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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Structure property correlations in wet-spun textile PAN fibers for cost-effective carbon fibers applicable in H 2 storage tank manufacturing

The economic viability of high-strength carbon fibers is pivotal for their integration into Type IV compressed hydrogen storage tanks. Oak Ridge National Laboratory is advancing this objective by developing cost-effective, textile-grade polyacrylonitrile (PAN) precursor fibers through an optimized wet spinning-process to garner more microstructural control over the precursor fibers. Here, this study examines the microstructural characteristics of PAN fibers, particularly the crystalline orientation factor, and their impact on mechanical properties in both precursor and thermally converted carbon fibers (CFs). Three wet-spun PAN fibers, all having diameters of 12-13 µm but varying orientation factors were assessed. Comprehensive characterization using X-ray scattering and microscopy revealed that fibers with higher orientation factors exhibited enhanced crystallinity and optimized crystallite sizes. Mechanical testing demonstrated that the PAN fiber with the highest orientation factor achieved the greatest tensile strength (98 ksi) and modulus (1.60 Msi). Additionally optical and scanning electron microscopy confirmed smooth and defect-free surfaces across all samples. These findings indicate that manipulating spinning parameters to maximize orientation factor is more impactful in achieving high strength and modulus over factors attributed to crystallinity and crystallite sizes. Here, highest performing CFs, thermally processed in lab from textile-grade precursor averaged 558 ksi, a 10% increase over previous results.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Building Structure-Property Relationships of Cycloalkanes in Support of Their Use in Sustainable Aviation Fuels

In 2018 13.7 EJ of fuel were consumed by the global commercial aviation industry. Worldwide, demand will increase into the foreseeable future. Developing Sustainable Aviation Fuels (SAFs), with decreased CO 2 and soot emissions, will be pivotal to the on-going mitigation efforts against global warming. Minimizing aromatics in aviation fuel is desirable because of the high propensity of aromatics to produce soot during combustion. Because aromatics cause o-rings to swell, they are important for maintaining engine seals, and must be present in at least 8 vol% under ASTM-D7566. Recently, cycloalkanes have been shown to exhibit some o-ring swelling behavior, possibly making them an attractive substitute to decrease the aromatic content of aviation fuel. Cycloalkanes must meet specifications for a number of other physical properties to be compatible with jet fuel, and these properties can vary greatly with the cycloalkane chemical structure, making their selection difficult. Building a database of structure-property relationships (SPR) for cycloalkanes greatly facilitates their furthered inclusion into aviation fuels. The work presented in this paper develops SPRs by building a data set that includes physical properties important to the aviation industry. The physical properties considered are energy density, specific energy, melting point, density, flashpoint, the Hansen solubility parameter, and the yield sooting index (YSI). Further, our data set includes cycloalkanes drawn from the following structural groups: fused cycloalkanes, n-alkylcycloalkanes, branched cycloalkanes, multiple substituted cycloalkanes, and cycloalkanes with different ring sizes. In addition, a select number of cycloalkanes are blended into Jet-A fuel (POSF-10325) at 10 and 30 wt%. Comparison of neat and blended physical properties are presented. One major finding is that ring expanded systems, those with more than six carbons, have excellent potential for inclusion in SAFs. Our data also indicate that polysubstituted cycloalkanes have higher YSI values.

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

Effect of Moisture and Feedstock Variability on the Rheological Behavior of Corn Stover Particles

