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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The impact of tritium phytoremediation on plant health as measured by fluorescence

Phytoremediation, using plants for soil, sediment, or water contaminant clean-up, is an established technology dependent on plant health. Tritium (3H), a radioactive isotope of hydrogen that is generally found in the environment as tritiated water (HTO), is a low-level beta emitter with a half-life of 12.32 years. Chlorophyll fluorescence (CF) for monitoring risk assessment of tritium to plant health was conducted at the Tritium Irrigation Facility (TIF) located on the US Department of Energy's Savannah River Site (SRS) near Aiken, SC. Two fluorometers were evaluated in conjunction with phytoremediation at the 25 –acre TIF where tritiated groundwater is being spray–irrigated on a mixed coniferous/deciduous forested watershed as a means of reducing tritium release to a nearby stream that serves as a tributary to the Savannah River. Tritium activity in irrigated water averaged 104 + 42 pCi mL -1 during the 2003 project. Fluorescence parameters measured by the two fluorometers were well correlated with each other (p < 0.0001). Tritium in water respired from oak leaves ranged up to 1845.13 pCi ml -1 and 2138.22 pCi ml -1 in pine needles. Trees in both the test and control sites were approximately 15 years old. In this report we demonstrated that fluorescence parameters provide an effective way to estimate the impact of HTO on plant health in a noninvasive, extremely rapid, and cost-effective manner. In the current study applying fluorometry, plants within the TIF phytoremediation site exposed to the site tritiated water were not significantly impacted by the tritium phytoremediation based on CF parameters as compared to the control, a nascent non-irrigated site.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

Molecular level characterization of wildfire aerosol induced changes to plant health and value

The potential impacts of wildfire smoke on plant health and value are of increasing concern, due both to increasing awareness, and more frequent wildfire events. Wildfires produce substantial amounts of atmospheric pollution in smoke and particulate matter which can travel thousands of miles. These smoke events can blanket entire agricultural regions and cause impacts to plant development. One notable example of this is ‘smoke taint’ in wine, where vines, exposed to smoke, absorb many small volatile phenolic (VP) compounds. These VPs can be metabolized (glycosylated) and transported throughout the plant. Later, during downstream processing (fermentation of the grape musts), these glycosylated VPs can be hydrolyzed to re-release and volatilize the aroma-active phenolic compounds. The final product, thus, smells of smoke. Despite the obvious commercial and general research interests here, the nature of wildfire impacts on plant health are incompletely understood. Using established metabolomics and organic matter (aerosol) characterization methods, the overall aim of this proposal is thus to study wildfire smoke impacts on plant health and value, in the context of a model system (V. vinifera). This project closed early, and this report reflects some of the limited work conducted prior to conclusions. Specifically, this report discusses some sample preparation and initial MALDI-mass spectrometry analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Enhanced transport of bacteria along root systems by protists can impact plant health

ABSTRACT Soil protists have been shown to contribute to the structure and function of the rhizosphere in a variety of ways. Protists are key contributors to nutrient cycling through the microbial loop, where biomass is digested by protists and otherwise stored nutrients are returned to the environment. Protists have also been shown to feed on plant pathogenic bacteria and alter root microbiomes in ways that may benefit plants. Recently, a mechanism involving bacterial transport, facilitated by protists, has been hypothesized to contribute to the spatial distribution of bacteria in the rhizosphere. Here, we observe the differential abilities of three soil protists: a ciliate (Colpodasp.), a flagellate (Cercomonassp.), and a naked amoeba (Acanthamoeba castellanii) to transport nitrogen-fixingSinorhizobium melilotito infectible root tips. Co-inoculation of protists plusS. melilotiresulted in the movement of bacteria, as measured by the presence of nitrogen-fixing nodules, up to 15 cm farther down the root systems when compared to plants inoculated withS. melilotialone. Co-inoculation of the ciliate, Colpodasp., withS. meliloti, resulted in shoot weights that were similar to plants that grew in nitrogen-replete potting mix.Colpodasp.-feeding style and motility likely contributed to their success at transporting bacteria through the rhizosphere. We observed that the addition of protists alone without the co-inoculum ofS. melilotiresulted in plants with larger shoot weights than control plants. Follow-up experiments showed that protists plus their associated microbiomes were aiding in plant health, likely through means of nutrient cycling. IMPORTANCE Protists represent a significant portion of the rhizosphere microbiome and have been shown to contribute to plant health, yet they are understudied compared to their bacterial and fungal counterparts. This study elucidates their role in the rhizosphere community and suggests a mechanism by which protists can be used to move bacteria along plant roots. We found that the co-inoculation of protists with nitrogen-fixing beneficial bacteria,Sinorhizobium meliloti, resulted in nodules farther down the roots when compared to plants inoculated with S.melilotialone, and shoot weights similar to plants that received nitrogen fertilizer. These data illustrate the ability of protists to transport viable bacteria to uninhabited regions of the root system.

