Spectral Analysis Research Articles

Synthesis and Antifungal Evaluation of Cinnamic Acid-Geraniol Hybrids as Potential Fungicides.

Cinnamic acid and geraniol are two well-known antifungal natural products and widely applied in food and cosmetics industries. To discover novel natural product-based fungicide candidates with more potent activity and good ecological compatibility for the management of plant diseases, a series of cinnamic acid-geraniol hybrids were prepared by means of molecular hybridization and their chemical structures were well confirmed by spectral analysis. The antifungal activities of the target compounds against three phytopathogenic fungi Fusarium graminearum, Gaeumannomycesgraminis (Sacc.) Arx et Oliver var. tritici (Sacc.) Walker, and Valsa mali were evaluated. Among them, compounds 5e and 5f showed the remarkable antifungal activity against G. graminis with the EC50 values of 82.719 and 91.828 μg/mL, respectively; while compounds 5f and 6b exhibited the obvious antifungal activity against V. mali. It suggested that compound 5f can be further optimized for the design of novel broad-spectrum fungicide molecules as the secondary lead compound. In addition, some interesting structure-antifungal activity relationships were obtained. This work will provide some reference and guidance for the further discovery of novel fungicide candidates based on cinnamic acid and geraniol.

Polyprenylated xanthones with potential anti-inflammatory and anti-HIV effects from the stems and leaves of Cratoxylum cochinchinense (Lour.) Blume.

A phytochemical study on the stems and leaves of Cratoxylum cochinchinense (Lour.) Blume resulted in the isolation and characterisation of a new polyprenylated xanthone, cratocochinone (1), as well as seven known analogues, fuscaxanthone K (2), pruniflorone Q (3), 1,3,5,8-tetrahy-droxy- 2-(3-methybut-2-enyl)-4-(3,7-dimethylocta-2,6-dienyl) xanthone (4), cochinensoxanthone (5), cratoxylum-xanthone B (6), cochinchinone I (7) and cochinchinone K (8). The chemical structure of 1 was determined by comprehensive spectral analyses. The known compounds 2 - 8 were identified by comparing their experimental spectroscopic data with those reported data in the literature. The anti-inflammatory and anti-HIV effects of all isolates 1-8 were evaluated. As a result, compounds 1-8 showed remarkable inhibitory effects against nitric oxide (NO) production induced by lipopolysaccharide in mouse macrophage RAW 264.7 cells showing IC50 values ranging from 0.68 ± 0.06 to 10.27 ± 0.18 μM. Meanwhile, compounds 1-8 displayed notable anti-HIV-1 reverse transcriptase (RT) effects with EC50 values ranging from 0.19 to 10.72 µM.

Exploring The Antimicrobial Potential of Novel 1,2,4‒Triazole Conjugates with Pyrazole: Synthesis, Biological Activity and In Silico Docking.

In the present study, a new series of 1,2,4‒triazole linked pyrazole hybrids (5a‒5l) were synthesized from dimethyl amino pyrazole (1) in good yield by three-step reaction. The chemical structures of the resulted compounds were thoroughly elucidated using spectral analyses such as IR, 1H-NMR, 13C-NMR, mass spectra and elemental analysis. The target compounds were screened for their antimicrobial activities against the various standard pathogen strains, Gram‒(‒ve) (E. coli, P. aeruginosa, K. pneumoniae, A. baumannii), and Gram‒(+ve) (S. aureus,S. faecalis) microorganisms. According to the results obtained, in particular, compounds 5b, 5f, 5h and 5j was effective at inhibiting the antibacterial growth of all the bacteria's, having MIC values ranging 0.983‒14.862 mg/mL and compared to moxifloxacin (1.391‒22.01 mg mL-1). The most active compounds were chosen to interact with the DNA gyrase and topoisomerase-IV targets via molecular docking. These selected ligands interacted with PDB targets 2XCO, 1S16 and docked into the active site of amino acids Ala-269, Gly-413, Asn-405, Ser-1182, Thr-1185, His-1186, His-1186, Lys-1189, and Trp-1213.The pharmacokinetic properties, stability, and drug-likeness parameters of all target molecules were estimated using SwissADME and PkCSM protocols. The current study used in silico approaches combining e-pharmacophore modeling and structure-based molecular docking of targets to identify antimicrobial agents.

Single-Shot Multispectral Encoding: Advancing Optical Lithography for Encryption and Spectroscopy.