Continuous feeding, processing, and handling of biomass powders is pivotal to the economic viability of integrated biorefineries. However, current challenges associated with the operational reliability of bulk solids handling and transport greatly impact the process economics and ultimately the widespread commercialization of integrated biorefineries. In this work, we examine the effect of moisture and feedstock variability on the flow behavior of corn stover biomass particles. The total flow energy, compressibility, shear properties, and wall friction angles were measured for corn stover samples A and B containing 0%, 15%, 25%, 50%, and 75% (mass fraction) moisture contents using a FT4 powder rheometer. In general, the flowability of both A and B was reduced when moisture was present as indicated by the stability and variable flow rate, compressibility, and shear tests. The 15% moisture sample had the highest flow energy, revealing the interplay between the increased surface tension and looser packing both of which were caused by liquid bridging. The 75% moisture sample had the highest compressibility and the lowest flowability factor (ff c ). The trend in wall friction angle was found to be dependent upon the surface hydrophobicity of the wall material. The wall friction angle on the hydrophilic, stainless-steel surface increased with moisture and therefore poses additional handling challenges. On the other hand, the wall friction angle on the hydrophobic polymer surfaces were the lowest for samples with intermediate moisture contents. Sample B had greater bulk density, smaller compressibility, and greater flowability than the sample A , as suggested by the compressibility and shear tests. The wall friction angle of sample B was higher than or equal to that of sample A depending on both the type and the surface roughness of the wall material.

09 BIOMASS FUELS↗
DOE OSTI2022

Editorial: Lignocellulose valorization: Fractionation, conversion and applications

Lignocellulosic biomass is the most abundant form of renewable feedstock on the Earth. Chemicals, energies, and materials derived from lignocellulosic biomass are renewable and sustainable, and have the potential to replace fossil feedstocks. Biorefinery, a process to fractionate lignocellulose into the three major components, is considered the most pivotal step for bioenergy, biomaterials and biochemicals. However, due to the complex hierarchy and chemical structures, only limited lignocellulose is valorized into value-added products, and most of them are burnt or just discarded. Therefore, there is a need to investigate the heterogeneous structure of lignocellulose, improve its efficient fractionation into cellulose, hemicelluloses and lignin, and develop the technology that can convert the lignocellulose into high-value chemical products and high-performance functional materials in a sustainable and promising configuration. In short, the ultimate goal of biomass utilization is that the production of biofuels and biomaterials in industrial applications must be cost-, and performance-competitive with petroleum-derived equivalents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Geochemistry and metagenomics analyses of bacterial community structure in selected waste dumpsites in Lagos Metropolis, Nigeria

Dumpsites are reservoirs of persistent organic pollutants (POPs) and heavy metals (HMs), constituting environmental hazards to humanity. Autochthonous microorganisms in dumpsites exhibit various degrees of responses to contaminants. Unfortunately, there is a dearth of information on the types and concentration of pollutants and the array of microorganisms in these dumpsites which may play important roles in the metabolism of such pollutants or other community processes. Therefore, determining the microbial community structure in such contaminated sites across a municipality is essential for profiling the taxa that would serve as consensus degraders of the pollutants. In this study, soil samples from three dumpsites (Cele, CS; Solous, SS; and Computer Village, CVS) were characterized for geochemical properties using GC-MS, MP-AES, and other analytical protocols, while the dynamics of bacterial communities were evaluated based on their 16S rRNA gene barcodes. A significant difference in the bacterial communities was observed among the dumpsites in relation to the extent of pollution caused by POPs and HMs. CVS, with the highest HM contamination, was rich in Actinobacteria (41.7%) and Acidobacteria (10.2%), in contrast to CS and SS. Proteobacteria (34.1%) and Firmicutes (20%) were the dominant phyla in CS (highest POP contamination), while Bacteroidetes (45.5%) and Proteobacteria (39.9%) were dominant in SS soil.Bacilluswas the dominant genus in the most polluted dumpsite. Canonical correspondence analysis revealed that polycyclic aromatic hydrocarbons (PAHs) and HMs shaped the structure of the bacterial operational taxonomic units (OTUs) in the most polluted dumpsite. Out of a total of 706 OTUs, 628 OTUs exhibited a significant correlation (>50%) with benzo(b)fluoranthene, azobenzene, dibenzofurans, pyrene, dibenzo(a,l)pyrene, Cu, and Zn. In particular, Proteobacteria (Achromobactersp. andSerratiasp.), Bacteroidetes (Zhouiasp.), and Firmicutes (Bacillussp.) were suggested to be pivotal to the ecophysiology of dumpsite soils contaminated with POPs and HMs. The results generally underscored the importance of metagenomic and physicochemical analyses of polluted systems in enabling correlations for useful prediction of drivers of such ecosystems. This will further improve our understanding of the metabolic potential and adaptation of organisms in such systems.

