About the BioSpec group
The BioSpec group has been at the forefront of national and international research in the field for several years, and has a broad portfolio of projects within the field, as well as a strong national and international network. The group focuses on the following research areas:
- Advanced vibrational spectroscopy of different biosystems - cells, tissues, and bioliquids
- Developing and optimizing microbial bioprocesses for the production of a wide range of bioproducts
- Understanding and modelling of scattering phenomena of systems in environmental sciences
- Data modelling of spectroscopic data
Bioprocesses and biosystems
Infrared spectroscopy (IR) of intact microbial cells provides highly specific fingerprint-like signatures, which reveals the total biochemical composition of the cell.
These fingerprints are used to characterize, differentiate, classify and identify different microbial species and strains. Microbial IR spectra can be used to detect intracellular compounds or structures such as inclusion bodies, storage materials and endospores. Infrared spectroscopy serves as an identification tool when the recorded spectrum is compared to reference spectral libraries and can also be applied in monitoring different microbial processes, such as fermentation.
Contact persons for Bioprocesses and Biosystems at the BioSpec group:
- Storaker Myrbråten I., Stamsås G.A., Chan H., Morales Angeles D., Mathiesen Knutsen T., Salehian Z., Shapaval V., Straume D., Kjos M.
SmdA is a Novel Cell Morphology Determinant in Staphylococcus aureus.
mBio 13 (2022) e03404-21 - Gaykawad S.S., Ramanand S.S., Blomqvist J., Zimmermann B., Shapaval V., Kohler A., Oostindjer M., Boccadoro C.
Submerged Fermentation of Animal Fat By-Products by Oleaginous Filamentous Fungi for the Production of Unsaturated Single Cell Oil
Fermentation 7 (2021) 300 - Dzurendova S., Shapaval V., Tafintseva V., Kohler A., Byrtusová D., Szotkowski M., Márová I., Zimmermann B.
Assessment of Biotechnologically Important Filamentous Fungal Biomass by Fourier Transform Raman Spectroscopy
International Journal of Molecular Sciences 22 (2021) 6710 - Carnovale G., Rosa F., Shapaval V., Dzurendova S., Kohler A., Wicklund T., Horn S.J., Barbosa M.J., Skjånes K.
Starch Rich Chlorella vulgaris: High-Throughput Screening and Up-Scale for Tailored Biomass Production
Applied Sciences 11 (2021) 9025 - Tafintseva V., Shapaval V., Blazhko U., Kohler A.
Correcting replicate variation in spectroscopic data by machine learning and model-based pre-processing
Chemometrics and Intelligent Laboratory Systems 215 (2021) 104350 - Byrtusová D., Szotkowski M., Kurowska K., Shapaval V., Márová I.
Rhodotorula kratochvilovae CCY 20-2-26—The Source of Multifunctional Metabolites
Microorganisms 9 (2021) 1280 - Brandenburg J., Blomqvist J., Shapaval V., Kohler A., Sampels S., Sandgren M., Passoth V.
Oleaginous yeasts respond differently to carbon sources present in lignocellulose hydrolysate
Biotechnology for Biofuels volume 14 (2021) 124 - Dzurendova S., Zimmermann B., Kohler A., Reitzel K., Nielsen U.G., Dupuy--Galet B.X., Leivers S., Horn S.J., Shapaval V.
Calcium affects polyphosphate and lipid accumulation in Mucoromycota fungi
Journal of Fungi 7 (2021) 300 - Langseter A.M., Dzurendova S., Shapaval V., Kohler A., Ekeberg D., Zimmermann B.
Evaluation and optimisation of direct transesterification methods for the assessment of lipid accumulation in oleaginous filamentous fungi
Microbial Cell Factories 20 (2021) 59 - Slaný O. , Klempová T., Shapaval V., Zimmermann B., Kohler A., Čertík M.
Animal Fat as a Substrate for Production of n-6 Fatty Acids by Fungal Solid-State Fermentation
Microorganisms 9 (2021) 170 - Smirnova M., Miamin U., Kohler A., Valentovich L., Akhremchuk A., Sidarenka A., Dolgikh A., Shapaval V.
Isolation and characterization of fast‐growing green snow bacteria from coastal East Antarctica
MicrobiologyOpen, 10 (2021) e1152 - Dzurendova S., Zimmermann B., Tafintseva V., Kohler A., Horn S.J., Shapaval V.
Metal and Phosphate Ions Show Remarkable Influence on the Biomass Production and Lipid Accumulation in Oleaginous Mucor circinelloides
Journal of Fungi 6 (2020) 260 - Dzurendova S., Zimmermann B., Tafintseva V., Kohler A., Ekeberg D., Shapaval V.
The influence of phosphorus availability and the nature of nitrogen on the biomass production and accumulation of lipids in oleaginous Mucoromycota fungi
Applied Microbiology and Biotechnology 104 (2020) 8065 - Byrtusová D., Shapaval V., Holub J., Šimanský S., Rapta M., Szotkowski M., Kohler A., Márová I.
Revealing the Potential of Lipid and β-Glucans Coproduction in Basidiomycetes Yeast
Microorganisms 8 (2020) 1034 - Dzurendova S., Zimmermann B., Kohler A., Tafintseva V., Slany O., Certik M., Shapaval V.
Microcultivation and FTIR spectroscopy-based screening revealed a nutrient-induced co-production of high-value metabolites in oleaginous Mucoromycota fungi
PLoS ONE 15 (2020) e0234870 - Meyer V., Basenko E.Y., Benz J.P., Braus G.H., Caddick M.X., Csukai M., de Vries R.P., Endy D., Frisvad J.C., Gunde‑Cimerman N., Haarmann T., Hadar Y., Hansen K., Johnson R.I., Keller N.P., Kraševec N., Mortensen U.H., Perez R., Ram A.F.J., Record E., Ross P., Shapaval V., Steiniger C., van den Brink H., van Munster J., Yarden O., Wösten H.A.B.
Growing a circular economy with fungal biotechnology: a white paper
Fungal Biology and Biotechnology 7 (2020) 5 - Szotkowski M., Byrtusova D., Haronikova A., Vysoka M., Rapta M., Shapaval V., Marova I.
