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

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At least 505 records · Page 28

Molecular mechanism of Rubisco activase: Dynamic assembly and Rubisco remodeling

Ribulose-1,5-bisphosphate (RuBP) carboxylase-oxygenase (Rubisco) enzyme is the limiting step of photosynthetic carbon fixation, and its activation is regulated by its co-evolved chaperone, Rubisco activase (Rca). Rca removes the intrinsic sugar phosphate inhibitors occupying the Rubisco active site, allowing RuBP to split into two 3-phosphoglycerate (3PGA) molecules. This review summarizes the evolution, structure, and function of Rca and describes the recent findings regarding the mechanistic model of Rubisco activation by Rca. New knowledge in these areas can significantly enhance crop engineering techniques used to improve crop productivity.

59 BASIC BIOLOGICAL SCIENCES↗

Validation of a metabolite–GWAS network for Populus trichocarpa family 1 UDP-glycosyltransferases

Metabolite genome-wide association studies (mGWASs) are increasingly used to discover the genetic basis of target phenotypes in plants such as Populus trichocarpa , a biofuel feedstock and model woody plant species. Despite their growing importance in plant genetics and metabolomics, few mGWASs are experimentally validated. Here, we present a functional genomics workflow for validating mGWAS-predicted enzyme–substrate relationships. We focus on uridine diphosphate–glycosyltransferases (UGTs), a large family of enzymes that catalyze sugar transfer to a variety of plant secondary metabolites involved in defense, signaling, and lignification. Glycosylation influences physiological roles, localization within cells and tissues, and metabolic fates of these metabolites. UGTs have substantially expanded in P. trichocarpa , presenting a challenge for large-scale characterization. Using a high-throughput assay, we produced substrate acceptance profiles for 40 previously uncharacterized candidate enzymes. Assays confirmed 10 of 13 leaf mGWAS associations, and a focused metabolite screen demonstrated varying levels of substrate specificity among UGTs. A substrate binding model case study of UGT-23 rationalized observed enzyme activities and mGWAS associations, including glycosylation of trichocarpinene to produce trichocarpin, a major higher-order salicylate in P. trichocarpa. We identified UGTs putatively involved in lignan, flavonoid, salicylate, and phytohormone metabolism, with potential implications for cell wall biosynthesis, nitrogen uptake, and biotic and abiotic stress response that determine sustainable biomass crop production. Our results provide new support for in silico analyses and evidence-based guidance for in vivo functional characterization.

59 BASIC BIOLOGICAL SCIENCES↗

GmMPK6 Positively Regulates Salt Tolerance through Induction of GmRbohI1 in Soybean

Salt stress is a critical environmental stress that impairs plant growth and development, especially in crop productivity; therefore, understanding the salt response in plants is the basis for their development of salt tolerance. Under salinity, soybean mitogen-activated protein kinase 6 (GmMPK6) is activated and positively regulates reactive oxygen species (ROS) generation. However, it is not yet elucidated how GmMPK6 regulates ROS generation and its role in salt tolerance. Here, we show that GmMPK6, solely activated in NaCl treatment, and gene expression of GmRbohI1 was not only reduced by MPK inhibitor SB202190 in NaCl treatment, but also increased in a GMKK1-expressing protoplast. Furthermore, SB202190 and the NADPH-oxidase inhibitor, diphenyleneiodonium chloride, increased susceptibility to salt stress. The expression of GmRD19A was induced by NaCl treatment, but this expression was compromised by SB202190. Consequently, we revealed that GmMPK6 induces ROS generation through the transcriptional regulation of GmRbohI1 and increases salt tolerance in soybean.

59 BASIC BIOLOGICAL SCIENCES↗

Inference of Gene Regulatory Network Uncovers the Linkage between Circadian Clock and Crassulacean Acid Metabolism in Kalanchoë fedtschenkoi

The circadian clock drives time-specific gene expression, enabling biological processes to be temporally controlled. Plants that conduct crassulacean acid metabolism (CAM) photosynthesis represent an interesting case of circadian regulation of gene expression as stomatal movement is temporally inverted relative to stomatal movement in C3 plants. The mechanisms behind how the circadian clock enabled physiological differences at the molecular level is not well understood. Recently, the rescheduling of gene expression was reported as a mechanism to explain how CAM evolved from C3. Therefore, we investigated whether core circadian clock genes in CAM plants were re-phased during evolution, or whether networks of phase-specific genes were simply re-wired to different core clock genes. We identified candidate core clock genes based on gene expression features and then applied the Local Edge Machine (LEM) algorithm to infer regulatory relationships between this new set of core candidates and known core clock genes in Kalanchoë fedtschenkoi. We further inferred stomata-related gene targets for known and candidate core clock genes and constructed a gene regulatory network for core clock and stomata-related genes. Our results provide new insight into the mechanism of circadian control of CAM-related genes in K. fedtschenkoi, facilitating the engineering of CAM machinery into non-CAM plants for sustainable crop production in water-limited environments.