Environmental Sciences & Ecology↗
DOE OSTI2024

Quantification of heterogeneity in human CD8 + T cell responses to vaccine antigens: an HLA-guided perspective

Vaccines have historically played a pivotal role in controlling epidemics. Effective vaccines for viruses causing significant human disease, e.g., Ebola, Lassa fever, or Crimean Congo hemorrhagic fever virus, would be invaluable to public health strategies and counter-measure development missions. Here, we propose coverage metrics to quantify vaccine-induced CD8 + T cell-mediated immune protection, as well as metrics to characterize immuno-dominant epitopes, in light of human genetic heterogeneity and viral evolution. Proof-of-principle of our approach and methods are demonstrated for Ebola virus, SARS-CoV-2, and Burkholderia pseudomallei (vaccine) proteins.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Expected occurrence of wildlife in US Atlantic offshore wind areas

Offshore wind energy has entered a pivotal phase of development for the U.S. Atlantic Outer Continental Shelf (OCS), a region that supports critical habitats, migratory corridors and flyways for many marine species. Assessing where and when marine wildlife occurs is a crucial first step in developing a risk assessment framework to evaluate potential risks and impacts of offshore wind development. In this study, we perform this initial assessment by evaluating the expected occurrence of marine mammal, seabird and sea turtle taxa in areas of interest to identify patterns and potential areas of concern. Specifically, this work depicts the expected monthly density of 84 marine species and taxa within each of the 29 active wind energy lease areas plus a 10 km buffer to account for nearby activity. We then compare these densities to subregional thresholds, evaluated as the 90th percentile of the subregion’s monthly density, to provide comparisons across the shelf region. This analysis synthesizes the most recent spatial distribution models of 31 marine mammal taxa (26 species and 5 guilds), 49 seabird species and 4 sea turtle species to provide a unified evaluation of the major marine wildlife in the region. Out of the 84 species and taxa analyzed, 56 exhibit levels of expected density in wind energy areas that exceed the corresponding 90th percentile subregional threshold at some point throughout the year. These results represent an initial assessment in the broader Occurrence, Exposure, Response, and Consequence (OERC) framework, originally developed by the U.S. Navy for marine species risk assessments. These results offer valuable guidance to marine spatial planners, management agencies and offshore wind developers on the expected locations and timing of interaction risk to wildlife species in or near wind energy areas across the region.

17 WIND ENERGY↗
DOE OSTI2024

Age over sex: evaluating gut microbiota differences in healthy Chinese populations

Age and gender have been recognized as two pivotal covariates affecting the composition of the gut microbiota. However, their mediated variations in microbiota seem to be inconsistent across different countries and races. In this study, 613 individuals, whom we referred to as the “healthy” population, were selected from 1,018 volunteers through rigorous selection using 16S rRNA sequencing. Three enterotypes were identified, namely, Escherichia–Shigella , mixture ( Bacteroides and Faecalibacterium ), and Prevotella . Moreover, 11 covariates that explain the differences in microbiota were determined, with age being the predominant factor. Furthermore, age-related differences in alpha diversity, beta diversity, and core genera were observed in our cohort. Remarkably, after adjusting for 10 covariates other than age, abundant genera that differed between age groups were demonstrated. In contrast, minimal differences in alpha diversity, beta diversity, and differentially abundant genera were observed between male and female individuals. Furthermore, we also demonstrated the age trajectories of several well-known beneficial genera, lipopolysaccharide (LPS)-producing genera, and short-chain fatty acids (SCFAs)-producing genera. Overall, our study further elucidated the effects mediated by age and gender on microbiota differences, which are of significant importance for a comprehensive understanding of the gut microbiome spectrum in healthy individuals.

