treatment (100% of background precipitation) and the following six altered precipitation treatments: (1) P(+): precipitation increased by 30%, (2) P(++): precipitation increased by 60%, (3) P(-): precipitation decreased by 30%, (4) P(--): precipitation decreased by 60%, (5) drought 1 (D1): 46-day drought from May 1st to June 15th, and (6) drought 2 (D2): 46-day drought from July 1st to August 15th. P(++) significantly increased root length, flower length-to-width ratio, both P(+) and P(++) significantly increased stem length and flower number in the plant growing seasons, while all of them decreased under P(-) and P(--). The annual herbaceous plants marginally increased the number of second-level stem branches and stem diameter in order to better resist the severe drought stress under P(--). P(+) and P(++) increased the root, stem, leaf, and flower dry weight, with the flower dry weight accounting for a larger proportion than the other aboveground parts. Under D2, the plants used the limited water resources more efficiently by increasing the root-to-shoot ratio compared with P(-), P(--) and D1, which reflects biomass allocation to belowground increased. The linear mixed-effects models and redundancy analysis showed that the root-to-shoot ratio and the dry weight of various plant components were significantly affected by morphological traits and altered precipitation magnitude. Our results showed that the herbaceous species have evolved morphological trait responses that allow them to adapt to climate change. Such differences in morphological traits may ultimately affect the growing patterns of annual herbaceous species, enhancing their drought-tolerant capacity in semiarid sandy grassland during the ongoing climate change.

Sun, Shan-Shan↗
DOE OSTI2023

Leaf Nitrogen and Carbon Content, and Leaf Mass Per Area, Kougarok Road, Seward Peninsula, Alaska, 2018

Nitrogen and carbon content, leaf mass per area (LMA) and leaf water content (LWC) of leaves sampled from locations on the Kougarok mile marker 64 NGEE Arctic site, Seward Peninsula, Alaska. Samples were collected in July 2018 from Alnus viridis, Betula nana, Betula glandulosa, Arctostaphylos alpina and Salix pulchra. This data package includes leaf sample information and trait data (*.csv). Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA207_flmd.csv. See data package NGA208 "Full spectrum 350-2500 nm canopy spectral reflectance, Seward Peninsula, Alaska, 2018" for linked canopy spectral reflectance data, dGPS locations and sample photographs. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The three-dimensional construction of leaves is coordinated with water use efficiency in conifers

Conifers prevail in the canopies of many terrestrial biomes, holding a great ecological and economic importance globally. Current increases in temperature and aridity are imposing high transpirational demands and resulting in conifer mortality. Therefore, identifying leaf structural determinants of water use efficiency is essential for predicting physiological impacts due to environmental variation. Here, using synchrotron-generated microtomography imaging, we extracted leaf volumetric anatomy and stomatal traits in 34 species across conifers with a special focus on Pinus , the richest conifer genus. We show that intrinsic water use efficiency (WUE i ) is positively driven by leaf vein volume. Needle-like leaves of Pinus , as opposed to flat leaves or flattened needles of other genera, showed lower mesophyll porosity, decreasing the relative mesophyll volume. This led to increased ratios of stomatal pore number per mesophyll or intercellular airspace volume, which emerged as powerful explanatory variables, predicting both stomatal conductance and WUE i . Our results clarify how the three-dimensional organisation of tissues within the leaf has a direct impact on plant water use and carbon uptake. By identifying a suite of structural traits that influence important physiological functions, our findings can help to understand how conifers may respond to the pressures exerted by climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Towards mapping biodiversity from above: Can fusing lidar and hyperspectral remote sensing predict taxonomic, functional, and phylogenetic tree diversity in temperate forests?

Abstract Aim Rapid global change is impacting the diversity of tree species and essential ecosystem functions and services of forests. It is therefore critical to understand and predict how the diversity of tree species is spatially distributed within and among forest biomes. Satellite remote sensing platforms have been used for decades to map forest structure and function but are limited in their capacity to monitor change by their relatively coarse spatial resolution and the complexity of scales at which different dimensions of biodiversity are observed in the field. Recently, airborne remote sensing platforms making use of passive high spectral resolution (i.e., hyperspectral) and active lidar data have been operationalized, providing an opportunity to disentangle how biodiversity patterns vary across space and time from field observations to larger scales. Most studies to date have focused on single sites and/or one sensor type; here we ask how multiple sensor types from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) perform across multiple sites in a single biome at the NEON field plot scale (i.e., 40 m × 40 m). Location Eastern USA. Time period 2017–2018. Taxa studied Trees. Methods With a fusion of hyperspectral and lidar data from the NEON AOP, we assess the ability of high resolution remotely sensed metrics to measure biodiversity variation across eastern US temperate forests. We examine how taxonomic, functional, and phylogenetic measures of alpha diversity vary spatially and assess to what degree remotely sensed metrics correlate with in situ biodiversity metrics. Results Models using estimates of forest function, canopy structure, and topographic diversity performed better than models containing each category alone. Our results show that canopy structural diversity, and not just spectral reflectance, is critical to predicting biodiversity. Main conclusions We found that an approach that jointly leverages spectral properties related to leaf and canopy functional traits and forest health, lidar derived estimates of forest structure, fine‐resolution topographic diversity, and careful consideration of biogeographical differences within and among biomes is needed to accurately map biodiversity variation from above.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Bioenergy sorghum maintains photosynthetic capacity in elevated ozone concentrations

