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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Coupling localized Noah-MP-Crop model with the WRF model improved dynamic crop growth simulation across Northeast China

Croplands play a critical role in regulating the energy and moisture exchanges between the land surface and atmosphere. However, the interactions between cropland and climate are usually poorly represented due to a lack of detailed representation in crop types and field management. Here, we coupled the Noah-MP-Crop model with the state-of-the-art Weather Research and Forecasting (WRF) model to explore and evaluate the crop growth dynamics in response to climate variations across Northeast China. The default parameters of the crop model were not exactly suitable for the agricultural ecosystems in Northeast China. The detailed cropland distribution, and crop phenology parameters including growing degree days (GDD) and planting (harvesting) date were first created using multi-source remote sensing products and reanalysis data, and was then successfully used to simulate the growth and yield for corn and soybean and associated energy exchanges. We also optimized and calibrated other crop parameters using the time-series of the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface products. The modified crop model substantially improved the simulation of crop growth, plant physiology, and biomass accumulation for both corn and soybean. Coupling the localized dynamic crop model into the WRF led to considerable decreases in the simulated mean-absolute-errors (MAEs) and biases of the leaf area index, evapotranspiration, and gross primary production compared with the MODIS observed values. Compared with the statistical yield from each province, the modified crop model underestimated the corn yield from 11.1% to 48.6%, whereas overestimated the soybean yield from 16.5% to 162.6%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Analysis of the cyanobacterial amino acid metabolism with a precise genome-scale metabolic reconstruction of Anabaena sp. UTEX 2576

Filamentous cyanobacteria such as Anabaena sp. UTEX 2576 (a.k.a., Nostoc sp. PCC 7120) are a sustainable platform for commodity and specialty chemical production. Anabaena is a model cyanobacterium adopted to study production of nitrogen-containing metabolites useful for chemical, cosmetic, and pharmaceutical industries. Therefore, a precise description of the Anabaena metabolic network is desired to analyze their amino-acid metabolism and elucidate potential applications of these cyanobacteria as host organisms for biotechnological production. Secondary metabolite production depends on the metabolic availability of amino acids. We provide new insight on the biotechnological utilization of Anabaena after predicting phycocyanobilin and amino-acid production rates, using a genome-scale metabolic model (iDN1004). This metabolic reconstruction is a highly comprehensive representation of the global metabolism of Anabaena, which also contains experimental biomass equations and constraints under photoautotrophic and photodiazotrophic growth. Modelling results ranked proteinogenic amino acids based on predicted metabolic fluxes through amino-acid producing reactions. From these, l-aspartate, glycine, l-serine, l-valine, l-alanine, l-threonine, and l-leucine were selected as the best branching points to conduct metabolic engineering, where l-aspartate, l-serine, l-valine and glycine serve as potential precursors of the secondary metabolites Schizokinen (a siderophore), Sphingosine (a ceramide), Lyngbyatoxin A (an alkaloid), and Shinorine (a sunscreen).

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2022

An Evaluation of Biomass Burning Aerosol Mass, Extinction, and Size Distribution in Geos Using Observations From Camp2EX

Biomass burning aerosol impacts aspects of the atmosphere and Earth system through radiative forcing, serving as cloud condensation nuclei, and air quality. Despite its importance, the representation of biomass burning aerosol is not always accurate in numerical weather prediction and climate models or reanalysis products. Using observations collected as part of the Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) in August through October of 2019, aerosol concentration and optical properties are evaluated within the Goddard Earth Observing System (GEOS) and its underlying aerosol module, GOCART. In the operational configuration, GEOS assimilates aerosol optical depth observations at 550 nm to constrain aerosol fields. Particularly for biomass burning aerosol, without the assimilation of aerosol optical depth, aerosol extinction is underestimated compared to observations collected in the Philippines region during the CAMP2Ex campaign. The assimilation process adds excessive amounts of carbon to account for the underestimated extinction, resulting in positive biases in the mass of black and organic carbon, especially within the boundary layer, relative to in situ observations from the Langley Aerosol Research Group Experiment. Counteracting this, GEOS is deficient in sulphate and nitrate aerosol just above the boundary layer. Aside from aerosol mass, extinction within GEOS is a function of ambient relative humidity and an assumed particle size distribution. The relationship between dry and ambient extinction in GEOS reveals that hygroscopic growth is too aggressive within the model for biomass burning aerosol. An additional concern lies in the assumed particle size distribution for GEOS, which has a mode radius that is too small for organic carbon. Variability in the observed particle size distribution for biomass burning aerosol within a single flight also illuminates the fact that a single assumed particle size distribution is not sufficient and that for a proper representation, a more advanced aerosol module with GEOS may be necessary.