Wu, Jiacheng↗
DOE OSTI2025

Integrating microbial communities into algal biotechnology: a pathway to enhanced commercialization

Microalgae are increasingly recognized for their potential in wastewater treatment and the sustainable production of feedstock for fuel, feed, food, and other bioproducts. Like conventional agricultural systems, algal cultivation involves complex microbial communities. However, despite their pivotal role in cultivation outcomes, especially at the commodity-scale, the critical interactions between microalgae and their microbiomes are often overlooked. Here we synthesize current knowledge on the taxonomic diversity, ecological roles, and biotechnological potential of algal microbiomes, with a focus on their interactions with algal hosts through nutrient exchange, growth modulation, pathogen defense, and environmental conditioning. We also examine how environmental factors such as nutrient availability, salinity, and temperature influence these interactions. Advances in microbiome engineering, including synthetic biology and ecological approaches, offer opportunities to enhance beneficial algal-microbiome interactions, thereby improving growth, resilience, and yield. These advancements could lead to more sustainable and economically viable microalgae cultivation, with far-reaching implications for environmental management and biotechnological innovation. By addressing key economic and environmental barriers, microbiome engineering holds transformative potential to revolutionize large-scale algae cultivation and provide sustainable solutions to global challenges.

Microbiology↗
DOE OSTI2022

Correlated Insulating Behavior in Infinite-Layer Nickelates

Unlike their cuprate counterparts, the undoped nickelates are weak insulators without long-range antiferromagnetic order. Identifying the origin of this insulating behavior, found on both sides of the superconducting dome, is potentially a crucial step in the development of a coherent understanding of nickelate superconductivity. In this work, we study the normal-state resistivity of infinite-layer nickelates using high magnetic fields to suppress the superconductivity and examine the impact of disorder and doping on its overall temperature ( T ) dependence. In superconducting samples, the resistivity of Nd- and La-based nickelates continues to exhibit weakly insulating behavior with a magnitude and functional form similar to that found in underdoped electron-doped cuprates. We find a systematic evolution of the insulating behavior as a function of nominal hole doping across different rare-earth families, suggesting a pivotal role for strong electron interactions, and uncover a correlation between the suppression of the resistivity upturn and the robustness of the superconductivity. By contrast, we find very little correlation between the level of disorder and the magnitude and onset temperature of the resistivity upturn. Combining these experimental observations with previous Hall effect measurements on these two nickelate families, we consider various possible origins for this correlated insulator behavior and its evolution across their respective phase diagrams.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Phylogenetic occurrence of the phenylpropanoid pathway and lignin biosynthesis in plants

The phenylpropanoid pathway serves as a rich source of metabolites in plants and provides precursors for lignin biosynthesis. Lignin first appeared in tracheophytes and has been hypothesized to have played pivotal roles in land plant colonization. In this review, we summarize recent progress in defining the lignin biosynthetic pathway in lycophytes, monilophytes, gymnosperms, and angiosperms. In particular, we review the key structural genes involved in p-hydroxyphenyl-, guaiacyl- and syringyl-lignin biosynthesis across plant taxa and consider and integrate new insights on major transcription factors, such as NACs and MYBs. We also review insight regarding a new transcriptional regulator, 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase, canonically identified as a key enzyme in the shikimate pathway. We use several case studies, including EPSP synthase, to illustrate the evolution processes of gene duplication and neo-functionalization in lignin biosynthesis. This review provides new insights into the genetic engineering of the lignin biosynthetic pathway to overcome biomass recalcitrance in bioenergy crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Why Black Flowers? An Extreme Environment and Molecular Perspective of Black Color Accumulation in the Ornamental and Food Crops