Biotechnology & Applied Microbiology↗
DOE OSTI2020

Integration of Data Analytics with Plant System Health Program

This report summarizes the R&D activities of the Plant Health Management (PHM) project during fiscal year 2020 (FY20). This project focuses on the development of methods that integrate component health data and propagate such information at the system level to evaluate system sources of risk. This project development lives in cooperation with the Risk Informed Asset Management (RIAM) project. The RIAM project, in fact, uses the reliability models and data generated by the PHM project to optimize plant operations (e.g., maintenance/replacement schedule, optimal maintenance posture). This year’s activities for the PHM project focused mainly on the development of two classes of models. The first one includes a series of component reliability models which include aging, testing and maintenance. The second class includes a series of system reliability models which focus on the secondary side of exiting U.S. reactors. These models are based on fault tree logic structures such that they can be used by existing plant PRA software. We also started to focus on the management of health data and we tackled this issue in two directions. The first one focuses on the integration of monitor data with simulation models to assess component health. This approach is moving from a classical data based to a model+data based approach with the goal of improving higher component health information. The second direction focuses on linking equipment reliability data (e.g., maintenance/failure reports, component monitoring data) directly to system reliability models using a safety margin based language rather than a probability based language. The main advantage of a safety margin based language is that it can provide to system engineers more tangible information on system/component health and how it propagates to the system level.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Microbial Community Analysis & Functional Evaluation in Soils

The overall objective of this proposal was to develop technologies to alter the composition and function of important members of microbial communities. In particular, the overall objective of the microbial community editing portion of the proposal focuses on developing foundational tools and understanding required to predict, alter and design grass rhizosphere communities impacting DOE missions. Specifically, the project is centered on the Microbial Community Analysis & Functional Evaluation in Soils (m-CAFES) to manipulate microbial consortia associated with plants of interest for the bioenergy sector, under the presumption that bacterial communities can be manipulated to enhance plant health. For tasks of specific interest to us, we are focusing on developing novel Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) based technologies (primarily focusing on Aim 1) and their delivery modalities (notably subaim 1.2) to edit specific bacterial genomes of interest to enhance their functionalities, and programmably ablate specific undesirable members of bacterial communities for plant health. We are focusing on engineering bacteriophages (bacterial viruses, for subaim 1.2) to carry programmable CRISPR-Cas systems (subaim 1.1) to target (ablate) or alter (edit) genomes of interest. This will enable us to carry out microbial perturbations that will impact community composition and function and ultimately plant growth and health, to enable the next phase of the project by deploying them in situ (subaims 1.3 and 1.4).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Genetic determinants of endophytism in the Arabidopsis root mycobiome

The roots of Arabidopsis thaliana host diverse fungal communities that affect plant health and disease states. Here, we sequence the genomes of 41 fungal isolates representative of the A. thaliana root mycobiota for comparative analysis with other 79 plant-associated fungi. Our analyses indicate that root mycobiota members evolved from ancestors with diverse lifestyles and retain large repertoires of plant cell wall-degrading enzymes (PCWDEs) and effector-like small secreted proteins. We identify a set of 84 gene families associated with endophytism, including genes encoding PCWDEs acting on xylan (family GH10) and cellulose (family AA9). Transcripts encoding these enzymes are also part of a conserved transcriptional program activated by phylogenetically-distant mycobiota members upon host contact. Recolonization experiments with individual fungi indicate that strains with detrimental effects in mono-association with the host colonize roots more aggressively than those with beneficial activities, and dominate in natural root samples. Furthermore, we show that the pectin-degrading enzyme family PL1_7 links aggressiveness of endophytic colonization to plant health.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Social Evolution and Cheating in Plant Pathogens