Aerosol Mass↗
NASA NTRS2015

Regional Rates of Young US Forest Growth Estimated From Annual Landsat Disturbance History and IKONOS Stereo Imagery

Forests of the Contiguous United States (CONUS) have been found to be a large contributor to the global atmospheric carbon sink. The magnitude and nature of this sink is still uncertain and recent studies have sought to define the dynamics that control its strength and longevity. The Landsat series of satellites has been a vital resource to understand the long-term changes in land cover that can impact ecosystem function and terrestrial carbonstock. We combine annual Landsat forest disturbance history from 1985 to 2011 with single date IKONOS stereoimagery to estimate the change in young forest canopy height and above ground live dry biomass accumulation for selected sites in the CONUS. Our approach follows an approximately linear growth rate following clearing over short intervals and does not estimate the distinct non-linear growth rate over longer intervals.We produced canopy height models by differencing digital surface models estimated from IKONOS stereo pairs with national elevation data (NED). Correlations between height and biomass were established independently using airborne LiDAR, and then applied to the IKONOS-estimated canopy height models. Graphing current biomass against time since disturbance provided biomass accumulation rates. For 20 study sites distributed across five regions of the CONUS, 19 showed statistically significant recovery trends (p is less than 0.001) with canopy growth from 0.26 m yr-1to 0.73 m yr-1. Above ground live dry biomass (AGB) density accumulation ranged from 1.31 t/ha yr-1 to 12.47 t/ha yr-1. Mean forest AGB accumulationwas 6.31 t/ha yr-1 among all sites with significant growth trends. We evaluated the accuracy of our estimates by comparing to field estimated site index curves of growth, airborne LiDAR data, and independent model predictions of C accumulation. Growth estimates found with this approach are consistent with site index curves and total biomass estimates fall within the range of field estimates. This is aviable approach to estimate forest biomass accumulation in regions with clear-cut harvest disturbances.

Neigh, Christopher S. R.↗
NASA NTRSDate not supplied

Evaluation of GEOS Aerosols Using CAMP2Ex Observations

Biomass burning aerosol impacts aspects of the atmosphere and Earth system through direct and semi-direct effects, as well as influencing air quality. Despite its importance, the representation of biomass burning aerosol is not always accurate in numerical weather prediction and climate models or reanalysis products. Using observations collected as part of the Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) in August through October of 2019, aerosol concentration and optical properties are evaluated within the Goddard Earth Observing System (GEOS) and its underlying aerosol module, GOCART. In the operational configuration, GEOS assimilates aerosol optical depth observations at 550 nm from AERONET and MODIS to constrain aerosol fields. Particularly for biomass burning aerosol, without the assimilation of aerosol optical depth, aerosol extinction is underestimated compared to observations collected in the Philippines region during the CAMP2Ex campaign. The assimilation process adds excessive amounts of carbon to account for the underestimated extinction, resulting in positive biases in the mass of black and organic carbon, especially within the boundary layer, relative to in situ observations from the Langley Aerosol Research Group Experiment. Counteracting this, GEOS is deficient in sulfate and nitrate aerosol just above the boundary layer. Aerosol extinction within GEOS is a function of the mass of different aerosol species, the ambient relative humidity, the assumed spectral optical properties, and particle size distribution per species. The relationship between dry and ambient extinction in GEOS reveals that hygroscopic growth is too high within the model for biomass burning aerosol. An additional concern lies in the assumed particle size distribution for GEOS, which has a single mode radius that is too small for organic carbon. Variability in the observed particle size distribution for biomass burning aerosol within a single flight also illuminates the fact that a single assumed particle size distribution is not sufficient and that for a proper representation, a more advanced aerosol module within GEOS may be necessary.