Pollinators are attracted to vibrant flower colors. That is why flower color is the key agent to allow successful fruit set in food or ornamental crops. However, black flower color is the least attractive to pollinators, although a number of plant species produce black flowers. Cyanidin-based anthocyanins are thought to be the key agents to induce black color in the ornamental and fruit crops. R2R3-MYB transcription factors (TFs) play key roles for the tissue-specific accumulation of anthocyanin. MYB1 and MYB11 are the key TFs regulating the expression of anthocyanin biosynthesis genes for black color accumulation. Post-transcriptional silencing of flavone synthase II ( FNS ) gene is the technological method to stimulate the accumulation of cyanidin-based anthocyanins in black cultivars. Type 1 promoter of DvIVS takes the advantage of FNS silencing to produce large amounts of black anthocyanins. Exogenous ethylene application triggers anthocyanin accumulation in the fruit skin at ripening. Environment cues have been the pivotal regulators to allow differential accumulation of anthocyanins to regulate black color. Heat stress is one of the most important environmental stimulus that regulates concentration gradient of anthocyanins in various plant parts, thereby affecting the color pattern of flowers. Stability of black anthocyanins in the extreme environments can save the damage, especially in fruits, caused by abiotic stress. White flowers without anthocyanin face more damages from abiotic stress than dark color flowers. The intensity and pattern of flower color accumulation determine the overall fruit set, thereby controlling crop yield and human food needs. This review paper presents comprehensive knowledge of black flower regulation as affected by high temperature stress, and the molecular regulators of anthocyanin for black color in ornamental and food crops. It also discusses the black color-pollination interaction pattern affected by heat stress for food and ornamental crops.

Ahmad, Sagheer↗
DOE OSTI2023

Stressing the importance of plant specialized metabolites: omics-based approaches for discovering specialized metabolism in plant stress responses

Plants produce a diverse range of specialized metabolites that play pivotal roles in mediating environmental interactions and stress adaptation. These unique chemical compounds also hold significant agricultural, medicinal, and industrial values. Despite the expanding knowledge of their functions in plant stress interactions, understanding the intricate biosynthetic pathways of these natural products remains challenging due to gene and pathway redundancy, multifunctionality of proteins, and the activity of enzymes with broad substrate specificity. In the past decade, substantial progress in genomics, transcriptomics, metabolomics, and proteomics has made the exploration of plant specialized metabolism more feasible than ever before. Notably, recent advances in integrative multi-omics and computational approaches, along with other technologies, are accelerating the discovery of plant specialized metabolism. In this review, we present a summary of the recent progress in the discovery of plant stress-related specialized metabolites. Emphasis is placed on the application of advanced omics-based approaches and other techniques in studying plant stress-related specialized metabolism. Additionally, we discuss the high-throughput methods for gene functional characterization. These advances hold great promise for harnessing the potential of specialized metabolites to enhance plant stress resilience in the future.

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↗
DOE OSTI2026

From chromatin to crop: epigenetic innovations in bioenergy systems

Energy crops encompass a diverse array of plant species cultivated primarily as a source of biomass for energy generation and biofuel production. As such, they play a pivotal role in the transition to sustainable energy systems. However, their productivity is often limited by environmental stresses, nutrient availability, and the need for optimized yield. While traditional breeding and genetic engineering have driven improvements, challenges such as narrow genetic diversity, long development cycles, trait instability, and unexpected gene interactions remain. Epigenetics offers a largely untapped opportunity to overcome these constraints by regulating gene expression through mechanisms that are dynamic, finely tuned, and responsive to environmental and developmental cues. Epigenetic modifications including DNA methylation, histone post-translational changes, and small non-coding RNAs influence nearly all aspects of plant development and physiology, including traits central to bioenergy crops. While these mechanisms are well characterized in model species such as Arabidopsis thaliana, they remain underexplored in many purpose-grown energy crops. This review summarizes the current state of knowledge of epigenetic regulation in bioenergy species, explores how these mechanisms can be leveraged to enhance crop resilience and productivity, and identifies gaps in our understanding. By characterizing epigenetic mechanisms and harnessing epigenetic variation, we can expand the toolkit for developing resilient, high-yielding bioenergy crops to meet future environmental and energy demands.