59 BASIC BIOLOGICAL SCIENCES↗

Examining the Characteristics of the Cropland Data Layer in the Context of Estimating Land Cover Change

The United States Department of Agriculture (USDA) Cropland Data Layer (CDL) provides spatially explicit information about crop production area and has served as a prevalent data source for characterizing cropland change in the U.S. in the last decade. Understanding the accuracy of the CDL is paramount because of the reliance on it for management and policy making. This study examined the characteristics of the CDL from 2007 to 2017 using comparisons to other USDA datasets. The results showed when examining the cropland area for the same year, the CDL produced comparable trends with other datasets (R 2 > 0.95), but absolute area differed. The estimated area of cropland changes from 2007 to 2012, 2008 to 2012 and 2012 to 2017 varied from weak to moderate correlation between the CDL and the tabular data (R 2 = 0.005~0.63). Differences in area of cropland change varied widely between data sources with the CDL estimating much larger change area. A series of image processing techniques designed to improve the confidence in cropland change estimated using the CDL reduced the area of estimated cropland change. The techniques also, unexpectedly, lowered the correlation in change estimated between the CDL and the tabular datasets. Estimated land cover change area varied widely based on analyses applied and could reverse from increasing to declining area in cropland. Further analyses showed unlikely change scenarios when comparing different year combinations. The authors recommend the CDL only be used for land cover change analysis if the error can be estimated and is within change estimates.

58 GEOSCIENCES↗

Predicting Short-Term Deformation in the Central Valley Using Machine Learning

Land subsidence caused by excessive groundwater pumping in Central Valley, California, is a major issue that has several negative impacts such as reduced aquifer storage and damaged infrastructures which, in turn, produce an economic loss due to the high reliance on crop production. This is why it is of utmost importance to routinely monitor and assess the surface deformation occurring. Two main goals that this paper attempts to accomplish are deformation characterization and deformation prediction. The first goal is realized through the use of Principal Component Analysis (PCA) applied to a series of Interferomtric Synthetic Aperture Radar (InSAR) images that produces eigenimages displaying the key characteristics of the subsidence. Water storage changes are also directly analyzed by the use of data from the Gravity Recovery and Climate Experiment (GRACE) twin satellites and the Global Land Data Assimilation System (GLDAS). The second goal is accomplished by building a Long Short-Term Memory (LSTM) model to predict short-term deformation after developing an InSAR time series using LiCSBAS, an open-source InSAR time series package. The model is applied to the city of Madera and produces better results than a baseline averaging model and a one dimensional convolutional neural network (CNN) based on a mean squared error metric showing the effectiveness of machine learning in deformation prediction as well as the potential for incorporation in hazard mitigation models. The model results can directly aid policy makers in determining the appropriate rate of groundwater withdrawal while maintaining the safety and well-being of the population as well as the aquifers’ integrity.

58 GEOSCIENCES↗

The 1971 corn blight watch experiment

The successful fulfillment of the objectives for the 1971 corn blight watch experiment is reported. The objectives were: (1) detect the development and spread of corn blight during the growing season across the Corn Belt; (2) assess different levels of infection in the Corn Belt; (3) amplify data acquired by ground observations to better appraise current blight status and the probable impact on crop production; and (4) estimate through extrapolation the applicability of these techniques to similar situations occurring in the future.

Clifton, J. W.↗

Identification of agricultural crops by computer processing of ERTS MSS data

Quantitative evaluation of computer-processed ERTS MSS data classifications has shown that major crop species (corn and soybeans) can be accurately identified. The classifications of satellite data over a 2000 square mile area not only covered more than 100 times the area previously covered using aircraft, but also yielded improved results through the use of temporal and spatial data in addition to the spectral information. Furthermore, training sets could be extended over far larger areas than was ever possible with aircraft scanner data. And, preliminary comparisons of acreage estimates from ERTS data and ground-based systems agreed well. The results demonstrate the potential utility of this technology for obtaining crop production information.