Study of Metabolic Adaptation of Red Yeasts to Waste Animal Fat Substrate
Microorganisms 7 (2019) 578 - Xiong Y., Shapaval V., Kohler A., Li J., From PJ.
A Fully Automated Robot for the Preparation of Fungal Samples for FTIR Spectroscopy Using Deep Learning
IEEE Access 7 (2019) 132763-132774 - Xiong Y., Shapaval V., Kohler A., From PJ.
A Laboratory-Built Fully Automated Ultrasonication Robot for Filamentous Fungi Homogenization
SLAS Technology (2019) 1-13 - Shapaval V., Brandenburg J., Blomqvist J., Tafintseva V., Passoth V., Sandgren M., Kohler A.
Biochemical profiling, prediction of total lipid content and fatty acid profile in oleaginous yeasts by FTIR spectroscopy
Biotechnology for Biofuels 12 (2019) 140 - Kosa G., Vuoristo K., Horn S.J., Zimmermann B., Afseth N.K., Kohler A., Shapaval V.
Assessment of the scalability of a microtiter plate system for screening of oleaginous microorganisms
Applied Microbiology and Biotechnology 102 (2018) 4915 - Kosa G., Zimmermann B., Kohler A., Ekeberg D., Afseth N.K., Mounier J., Shapaval V.
High-throughput screening of Mucoromycota fungi for production of low- and high value lipids
Biotechnology for Biofuels 11:66 (2018) - Tafintseva V., Vigneau E., Shapaval V., Cariou V., Qannari E.M., Kohler A.
Hierarchical classification of microorganisms based on high-dimensional phenotypic data
Journal of Biophotonics 11 (2018) - Tzimorotas D., Afseth N. K., Lindberg D., Kjørlaug O., Axelsson L., Shapaval V.
Pretreatment of different food rest materials for bioconversion into fungal lipid-rich biomass
Journal of Bioprocess and Biosystems Engineering 41 (2018) 1039. - Vanek M., Mravec F., Szotkowski M., Byrtusova D., Haronikova A., Certik M., Shapaval V., Marova I.
Fluorescence lifetime imaging of red yeast Cystofilobasidium capitatum during growth
The EuroBiotech Journal 2 (2018) 114. - Kosa G., Shapaval V., Kohler A., Zimmermann B.
FTIR spectroscopy as a unified method for simultaneous analysis of intra- and extracellular metabolites in high-throughput screening of microbial bioprocesses
Microbial Cell Factories 16 (2017) 195 - Forfang, K., Zimmermann B., Kosa, G. Kohler A., Shapaval V.
FTIR spectroscopy for evaluation and monitoring of lipid extraction efficiency for oleaginous fungi
PLOS One 12 (2017) e0170611. - Kosa G., Kohler A., Tafintseva V., Zimmermann B., Forfang K., Afseth N.K., Tzimorotas D., Vuoristo K.S., Horn S.J., Mounier J., Shapaval V.
Microtiter plate cultivation of oleaginous fungi and monitoring of lipogenesis by high-throughput FTIR spectroscopy
Microbial Cell Factories 16(2017) 101 - Marova I., Rapta M., Vanek M., Haronikova A., Szotkowski M., Shapaval V.
Use of high-throughput techniques to study simultaneous production of lipid metabolites in carotenogenic yeasts grown on waste animal fat.
Journal of Biotechnology 256 (2017) 42. - Shapaval V., Møretrø T., Suso H-P., Schmitt J., Lilehaug D., Kohler A.
A novel library-independent approach based on FTIR spectroscopy for source tracking of moulds contamination in food
Letters in Applied Microbiology 64 (2017) 335 - Colabella C., Corte L., Roscini L., Shapaval V., Kohler A., Tafintseva V., Tascini C., Cardinali G.
Merging FT-IR and NGS for simultaneous phenotypic and genotypic identification of pathogenic Candida species
PLoS One 12 (2017) e0188104 - Marova I., Szotkowski M., Vanek M., Rapta M., Byrrtusova D., Mikheichyk N., Haronikova A., Certik M., Shapaval V.
Utilization of animal fat waste as carbon source by carotenogenic yeasts – a screening study
The EuroBiotech Journal 1 (2017) 310 - Li J., Shapaval V., Kohler A., Talintyre R., Schmitt J., Stone R., Gallant A.J., Zeze D.A.
A Modular Liquid Sample Handling Robot for High-Throughput Fourier Transform Infrared Spectroscopy
In Ding X., Kong X. & Dai S.J. (eds) Advances in Reconfigurable Mechanics and Robotics II (2015). Cham: Springer International Publishing - Shapaval, V., Afseth, N.K., Vogt, G., Kohler, A
Fourier Transform Infrared Spectroscopy for the prediction of fatty acid profiles in Mucor fungi in media with different carbone sources
Microbial Cell Factories 4 (2014) - Kohler, A., Boecker, U., Shapaval, V., Forsmark, A., Anderssion, M., Warringer, J., Martens, H., Omholt, S.W., Blomberg, A.
High-throughput biochemical fingerprinting of Saccharomyces cerevisiae by Fourier transform infrared spectroscopy
PLOS One 10 (2014) e0118052 - Hovde Liland, K., Kohler A., Shapaval V.
Hot PLS—a framework for hierarchically ordered taxonomic classification by partial least squares
Chemometrics and Intelligent Laboratory Systems 15 (2014) - Shapaval V., Schmitt J., Møretrø T., Suso HP, Skaar I., Åsli AW., Lilehaug D., and Kohler A.
Characerization of food spoilage fungi by FTIR spectroscopy
Journal of Applied Microbiology 114 (2013) - Shapaval V., Walczak B., Gognies S., Møretrø T., Suso HP, Åsli AW., Belarbi A., and Kohler A.
FTIR spectroscopic characterization of differently cultivated food related yeasts
Analyst 138 (2012) - Shapaval V., Møretrø T., Suso HP, Åsli AW., Schmitt J., Lilehaug D., Martens H, Boecker U., and Kohler A.
A high-throughput microcultivation protocol for FTIR spectroscopic characterization and identification of fungi
Journal of Biophotonics 3 (2010)
- Storaker Myrbråten I., Stamsås G.A., Chan H., Morales Angeles D., Mathiesen Knutsen T., Salehian Z., Shapaval V., Straume D., Kjos M.