Allison Collow↗
DOE OSTI2023

Controlling circuitry underlies the growth optimization of Saccharomyces cerevisiae

Microbial growth emerges from coordinated synthesis of various cellular components from limited resources. In Saccharomyces cerevisiae, cyclic AMP (cAMP)-mediated signaling is shown to orchestrate cellular metabolism; however, it remains unclear quantitatively how the controlling circuit drives resource partition and subsequently shapes biomass growth. Here we combined experiment with mathematical modeling to dissect the signaling-mediated growth optimization of S. cerevisiae. We showed that, through cAMP-mediated control, the organism achieves maximal or nearly maximal steady-state growth during the utilization of multiple tested substrates as well as under perturbations impairing glucose uptake. However, the optimal cAMP concentration varies across cases, suggesting that different modes of resource allocation are adopted for varied conditions. Under settings with nutrient alterations, S. cerevisiae tunes its cAMP level to dynamically reprogram itself to realize rapid adaptation. Moreover, to achieve growth maximization, cells employ additional regulatory systems such as the GCN2-mediated amino acid control. This study establishes a systematic understanding of global resource allocation in S. cerevisiae, providing insights into quantitative yeast physiology as well as metabolic strain engineering for biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Data for Controlling Circuitry Underlies the Growth Optimization of Saccharomyces cerevisiae

Microbial growth emerges from coordinated synthesis of various cellular components from limited resources. In Saccharomyces cerevisiae , cyclic AMP (cAMP)-mediated signaling is shown to orchestrate cellular metabolism; however, it remains unclear quantitatively how the controlling circuit drives resource partition and subsequently shapes biomass growth. Here we combined experiment with mathematical modeling to dissect the signaling-mediated growth optimization of S. cerevisiae . We showed that, through cAMP-mediated control, the organism achieves maximal or nearly maximal steady-state growth during the utilization of multiple tested substrates as well as under perturbations impairing glucose uptake. However, the optimal cAMP concentration varies across cases, suggesting that different modes of resource allocation are adopted for varied conditions. Under settings with nutrient alterations, S. cerevisiae tunes its cAMP level to dynamically reprogram itself to realize rapid adaptation. Moreover, to achieve growth maximization, cells employ additional regulatory systems such as the GCN2-mediated amino acid control. This study establishes a systematic understanding of global resource allocation in S. cerevisiae , providing insights into quantitative yeast physiology as well as metabolic strain engineering for biotechnological applications.

Conversion↗
DOE OSTI2023

Constraining long‐term model predictions for woody growth using tropical tree rings

The strength and persistence of the tropical carbon sink hinges on the long-term responses of woody growth to climatic variations and increasing CO 2 . However, the sensitivity of tropical woody growth to these environmental changes is poorly understood, leading to large uncertainties in growth predictions. Here, we used tree ring records from a Southeast Asian tropical forest to constrain ED2.2-hydro, a terrestrial biosphere model with explicit vegetation demography. Specifically, we assessed individual-level woody growth responses to historical climate variability and increases in atmospheric CO 2 (C a ). When forced with historical C a , ED2.2-hydro reproduced the magnitude of increases in intercellular CO 2 concentration (a major determinant of photosynthesis) estimated from tree ring carbon isotope records. In contrast, simulated growth trends were considerably larger than those obtained from tree rings, suggesting that woody biomass production efficiency (WBPE = woody biomass production:gross primary productivity) was overestimated by the model. The estimated WBPE decline under increasing C a based on model-data discrepancy was comparable to or stronger than (depending on tree species and size) the observed WBPE changes from a multi-year mature-forest CO 2 fertilization experiment. In addition, we found that ED2.2-hydro generally overestimated climatic sensitivity of woody growth, especially for late-successional plant functional types. The model-data discrepancy in growth sensitivity to climate was likely caused by underestimating WBPE in hot and dry years due to commonly used model assumptions on carbon use efficiency and allocation. To our knowledge, this is the first study to constrain model predictions of individual tree-level growth sensitivity to C a and climate against tropical tree-ring data. Our results suggest that improving model processes related to WBPE is crucial to obtain better predictions of tropical forest responses to droughts and increasing C a . Finally, more accurate parameterization of WBPE will likely reduce the stimulation of woody growth by C a rise predicted by biosphere models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Increased microbial growth, biomass, and turnover drive soil organic carbon accumulation at higher plant diversity