Abstract Elevated tropospheric ozone concentration (O 3 ) significantly reduces photosynthesis and productivity in several C 4 crops including maize, switchgrass and sugarcane. However, it is unknown how O 3 affects plant growth, development and productivity in sorghum ( Sorghum bicolor L.), an emerging C 4 bioenergy crop. Here, we investigated the effects of elevated O 3 on photosynthesis, biomass and nutrient composition of a number of sorghum genotypes over two seasons in the field using free‐air concentration enrichment (FACE), and in growth chambers. We also tested if elevated O 3 altered the relationship between stomatal conductance and environmental conditions using two common stomatal conductance models. Sorghum genotypes showed significant variability in plant functional traits, including photosynthetic capacity, leaf N content and specific leaf area, but responded similarly to O 3 . At the FACE experiment, elevated O 3 did not alter net CO 2 assimilation ( A ), stomatal conductance ( g s ), stomatal sensitivity to the environment, chlorophyll fluorescence and plant biomass, but led to reductions in the maximum carboxylation capacity of phosphoenolpyruvate and increased stomatal limitation to A in both years. These findings suggest that bioenergy sorghum is tolerant to O 3 and could be used to enhance biomass productivity in O 3 polluted regions.

09 BIOMASS FUELS↗
DOE OSTI2021

Data from Bioenergy Sorghum Maintains Photosynthetic Capacity in Elevated Ozone Concentrations

Elevated tropospheric ozone concentration (O3) significantly reduces photosynthesis and productivity in several C4 crops including maize, switchgrass and sugarcane. However, it is unknown how O3 affects plant growth, development and productivity in sorghum ( Sorghum bicolor L.), an emerging C4 bioenergy crop. Here, we investigated the effects of elevated O3 on photosynthesis, biomass and nutrient composition of a number of sorghum genotypes over two seasons in the field using free-air concentration enrichment (FACE), and in growth chambers. We also tested if elevated O3 altered the relationship between stomatal conductance and environmental conditions using two common stomatal conductance models. Sorghum genotypes showed significant variability in plant functional traits, including photosynthetic capacity, leaf N content and specific leaf area, but responded similarly to O3. At the FACE experiment, elevated O3 did not alter net CO2 assimilation (A), stomatal conductance (gs), stomatal sensitivity to the environment, chlorophyll fluorescence and plant biomass, but led to reductions in the maximum carboxylation capacity of phosphoenolpyruvate and increased stomatal limitation to A in both years. These findings suggest that bioenergy sorghum is tolerant to O3 and could be used to enhance biomass productivity in O3 polluted regions.

Feedstock Production↗
DOE OSTI2023

Similar photosynthetic, but different yield responses of C3 and C4 crops to elevated O3

This dataset contains leaf photosynthetic and biochemical traits, plant biomass, and yield in five C3 crops (chickpea, rice, snap bean, soybean, wheat) and four C4 crops (sorghum, maize, Miscanthus × giganteus, switchgrass) grown under ambient and elevated O3 concentration ([O3]) in the field at free-air O3 concentration enrichment (O3-FACE) facilities over the past 20 years.

C3 and C4 crops↗
DOE OSTI2020

Foliar functional traits from imaging spectroscopy across biomes in eastern North America

Summary Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes. With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America. Model validation accuracy varied among traits (normalized root mean squared error, 9.1–19.4%; coefficient of determination, 0.28–0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28–81% provided high confidence for multiple traits concurrently. Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental‐scale functional diversity.

Wang, Zhihui↗
DOE OSTI2022

The leaf economics spectrum of triploid and tetraploid C 4 grass Miscanthus x giganteus

Abstract The leaf economics spectrum (LES) describes multivariate correlations in leaf structural, physiological and chemical traits, originally based on diverse C 3 species grown under natural ecosystems. However, the specific contribution of C 4 species to the global LES is studied less widely. C 4 species have a CO 2 concentrating mechanism which drives high rates of photosynthesis and improves resource use efficiency, thus potentially pushing them towards the edge of the LES. Here, we measured foliage morphology, structure, photosynthesis, and nutrient content for hundreds of genotypes of the C 4 grass Miscanthus × giganteus grown in two common gardens over two seasons. We show substantial trait variations across M .× giganteus genotypes and robust genotypic trait relationships. Compared to the global LES, M .× giganteus genotypes had higher photosynthetic rates, lower stomatal conductance, and less nitrogen content, indicating greater water and photosynthetic nitrogen use efficiency in the C 4 species. Additionally, tetraploid genotypes produced thicker leaves with greater leaf mass per area and lower leaf density than triploid genotypes. By expanding the LES relationships across C 3 species to include C 4 crops, these findings highlight that M .× giganteus occupies the boundary of the global LES and suggest the potential for ploidy to alter LES traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