09 BIOMASS FUELS↗
DOE OSTI2023

Editorial: Advances in observations and modeling of snow, forest-snow processes and snow hydrology

Seasonal snowpack plays a pivotal role in the regional water cycle. In Western mountainous regions, where precipitation predominantly occurs as snow during winter and is limited in the summer months when water demand peaks, snowpack serves as a critical water source essential for sustaining water supply, ecosystems, agriculture, and industries. Additionally, snowpack dynamically influences extreme events, such as floods, droughts, and wildfires, through intricate land-atmosphere feedback. Nevertheless, significant knowledge gaps persist within this field due to data limitations and the complexity of the physics involved in modeling snow and snow hydrology (i.e., snow acts as a critical upstream hydrological process). Here, this research topic presents a collection of manuscripts that address some of these important research gaps.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Deep learning models for interpretation of point of care ultrasound in military working dogs

Introduction: Military working dogs (MWDs) are essential for military operations in a wide range of missions. With this pivotal role, MWDs can become casualties requiring specialized veterinary care that may not always be available far forward on the battlefield. Some injuries such as pneumothorax, hemothorax, or abdominal hemorrhage can be diagnosed using point of care ultrasound (POCUS) such as the Global FAST® exam. This presents a unique opportunity for artificial intelligence (AI) to aid in the interpretation of ultrasound images. In this article, deep learning classification neural networks were developed for POCUS assessment in MWDs. Methods: Images were collected in five MWDs under general anesthesia or deep sedation for all scan points in the Global FAST® exam. For representative injuries, a cadaver model was used from which positive and negative injury images were captured. A total of 327 ultrasound clips were captured and split across scan points for training three different AI network architectures: MobileNetV2, DarkNet-19, and ShrapML. Gradient class activation mapping (GradCAM) overlays were generated for representative images to better explain AI predictions. Results: Performance of AI models reached over 82% accuracy for all scan points. The model with the highest performance was trained with the MobileNetV2 network for the cystocolic scan point achieving 99.8% accuracy. Across all trained networks the diaphragmatic hepatorenal scan point had the best overall performance. However, GradCAM overlays showed that the models with highest accuracy, like MobileNetV2, were not always identifying relevant features. Conversely, the GradCAM heatmaps for ShrapML show general agreement with regions most indicative of fluid accumulation. Discussion: Overall, the AI models developed can automate POCUS predictions in MWDs. Preliminarily, ShrapML had the strongest performance and prediction rate paired with accurately tracking fluid accumulation sites, making it the most suitable option for eventual real-time deployment with ultrasound systems. Further integration of this technology with imaging technologies will expand use of POCUS-based triage of MWDs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Hyperspectral Reflectance-Based High Throughput Phenotyping to Assess Water-Use Efficiency in Cotton

Cotton is a pivotal global commodity underscored by its economic value and widespread use. In the face of climate change, breeding resilient cultivars for variable environmental conditions becomes increasingly essential. However, the process of phenotyping, crucial to breeding programs, is often viewed as a bottleneck due to the inefficiency of traditional, low-throughput methods. To address this limitation, this study utilizes hyperspectral remote sensing, a promising tool for assessing crucial crop traits across forty cotton varieties. The results from this study demonstrated the effectiveness of four vegetation indices (VIs) in evaluating these varieties for water-use efficiency (WUE). The prediction accuracy for WUE through VIs such as the simple ratio water index (SRWI) and normalized difference water index (NDWI) was higher (up to R2 = 0.66), enabling better detection of phenotypic variations (p < 0.05) among the varieties compared to physiological-related traits (from R2 = 0.21 to R2 = 0.42), with high repeatability and a low RMSE. These VIs also showed high Pearson correlations with WUE (up to r = 0.81) and yield-related traits (up to r = 0.63). We also selected high-performing varieties based on the VIs, WUE, and fiber quality traits. This study demonstrated that the hyperspectral-based proximal sensing approach helps rapidly assess the in-season performance of varieties for imperative traits and aids in precise breeding decisions.

Agriculture↗