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Spectroscopy for Biochemical Imaging and Sensing
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Spectroscopy for Biochemical Imaging and Sensing

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biosensors".

Deadline for manuscript submissions: 31 August 2025 | Viewed by 2818

Special Issue Editor

Dr. Bruno Wacogne

E-Mail Website
Guest Editor
1. FEMTO-ST Institute UMR CNRS 6174, University Bourgogne Franche-Comte, Besançon, France
2. Clinical Investigation Center, INSERM CIC 1431, Besançon University Hospital, Besançon, France
Interests: health technologies; translational sciences; medical devices
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

“Spectroscopy for biochemical imaging and sensing” refers to the use of spectroscopic techniques to study and analyze biochemical processes, molecules, and structures within biological systems. This interdisciplinary field combines principles from spectroscopy, biology, chemistry, and imaging to investigate the composition, structure, dynamics, and interactions of biomolecules in living organisms.

Spectroscopic methods, including, but not limited to, infrared spectroscopy, Raman spectroscopy, fluorescence spectroscopy, and nuclear magnetic resonance spectroscopy, are employed to gather information about the molecular composition and behavior of biological samples. By harnessing these techniques, researchers can gain insights into various biological phenomena, including disease mechanisms, drug interactions, metabolic pathways, and cellular functions. Additionally, spectroscopic imaging and sensing methods enable non-invasive or minimally invasive detection and visualization of biochemical processes, offering valuable tools for biomedical research, diagnostics, and therapeutic development.

For this Special Issue, we invite you to share your latest advancements in biochemical analysis that are relevant to the topics published in Sensors. Discover practical applications of spectroscopic techniques in understanding biological systems, stay informed, and gain valuable insights into the evolving field of spectroscopy in biochemistry.

Dr. Bruno Wacogne
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biochemical imaging
  • sensing techniques
  • optical spectroscopy
  • fluorescence spectroscopy
  • Raman spectroscopy
  • infrared spectroscopy
  • near-infrared spectroscopy
  • surface-enhanced Raman spectroscopy
  • hyperspectral/mulitspectral imaging
  • fluorescence imaging
  • molecular imaging

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Published Papers (2 papers)

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Research

19 pages, 2090 KiB  
Article
Predicting Perennial Ryegrass Cultivars and the Presence of an Epichloë Endophyte in Seeds Using Near-Infrared Spectroscopy (NIRS)
by Simone Vassiliadis, Kathryn M. Guthridge, Priyanka Reddy, Emma J. Ludlow, Inoka K. Hettiarachchige and Simone J. Rochfort
Sensors 2025, 25(4), 1264; https://doi.org/10.3390/s25041264 - 19 Feb 2025
Viewed by 386
Abstract
Perennial ryegrass is an important temperate grass used for forage and turf worldwide. It forms symbiotic relationships with endophytic fungi (endophytes), conferring pasture persistence and resistance to herbivory. Endophyte performance can be influenced by the host genotype, as well as environmental factors such [...] Read more.
Perennial ryegrass is an important temperate grass used for forage and turf worldwide. It forms symbiotic relationships with endophytic fungi (endophytes), conferring pasture persistence and resistance to herbivory. Endophyte performance can be influenced by the host genotype, as well as environmental factors such as seed storage conditions. It is therefore critical to confirm seed quality and purity before a seed is sown. DNA-based methods are often used for quality control purposes. Recently, near-infrared spectroscopy (NIRS) coupled with hyperspectral imaging was used to discriminate perennial ryegrass cultivars and endophyte presence in individual seeds. Here, a NIRS-based analysis of bulk seeds was used to develop models for discriminating perennial ryegrass cultivars (Alto, Maxsyn, Trojan and Bronsyn), each hosting a suite of eight to eleven different endophyte strains. Sub-sampling, six per bag of seed, was employed to minimize misclassification error. Using a nested PLS-DA approach, cultivars were classified with an overall accuracy of 94.1–98.6% of sub-samples, whilst endophyte presence or absence was discriminated with overall accuracies between 77.8% and 96.3% of sub-samples. Hierarchical classification models were developed to discriminate bulked seed samples quickly and easily with minimal misclassifications of cultivars (<8.9% of sub-samples) or endophyte status within each cultivar (<11.3% of sub-samples). In all cases, greater than four of the six sub-samples were correctly classified, indicating that innate variation within a bag of seeds can be overcome using this strategy. These models could benefit turf- and pasture-based industries by providing a tool that is easy, cost effective, and can quickly discriminate seed bulks based on cultivar and endophyte content. Full article
(This article belongs to the Special Issue Spectroscopy for Biochemical Imaging and Sensing)
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14 pages, 3937 KiB  
Article
Concentration vs. Optical Density of ESKAPEE Bacteria: A Method to Determine the Optimum Measurement Wavelength
by Bruno Wacogne, Marine Belinger Podevin, Naïs Vaccari, Claudia Koubevi, Céline Codjiová, Emilie Gutierrez, Lucie Davoine, Marjorie Robert-Nicoud, Alain Rouleau and Annie Frelet-Barrand
Sensors 2024, 24(24), 8160; https://doi.org/10.3390/s24248160 - 21 Dec 2024
Cited by 2 | Viewed by 2068
Abstract
Optical density measurement has been used for decades to determine the microorganism concentration and more rarely for mammalian cells. Although this measurement can be carried out at any wavelength, studies report a limited number of measurement wavelengths, mainly around 600 nm, and no [...] Read more.
Optical density measurement has been used for decades to determine the microorganism concentration and more rarely for mammalian cells. Although this measurement can be carried out at any wavelength, studies report a limited number of measurement wavelengths, mainly around 600 nm, and no consensus seems to be emerging to propose an objective method for determining the optimum measurement wavelength for each microorganism. In this article, we propose a method for analyzing the absorbance spectra of ESKAPEE bacteria and determining the optimum measurement wavelength for each of them. The method is based on the analysis of the signal-to-noise ratio of the relationships between concentrations and optical densities when the measurement wavelength varies over the entire spectral range of the absorbance spectra measured for each bacterium. These optimum wavelengths range from 612 nm for Enterococcus faecium to 705 nm for Acinetobacter baumannii. The method can be directly applied to any bacteria, any culture method, and also to any biochemical substance with an absorbance spectrum without any particular feature such as an identified maximum. Full article
(This article belongs to the Special Issue Spectroscopy for Biochemical Imaging and Sensing)
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