Search NASA⌕ Search

SEARCH · Search NASA

Results for “crop yields”

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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Variations in cell wall traits impact saccharification potential of Salix famelica and Salix eriocephala

Increasing global populations, finite arable land, and the anthropogenic release of carbon dioxide into the atmosphere are driving the search for bio-based alternatives to the petroleum-derived fuels and chemicals that underpin the global economy. With rapid growth rates, a propensity for coppicing, and a wide geographic range across Canada, native shrub willows (Salix spp.) are an attractive source of low-input, high-volume biomass. To date, most willow research has focused on increasing yields and improving cropping systems, while comparatively little work has been done to assess the intrinsic diversity in cell wall traits and bioenergy potential. In this study, we characterized the cell wall composition and wood ultrastructure of 338 xylem samples from two Canadian willow species, Salix famelica and Salix eriocephala, harvested from a common garden experimental plot. Lignin content ranged from 17.5–25.1% in S. famelica and 18.6–24.3% in S. eriocephala. Following alkali pretreatment with 62.5 mM NaOH at 90 °C for 3 h and a 70-h enzymatic digestion with Accellerase 1000, glucose release ranged from 23.0–38.9 wt% in S. famelica and from 20.5–37.7 wt% in S. eriocephala, while xylose release ranged from 9.4–14.9% in S. famelica and from 9.5–15.2% in S. eriocephala. Here, partial least squares regression modelling showed that lignin content and composition were important negative regulators of glucose release. Overall, this work highlights the innate variability in cell wall traits of native willows and identifies potential genotypes that should be considered in future breeding and deployment strategies for Canadian bioenergy production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

SAGA1 and MITH1 produce matrix-traversing membranes in the CO2-fixing pyrenoid

Abstract Approximately one-third of global CO 2 assimilation is performed by the pyrenoid, a liquid-like organelle found in most algae and some plants. Specialized pyrenoid-traversing membranes are hypothesized to drive CO 2 assimilation in the pyrenoid by delivering concentrated CO 2 , but how these membranes are made to traverse the pyrenoid matrix remains unknown. Here we show that proteins SAGA1 and MITH1 cause membranes to traverse the pyrenoid matrix in the model alga Chlamydomonas reinhardtii . Mutants deficient in SAGA1 or MITH1 lack matrix-traversing membranes and exhibit growth defects under CO 2 -limiting conditions. Expression of SAGA1 and MITH1 together in a heterologous system, the model plant Arabidopsis thaliana , produces matrix-traversing membranes. Both proteins localize to matrix-traversing membranes. SAGA1 binds to the major matrix component, Rubisco, and is necessary to initiate matrix-traversing membranes. MITH1 binds to SAGA1 and is necessary for extension of membranes through the matrix. Our data suggest that SAGA1 and MITH1 cause membranes to traverse the matrix by creating an adhesive interaction between the membrane and matrix. Our study identifies and characterizes key factors in the biogenesis of pyrenoid matrix-traversing membranes, demonstrates the importance of these membranes to pyrenoid function and marks a key milestone toward pyrenoid engineering into crops for improving yields.

Hennacy, Jessica H.↗
DOE OSTI2024

BioSiting Tool (BioSiting) v2

The BioSiting Tool provides a geospatial interface for analyzing bioeconomy resources and infrastructure across the continental U.S. The tool integrates empirical and modeled data from a broad range of sources. Bioeconomy resources mapped in the tool include agricultural residues, forest residues, municipal solid waste streams, food waste, manure, fats, oils and greases and potential yields of energy crops. Infrastructure mapped in the tool includes biorefineries, material recovery facilities, anaerobic digesters, wastewater treatment plants, combustion plants, district energy systems, crude oil pipelines, petroleum pipelines, natural gas pipelines, railways and freight terminals. Additional data layers include environmental justice indicators at the census tract level and carbon dioxide geologic storage potential. Users can select a location on the map, define a buffer radius in kilometers and generate an inventory of all bioecomony resources within the buffer zone. Data from the tool can be downloaded from individual buffer zones, or at the state or national level.