Most modern optical display and sensing devices utilize a limited number of spectral units within the visible range, based on human color perception. In contrast, the rapid advancement of machine-based pattern recognition and spectral analysis could facilitate the use of multispectral functional units, yet the challenge of creating complex, high-definition, and reproducible patterns with an increasing number of spectral units limits their widespread application. Here, we report a technique for optical lithography that employs a single-shot exposure to reproduce perovskite films with spatially controlled optical band gaps through light-induced compositional modulations. Luminescent patterns are designed to program correlations between spatial and spectral information, covering the entire visible spectral range. Using this platform, we demonstrate multispectral encoding patterns for encryption and multivariate optical converters for dispersive optics-free spectroscopy with high spectral resolution. The fabrication process is conducted at room temperature and can be extended to other material and device platforms.

Repeatability of alkaline inorganic phosphate quantification in the skeletal muscle using 31P-magnetic resonance spectroscopy at 3T.

The detection of a secondary inorganic phosphate (Pi) resonance, a possible marker of mitochondrial content in vivo, using phosphorus magnetic resonance spectroscopy (31P-MRS), poses technical challenges at 3Tesla (T). Overcoming these challenges is imperative for the integration of this biomarker into clinical research. To evaluate the repeatability and reliability of measuring resting skeletal muscle alkaline Pi (Pialk) using with 31P-MRS at 3 T. After an initial set of experiments on five subjects to optimize the sequence, resting 31P-MRS of the quadriceps muscles were acquired on two visits (~4days apart) using an intra-subjects design, from 13 sedentary to moderately active young male and female adults (22 ± 3years old) within a whole-body 3T MR system. Measurement variability attributed to changes in coil position, shimming procedure, and spectral analysis were quantified. 31P-MRS data were acquired with a 31P/-proton (1H) dual-tuned surface coil positioned on the quadriceps using a pulse-acquire sequence. Test-retest absolute and relative repeatability was analyzed using the coefficient of variation (CV) and intra-class correlation coefficients (ICC), respectively. After sequence parameter optimization, Pialk demonstrated high intra-subject repeatability (CV: 10.6 ± 5.4%, ICC: 0.80). Proximo-distal change in coil position along the length of the quadriceps introduced Pialk quantitation variability (CV: 28 ± 5%), due to magnetic field inhomogeneity with more distal coil locations. In contrast, Pialk measurement variability due to repeated shims from the same muscle volume (0.40 ± 0.09mM; CV: 6.6%), and automated spectral processing (0.37 ± 0.01mM; CV: 2.3%), was minor. The quantification of Pialk in skeletal muscle via surface coil 31P-MRS at 3T demonstrated excellent reproducibility. However, caution is advised against placing the coil at the distal part of the quadriceps to mitigate shimming inhomogeneity.

Electronic Fourier–Galois Spectrum Analyzer for the Field GF(31)

A scheme for the Fourier–Galois spectrum analyzer for the field GF(31) is proposed. It is shown that this analyzer allows for solving a wide enough range of problems related to image processing, in particular those arising in the course of experimental studies in the field of physical chemistry. Such images allow digital processing when divided into a relatively small number of pixels, which creates an opportunity to use Galois fields of relatively small size. The choice of field GF(31) is due to the fact that the number 31 is a Mersenne prime number, which considerably simplifies the algorithm of calculating the Fourier–Galois transform in this field. The proposed scheme of the spectrum analyzer is focused on the use of threshold sensors, at the output of which signals corresponding to binary logic are formed. Due to this fact, further simplification of the proposed analyzer scheme is achieved. The constructiveness of the proposed approach is proven using digital modeling of electronic circuits. It is concluded that when solving applied problems in which an image can be divided into a relatively small number of pixels, it is important to take into account the specificity of particular Galois fields used for their digital processing.

Cholesterol Conformational Structures in Phospholipid Membranes.

Cholesterol is a major component of biomembranes that impacts membrane order, permeability, and lateral organization, but the precise molecular mechanisms of cholesterol's actions are still under investigation. Density functional theory (DFT) calculations have opened the fingerprint vibration bands of large molecules to detailed spectral analysis. For cholesterol, Raman spectral interpretation for conformational structure and hydrogen bonding is now possible. Here, DFT calculations of cholesterol conformers identify 10 structure types that also have unique low-frequency Raman spectra. By fitting experimental spectra to these types, the distribution of cholesterol structures present in phospholipid (PL) membrane vesicles was measured. The distributions reveal that the cholesterol iso-octyl chain tends to align with saturated PL chains and shifts to a thermal distribution for unsaturated PL chains. The results agree with the templating effect of cholesterol on PL membranes and show that the top of the iso-octyl chain is rigid like the rings. It is also shown that the inclusion of water molecules hydrogen bonded to the cholesterol hydroxy group in the DFT calculations may improve the spectral fitting for future studies.