Plant pathogens are a critical component of the microbiome that exist as populations undergoing ecological and evolutionary processes within their host. Many aspects of virulence rely on social interactions mediated through multiple forms of public goods, including quorum-sensing signals, exoenzymes, and effectors. Virulence and disease progression involve life-history decisions that have social implications with large effects on both host and microbe fitness, such as the timing of key transitions. Considering the molecular basis of sequential stages of plant–pathogen interactions highlights many opportunities for pathogens to cheat, and there is evidence for ample variation in virulence. Case studies reveal systems where cheating has been demonstrated and others where it is likely occurring. Harnessing the social interactions of pathogens, along with leveraging novel sensing and -omics technologies to understand microbial fitness in the field, will enable us to better manage plant microbiomes in the interest of plant health.

Plant Sciences↗
DOE OSTI2025

Rhizosphere Microbiome Diversity Potentially Supports Robust Nature of Field Pennycress ( Thlaspi arvense L.) in Dryland Cropping Systems of Eastern Washington

ABSTRACT Field pennycress ( Thlaspi arvense L.) is an annual in the Brassicaceae family and is currently being developed as an oilseed intermediate crop suitable for renewable biodiesel and jet fuel. It displays many desirable characteristics for this role including cold tolerance, a rapid life cycle, and a seed fatty acid profile conducive to bioenergy generation. These traits make field pennycress favorable for winter oilseed cultivation in the inland Pacific Northwest (iPNW). Simultaneously, intermediate crops are an increasingly recognized component of both agronomic sustainability and soil health management. Intermediate crops enhance soil microbial diversity, which benefits both soil and plant health. To understand the impact of field pennycress on soil microbial diversity, two natural accessions and seven experimental accessions were grown at three sites in Eastern Washington. Aboveground biomass and rhizosphere soil were then collected. Soil genomic DNA was extracted from rhizosphere samples and used to generate an amplicon library for bacterial (16S) and fungal (ITS) rRNA sequences. The resulting libraries were analyzed in QIIME2, which revealed that not only did the fad2 deficient line from the Spring32‐10 background have significantly increased aboveground biomass production compared to other pennycress genotypes, but also displayed significantly higher β‐diversity in the rhizosphere community specifically at the site experiencing the driest conditions. ANCOM analysis showed that multiple sequences similar to beneficial plant and soil health enhancing organisms such as Trichoderma spirale , Pseudomonas spp., and Methylobacterium goesingense were found to be enriched in the microbiome of the fad2 Spring32‐10 background also at that site. To add additional context to rhizosphere community data, root exudates from two pennycress genotypes were captured in magenta boxes and analyzed using HPLC. Future work will expand our understanding of the mechanisms by which field pennycress creates diversity in the rhizosphere, thus expanding our ability to cultivate this crop in the iPNW.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Causal Approach to Integrate Component Health Data into System Reliability Models

Two of the challenges of current plant reliability approaches are the ability to integrate plant health data, and to support decision making. Condition based data and diagnostic/prognostic information are in fact not considered into plant reliability models to inform system engineers on the most critical components. Currently, the propagation of quantitative health data from the component to the system level is a challenge given the diverse nature/structure of the data. On the other hand, plant reliability methods (which are typically based on fault-trees or reliability block diagrams) can effectively propagate data from the component to the system level, but values of failure rates or failure probabilities are an approximated integral representation of the past industry-wide operational experience, and it neglects the present component health status (e.g., diagnostic and condition-based data) and health projection (when available from prognostic data). Our first claim is that system reliability models should propagate health information from the component to the system/plant level in order to provide a quantitative snapshot of system/plant health and identify the most critical components. Our second claim is that component health should be informed solely by that specific component current and historical performance data and should not be an approximated integral representation of the past industry-wide operational experience. This paper is directly supporting these two claims by proposing a different approach to perform reliability modeling which relies on available component diagnostic, prognostic and condition-based data to measure component health, and it propagates this information through fault tree models. The propagation of health data from the component to the system level is performed not in terms of probability, but in terms of margins where margin is defined as the “distance” between the present actual status and an undesired event (e.g., failure or unacceptable performance). Through a cause-effect lens, while classical reliability models target the effect associated to a component performance, a margin-based approach focuses on the cause of an undesired component performance (i.e., component health). Hence, thinking of reliability in terms of margins implies decision making based on causal reasoning. We will show how fault tree models can be solved using a margin language and how this process can effectively assist system engineers to identify the most critical components.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Metabolic Interactions between Brachypodium and Pseudomonas fluorescens under Controlled Iron-Limited Conditions