- SAFE - Sustainable aquaculture feed based on novel biomass from wood by-products
NordForsk (The Nordic Research and Innovation Programme for Sustainable Aquaculture, project Nº. 103506). Coordinator: Volha Shapaval. - COFUN - Developing co-production of lipids and chitosan in oleaginous filamentous fungi
Research Council of Norway (DAAD Mobility, project Nº. 309220). Coordinator: Volha Shapaval. - Industrial Biotechnology - Centre for Industrial Biotechnology
Research Council of Norway (SFI, project Nº. 309558). Coordinator: SINTEF - BYPROVALUE - Multifunctional high-value fungal biomass from the Norwegian agriculture supply chain by-products
Research Council of Norway (MATFONDAVTALE, project Nº. 301834). Coordinator: Volha Shapaval. - SLUDGErecover - Bio-recovery of nutrients from aquaculture sludge by the production of high-value biomass
MABIT. Coordinator: Aquaculture Innovations AS. - Oil4Feed - Oil from oleaginous microbial biomass derived from Norwegian resources as a sustainable alternative to replace Fish/Plant oils in fish feed
Research Council of Norway (HAVBRUK 2, project Nº. 302543). Coordinator: Volha Shapaval. - LIGNOLIPP - From lignocellulose sugars to high-value lipids and biopolymers in a single fermentation process
Research Council of Norway - Bioeconomy in the North (BIONÆR, project Nº. 305215). Coordinator: Volha Shapaval. - Bio4Fuels - Centre for Environment-friendly Energy Research
Research Council of Norway (FMETEKN, project Nº. 257622). Coordinator: NMBU. - SOLEIL 2019 - Synchrotron infrared micro- and nano-spectroscopy of lipid bodies of oleaginous fungi
SOLEIL, French national synchrotron facility (SOLEIL, project Nº. 20181079). Coordinator: NMBU and SOLEIL. - Belanoda - Multidisciplinary graduate and post-graduate education in big data analysis for life sciences
Senter for internasjonalisering av utdanning (SiU-CPEA-LT, project Nº. 2016/10126). Coordinator Norway: Achim Kohler. - LipoFungi - Bioconversion of low-cost fat materials into high-value PUFA-Carotenoid-rich biomass
Research Council of Norway (BIONÆR, project Nº. 268305). Coordinator: Achim Kohler. - FunLip - Single cell lipidomics of oleaginous microorganisms by modern vibrational spectroscopy
Research Council of Norway (IS-AUR, project Nº. 281357). Coordinator: Volha Shapaval. - Single Cell Oil - Single cell oil PUFA production by food rest materials
Research Council of Norway (BIONÆR, project Nº. 234258). Coordinator: NutraQ AS. Project manager: Achim Kohler. - FUST - Source tracking and monitoring of mould contamination in food production
European Commision (FP7-SME project Nº. 315271). Coordinator: Nofima.
- SAFE - Sustainable aquaculture feed based on novel biomass from wood by-products
Data science
Our group is specialized on the analysis of high-dimensional data in the field of life sciences. We are developing tools for the integration of different types of data from life sciences such as FTIR and Raman spectroscopy data, data from proteomics, metabolomics, DNA, mRNA. We are specialized in methods based on latent variables. Examples are multiblock methods for the integration of different types of data and sparse methods for biomarker detection.
Members of our group have invested heavily in being at the forefront in advanced multivariate data analysis for vibrational spectroscopic techniques (FTIR and Raman etc.) for many years. We have contributed substantially to the development of pre-processing techniques for the separation of scatter contributions from chemical information for infrared spectra of biological materials. These techniques are widely used in the field of life sciences and in the medical.
We are developing techniques for classification and calibration, which are tailored for FTIR spectroscopic data from biological materials. FTIR spectroscopy has been proven a powerful tool for the identification and characterization of microorganisms such as bacteria, yeasts, moulds and pollen. It is a sensitive biophysical technique, which performs microbial identification at the species and in some cases even strains level. Spectral reference libraries are used to establish hierarchical classification trees that allow identification of microorganisms at different taxonomic levels. We are specialized on sparse calibration methods. These methods allow establishing robust calibration models which can easily be interpreted. Biomarker selection tools provide valuable information on the principal differences among classes.
In addition to identification, biochemical composition of microorganisms can be obtained from FTIR analysis using Sparse PLSR based models. This allows screening lots of strains for oil production or other valuable components in microorganisms. We are specialized on establishing calibration models for the prediction of metabolites in cells by FTIR spectroscopy. Examples are the use of FTIR spectroscopy for estimating lipid profiles in biotechnologically relevant strains.
Orange and Quasar:
Orange is an open-source data visualization, machine learning and data mining toolkit. It features a visual programming front-end for explorative data analysis and interactive data visualization, and can also be used as a Python library. This science platform contains a number of data mining tools for classification, prediction and visualization for multivariate spectral data. It was recently extended to Orange Infrared, with tools specifically developed for the visualization and analysis of vibrational spectra, by an international initiative in which BioSpec Norway is heavily involved. It contains handy visualization tools for vibrational spectroscopic data for all scales. It allows visualization of complex vibrational spectroscopy data such as 3D data cubes from macro and nano vibrational spectroscopy. The Orange Platform is currently being extended to Orange Infrared by an international initiative in which BioSpec Norway is heavily involved. See the tutorial video for Spectral Orange, a part of Orange for analyzing spectroscopy data:
Quasar is an open source project, a collection of data analysis toolboxes extending the Orange suite.
Contact persons for Data Science at the BioSpec group:
- Kong B., Brandsrud M.A., Heitmann Solheim J., Nedrebø I., Blümel R., Kohler A.
Effects of the coupling of dielectric spherical particles on signatures in infrared microspectroscopy
Scientific Reports 12 (2022) 13327 - Akulava V., Miamin U., Akhremchuk K., Valentovich L., Dolgikh A., Shapaval V.
Isolation, Physiological Characterization, and Antibiotic Susceptibility Testing of Fast-Growing Bacteria from the Sea-Affected Temporary Meltwater Ponds in the Thala Hills Oasis (Enderby Land, East Antarctica).