Species-rich plant communities have been shown to be more productive and to ­exhibit increased long-term soil organic carbon (SOC) storage. Soil microorganisms are central to the conversion of plant organic matter into SOC, yet the relationship between plant diversity, soil microbial growth, turnover as well as carbon use efficiency (CUE) and SOC accumulation is unknown. As heterotrophic soil microbes are primarily carbon limited, it is important to understand how they respond to increased plant-derived carbon inputs at higher plant species richness (PSR). We used the long-term grassland biodiversity experiment in Jena, Germany, to examine how microbial physiology responds to changes in plant diversity and how this affects SOC content. The Jena Experiment considers different numbers of species (1–60), functional groups (1–4) as well as functional identity (small herbs, tall herbs, grasses, and legumes). We found that PSR accelerated microbial growth and turnover and increased microbial biomass and necromass. PSR also accelerated microbial respiration, but this effect was less strong than for microbial growth. In contrast, PSR did not affect microbial CUE or biomass-specific respiration. Structural equation models revealed that PSR had direct positive effects on root biomass, and thereby on microbial growth and microbial biomass carbon. Finally, PSR increased SOC content via its positive influence on microbial biomass carbon. We suggest that PSR favors faster rates of microbial growth and turnover, likely due to greater plant productivity, resulting in higher amounts of microbial biomass and necromass that translate into the observed increase in SOC. We thus identify the microbial mechanism linking species-rich plant communities to a carbon cycle process of importance to Earth's climate system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Water Temperature, Prey Concentration and Salmonid Density Influence Daily Growth of Wild Juvenile Salmonids in Tributaries of the Upper Salmon River, Idaho ( USA )

ABSTRACT Theory, experiments and field studies indicate that the somatic growth rate of freshwater consumers is shaped by the individual, additive and multiplicative effects of multiple factors, including consumer size and condition, temperature, prey resources and biotic interactions. While our understanding of how these factors affect wild populations of freshwater consumers is improving, the topic remains poorly studied, especially with respect to mobile species. Here, we report on an 8‐year, seven‐stream ( n = 49 stream‐year combinations) observational study examining the individual and interactive effects of invertebrate prey concentration (F, mg/m 3 ), mean daily water temperature (T, °C) and juvenile Chinook salmon ( Oncorhynchus tshawytscha ) density (D, fish/100 m 2 ) on summer daily growth rates (%/d) of mobile, anadromous, juvenile Chinook salmon (age‐0+, n = 382) and sub‐yearling (age‐0+, n = 61) and yearling (age‐1+) steelhead trout ( O. mykiss , n = 70) rearing in cold (mean daily summer: 12.1°C, range: 4.2°C–16.7°C) mountain tributaries of the Salmon River basin in central Idaho (USA). AIC c model selection indicated that daily juvenile salmonid growth positively correlated with water temperature, prey biomass concentration, local juvenile Chinook density and the interaction between water temperature and food but with species and age‐specific differences. Water temperature was a covariate in all top‐ranked models, with daily growth (%/day) rate increasing (0.05%–0.23%/d) linearly with mean daily summer water temperature. In addition to a direct positive relationship with daily growth rate, there was evidence that prey concentration positively interacted with water temperature to accelerate daily growth (F × T). The positive relationship between juvenile salmonid daily growth rate and juvenile Chinook density is difficult to explain and could result from confounding factors. The individual success observed in these streams may contribute to population‐level benefits for the focal consumers, as prey‐rich, warm summers may result in larger individuals with higher energy reserves at the end of the summer/autumn growing season, contributing to improved overwinter survival. Our results, taken in combination with evidence from models, experiments and observational studies, have climate change implications. Current and predicted increases in water temperature will necessitate higher rates of prey consumption by aquatic ectothermic consumers to offset accelerated metabolic demands. Thus, to improve the resilience of mobile freshwater consumers in a warming climate, we suggest that natural resource managers not only consider physical and chemical habitat conditions but also biotic conditions, including the spatiotemporal quantity and quality of prey resources.

Kiffney, Peter. M. [Fish Ecology, Northwest Fisher↗
NASA NTRS1997

Characterization of Proteins in Filtrate from Biodegradation of Crop Residue

Biodegradation of plant biomass is a feasible path for transformation of crop residue and recycling of nutrients for crop growth. The need to model the effects of factors associated with recycling of plant biomass resulting from hydroponic sweet potato production has led to investigation of natural soil isolates with the capacity for starch hydrolysis. This study sought to use nondenaturing gel electrophoresis to characterize the proteins present in filtered effluent from bioreactors seeded with starch hydrolyzing bacterial culture used in the biodegradation of senesced sweet potato biomass. The study determined the relative molecular weight of proteins in sampled effluent and the protein banding pattern was characterized. The protein profiles of effluent were similar for samples taken from independent runs under similar conditions of starch hydrolysis. The method can be used as a quality control tool for confirmation of starch hydrolysis of crop biomass. In addition, this method will allow monitoring for presence of contaminants within the system-protein profiles indicative of new enzymes in the bioreactors.