Plant iron (Fe) nutritional status has a significant impact on rhizosphere microbial communities. While this effect has been attributed to alterations in the composition of root exudates, the underlying mechanisms are not known. Here, we investigated the effect of Fe deficiency on the interactions between the grass Brachypodium distachyon and the common soil bacteria Pseudomonas fluorescens SBW25. Increased phytosiderophore production was the most significant response of Brachypodium root exudation to Fe deficiency. We observed upregulated expression of phytosiderophore biosynthesis genes but lower accumulated exudate concentrations in the presence of Pseudomonas, indicating that the bacteria degrade these phytosiderophores. Pseudomonas did not produce endogenous siderophores under the low Fe conditions. Rather, the bacterial transcriptome revealed upregulation of four genes in response to Fe deficiency that contain motifs associated with cellular uptake of small molecules. Collectively, these results suggest that rhizosphere Pseudomonas fluorescens may take up phytosiderophores produced by grasses in response to Fe deficiency, and we propose target genes that may be involved. Our findings provide insight into the molecular basis for the exchange of C, N, and Fe between plants and bacteria under Fe deficient conditions. These interactions may contribute to differences in the rhizosphere microbial community structure across soil pH regimes.

Boiteau, Rene M.↗
DOE OSTI2020

New Transformer Testing Approach Reduces Reactor Down Time

The ATR-774 transformer yard has been in operation for 57 years. It's old, outdated, and reaching end of life. Plant health has decided to construct a new transformer yard, which will require testing. I've explored the standards library and compiled a list of tests that need to be performed on the transformer yard. This effort led to a significant speed-up in the testing process.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Uncovering the dominant role of root metabolism in shaping rhizosphere metabolome under drought in tropical rainforest plants

Plant-soil-microbe interactions are crucial for driving rhizosphere processes that contribute to metabolite turnover and nutrient cycling. With the increasing frequency and severity of water scarcity due to climate warming, understanding how plant-mediated processes, such as root exudation, influence soil organic matter turnover in the rhizosphere is essential. In this study, we used 16S rRNA gene amplicon sequencing, rhizosphere metabolomics, and position-specific 13 C-pyruvate labeling to examine the effects of three different plant species (Piper auritum, Hibiscus rosa sinensis, and Clitoria fairchildiana) and their associated microbial communities on soil organic carbon turnover in the rhizosphere. Here, our findings indicate that in these tropical plants, the rhizosphere metabolome is primarily shaped by the response of roots to drought rather than direct shifts in the rhizosphere bacterial community composition. Specifically, the reduced exudation of plant roots had a notable effect on the metabolome of the rhizosphere of P. auritum, with less reliance on neighboring microbes. Contrary to P. auritum, H. rosa sinensis and C. fairchildiana experienced changes in their exudate composition during drought, causing alterations to the bacterial communities in the rhizosphere. This, in turn, had a collective impact on the rhizosphere's metabolome. Furthermore, the exclusion of phylogenetically distant microbes from the rhizosphere led to shifts in its metabolome. Additionally, C. fairchildiana appeared to be associated with only a subset of symbiotic bacteria under drought conditions. These results indicate that plant species-specific microbial interactions systematically change with the root metabolome. As roots respond to drought, their associated microbial communities adapt, potentially reinforcing the drought tolerance strategies of plant roots. These findings have significant implications for maintaining plant health and preference during drought stress and improving plant performance under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Fire alters plant microbiome assembly patterns: integrating the plant and soil microbial response to disturbance