Biology 11 (2022) 1143 - Smirnova M., Tafintseva V., Kohler A., Miamin U., Shapaval V.
Temperature-and Nutrients-Induced Phenotypic Changes of Antarctic Green Snow Bacteria Probed by High-Throughput FTIR Spectroscopy.
Biology 11 (2022) 890 - Rehman H.U., Tafintseva V., Zimmermann B., Solheim J., Virtanen V., Shaikh R., Nippolainen E., Afara I., Saarakkala S, Rieppo L., Krebs P., Fomina P., Mizaikoff B., Kohler A.
Preclassification of broadband and sparse infrared data by multiplicative signal correction approach.
Molecules 27 (2022) 2298 - Virtanen V., Tafintseva V., Shaikh R., Nippolainen E., Haas J., Afara I., Töyräs J., Kröger H., Solheim J., Zimmermann B., Kohler A., Mizaikoff B., Finnilä M., Rieppo L., Saarakkala S.
Infrared spectroscopy is suitable for objective assessment of articular cartilage health
Osteoarthritis and Cartilage Open 4 (2022) 100250 - Tafintseva V., Lintvedt T.A., Solheim J., Zimmermann B., Rehman H.U., Virtanen V., Shaikh R., Nippolainen E., Afara I., Saarakkala S, Rieppo L., Krebs P., Fomina P., Mizaikoff B., Kohler A.
Preprocessing Strategies for Sparse Infrared Spectroscopy: A Case Study on Cartilage Diagnostics.
Molecules 27 (2022) 873 - Heitmann Solheim J., Borondics F., Zimmermann B., Sandt C., Muthreich F., Kohler A.
An automated approach for fringe frequency estimation and removal in infrared spectroscopy and hyperspectral imaging of biological samples
Journal of Biophotonics 14 (2021) e202100148 - Figoli C.B., Garcea M., Bisioli C., Tafintseva V., Shapaval V., Gómez Peña M., Gibbons L., Althabe F., Yantorno O.M., Horton M., Schmitt J., Lasch P., Kohler A., Bosch A.
A robust metabolomics approach for the evaluation of human embryos from in vitro fertilization
Analyst 146 (2021) 6156 - Blazhko U., Shapaval V., Kovalev V., Kohlera A.
Comparison of augmentation and pre-processing for deep learning and chemometric classification of infrared spectra
Chemometrics and Intelligent Laboratory Systems 215 (2021) 104367. - Virtanen V., Nippolainen E., Shaikh R., Afara I.O., Töyräs J., Solheim J., Tafintseva V., Zimmermann B., Kohler A., Saarakkala S., Rieppo L.
Infrared Fiber-Optic Spectroscopy Detects Bovine Articular Cartilage Degeneration
Cartilage (2021) - Curtasu M.V., Tafintseva V., Bendiks Z., Marco M.L., Kohler A., Xu Y., Nørskov N.P., Nygaard Lærke H., Knudsen K.E.B., Hedemann M.S.
Obesity-Related Metabolome and Gut Microbiota Profiles of Juvenile Göttingen Minipigs—Long-Term Intake of Fructose and Resistant Starch
Metabolites 10 (2020) 456 - Tafintseva V., Shapaval V., Smirnova M., Kohler A.
Extended multiplicative signal correction for FTIR spectral quality test and pre‐processing of infrared imaging data.
Journal of Biophotonics 13 (2020) e201960112 - Trukhan S., Tafintseva V., Tøndel K., Großerueschkamp F., Mosig A., Kovalev V., Gerwert K., Kohler A.
Grayscale representation of infrared microscopy images by Extended Multiplicative Signal Correction for registration with histological images.
Journal of Biophotonics 13 (2020) e201960223 - Sirovica, S., Heitmann Solheim J., Skoda, M.W.A., Hirschmugl C.J., Mattson E.C., Aboualizadeh E., Guo Y., Chen X., Kohler A., Romanyk D.L., Rosendahl S.M., Morsch S., Martin R.A., Addison O.
Origin of micro-scale heterogeneity in polymerisation of photo-activated resin composites.
Nature Communications 11 (2020) 1849 - Kohler A., Solheim J., Tafintseva V., Zimmermann B., Shapaval V.
Model-Based Pre-Processing in Vibrational Spectroscopy
Comprehensive Chemometrics, Second Edition (2020) 83 - Tafintseva V., Shapaval V., Smirnova M., Kohler A.
Extended multiplicative signal correction for FTIR spectral quality test and pre‐processing of infrared imaging data.
Journal of Biophotonics 13 (2020) e201960112 - Solheim J., Gunko E., Petersen D., Grosserruschkamp F., Gerwert K., Kohler A.
An open source code for Mie Extinction EMSC for infrared microscopy spectra of cells and tissues.
Journal of Biophotonics 12 (2019) e201800415 - Guoa S., Kohler A., Zimmermann B., Heinke R., Stöckel S., Rösch P., Popp J., Bocklitz T.
EMSC based model transfer for Raman spectroscopy in biological applications.
Analytical Chemistry 90 (2018) 9787. - Tafintseva V., Vigneau E., Shapaval V., Cariou V., Qannari E.M., Kohler A.
Hierarchical classification of microorganisms based on high-dimensional phenotypic data.
Journal of Biophotonics 11 (2018) - Karaman I., Nørskov N.P., Yde C.C., Skou Hedemann M., Bach Knudsen K.E., Kohler A.
Sparse multi-block PLSR for biomarker discovery when integrating data from LC-MS and NMR metabolomics.
Metabolomics 11 (2015) 367. - Shapaval V., Afseth N.K., Vogt G., Kohler A.
Fourier Transform Infrared Spectroscopy for the prediction of fatty acid profiles in Mucor fungi in media with different carbone sources.
Microbial Cell Factories 4 (2014) - Kohler A., Boecker U., Shapaval V., Forsmark A., Anderssion M., Warringer J., Martens H., Omholt S.W., Blomberg A.
High-throughput biochemical fingerprinting of Saccharomyces cerevisiae by Fourier transform infrared spectroscopy.
PLOS One 10 (2014) e0118052 - Hovde Liland K., Kohler A., Shapaval V.
Hot PLS—a framework for hierarchically ordered taxonomic classification by partial least squares.