Horton, Wileatha↗
DOE OSTI2024

Cyanobacteria newly isolated from marine volcanic seeps display rapid sinking and robust, high-density growth

Cyanobacteria are photosynthetic organisms that play important roles in carbon cycling and are promising bioproduction chassis. Here, we isolate two novel cyanobacteria with 4.6Mbp genomes, UTEX 3221 and UTEX 3222, from a unique marine environment with naturally elevated CO₂. We describe complete genome sequences for both isolates and, focusing on UTEX 3222 due to its planktonic growth in liquid, characterize biotechnologically relevant growth and biomass characteristics. UTEX 3222 outpaces other fast-growing model strains on a solid medium. It can double every 2.35 hours in a liquid medium and grows to high density (>31 g/L biomass dry weight) in batch culture, nearly double that of Synechococcus sp. PCC 11901, whose high-density growth was recently reported. In addition, UTEX 3222 sinks readily, settling more quickly than other fast-growing strains, suggesting favorable economics of harvesting UTEX 3222 biomass. These traits may make UTEX 3222 a compelling choice for marine carbon dioxide removal (CDR) and photosynthetic bioproduction from CO₂. Overall, we find that bio-prospecting in environments with naturally elevated CO₂ may uncover novel CO₂-metabolizing organisms with unique characteristics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A novel semi-structured kinetic model of methanotroph-photoautotroph cocultures for biogas conversion

Through metabolic coupling of methane oxidation and oxygenic photosynthesis, methanotroph-photoautotroph (M-P) cocultures offer a highly promising technology platform for biogas conversion. However, there has not been any quantitative modeling of the coculture growth kinetics. This is mainly due to the inherent difficulty associated with real time characterization of the M-P cocultures and the complex interactions such as the cross-feeding mechanism within the coculture. To address this challenge, we recently developed a novel experimental-computational (E-C) protocol to accurately characterize the M-P coculture in real-time, and validated its accuracy through cell counting. Enabled by the E-C protocol, this work presents the very first kinetic model for M-P cocultures. By explicitly modeling the exchange of in situ produced O 2 /CO 2 within the M-P coculture and coupling the individual biomass growth with mass transfer between the gas and liquid phases, the semi-structured kinetic model accurately predicts the growth dynamics of the M-P coculture under a wide range of growth conditions. The proposed model is validated by a series of wet-lab experiments using Methylomicrobium buryatense 5GB1 - Arthrospira platensis as the model coculture. Although it has been speculated that there may exist other emergent metabolic interactions within the M-P coculture, in addition to the exchange of in situ produced O 2 /CO 2 , there has not been any experimental validation prior to this study. By integrating designed experiments with the semi-structured kinetic model, this study is the first to confirm the existence of the additional emergent metabolic exchanges within the coculture. Furthermore, this study further quantifies the effect of these unknown metabolic interactions on the growth of both species in the model coculture, supporting further research to identify these exchanged metabolites for metabolic engineering.

42 ENGINEERING↗
DOE OSTI2024

Representing cropping systems with the MEMS 2 ecosystem model

Abstract Croplands have been the focus of substantial investigation due to their considerable potential for sequestering carbon. Understanding the potential for soil organic carbon (SOC) sequestration and necessary management strategies will be enabled with accurate process‐based models. Accurately representing crop growth and agricultural practices will be critical for realistic SOC modeling. The MEMS 2 model incorporates a current understanding of SOC formation and stabilization, measurable SOC pools, and deep SOC dynamics and is seen as a highly promising tool to inform management intervention for SOC sequestration. Thus far, MEMS 2 has been developed to represent grasslands. In this study, we further developed MEMS 2 to model annual grain crops and common agricultural practices, such as irrigation, fertilization, harvesting, and tillage. Using four Ameriflux sites, we demonstrated an accurate simulation of crop growth and development. Model performance was strong for simulating aboveground biomass (index of agreement [d] range of 0.89–0.98) and green leaf area index (dfrom 0.90 to 0.96) across corn, soybean, and winter wheat. Good agreement with observations was also achieved for net ecosystem CO 2 exchange (dfrom 0.90 to 0.96), evapotranspiration (dfrom 0.91 to 0.94), and soil temperature (dof 0.96), while discrepancy with the available soil water content data remain (dfrom 0.14 to 0.81 at four depths to 100 cm). While we will continue model testing and improvement, MEMS 2 (version 2.14) has now demonstrated its ability to effectively simulate the growth of common grain crops and practices.