Summary It is increasingly evident that the plant microbiome is a strong determinant of plant health. While the ability to manipulate the microbiome in plants and ecosystems recovering from disturbance may be useful, our understanding of the plant microbiome in regenerating plant communities is currently limited. Using 16S ribosomal RNA (rRNA) gene and internal transcribed spacer (ITS) region amplicon sequencing, we characterized the leaf, stem, fine root, rhizome, and rhizosphere microbiome of < 1‐yr‐old aspen saplings and the associated bulk soil after a recent high‐intensity prescribed fire across a burn severity gradient. Consistent with previous studies, we found that soil microbiomes are responsive to fire. We extend these findings by showing that certain plant tissue microbiomes also change in response to fire. Differences in soil microbiome compositions could be attributed to soil chemical characteristics, but, generally, plant tissue microbiomes were not related to plant tissue elemental concentrations. Using source tracking modeling, we also show that fire influences the relative dominance of microbial inoculum and the vertical inheritance of the sapling microbiome from the parent tree. Overall, our results demonstrate how fire impacts plant microbiome assembly, diversity, and composition and highlights potential for further research towards increasing plant fitness and ecosystem recovery after fire events.

16rRNA↗
DOE OSTI2023

Benefits of symbiotic ectomycorrhizal fungi to plant water relations depend on plant genotype in pinyon pine

Rhizosphere microbes, such as root-associated fungi, can improve plant access to soil resources, affecting plant health, productivity, and stress tolerance. While mycorrhizal associations are ubiquitous, plant–microbe interactions can be species specific. Here we show that the specificity of the effects of microbial symbionts on plant function can go beyond species level: colonization of roots by ectomycorrhizal fungi (EMF) of the genus Geopora has opposite effects on water uptake, and stomatal control of desiccation in drought tolerant and intolerant genotypes of pinyon pine (Pinus edulis Engelm.). These results demonstrate, for the first time, that microorganisms can have significant and opposite effects on important plant functional traits like stomatal control of desiccation that are associated with differential mortality and growth in nature. They also highlight that appropriate pairing of plant genotypes and microbial associates will be important for mitigating climate change impacts on vegetation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Quantitative phenotyping of crop roots with spectral electrical impedance tomography: a rhizotron study with optimized measurement design

Background: Root systems are key contributors to plant health, resilience, and, ultimately, yield of agricultural crops. To optimize plant performance, phenotyping trials are conducted to breed plants with diverse root traits. However, traditional analysis methods are often labour-intensive and invasive to the root system, therefore limiting high-throughput phenotyping. Spectral electrical impedance tomography (sEIT) could help as a non-invasive and cost-efficient alternative to optical root analysis, potentially providing 2D or 3D spatio-temporal information on root development and activity. Although impedance measurements have been shown to be sensitive to root biomass, nutrient status, and diurnal activity, only few attempts have been made to employ tomographic algorithms to recover spatially resolved information on root systems. In this study, we aim to establish relationships between tomographic electrical polarization signatures and root traits of different fine root systems (maize, pinto bean, black bean, and soy bean) under hydroponic conditions. Results: Our results show that, with the use of an optimized data acquisition scheme, sEIT is capable of providing spatially resolved information on root biomass and root surface area for all investigated root systems. We found strong correlations between the total polarization strength and the root biomass (R 2 = 0.82) and root surface area (R 2 = 0.8). Our findings suggest that the captured polarization signature is dominated by cell-scale polarization processes. Additionally, we demonstrate that the resolution characteristics of the measurement scheme can have a significant impact on the tomographic reconstruction of root traits. Conclusion: Our findings showcase that sEIT is a promising tool for the tomographic reconstruction of root traits in high-throughput root phenotyping trials and should be evaluated as a substitute for traditional, often time-consuming, root characterization methods.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A plant genetic network for preventing dysbiosis in the phyllosphere