Chemometrics and Intelligent Laboratory Systems 15 (2014) - Hassani S., Hanafi M., Qannari M., Kohler A.
Deflation strategies for multi-block principal component analysis revisited.
Chemometrics and Intelligent Laboratory Systems. 120 (2013) 154–168. - Karaman I., Qannari M., Martens H., Skou Hedemann M., Bach Knudsen K.E., Kohler A.,
Comparison of Sparse and Jack-knife partial least squares regression methods for variable selection.
Chemometrics and Intelligent Laboratory Systems. 122 (2013) 65-77. - Eslami A., Qannari E.M., Kohler A., Bougeard S.
Analyses factorielles de données structurées en groupes d’individus (Multivariate data analysis of multi-group datasets).
Journal de la Société Française de Statistique 44 (2013) 2102. - Eslami A., Qannari E.M., Kohler A., Bougeard S.,
General overview of methods of analysis of multi-group datasets.
Revue des Nouvelles Technologies de l’information (RNTI) 25 (2013) 113. - Shapaval V., Schmitt J., Møretrø T., Suso HP, Skaar I., Åsli AW., Lilehaug D., and Kohler A.
Characerization of food spoilage fungi by FTIR spectroscopy.
Journal of Applied Microbiology 114 (2013) - Hassani S., Martens H., Qannari M., Kohler A.
Degrees of freedom estimation in Principal Component Analysis and consensus principal component analysis.
Chemometrics and Intelligent Laboratory Systems 118 (2012) 246-259 - Hassani S., Martens H., Qannari M., Hanafi M., Kohler A.
Model validation and error estimation in multi-block partial least squares regression.
Chemometrics and Intelligent Laboratory Systems 117 (2012) 42-53 - Hanafi M., Kohler A., Qannari M.
Connections between multiple co-inertia analysis and consensus principal component analysis.
Chemometrics and Intelligent Laboratory Systems 106 (2011) 37-40. - Hanafi M., Kohler A., Quannari, M.
Shedding new light on Hierarchical Principal Component Analysis.
Journal of Chemometics 24 (2010) 703-709. - Hassani S., Martens H., Qannari M., Hanafi M., Borge G.I., Kohler A.
Analysis of –omics data: Graphical interpretation- and validation tools in multi–block methods.
Chemometrics and Intelligent Laboratory Systems 104 (2010) 140-153.
- Kong B., Brandsrud M.A., Heitmann Solheim J., Nedrebø I., Blümel R., Kohler A.
- PHOTONFOOD - Flexible Mid-Infrared Photonic Solution for Rapid Farm-to-Fork Sensing of Food Contaminants
European Commision (H2020-ICT-2020-2, Project Nº 101016444). Coordinator: Achim Kohler. - DigiFoods - Digital Food Quality
Research Council of Norway (SFI project Nº. 309259). Coordinator: Nofima. - DeepHyperSpec - Combining spectral and image information in the analysis of hyperspectral imaging data
Research Council of Norway (FRINATEK project Nº. 289518). Coordinator: Achim Kohler. - Belanoda - Multidisciplinary graduate and post-graduate education in big data analysis for life sciences
Senter for internasjonalisering av utdanning (SiU-CPEA-LT-2016/10126). Coordinator Norway: Achim Kohler. - MIRACLE - Mid-infrared arthroscopy innovative imaging system for real-time clinical in depth examination and diagnosis of degenerative joint diseases
European Commision (H2020-ICT Nº. 780598). Coordinator: University of Oulu. - LipoFungi - Bioconversion of low-cost fat materials into high-value PUFA-Carotenoid-rich biomass
Research Council of Norway (BIONÆR, project Nº. 268305) - Single Cell Oil - Single cell oil PUFA production by food rest materials
Research Council of Norway (BIONÆR, project Nº. 234258). Coordinator: Achim Kohler. - BigSpecData - Data analysis for big vibrational spectroscopic data
Research Council of Norway (IS-AUR, project Nº. 281263). Coordinator: Achim Kohler. - FUST - Source tracking and monitoring of mould contamination in food production
European Commision (FP7-SME Nº. 315271). Coordinator: Nofima. - MERITS - Development and mitigation of metabolic syndrome
Innovation Fund Denmark (Grant Nº. 2014-5158). Coordinator: Aarhus University. - AMS - New approaches for management and breeding of dairy cows in automatic milking systems
Research Council of Norway (MATFONDAVTALE, Project Nº 244231). Coordinator: VET, NMBU.
- PHOTONFOOD - Flexible Mid-Infrared Photonic Solution for Rapid Farm-to-Fork Sensing of Food Contaminants
Scattering and absorption in infrared biospectroscopy and in energy physics
When electromagnetic radiation impinges on an scatterer, in general, a part of the radiation power is scattered, another part is absorbed and the rest of the radiation power is transmitted through the obstacle. In infrared transmission spectroscopy, the transmitted light is collected in order to identify the part that is lost from the initial radiation power of the source. The lost part is expected to describe the absorption properties of the scatterer. When a substantial part of the light is lost due to scattering, the interpretation of the data becomes difficult, since it is difficult to decide if the radiation power at a certain wavelength is lost due to scattering or chemical absorption. If the wavelength of the electromagnetic wave is comparable to the size of the scatterer, the part of the radiation power that is lost due to scattering is very high. When the scatterer has spherical symmetry, the scattering is called Mie type scattering.
Scattering spectra Photo: Rozalia Lukacs In the infrared spectroscopy of single cells and tissues, strong Mie scattering signatures distort the spectra. The chemical interpretation of the absorption peaks and the multivariate analysis is difficult in this case. Therefore, there is a need for algorithms that can separate the chemical information (absorption) from the physical properties (scattering). Has during recent years contributed substantially to the development of spectral correction methods for removing Mie type scattering and other spectral distortions. The group developed algorithms that are today used by a broad community in the field.
Contact persons for Scattering at the BioSpec group
- Kong B., Brandsrud M.A., Heitmann Solheim J., Nedrebø I., Blümel R., Kohler A.
Effects of the coupling of dielectric spherical particles on signatures in infrared microspectroscopy
Scientific Reports 12 (2022) 13327 - Solheim J.H., Zimmermann B., Tafintseva V., Dzurendová S., Shapaval V., Kohler A.