NEON AOP foliar trait maps, maps of model uncertainty estimates, and conifer map, East River, CO 2018

This data package contains mapped trait estimates and their uncertainties, and conifer map, for the National Ecological Observatory Network's Airborne Observation Platform survey data acquired over the Upper East River, Colorado in 2018. For full details, please see associated reference. in brief, trait models were developed independently for needle and non-needle leaf species using partial least squares regression (PLSR) using ground data from additional datasets: doi:10.15485/1618130, doi:10.15485/1618132, and doi:10.15485/1631278, merged with extracted spectral data from doi:10.15485/1618131. We separated vegetated pixels into needle and non-needle classes in order to generate a classification map based on the spectral differences between these leaf types (conifer.tif). We trained a deep learning model with custom architecture, detailed in Chadwick et al. In Press. The model performed with 0.998 true positive rate and 0.982 true negative rate, with ‘positives’ being non-needle identification. We then utilized PLSR to generate models of foliar traits for each leaf type. So that we could also map uncertainty in these predictions, we generated ten different models for needle and non-needle leaf species using different testing holdout sets of discrete sites. Each of these models was developed with a 100-fold cross validation procedure that utilized a 70% training set and 30% validation set with each fold, and then assessed based on the 10% of testing sites that were not included in that model’s development. The mean predicted value across the 10 models is used for the trait estimate in each pixel across the study area. The models are applied according to the leaf type designation in the conifer.tif map. The errors are the standard deviation across the 10 different models developed, with high error suggesting instability in model prediction and areas where values may not be reliable for ecological inference. These maps are only applied to areas with a NDVI > 0.5 to exclude non-vegetated areas. Shade masks could be applied to these data (doi:10.15485/1618131), but have not been for this data package. These data are also available on Google Earth Engine: https://code.earthengine.google.com/?asset=users/kdc/ER_NEON

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A systems genetics approach to deciphering the effect of dosage variation on leaf morphology in Populus

Abstract Gene copy number variation is frequent in plant genomes of various species, but the impact of such gene dosage variation on morphological traits is poorly understood. We used a large population of Populus carrying genomically characterized insertions and deletions across the genome to systematically assay the effect of gene dosage variation on a suite of leaf morphology traits. A systems genetics approach was used to integrate insertion and deletion locations, leaf morphology phenotypes, gene expression, and transcriptional network data, to provide an overview of how gene dosage influences morphology. Dosage-sensitive genomic regions were identified that influenced individual or pleiotropic morphological traits. We also identified cis-expression quantitative trait loci (QTL) within these dosage QTL regions, a subset of which modulated trans-expression QTL as well. Integration of data types within a gene co-expression framework identified co-expressed gene modules that are dosage sensitive, enriched for dosage expression QTL, and associated with morphological traits. Functional description of these modules linked dosage-sensitive morphological variation to specific cellular processes, as well as candidate regulatory genes. Together, these results show that gene dosage variation can influence morphological variation through complex changes in gene expression, and suggest that frequently occurring gene dosage variation has the potential to likewise influence quantitative traits in nature.

Biochemistry & Molecular Biology↗
DOE OSTI2022

Data for The Leaf Economics Spectrum of Triploid and Tetraploid C4 Grass Miscanthus x giganteus

The leaf economics spectrum (LES) describes multivariate correlations in leaf structural, physiological and chemical traits, originally based on diverse C3 species grown under natural ecosystems. However, the specific contribution of C4 species to the global LES is studied less widely. C4 species have a CO2 concentrating mechanism which drives high rates of photosynthesis and improves resource use efficiency, thus potentially pushing them towards the edge of the LES. Here, we measured foliage morphology, structure, photosynthesis, and nutrient content for hundreds of genotypes of the C4 grass Miscanthus × giganteus grown in two common gardens over two seasons. We show substantial trait variations across M. × giganteus genotypes and robust genotypic trait relationships. Compared to the global LES, M. × giganteus genotypes had higher photosynthetic rates, lower stomatal conductance, and less nitrogen content, indicating greater water and photosynthetic nitrogen use efficiency in the C4 species. Additionally, tetraploid genotypes produced thicker leaves with greater leaf mass per area and lower leaf density than triploid genotypes. By expanding the LES relationships across C3 species to include C4 crops, these findings highlight that M. × giganteus occupies the boundary of the global LES and suggest the potential for ploidy to alter LES traits.