Bauer, M. E.↗

Remote sensing applications in agriculture and forestry. Applications of aerial photography and ERTS data to agricultural, forest and water resources management

Remote sensing techniques are being used in Minnesota to study: (1) forest disease detection and control; (2) water quality indicators; (3) forest vegetation classification and management; (4) detection of saline soils in the Red River Valley; (5) corn defoliation; and (6) alfalfa crop productivity. Results of progress, and plans for future work in these areas, are discussed.

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Widening ERTS applications

In less than two years of operation ERTS-1 is shown to have successfully completed its experimental mission and to be delivering an ever-increasing roster of benefits. The widening ERTS applications reviewed include air quality and weather modification, aid to oil exploration, ore-deposit exploration, short-lived event observation, flood area assessment and flood-plain mapping, land and water quality assessment, soil association mapping, crop production measurements, wildlife resources, drought and desertification studies, ground-water exploration, watershed surveys, snow and ice monitoring, surface water mapping, and iceberg surveys. Future projects and developments are also briefly reviewed.

Mercanti, E. P.↗

A preliminary assessment of the feasibility of deriving liquid and gaseous fuels from grown and waste organics

The anticipated depletion of our resources of natural gas and petroleum in a few decades has caused a search for renewable sources of fuel. Among the possibilities is the chemical conversion of waste and grown organic matter into gaseous or liquid fuels. The overall feasibility of such a system is considered from the technical, economic, and social viewpoints. Although there are a number of difficult problems to overcome, this preliminary study indicates that this option could provide between 4 and 10 percent of the U.S. energy needs. Estimated costs of fuels derived from grown organic material are appreciably higher than today's market price for fossil fuel. The cost of fuel derived from waste organics is competitive with fossil fuel prices. Economic and social reasons will prohibit the allocation of good food producing land to fuel crop production.

Graham, R. W.↗

Benefit assessment of NASA space technology goals

The socio-economic benefits to be derived from system applications of space technology goals developed by NASA were assessed. Specific studies include: electronic mail; personal telephone communications; weather and climate monitoring, prediction, and control; crop production forecasting and water availability; planetary engineering of the planet Venus; and planetary exploration.

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An operational earth resources satellite system: The LANDSAT follow-on program

The LANDSATS 1 and 2 have demonstrated the role of remote sensing from satellite in research, development, and operational activities essential to the better management of our resources. Hundreds of agricultural, geological, hydrological, urban land use, and other investigations have raised the question of the development of an operational system providing continuous, timely data. The LANDSAT Follow-on Study addressed the economics, technological performance, and design of a system in transition from R and D to operations. Economic benefits were identified; and a complete system from sensors to the ultilization in forecasting crop production, oil and mineral exploration, and water resources management was designed.

Stroud, W. G.↗

An operational earth resources satellite system - The Landsat follow-on program

The Landsats 1 and 2 have demonstrated the role of remote sensing from satellite in research, development, and operational activities essential to the better management of our resources. Hundreds of agricultural, geological, hydrological, urban land use, and other investigations have raised the question of the development of an operational system providing continuous, timely data. The Landsat follow-on study addressed the economics, technological performance, and design of a system in transition from R&D to operations. Economic benefits were identified; and a complete system from sensors to the utilization in forecasting crop production, oil and mineral exploration, water resources management was designed. Benefits-to-costs ratio in present-worth dollars is at least 4:1.

Stroud, W. G.↗

Study of future world markets for agricultural aircraft

The future world market for US-manufactured agricultural aircraft was studied and the technology needs for foreign markets were identified. Special emphasis was placed on the developing country market, but the developed countries and the communist group were also included in the forecasts. Aircraft needs were projected to the year 2000 by a method which accounted for field size, crop production, treated area, productivity, and attrition of the fleet. A special scenario involving a significant shift toward aerial fertilization was also considered. An operations analysis was conducted to compare the relative application costs of various existing and hypothetical future aircraft. A case study was made of Colombia as an example of a developing country in which aviation is emerging as an important industry.

Gobetz, F. W.↗

Meteorological satellite data: A tool to describe the health of the world's agriculture

Local area coverage data acquired aboard the TIROS-N satellite family by the advanced very high resolution radiometer systems was examined to determine the agricultural information current. Albedo differences between channel 2 and channel 1 of the advanced very high resolution radiometer LAC (called EVI) are shown to be closely correlated to the Ashburn vegetative index produced from LANDSAT multispectral scanner data which have been shown to vary in response to "greenness", soil moisture, and crop production. The statistical correlation between the EVI and the Ashburn Vegetative Index (+ or - 1 deg) is 0.86.

Gray, T. I., Jr.↗