Huntington, Tyler↗
DOE OSTI2020

Chlorophyll fluorescence imaging captures photochemical efficiency of grain sorghum (Sorghum bicolor) in a field setting

Abstract Background Photosynthesis is one of the most important biological reactions and forms the basis of crop productivity and yield on which a growing global population relies. However, to develop improved plant cultivars that are capable of increased productivity, methods that can accurately and quickly quantify photosynthetic efficiency in large numbers of genotypes under field conditions are needed. Chlorophyll fluorescence imaging is a rapid, non-destructive measurement that can provide insight into the efficiency of the light-dependent reactions of photosynthesis. Results To test and validate a field-deployed fluorescence imaging system on the TERRA-REF field scanalyzer, leaves of potted sorghum plants were treated with a photosystem II inhibitor, DCMU, to reduce photochemical efficiency (F V /F M ). The ability of the fluorescence imaging system to detect changes in fluorescence was determined by comparing the image-derived values with a handheld fluorometer. This study demonstrated that the imaging system was able to accurately measure photochemical efficiency (F V /F M ) and was highly correlated ( r = 0.92) with the handheld fluorometer values. Additionally, the fluorescence imaging system was able to track the decrease in photochemical efficiency due to treatment of DCMU over a 7 day period. Conclusions The system’s ability to capture the temporal dynamics of the plants’ response to this induced stress, which has comparable dynamics to abiotic and biotic stressors found in field environments, indicates the system is operating correctly. With the validation of the fluorescence imaging system, physiological and genetic studies can be undertaken that leverage the fluorescence imaging capabilities and throughput of the field scanalyzer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Sorghum bicolor Core Metabolism Model

Upregulation of triacylglycerols (TAGs) in vegetative plant tissues such as leaves has the potential to drastically increase the energy density and biomass yield of bioenergy crops. In this context, constraint-based analysis has the promise to improve metabolic engineering strategies. Here we present a core metabolism model for the C4 biomass crop Sorghum bicolor (iTJC1414) along with a minimal model for photosynthetic CO2 assimilation, sucrose and TAG biosynthesis in C3 plants. Extending iTJC1414 to a four-cell diel model we simulate C4 photosynthesis in mature leaves with the principal photo-assimilatory product being replaced by TAG produced at different levels. Independent of specific pathways and per unit carbon assimilated, energy content and biosynthetic demands in reducing equivalents are about 1.3 to 1.4 times higher for TAG than for sucrose. For plant generic pathways, ATP- and NADPH-demands per CO2 assimilated are higher by 1.3- and 1.5-fold, respectively. If the photosynthetic supply in ATP and NADPH in iTJC1414 is adjusted to be balanced for sucrose as the sole photo-assimilatory product, overproduction of TAG is predicted to cause a substantial surplus in photosynthetic ATP. This means that if TAG synthesis was the sole photo-assimilatory process, there could be an energy imbalance that might impede the process. Adjusting iTJC1414 to a photo-assimilatory rate that approximates field conditions, we predict possible daily rates of TAG accumulation, dependent on varying ratios of carbon partitioning between exported assimilates and accumulated oil droplets (TAG, oleosin) and in dependence of activation of futile cycles of TAG synthesis and degradation. We find that, based on the capacity of leaves for photosynthetic synthesis of exported assimilates, mature leaves should be able to reach a 20% level of TAG per dry weight within one month if only 5% of the photosynthetic net assimilation can be allocated into oil droplets. From this we conclude that high TAG levels should be achievable if TAG synthesis is induced only during a final phase of the plant life cycle.

Feedstock Production↗
DOE OSTI2023

A novel transfer learning framework for sorghum biomass prediction using UAV-based remote sensing data and genetic markers