Agriculture↗
DOE OSTI2022

A Macroalgal Cultivation Modeling System (MACMODS): Evaluating the Role of Physical-Biological Coupling on Nutrients and Farm Yield

Offshore aquaculture has the potential to expand the macroalgal industry. However, moving into deeper waters requires suspended structures that will present novel farm-environment interactions. Here, we present a computational modeling framework, the Macroalgal Cultivation Modeling System (MACMODS), to explore within-farm modifications to light, seawater flow, and nutrient fields across time and space scales relevant to macroalgae. A regional ocean model informs the site-specific setting, the Santa Barbara Channel in the Southern California Bight. A fine-scale hydrodynamic model predicts modified flows and turbulent mixing within the farm. A spatially resolved macroalgal growth model, parameterized for giant kelp, Macrocystis pyrifera , predicts kelp biomass. Key findings from model integration are that regional ocean conditions set overall farm performance, while fine-scale within-farm circulation and nutrient delivery are important to resolve variation in within-farm macroalgal performance. Therefore, we conclude that models resolving within-farm dynamics can provide benefit to farmers with insight on how farm design and regional ocean conditions interact to influence overall yield. Here, the presence of repeating longlines aligned with the mean current generate flow diversions around the farm as well as attached Langmuir circulations and increased turbulence intensity. These flow-induced phenomena lead to less biomass in the interior portion of the farm relative to the edges. We also find that there is an effluent “footprint” that extends as much as 20 km beyond the farm. In this regard, MACMODS can be used to not only evaluate farm design and cultivation practices that maximize yield but also explore interactions between the farm and ecosystem in order to minimize impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Development of a kinetic model to describe six types of symbiotic interactions in a formate utilizing microalgae-bacteria cultivation system

This study investigated an algae/formate-utilizing-bacteria system that has been developed for carbon capture. This photomixotrophic consortium consumed formate to support bacterial growth so that the resulting respiration CO 2 could be simultaneously used by algae to avoid CO 2 gas-lipid mass transfer limitation. To understand biomass growth and population interactions in this unique system, a kinetic model has been developed to describe algae and bacteria multiplication, formate and nitrogen utilizations, CO 2 mass transfer, O 2 generation and consumption, lighting condition and shading effect. The simulation indicated that this ecosystem could form six types of interactions (mutualism, commensalism, parasitism, neutralism, amensalism, and competition) depending on the light intensity and nutrient availability. Furthermore, the simulation of both batch culture and chemostat, along with parameter sensitivity tests and experimental observations, offered insights into optimal applications of algae-bacteria consortium based photobiorefinery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Microbial maintenance energy quantified and modeled with microcalorimetry

Refining the energetic costs of cellular maintenance is essential for predicting microbial growth and survival in the environment. In this work, we evaluate a simple batch culture method to quantify energy partitioning between growth and maintenance using microcalorimetry and thermodynamic modeling. The constants derived from the batch culture system were comparable to those that have been reported from meta-analyses of data derived from chemostat studies. The model accurately predicted temperature-dependent biomass yield and the upper temperature limit of growth for Desulfovibrio alaskensis G20, suggesting the method may have broad application. An Arrhenius temperature dependence for the specific energy consumption rate, inferred from substrate consumption and heat evolution, was observed over the entire viable temperature range. By combining this relationship for specific energy consumption rates and observed specific growth rates, the model describes an increase in nongrowth associated maintenance at higher temperatures and the corresponding decrease in energy available for growth. This analytical and thermodynamic formulation suggests that simply monitoring heat evolution in batch culture could be a useful complement to the recognized limitations of estimating maintenance using extrapolation to zero growth in chemostats.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1983

A mathematical model for crop spectral-temporal trajectories based on a plant growth model

The Kubelka-Munk radiative transfer model is combined with an approximation of Kauth-Thomas greeness and brightness transforms to derive approximate closed form expressions for crop greeness and brightness surrogates in terms of canopy biomass. The greeness relation derived resembles an existing empirical relation between leaf area index and greeness. A simple growth model based on interception and utilization of photosynthetically active radiation is developed and used to describe the time evolution of greeness and brightness. The model developed does not yet yield definitive profile calculations but suggests a conceptual framework which may be found useful for further profile analysis.

Woolford, T. L.↗