The Use of Constituent Spectra and Weighting in Extended Multiplicative Signal Correction in Infrared Spectroscopy.
Molecules 27 (2022) 1900 - Heitmann Solheim J., Borondics F., Zimmermann B., Sandt C., Muthreich F., Kohler A.
An automated approach for fringe frequency estimation and removal in infrared spectroscopy and hyperspectral imaging of biological samples.
Journal of Biophotonics 14 (2021) e202100148 - Seim E., Kohler A., Lukacs R., Brandsrud M.A, Marstein E.S, Olsen E., Blümel R.
Wave chaos enhanced light trapping in optically thin solar cells
Chaos 31 (2021) 063136 - Blazhko U., Shapaval V., Kovalev V., Kohlera A.
Comparison of augmentation and pre-processing for deep learning and chemometric classification of infrared spectra
Chemometrics and Intelligent Laboratory Systems 215 (2021) 104367. - Brandsrud M.A., Blümel R., Lukacs R., Seim E., Stensrud Marstein E, Olsen E., Kohler A.
Investigation of resonance structures in optically thin solar cells
Journal of Photonics for Energy, 11 (2021) 024501. - Brandsrud M.A., Blümel R., Heitmann Solheim J., Kohler A.
The effect of deformation of absorbing scatterers on Mie-type signatures in infrared microspectroscopy
Scientific Reports 11 (2021) 4675 - Almklov Magnussen E., Heitmann Solheim J., Blazhko U., Tafintseva V., Tøndel K., Liland K.H., Dzurendova S., Shapaval V., Kohler A.
Deep convolutional neural network recovers pure absorbance spectra from highly scatter‐distorted spectra of cells
Journal of Biophotonics (2020) e202000204. - Schofield A.J., Blümel R., Kohler A., Lukacs R., Hirschmugl C.J.
Extracting pure absorbance spectra in infrared microspectroscopy by modeling absorption bands as Fano resonances.
Journal of Chemical Physics 150 (2019) 154124. - Heitmann Solheim J., Gunko E., Petersen D., Grosserruschkamp F., Gerwert K., Kohler A.
An open source code for Mie Extinction EMSC for infrared microscopy spectra of cells and tissues.
Journal of Biophotonics 12 (2019) e201800415 - Brandsrud M.A., Seim E., Lukacs R., Kohler A., Marstein E.S., Olsen E., Blümel R.
Exact ray theory for the calculation of the optical generation rate in optically thin solar cells.
Physica E: Low-dimensional Systems and Nanostructures 105 (2019) 125 – 138. - Seim E., Kohler A., Lukacs R., Brandsrud M.A, Stensrud Marstein E., Olsen E., Blümel R.
Chaos: A new mechanism for enhancing the optical generation rate in thin-film solar cells.
SPIE West 10913 (2019). Chaos 29 (2019) 093132 - Konevskikh T., Lukacs R., Kohler A.
An improved algorithm for fast resonant Mie scatter correction of infrared spectra of cells and tissues
Journal of Biophotonics 11 (2018) DOI: 10.1002/jbio.201600307 - Blümel R., Lukacs R., Zimmermann B., Bağcıoğlu M., Kohler A.
Observation of Mie ripples in the synchrotron FTIR spectra of spheroidal pollen grains.
Journal of the Optical Society of America A 35 (2018) 1769. - Azarfar G., Aboualizadeh E., Walter N.M., Ratti S., Olivieri C., Norici A., Nasse M., Kohler A., Giordano M., Hirschmugl C.J.
Estimating and correcting interference fringes in infrared spectra in infrared hyperspectral imaging.
Analyst 143 (2018) 4674. - Hovde Liland K., Kohler A., Afseth N.K.
Model-based pre-processing in Raman spectroscopy of biological samples.
Journal of Raman Spectroscopy (2016) DOI: 10.1002/jrs.4886. - Konevskikh T., Lukacs R., Blümel R., Ponossov A., Kohler A.
Mie scatter corrections in single cell infrared microspectroscopy.
Faraday Discussions 187 (2016) 235. - Konevskikh T., Ponossov A., Blumel R., Lukacs R., Kohler A.
Fringes in FTIR spectroscopy revisited: understanding and modelling fringes in infrared spectroscopy of thin films.
Analyst 140 (2015) 3969. - Lukacs R., Blümel R., Zimmermann B., Bağcıoğlu M., Kohler A.
Recovery of absorbance spectra of micrometer-sized biological and inanimate particles.
Analyst 140 (2015) 3273. - Zimmerman B., Kohler A.
Optimizing Savitzky-Golay parameters for improving spectral resolution and quantification in infrared spectroscopy. Applied Spectroscopy.
Applied Spectroscopy. 67 (2013) 892. - Bassan P., Sachdevaa A., Kohler A., Hughes C., Henderson A., Boyle J., Shanks J.H., Brown M., Clarke N.W., Gardner P.
FTIR Microscopy of biological cells and tissue: data analysis using resonant Mie scattering (RMieS) EMSC algorithm.
Analyst 137 (2012) 1370. - Afseth N.K., Kohler A.
Extended multiplicative signal correction in vibrational spectroscopy, a tutorial.
Chemometrics and Intelligent Laboratory Systems 117 (2012) 92. - Bassan P., Kohler A., Martens H., Lee J., Byrne H., Gardner P.
The RMieS-EMSC correction algorithm for infrared spectra of biological cells: Extension using full Mie scattering theory and speed optimisation using graphics processing unit (GPU) computing.
Biophotonics Journal 3 (2010) 609. - Bassan P., Kohler A., Martens H., Lee J., Byrne H.J., Dumas P., Gazi E., Brown M., Clarke N., Gardner P.
Resonant Mie Scattering (RMieS) Correction of Infrared Spectra from Highly Scattering Biological Samples.
Analyst 135 (2010) 268. - Kohler A., Böcker U., Warringer J., Blomberg A., Omholt S.W., Stark E., Martens H.
Reducing inter-replicate variation in Fourier-transform infrared spectroscopy by extended multiplicative signal correction.