Yield for biofuel crops is measured in terms of biomass, so measurements throughout the growing season are crucial in breeding programs, yet traditionally time- and labor-consuming since they involve destructive sampling. Modern remote sensing platforms, such as unmanned aerial vehicles (UAVs), can carry multiple sensors and collect numerous phenotypic traits with efficient, non-invasive field surveys. However, modeling the complex relationships between the observed phenotypic traits and biomass remains a challenging task, as the ground reference data are very limited for each genotype in the breeding experiment. In this study, a Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN) model is proposed for sorghum biomass prediction. The architecture is designed to exploit the time series remote sensing and weather data, as well as static genotypic information. As a large number of features have been derived from the remote sensing data, feature importance analysis is conducted to identify and remove redundant features. A strategy to extract representative information from high-dimensional genetic markers is proposed. To enhance generalization and minimize the need for ground reference data, transfer learning strategies are proposed for selecting the most informative training samples from the target domain. Consequently, a pre-trained model can be refined with limited training samples. Field experiments were conducted over a sorghum breeding trial planted in multiple years with more than 600 testcross hybrids. The results show that the proposed LSTM-based RNN model can achieve high accuracies for single year prediction. Further, with the proposed transfer learning strategies, a pre-trained model can be refined with limited training samples from the target domain and predict biomass with an accuracy comparable to that from a trained-from-scratch model for both multiple experiments within a given year and across multiple years.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Two related families of metal transferases, ZNG1 and ZNG2, are involved in acclimation to poor Zn nutrition in Arabidopsis

Metal homeostasis has evolved to tightly modulate the availability of metals within the cell, avoiding cytotoxic interactions due to excess and protein inactivity due to deficiency. Even in the presence of homeostatic processes, however, low bioavailability of these essential metal nutrients in soils can negatively impact crop health and yield. While research has largely focused on how plants assimilate metals, acclimation to metal-limited environments requires a suite of strategies that are not necessarily involved in metal transport across membranes. The identification of these mechanisms provides a new opportunity to improve metal-use efficiency and develop plant foodstuffs with increased concentrations of bioavailable metal nutrients. Here, we investigate the function of two distinct subfamilies of the nucleotide-dependent metallochaperones (NMCs), named ZNG1 and ZNG2, that are found in plants, using Arabidopsis thaliana as a reference organism. AtZNG1 (AT1G26520) is an ortholog of human and fungal ZNG1, and like its previously characterized eukaryotic relatives, localizes to the cytosol and physically interacts with methionine aminopeptidase type I (AtMAP1A). Analysis of At ZNG1 , At MAP1A , At MAP2A , and At MAP2B transgenic mutants are consistent with the role of Arabidopsis ZNG1 as a Zn transferase for AtMAP1A, as previously described in yeast and zebrafish. Structural modeling reveals a flexible cysteine-rich loop that we hypothesize enables direct transfer of Zn from AtZNG1 to AtMAP1A during GTP hydrolysis. Based on proteomics and transcriptomics, loss of this ancient and conserved mechanism has pleiotropic consequences impacting the expression of hundreds of genes, including those involved in photosynthesis and vesicle transport. Members of the plant-specific family of NMCs, ZNG2A1 (AT1G80480) and ZNG2A2 (AT1G15730), are also required during Zn deficiency, but their target protein(s) remain to be discovered. In conclusion, RNA-seq analyses reveal wide-ranging impacts across the cell when the genes encoding these plastid-localized NMCs are disrupted.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Understanding the dynamic interactions of root-knot nematodes and their host: role of plant growth promoting bacteria and abiotic factors

Root-knot nematodes (Meloidogyne spp., RKN) are among the most destructive endoparasitic nematodes worldwide, often leading to a reduction of crop growth and yield. Insights into the dynamics of host-RKN interactions, especially in varied biotic and abiotic environments, could be pivotal in devising novel RKN mitigation measures. Plant growth-promoting bacteria (PGPB) involves different plant growth-enhancing activities such as biofertilization, pathogen suppression, and induction of systemic resistance. We summarized the up-to-date knowledge on the role of PGPB and abiotic factors such as soil pH, texture, structure, moisture, etc. in modulating RKN-host interactions. RKN are directly or indirectly affected by different PGPB, abiotic factors interplay in the interactions, and host responses to RKN infection. We highlighted the tripartite (host-RKN-PGPB) phenomenon with respect to (i) PGPB direct and indirect effect on RKN-host interactions; (ii) host influence in the selection and enrichment of PGPB in the rhizosphere; (iii) how soil microbes enhance RKN parasitism; (iv) influence of host in RKN-PGPB interactions, and (v) the role of abiotic factors in modulating the tripartite interactions. Furthermore, we discussed how different agricultural practices alter the interactions. Finally, we emphasized the importance of incorporating the knowledge of tripartite interactions in the integrated RKN management strategies.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1973