Deep Multimodal Fusion of Visual and Auditory Features for Robust Material Recognition

This paper presents a deep neural network incorporating visual and auditory data fusion to enhance material recognition performance. Traditional recognition techniques relying on single data modalities face accuracy and robustness limitations, especially in complex real-world environments. To address these challenges, we develop a multimodal fusion-based model. The proposed approach first extracts features from input images and sounds separately using CNNs and spectral analysis. A concatenation layer then integrates the visual and auditory features. Extensive experiments demonstrate superior material classification over uni-modal methods, with 100% test accuracy across seven material types. The multi-modal fusion model also demonstrates stronger resilience to noise and illumination variations. This research provides a valuable foundation for robust material perception in intelligent systems.

Front Cover: Raman Spectral Analysis in the CHx‐Stretching Region as a Guiding Beacon for Non‐Targeted, Disruption‐Free Monitoring of Germination and Biofilm Formation in the Green Seaweed Ulva (ChemPhysChem 17/2024)

Front Cover: Raman Spectral Analysis in the CH_x‐Stretching Region as a Guiding Beacon for Non‐Targeted, Disruption‐Free Monitoring of Germination and Biofilm Formation in the Green Seaweed <i>Ulva</i> (ChemPhysChem 17/2024)

Design your own universe: a physics-informed agnostic method for enhancing graph neural networks

AbstractPhysics-informed Graph Neural Networks have achieved remarkable performance in learning through graph-structured data by mitigating common GNN challenges such as over-smoothing, over-squashing, and heterophily adaption. Despite these advancements, the development of a simple yet effective paradigm that appropriately integrates previous methods for handling all these challenges is still underway. In this paper, we draw an analogy between the propagation of GNNs and particle systems in physics, proposing a model-agnostic enhancement framework. This framework enriches the graph structure by introducing additional nodes and rewiring connections with both positive and negative weights, guided by node labeling information. We theoretically verify that GNNs enhanced through our approach can effectively circumvent the over-smoothing issue and exhibit robustness against over-squashing. Moreover, we conduct a spectral analysis on the rewired graph to demonstrate that the corresponding GNNs can fit both homophilic and heterophilic graphs. Empirical validations on benchmarks for homophilic, heterophilic graphs, and long-term graph datasets show that GNNs enhanced by our method significantly outperform their original counterparts.

Magnetic seed technology for the efficient removal of nitrogen from wastewater

AbstractNitrogen pollution is a global issue impacting ecosystems, climate change, human health, and the economy. The challenge to reduce nitrogen pollution as a priority highlights the wastewater treatment system an important point of control. Coagulation, a common water treatment process, has a positive impact on the overall treatment process but often struggles to address nitrogen pollution effectively. Our study introduces a novel magnetic seed to enhance coagulation in treating nitrogen pollution, offering a new solution for the global water treatment industry. We focus on the efficiency, mechanistic detail, and recovery potential of a magnetic zirconium tannate in treating real-world wastewater nitrogen under coagulation conditions. Results show that 9 g/L of magnetic zirconium tannate effectively removes ammonia nitrogen, organic nitrogen, and total nitrogen from five different wastewater types. For low-concentration wastewater with ammonia nitrogen below 20 mg/L and organic nitrogen below 5 mg/L, removal rates reach up to 100%. For high-concentration wastewater with ammonia nitrogen below 98 mg/L and organic nitrogen below 86 mg/L, the maximum removal rate is 59% for ammonia nitrogen and 88% for organic nitrogen. Spectral analysis reveals that magnetic zirconium tannate adsorbs nitrogen compounds in water through both hydrogen bonding and electrostatic interactions, achieving excellent treatment outcomes. It can be efficiently recovered without using complex organic eluents and is easily separated from the flocculate. This technology offers non-disruptive supplement for current treatment approaches to meet the global nitrogen pollution challenge head on.