The aboveground parts of terrestrial plants, collectively called the phyllosphere, have a key role in the global balance of atmospheric carbon dioxide and oxygen. The phyllosphere represents one of the most abundant habitats for microbiota colonization. Whether and how plants control phyllosphere microbiota to ensure plant health is not well understood. Here we show that the Arabidopsis quadruple mutant (min7 fls2 efr cerk1; hereafter, mfec)1, simultaneously defective in pattern-triggered immunity and the MIN7 vesicle-trafficking pathway, or a constitutively activated cell death1 (cad1) mutant, carrying a S205F mutation in a membrane-attack-complex/perforin (MACPF)-domain protein, harbour altered endophytic phyllosphere microbiota and display leaf-tissue damage associated with dysbiosis. The Shannon diversity index and the relative abundance of Firmicutes were markedly reduced, whereas Proteobacteria were enriched in the mfec and cad1S205F mutants, bearing cross-kingdom resemblance to some aspects of the dysbiosis that occurs in human inflammatory bowel disease. Bacterial community transplantation experiments demonstrated a causal role of a properly assembled leaf bacterial community in phyllosphere health. Here, the pattern-triggered immune signalling, MIN7 and CAD1 are found in major land plant lineages and are probably key components of a genetic network through which terrestrial plants control the level and nurture the diversity of endophytic phyllosphere microbiota for survival and health in a microorganism-rich environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Predicting receptor-ligand pairing preferences in plant-microbe interfaces via molecular dynamics and machine learning

Microbiome assembly, structure, and dynamics significantly influence plant health. Secreted microbial signaling molecules initiate and mediate symbiosis by binding to structurally compatible plant receptors. For example, lipo-chitooligosaccharides (LCOs), produced by nitrogen-fixing rhizobial bacteria and various fungi, are recognized by plant lysin motif receptor-like kinases (LysM-RLKs), which activate the common symbiotic pathway. Accurately predicting these molecular interactions could reveal complementary signatures underlying the initial stages of endosymbiosis. Despite the breakthrough in protein-ligand structure prediction with deep learning-based tools, such as AlphaFold3, the large size and highly flexible nature of signaling compounds like LCOs present major challenges for detailed structural characterization and binding-affinity prediction. Typical structure-/physics-based methods of ligand virtual screening are designed for small, drug-like molecules, often rely on high-resolution, experimentally determined structures of the protein receptors, and rarely achieve sufficient sampling to obtain converged thermodynamic quantities with large ligands. In this study, we developed a hybrid molecular dynamics/machine learning (MD/ML) approach capable of predicting binding affinity rankings with high accuracy in systems involving large, flexible ligands, despite limited experimental structural information. Using coarse initial structural models, the predictions using the MD/ML workflow achieved strong alignment with experimental trends, particularly in the top-affinity tier for four legume LysM-RLKs (LYR3) binding to LCOs and a chitooligosaccharide. Furthermore, the MD-based conformation selection protocol provided critical structural insights into substrate specificity and binding mechanisms. This study demonstrates a powerful method to screen for challenging cognate ligand-receptors and advance our understanding of the molecular basis of microbial colonization in plants.

Lipo-chitooligosaccharides↗
DOE OSTI2025

Hyperspectral segmentation of plants in fabricated ecosystems

Hyperspectral imaging provides a powerful tool for analyzing above-ground plant characteristics in fabricated ecosystems, offering rich spectral information across diverse wavelengths. This study presents an efficient workflow for hyperspectral data segmentation and subsequent data analytics, minimizing the need for user annotation through the use of ensembles of sparse mixed scale convolution neural networks. The segmentation process leverages the diversity of ensembles to achieve high accuracy with minimal labeled data, reducing labor-intensive annotation efforts. To further enhance robustness, we incorporate image alignment techniques to address spatial variability in the dataset. Downstream analysis focuses on using the segmented data for processing spectral data, enabling monitoring of plant health. This approach provides a scalable solution for spectral segmentation, and facilitates actionable insights into plant conditions in complex, controlled environments. Our results demonstrate the utility of combining advanced machine learning techniques with hyperspectral analytics for high-throughput plant monitoring.

Zwart, Petrus H.↗