Identification of soil associations in western South Dakota on ERTS-1 imagery

Soil association maps show the spatial relationships of land units having characteristic soil depths and textures, available water capacities, permeabilities, pH characteristics, plasticity indices, liquid limits, and the like, from which broad interpretations can be made such as how the soil is suited as a source for top soil, and as a source for sand and gravel, and how corrosive the soil is for steel and concrete, and what crop and grass yields can be expected. Film color composites of bands 4, 5 and 7 viewed over a light table with magnification show the soil associations of western South Dakota that are now recognized, and, in addition, several new soil association areas have been brought to light.

Westin, F. C.↗
NASA NTRS1979

Predicting crop production from satellite data

Crop area and yield for winter wheat is found by analysis of LANDSAT pictures. Correlation between measure and yield is established from measurements on known wheatfields with known yields.

Colwell, J. E.↗
NASA NTRS1978

Briefing Materials for Technical Presentations, Volume B: The LACIE Symposium

Tables, charts, and LACIE segments are used to demonstrate the accuracy of estimated crop conditions and yield from 1974 to 1976, and to demonstrate the benefits of meteorological and LANDSAT data. Developments in data acquisition, sampling, and reduction are reviewed. The USDA application test system is highlighted with emphasis on user requirements, technology transfer, data base design, and cost data models for data base operation and management.

Source record↗
NASA NTRS1982

An application of cluster analysis for determining homogeneous subregions: The agroclimatological point of view

A stratification oriented to crop area and yield estimation problems was performed using an algorithm of clustering. The variables used were a set of agroclimatological characteristics measured in each one of the 232 municipalities of the State of Rio Grande do Sul, Brazil. A nonhierarchical cluster analysis was used and the pseudo F-statistics criterion was implemented for determining the "cut point" in the number of strata.

Parada, N. D. J.↗
NASA NTRS1992

The dynamics of hydroponic crops for simulation studies of the CELSS initial reference configurations

The goal of this research is to develop a progressive series of mathematical models for the CELSS hydroponic crops. These models will systematize the experimental findings from the crop researchers in the CELSS Program into a form useful to investigate system-level considerations, for example, dynamic studies of the CELSS Initial Reference Configurations. The crop models will organize data from different crops into a common modeling framework. This is the fifth semiannual report for this project. The following topics are discussed: (1) use of field crop models to explore phasic control of CELSS crops for optimizing yield; (2) seminar presented at Purdue CELSS NSCORT; and (3) paper submitted on analysis of bioprocessing of inedible plant materials.

Volk, Tyler↗
NASA NTRS1998

NASA's Current Earth Science Program

NASA's Earth science program is a scientific endeavor whose goal is to provide long-term understanding of the Earth as an integrated system of land, water, air and life. A highly developed scientific knowledge of the Earth system is necessary to understand how the environment affects humanity, and how humanity may be affecting the environment. The remote sensing technologies used to gather the global environmental data used in such research also have numerous practical applications. Current applications of remote sensing data demonstrate their practical benefits in areas such as the monitoring of crop conditions and yields, natural disasters and forest fires; hazardous waste clean up; and tracking of vector-borne diseases. The long-term availability of environmental data is essential for the continuity of important research and applications efforts. NASA's Earth observation program has undergone many changes in the recent past.

Charles, Leslie Bermann↗
NASA NTRS2015

A Climate Generator for Agricultural Planning in Southeastern South America

A method is described for the generation of climate scenarios in a form suitable for driving agricultural models. The scenarios are tailored to the region in southeastern South America bounded by 25-40 deg S, 45-65 deg W, denoted here as SESA. SESA has been characterized by increasing summer precipitation, particularly during the late 20th century, which, in the context of favorable market conditions, has enabled increases in agricultural production. Since about year 2000, however, the upward tendency appears to have slowed or possibly stopped, raising questions about future climate inputs to regional agricultural yields. The method is not predictive in the deterministic sense, but rather attempts to characterize uncertainty in near-term future climate, taking into account both forced trends and unforced, natural climate fluctuations. It differs from typical downscaling methods in that GCM information is utilized only at the regional scale, subregional variability being modeled based on the observational record. Output, generated on the monthly time scale, is disaggregated to daily values with a weather generator and used to drive soybean yields in the crop model DSSAT-CSM, for which preliminary results are discussed. The simulations produced permit assessment of the interplay between long-range trends and near-term climate variability in terms of agricultural production.