Modern methods for determining heavy metals in soil

This article discusses the problem of heavy metal detection in soil and its impact on vegetation. Based on the experience of foreign and domestic research, this article discusses global fundamental problems and challenges, modern methods of heavy metal detection, as well as prospects for further research and new challenges facing the scientific community. The aim of the study is to identify modern and established methods for the detection of heavy metals in soil, such as spectral analysis methods and reflectance spectra of plant parts. The review summarizes the results of experimental studies confirming the effectiveness of the combined sampling and spectrometry method for estimating the concentration of heavy metals in soil, as well as the feasibility of using plant reflectance spectra to measure pollution. World experience confirms the expediency of using spectral approaches to determine heavy metals in soil and analyze their impact on vegetation. The results of the research have practical application in the field of ecology, agriculture and nature protection, allow effectively controlling the level of heavy metal pollution and taking measures for its elimination.

Synthesis, Characterization and Antimicrobial Activity of Homonuclear Cu(II) and Ni(II) Schiff Base Complexes

The current study aimed to synthesise, characterise, and investigate the antimicrobial activity of homonuclear Cu(II) and Ni(II) Schiff base complexes. Homonuclear Schiff Base Complexes chelates of Cu(II) and Ni(II) were synthesised. It appears that the complex is a potential metallo-ligand. It forms binuclear complexes when it reacts with two different metal salts, Ni and Cu. Using a Schiff base ligand made from 4-chloro-o-phenylenediamine and 3,5-dichloro-2-hydroxyacetophenone, the homo and hetero binuclear oxygen bridging Cu(II) and Ni(II) complexes were synthesized. Numerous common physicochemical methods, including elemental analysis, spectroscopic, thermal, cyclic voltammetry, and magnetic moment tests, have been used to characterise the synthesised complexes. For the mono- and binuclear compound of Cu(II) &amp; Ni(II), spectral analysis reveals square planer shape. The antibacterial data indicates that the homo-binuclear copper complex is more active than the other mono- and binuclear complexes. Research has been done on the Schiff base and its complexes' anticancer properties.

Qualitative versus quantitative assessment of electroencephalography in cognitive decline: Comparison in a clinical population

This study aimed to compare the diagnostic performance of visual assessment of electroencephalography (EEG) using the Grand Total EEG (GTE) score and quantitative EEG (QEEG) using spectral analysis in the context of cognitive impairment.This was a retrospective study of patients with mild cognitive impairment, with (MCI+V) or without (MCI) vascular dysfunction, and patients with dementia including Alzheimer's disease, Lewy Body Dementia and vascular dementia.The results showed that the GTE is a simple scoring system with some potential applications, but limited ability to distinguish between dementia subtypes, while spectral analysis appeared to be a powerful tool, but its clinical development requires the use of artificial intelligence tools.

Enhancing Thomson scattering polychromator performance with multi-pass spectral filters.

In photon-deficient, noncollective Thomson scattering diagnostics, filter polychromators are typically employed in the spectral analysis of Thomson-scattered signals to achieve acceptable signal-to-noise performance. Currently, the most common polychromator filter configuration employs a set of single-passband optical filters that define individual spectral channels. Here, we introduce a new spectral analysis method for Thomson scattering based on spectral filters with multiple passbands, referred to as Thomson scattering spectral multiplexing. Implementing multi-bandpass spectral filters on polychromators increases the achievable range of electron temperature measurement for a given number of filters employed. In addition, Thomson scattering spectral multiplexing reduces systematic measurement uncertainty, with fewer required spectral channels, thereby decreasing light loss from reduced optical element interactions. A multi-bandpass filter set, optimized by a genetic algorithm, has been successfully installed and tested on the Helically Symmetric eXperiment (HSX), demonstrating the benefits of the Thomson scattering spectral multiplexing method.

Multi-ligand strategy for enhanced removal of heavy metal ions by thiol-functionalized defective Zr-MOFs

Given the significant global concern about heavy metal pollution, the development of effective adsorbents to capture pollutants has become an urgent issue. In this work, thiol-functionalized defective Zr-MSA-DMSA was designed by mixing 2,3-dimercaptosuccinic acid and mercaptosuccinic acid, which was applied for the rapid and efficient removal of M(II) (i.e., Pb(II), Hg(II), Cd(II)) from wastewater. Zr-MSA-DMSA exhibited excellent adsorption performance, and the maximum adsorption capacities for Pb(II), Hg(II), and Cd(II) were 715.2mgg-1, 862.7mgg-1, and 450.5mgg-1. In actual wastewater, Zr-DMSA-MSA exhibited up to 97% M(II) removal efficiency and excellent anti-interference ability. It also maintained good structural stability after five adsorption/regeneration cycles. Thus, the abundant oxygen vacancies and unsaturated adsorption sites on Zr-MSA-DMSA significantly improved the adsorption performance of M(II). Spectral analysis and DFT calculations confirmed that Zr-MSA-DMSA mainly relied on the coordination of sulfur and oxygen atoms, electrostatic attraction and a large number of defective sites to achieve the adsorption of M(II). Fixed bed experiments showed that Zr-MSA-DMSA exhibited a depletion time of 10500min and a volume of 7.0L. In summary, Zr-MSA-DMSA holds significant potential for treating heavy metal wastewater and provides potential applications for defect engineering.