Biomass Analytics↗
DOE OSTI2022

At least it is a dry cold: the global distribution of freeze–thaw and drought stress and the traits that may impart poly-tolerance in conifers

Abstract Conifers inhabit some of the most challenging landscapes where multiple abiotic stressors (e.g., aridity, freezing temperatures) often co-occur. Physiological tolerance to multiple stressors (‘poly-tolerance’) is thought to be rare because exposure to one stress generally limits responses to another through functional trade-offs. However, the capacity to exhibit poly-tolerance may be greater when combined abiotic stressors have similar physiological impacts, such as the disruption of hydraulic function imposed by drought or freezing. Here, we reviewed empirical data in light of theoretical expectations for conifer adaptations to drought and freeze–thaw cycles with particular attention to hydraulic traits of the stem and leaf. Additionally, we examined the commonality and spatial distribution of poly-stress along indices of these combined stressors. We found that locations with the highest values of our poly-stress index (PSi) are characterized by moderate drought and moderate freeze–thaw, and most of the global conifer distribution occupies areas of moderate poly-stress. Among traits examined, we found diverse responses to the stressors. Turgor loss point did not correlate with freeze–thaw or drought stress individually, but did with the PSi, albeit inverse to what was hypothesized. Leaf mass per area was more strongly linked with drought stress than the poly-stress and not at all with freeze–thaw stress. In stems, the water potential causing 50% loss of hydraulic conductivity became more negative with increasing drought stress and poly-stress but did not correlate with freeze–thaw stress. For these traits, we identified a striking lack of coverage for substantial portions of species ranges, particularly at the upper boundaries of their respective PSis, demonstrating a critical gap in our understanding of trait prevalence and plasticity along these stress gradients. Future research should investigate traits that confer tolerance to both freeze–thaw and drought stress in a wide range of species across broad geographic scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The global spectrum of plant form and function: enhanced species-level trait dataset

Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass – define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Divergences in hydraulic conductance and anatomical traits of stems and leaves in three temperate tree species coping with drought, N addition and their interactions

Drought and N addition have been shown to affect tree hydraulic traits, but few studies have been made on their interactions across species with different wood types or leaf forms. We examined the responses of hydraulic conductance and xylem anatomical traits of Quercus mongolica (ring-porous with simple-leaves), Fraxinus mandshurica (ring-porous with compound-leaves), and Tilia amurensis (diffuse-porous with simple-leaves) to drought, N addition and their interactions. Drought stress decreased current-year xylem-specific conductivity in stems (Ksx) and leaf hydraulic conductance (Kleaf), but N addition affected Ksx and Kleaf differently among species and watering regimes. These divergent effects were associated with different responses of anatomical traits and leaf forms. Higher mean vessel diameter in stems (Dstem) and lower vessel density in leaves (VDvein) were observed with N addition. The three-way interactive effects of drought, N addition and tree species were significant for most values of anatomical traits. These results were also reflected in large differences in vessel diameter and density among species with different wood types or leaf forms. The two-way interactive effects of drought and N addition were significant on Kleaf and predawn water potential (?pd), but not Ksx, indicating that leaves were more sensitive than stems to a combination of drought stress and N addition. Our results provide mechanistic insight into the variable responses of xylem water transport to the interactions of drought and N availability.

Hydraulic conductance, hydraulic architecture, N f↗
DOE OSTI2021

Source:sink imbalance detected with leaf and canopy-level spectroscopy in a field-grown crop

The finely-tuned balance between sources and sinks determines plant resource partitioning and regulates growth and development. Understanding and measuring metabolic indicators of source or sink limitation forms a vital part of global efforts to increase crop yield for future food security. Here, we measured metabolic profiles of Cucurbita pepo (zucchini) grown in the field under carbon sink limitation and control conditions. We demonstrate that these profiles can be measured non-destructively using hyperspectral reflectance at both leaf and canopy scales. Total non-structural carbohydrates (TNC) increased 82% in sink-limited plants; leaf mass per unit area (LMA) increased 38%; free amino acids increased 22%. Partial least-squares regression models link these measured functional traits with reflectance data, enabling high-throughput estimation of traits comprising the sink limitation response. Leaf- and canopy-scale models for TNC had R 2 values of 0.93 and 0.64 and %RMSE of 13% and 38% respectively. For LMA, R 2 values were 0.91 and 0.60 and %RMSE 7% and 14%; for free amino acids, R 2 was 0.53 and 0.21 with %RMSE 20% and 26%. Remote sensing can enable accurate, rapid detection of sink limitation in the field at the leaf and canopy scale, greatly expanding our ability to understand and measure metabolic responses to stress.

54 ENVIRONMENTAL SCIENCES↗