climate simulation↗
NASA NTRSDate not supplied

Biological Insights at the Interface of Multiple Arabidopsis Legacy Datasets

The NASA GeneLab database includes an open-access collection of datasets yielded by space biology experiments. Six Gene Lab Data Sets (GLDS’s) performed in Arabidopsis were selected for analysis (7/17/44/121/205/213), all of which included transcriptome data from spaceflight and ground control environments. Hardware, ecotype, environmental conditions, and other experimental conditions varied, allowing the observations of overarching gene expression impacts of microgravity on plant life without focusing on effects of specific experimental conditions. Using GeneLab pre-processed datasets as the basis for the study, RNA microarray data were analyzed to identify genes that showed altered expression in microgravity when compared to control samples for each individual GLDS. All differentially expressed genes were compared to locate differentially expressed genes common between spaceflight experiments. The most noteworthy result is that not one gene shared differential expression among the six GLDS’s. However, gene expression was not influenced randomly by the microgravity environment, as there were several gene ontology terms that were significantly enriched across all experiments. These included 20 significantly enriched biological processes, and although the genes which enriched each term varied, there were many cases of specific genes common to clusters of multiple GLDS’s. Gene expression such as NAC92 and ERF011 or membrane structural element FFP6 provide insight and direction toward understanding the plant response to spaceflight. Characterizing these common processes and the shared differentially expressed genes has demonstrated potential targets for further study to understand and modulate the biological response of plants in microgravity. Life on Earth has never been subjected to the absence of gravity as a selective pressure, so observing how life forms react to a microgravity environment could provide insight to our shared fundamental biological processes. It is also feasible that the genetic modification of specific genes linked to the microgravity response could improve health and yield of space crops.

Joseph Emhof↗
NASA NTRSDate not supplied

Oxygen Deficiency in Spaceflight & its Impact on Plants’ Adaptive Changes

The goal of this study was to investigate the effects of hypoxic conditions in spaceflight. The distribution of genes involved with hypoxia in Arabidopsis thaliana and Brassica rapa were analyzed with the results from past spaceflight experiments to evaluate genes for future studies. Transcriptomes data of two different spaceflight studies of Arabidopsis thaliana from the NASA GeneLab database, GLDS-7 and GLDS-17, were compared. DNA microarrays were utilized for transcription profiling to conduct these studies. For GLDS-7, the response in spaceflight was studied with approaches that collected gene expression data. Leaves, hypocotyls, and root tissues were compared to the whole plant. For GLDS-17, seedlings and undifferentiated cultured cells were placed in the Biological Research in Canisters (BRIC), specifically BRIC-16. The genes related to hypoxia in Arabidopsis thaliana from these two studies were compared to genes in Brassica rapa with the TOAST database to evaluate similarities. When transcriptomes were analyzed for GLDS-7 and 17, genes that were considered significant had p-values ≤ 0.05 and log fold change values ≤ -1 or ≥1. Sixteen genes fulfilled the criteria. The genes related to hypoxia were alcohol dehydrogenase, elongation factor, ethylene-responsive factor, GUS, heat-shock proteins, NAP, RAP2.12, and RD20. The genes most impacted by spaceflight were heat-shock proteins. These genes were compared with Brassica rapa through Arabidopsis Ensemble Orthology from the TOAST Database. Similarities were seen in alcohol dehydrogenase, elongation factor, ethylene-responsive factor, heat-shock proteins, NAP, and RAP2.12. Overall, transcription profiling indicates that plants’ survival in spaceflight is dependent on adaptive changes with gene expression. This study also indicates that there are similarities in gene expression between Arabidopsis thaliana and Brassica rapa with comparable gene expression. Future studies could include analyzing additional species to understand which genes could be modified to ensure better yield of space crops amid hypoxic conditions.

hypoxia↗
NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