Biotransformation of Cinnamic Acid, Cinnamaldehyde, Furfural and Epoxidation of Cyclohexene by Plant Catalase

Background: Epoxides are widely useful in various fields such as pharmaceuticals, pesticides, cosmetics, polymer synthesis, fragrance compounds, and food additives. However, the synthesis of epoxides involves heavy metal catalysts and toxic, unstable organic catalysts which causes serious environmental and safety concerns. In recent years, biocatalysts have received a great deal of interest in the synthesis of olefin-derived epoxides due to their mild reaction conditions, environmental friendliness, good selectivity, and sustainability. This study focuses on catalases as a biocatalyst for potential epoxidation reactions of olefins. Objective:: To determine the possibility of using biocatalyst catalase from a novel source Sechium edule (squash) for epoxidation of olefins in the presence of H2O2. Methods: UV-Vis spectrophotometer was used to monitor the formation of epoxide from substrates- cyclohexene, cinnamic acid, cinnamaldehyde, furfural in acetonitrile solvent and a suitable aliquot of the enzyme solution in the presence of H2O2. The products formed were analyzed using FTIR and GC-MS. For the immobilized enzyme, chitosan beads activated with TPP were used in place of the enzyme and a similar procedure was followed for the analysis. Results: Four different olefin substrates (cyclohexene, cinnamic acid, cinnamaldehyde, and furfural) were selected to study the catalysis reaction of epoxidation by the catalase enzyme. The course of the epoxidation was monitored by UV-Vis, FTIR, and GC-MS methods. However, under optimized reaction conditions and spectral analysis, further confirmed by GC-MS, data showed only epoxide formation from cyclohexene. CAT completely catalyzed other olefins like furfural, cinnamic acid, and cinnamaldehyde into its degraded products biochemically. Therefore, cyclohexene was selected for further immobilization studies and the identified metabolites of olefins and their degradation mechanism. Major biodegradation products of cinnamic acid were found to be styrene( m/z 104.0) and benzaldehyde(m/z 105.0). GC-MS data of biotransformation of cinnamaldehyde, identified 2,4 dimethyl benzaldehyde(m/z 133) as the main product. The catalytic biotransformation of furfural investigated by GC-MS data identified 2,5 dimethyl benzaldehyde (m/z 133), dodecanol (m/z 181) and Pentanoic acid, 5 hydroxy, 2,4 dibutyl phenyl ester(m/z 306) as the major product. Three major oxidized products were detected in GC-MS data from the epoxidation of cyclohexene viz., cyclohexane diol(m/z 116), cyclohexene epoxide-1-ol(m/z 110), cyclohexene epoxide-1-one(m/z 110). Conclusion: In this investigation, catalase purified from Sechium edule(squash) was developed as an efficient catalytic tool for the biotransformation of olefins and selective epoxidation of cyclohexene. Under optimized conditions, the experimental results revealed the main products found in cinnamaldehyde as benzaldehyde (m/z 133.0) and cinnamic acid as benzaldehyde (m/z 133), styrene (m/z 104.0) and benzoic acid (m/z 122.0), while the data from furfural oxidation could not be justified from previous studies. The optimal concentration of CH3CN solvent for cyclohexene epoxidation was found to be 4 mM. Enzymatic characterization of free and immobilized catalase on chitosan was investigated using cyclohexene as a variable substrate and found to be 0.017 mM, 83.33 μmol/min for Km and Vmax values, pH 6.8 and 30˚C for free CAT and 0.03 mM, 200 μmol/min, pH 7.6 and 35˚C for immobilized one. Immobilization increases the thermal stability of the CAT and changes the pH to alkalinity. The possible oxidation of cyclohexene was deduced as the radical chain mechanism for the generation of epoxide with the key products obtained as cyclohexane diol(m/z 116), cyclohexene epoxide-1-ol(m/z 110) and cyclohexene epoxide-1-one(m/z 110). The reusability of the biocatalytic tool opens up the opportunity to reduce the cost of various catalytic reactions. Further studies can focus on the separation and advancement of epoxide yields, improved immobilization strategy for maximum repetitive cycles, and chemo-enzymatic epoxidation on biological olefins.

FedCut: A Spectral Analysis Framework for Reliable Detection of Byzantine Colluders.

This paper proposes a general spectral analysis framework that thwarts a security risk in federated Learning caused by groups of malicious Byzantine attackers or colluders, who conspire to upload vicious model updates to severely debase global model performances. The proposed framework delineates the strong consistency and temporal coherence between Byzantine colluders' model updates from a spectral analysis lens, and, formulates the detection of Byzantine misbehaviours as a community detection problem in weighted graphs. The modified normalized graph cut is then utilized to discern attackers from benign participants. Moreover, the Spectral heuristics is adopted to make the detection robust against various attacks. The proposed Byzantine colluder resilient method, i.e., FedCut, is guaranteed to converge with bounded errors. Extensive experimental results under a variety of settings justify the superiority of FedCut, which demonstrates extremely robust model accuracy (MA) under various attacks. It was shown that FedCut's averaged MA is 2.1% to 16.5% better than that of the state of the art Byzantine-resilient methods. In terms of the worst-case model accuracy (MA), FedCut is 17.6% to 69.5% better than these methods.

Identifying Sulphurous Water Discharge from Legacy Oil and Gas Wells using Spectral Band Analysis of Aerial and Satellite Imagery

Legacy oil and gas wells are a significant source of hydrogen sulphide and methane gas release to the atmosphere. Unanticipated occurrences of gas release in urbanized areas can pose human health risks. Several high hydrogen sulphide-emitting wells have been identified in Norfolk County, Ontario, Canada, based on the remote detection of sulphurous water discharging to the surface along the wellbore. Although oil and gas well records report well status and location, community reports of noxious hydrogen sulphide odours suggest potentially compromised well seals and inaccuracies in their documented location. Given the broad-scale nature of this issue and limitations in site access, a remote-sensing based methodology utilizing satellite and high-resolution aerial photography could support identification of undocumented sulphurous water leaks associated with compromised oil and gas wells and subsequent characterization of hydrological and ecohydrological impacts over time. This study presents a multifaceted approach to identifying sulphurous leaking wells utilizing complimentary remote sensing imagery and image analysis tools within ArcGIS. Southwestern Ontario Orthophotography Project air photos and Sentinel-2 satellite imagery were determined to be the most applicable sources of imagery based on their respective advantages in resolution and revisit time. The application of a normalized difference vegetation index showed that major well leaks could exhibit signs of vegetative scarcity, while minor well leaks may have only a limited impact on vegetation. A band combination utilizing the green and near infrared bands was created to enhance the detection of sulphurous water leaks. Utilizing the identified band combination, a pair of potentially undiscovered leaks were located west of a fluvial river channel. Continued research should attempt to employ an automated approach for discerning additional sulphurous water leaks in the region or at different points in time. Possible techniques may involve the deep learning object and change detection models incorporated in ArcGIS.

Classifying Plant Communities in the North American Coastal Plain With PRISMA Spaceborne Hyperspectral Imagery and the Spectral Mixture Residual

AbstractThe effort to map terrestrial biodiversity, in recent years limited mostly to the use of broadband multispectral remote sensing at decameter scales, can be greatly enhanced by harnessing hyperspectral imagery. Interpretation of hyperspectral imagery may be aided by the Mixture Residual (MR) spectral preprocessing transformation. MR integrates the benefits of spectral mixture analysis with the absorption peak‐enhancing characteristics of continuum removal. MR characterizes each pixel as a linear combination of generic end‐members estimating the spectral continuum, from which the residual of each wavelength is computed and treated as a source of additional information. Using Hyperspectral Precursor of the Application Mission (PRISMA) imagery, we tested the ability of MR‐transformed reflectance as compared to untransformed surface reflectance (SR) to map plant associations and land cover using ground truthing and random forest classifications across four landscapes within the North American Coastal Plain. We used a forward stepwise selection algorithm to choose bands for each classification and subsequently compared these between SR and MR. Our MR classifications distinguished land cover with 5% greater balanced accuracy on average than the SR‐based classifications across all four landscapes. The MR‐based classification that integrated data from all landscapes into a unified model encompassing all 21 land cover types achieved a 76% average balanced accuracy over three iterations. Generally, MR utilized the near‐infrared region to a greater degree than SR while deemphasizing the green peak. Based on our results, MR improves the accuracy of mapping terrestrial biodiversity, likely extending to other current and planned satellite hyperspectral missions.