Applied spectroscopy 63 (2009) 296. - Kohler A., Sulé-Suso J., Sockalingum G.D., Tobin M., Bahrami F., Yang Y., Pijanka J., Dumas P., Cotte M., Martens H.
Estimating and correcting Mie scattering in synchrotron based microscopic FTIR spectra by extended multiplicative signal correction (EMSC).
Applied Spectroscopy 62 (2008) 259. - Martens H., Bruun S.W., Adt I., Sockalingum G.D., Kohler A.
Pre-processing in biochemometrics: correction for path-length and temperature effects of water in FTIR bio-spectroscopy by EMSC.
Journal of Chemometrics 20 (2006) 402. - Bruun S.W., Kohler A., Adt I., Sockalingum G.D., Manfait M., Martens H.
Correcting attenuated total reflection-Fourier transform infrared spectra for water vapour and carbon dioxide.
Applied Spectroscopy 60 (2006) 1029. - Thennadil S., Martens H., Kohler A.
Physics-based Multiplicative Scatter Correction Approaches for Improving the Performance of Calibration Models.
Applied Spectroscopy 60 (2006) 315. - Kohler A., Kirschner C., Oust A., Martens H.
Extended multiplicative signal correction as a tool for separation and characterisation of physical and chemical information in Fourier transform infrared microscopy images of cryo-sections of beef loin.
Applied Spectroscopy 59 (2005) 707.
- Kong B., Brandsrud M.A., Heitmann Solheim J., Nedrebø I., Blümel R., Kohler A.
- DeepHyperSpec - Combining spectral and image information in the analysis of hyperspectral imaging data
Research Council of Norway (FRINATEK project Nº. 289518). Coordinator: Achim Kohler. - Development of a New Ray Model for Understanding the Coupling Between Dielectric Spheres for Photovoltaics with Higher Efficiency
Research Council of Norway (FRINATEK project Nº. 250678). Coordinator: Rozalia Lukacs. - Hyperspectral imaging in biophysics and energy physics
Research Council of Norway (ISPNATTEK project Nº. 216687). Coordinator: Achim Kohler. - Advancing 3D Chemical Imaging: FTIR Spectro-microtomography, FTIR Spectro-microlaminography and Hyperspectral Data Analysis
National Science Foundation - USA (Chemical Measurement & Imaging project Nº: 1508240). Coordinator: University of Wisconsin - Milwaukee.
- DeepHyperSpec - Combining spectral and image information in the analysis of hyperspectral imaging data
Spectroscopy in ecology and botany
Pollen and spores are the reproductive structures (microorganisms) of plants and fungi, and thus have key function during plant and fungal life cycles. Identification of pollen and spores provides useful information in various fields, for instance in public health for allergy forecasts, in ecology for monitoring of life cycles of vegetation and mycobiota, and in forensics for temporal and spatial determination of a criminal event. Unfortunately, current studies are still confined to visual measurements of pollen and spore morphologies under a microscope and the research has remained basically unchanged over the last hundred years. The identification requires laborious visual recognition of bioparticles by a skilled microscopist with specific knowledge of pollen and spore morphology.
Male cones with pollen of Mediterranean cypress (left) and Greek fir (right). The corresponding FTIR spectra of pollen (middle); the marked vibrational bands are associated with lipids (L), proteins (P), sporopollenins (S) and carbohydrates (C). Photo: Boris Zimmermann
Recently, infrared (FTIR) and Raman spectroscopies have attracted attention as methods for characterisation of plants and fungi. As opposed to morphological characterisation with microscopy, these two vibrational spectroscopy techniques offer an operator-independent approach based on chemical characterisation via identifiable spectral features. Roughly, a spectrum of a microorganism contains specific signatures of the constituent biomolecules, such as lipids, proteins, carbohydrates, pigments and grain wall biopolymers (sporopollenins, cellulose, glucan and chitin). These chemicals are the principal structural and nutritious components of microorganisms, and they are responsible for the majority of phenotypic attributes. Since the corresponding spectral signals of these chemicals are highly specific, vibrational spectroscopy is an excellent tool for biochemical analysis of plants and fungi.Contact persons for Spectroscopy of Ecology and Botany at the BioSpec group:
- Heitmann Solheim J., Borondics F., Zimmermann B., Sandt C., Muthreich F., Kohler A.
An automated approach for fringe frequency estimation and removal in infrared spectroscopy and hyperspectral imaging of biological samples
Journal of Biophotonics (2021) - Diehn S., Zimmermann B., Tafintseva V., Bağcıoğlu M., Kohler A., Ohlson M., Fjellheim S., Kneipp J.
Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains
Analytical and Bioanalytical Chemistry 412 (2020) 6459-6474 - Diehn S., Zimmermann S., Tafintseva V., Seifert S., Bagcioglu M., Ohlson M., Weidner S., Fjellheim S., Kohler A., Kneipp J.
Combining chemical information from grass pollen in multimodal characterization
Frontiers in Plant Science 10 (2020) 1788 - Muthreich F., Zimmermann B., Birks H.J.B., Vila‐Viçosa C.M., Seddon A.W.R.
Chemical variations in Quercus pollen as a tool for taxonomic identification: Implications for long‐term ecological and biogeographical research
Journal of Biogeography 47 (2020) 1298 - Kenđel A., Zimmermann B.
Chemical Analysis of Pollen by FT-Raman and FTIR Spectroscopies.
Frontiers in Plant Science 11 (2020) 352 - Seddon A.W.R., Festi D., Robson T.M., Zimmermann B.
Fossil pollen and spores as a tool for reconstructing ancient solar-ultraviolet irradiance received by plants: an assessment of prospects and challenges using proxy-system modelling
Photochemical and Photobiological Sciences 18 (2019) 275 - Innes S.N., Arve L.E., Zimmermann B., Nybakken L., Melby T.I., Solhaug K.A., Olsen J.E., Torre S.
Elevated air humidity increases UV mediated leaf and DNA damage in pea (Pisum sativum) due to reduced flavonoid content and antioxidant power
Photochemical and Photobiological Sciences 18 (2019) 387 - Diehn S., Zimmermann B., Bağcıoğlu M., Seifert S., Kohler A., Ohlson M., Fjellheim S., Weidner S., Kneipp J.
Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) shows adaptation of grass pollen composition
Scientific Reports 8 (2018) 16591. - Blümel R., Lukacs R., Zimmermann B., Bağcıoğlu M., Kohler A.
Observation of Mie ripples in the synchrotron FTIR spectra of spheroidal pollen grains
Journal of the Optical Society of America A 35 (2018) 1769 - Zimmermann B.
Chemical characterization and identification of Pinaceae pollen by infrared microspectroscopy.
Planta 247 (2018) 171. - Zimmermann B., Bağcıoğlu M., Tafinstseva V., Kohler A., Ohlson M., Fjellheim S.
A high-throughput FTIR spectroscopy approach to assess adaptive variation in pollen quality
Ecology and Evolution 7 (2017) 10839 - Bağcıoğlu M., Kohler A., Seifert S., Kneipp J., Zimmermann B.
Monitoring of plant-environment interactions by high throughput FTIR spectroscopy of pollen
Methods in Ecology and Evolution 8 (2017) 870 - Zimmermann B., Tafintseva V., Bağcıoğlu M., Høegh Berdahl M., Kohler A.
Analysis of allergenic pollen by FTIR microspectroscopy
Analytical Chemistry 88 (2016) 803 - Bağcıoğlu M., Zimmermann B., Kohler A.
A multiscale vibrational spectroscopic approach for identification and biochemical characterization of pollen
PLOS One 10 (2015) e0137899 - Zimmermann B., Bağcıoğlu M., Sandt C., Kohler A.
Vibrational microspectroscopy enables chemical characterization of single pollen grains as well as comparative analysis of plant species based on pollen ultrastructure
Planta 242 (2015) 1237 - Zimmermann B., Tkalčec Z., Mešić A., Kohler A.
Characterizing aeroallergens by infrared spectroscopy of fungal spores and pollen
PLOS One 10 (2015) e0124240 - Lukacs R., Blümel R., Zimmermann B., Bağcıoğlu M., Kohler A.
Recovery of absorbance spectra of micrometer-sized biological and inanimate particles
Analyst 140 (2015) 3273-3284 - Zimmermann B., Kohler A.
Infrared spectroscopy of pollen identifies plant species and genus as well as environmental conditions
PLOS One 9 (2014) e95417 - Zimmermann B.
Characterization of pollen by vibrational spectroscopy
Applied Spectroscopy 64 (2010) 1364
- Heitmann Solheim J., Borondics F., Zimmermann B., Sandt C., Muthreich F., Kohler A.
- QUEST-UV - Quantitative estimates of past UV-B irradiance from fossil pollen
Research Council of Norway (FRIMEDBIO, project Nº. 324670). Coordinator: University of Bergen. - Bessy Pollen - Selectivity of FTIR microspectra from single grass pollen grains for species identification
Helmholtz Zentrum Berlin (HZB projects Nº. 18207701 and 19107969). Coordinator: Boris Zimmermann. - PollChem - Pollen Chemistry as the Next Generation Tool in Palaeoecological Research – Theory, Methods and Applications
Research Council of Norway (FRIMEDBIO, project Nº. 249844). Coordinator: University of Bergen. - Pollen - Plant Phenotyping by Vibrational Spectroscopy of Pollen
European Commission, Research Executive Agency (FP7-PEOPLE-2012-IEF, project Nº. 328289). Coordinator: Achim Kohler. - PollenSvalbard - Phenotyping of flora of Svalbard by vibrational spectroscopy of pollen and seeds
Svalbard Science Forum (AFG project Nº. 246125, RiS 10113). Coordinator: Boris Zimmermann. - Combined FTIR and Raman analysis of pollen composition for studying plant adaptation to environmental changes
Research Council of Norway (DAADppp mobility grants, project Nº. 233941). Coordinator: Achim Kohler. - Synchrotron infrared microspectroscopy of pollen grains
SOLEIL, French national synchrotron facility (SOLEIL, project Nº. 20120345). Coordinator: NMBU and SOLEIL.
- QUEST-UV - Quantitative estimates of past UV-B irradiance from fossil pollen
Spectroscopy of food
Fourier Transform Infrared Spectroscopy (FTIR) has been shown to be a powerful tool for the food quality control and safety. One of the areas where FTIR is used is characterization of the chemical composition of milk in the dairy industry. Routine FTIR milk analyzers are used in milk production facilities all over the world to predict bulk parameters such as fat, lactose, protein, urea, pH, etc. Members of our group have been among the first researchers establishing calibration models for fatty acid composition. By these models in collaboration with IHA lipid profiles of millions of cows were obtained and used in breeding programs and for genetic improvement of milk quality: fat content and fat composition of milk. Since both characteristics are highly heritable traits they can be effectively improved by breeding.
In collaboration with ProMed at NMBU we have showed that FTIR spectra can not only provide the information of milk composition but also monitor cow’s health predicting health traits like energy balance (EB), dry matter intake (DMI) and efficient energy intake (EEI)) in lactating dairy cows as well as cows with subclinical ketosis.
Food safety is another area where FTIR spectroscopy is used as a powerful method. Our group is involved in research of new photonic devices that can be used along production chain. We are coordinating an EU project called PHOTONFOOD. The objective of the research project is to design a portable and flexible device to identify microbial and chemical contamination in the food production chain and in finished food products. The aim of developing, testing and demonstrating a compact, portable, adaptable and multifunctional technology solution is to significantly cut the costs of testing for fungi, mycotoxins, pesticides and antibiotics in all parts of the food chain.
Togeter with partners in Digital Food Quality (DigiFoods) we will be involved in the development of smart sensors for food quality assessment directly in the processing lines. The obtained information will be used for optimization of processes and value chains and make the food industry more efficient and sustainable.
Contact persons for Spectroscopy of Food at the BioSpec group:
- Knutsen T.M., Olsen H.G., Ketto I.A., Sundsaasen K.K, Kohler A., Tafintseva V., Svendsen M., Kent M.P., Lien S.
Genetic variants associated with two major bovine milk fatty acids offer opportunities to breed for altered milk fat composition.
Genetics Selection Evolution 54 (2022) 35 - Rachah A., Reksen O., Afseth N., Tafintseva V., Ferneborg S., Martin A., Kohler A., Prestløkken E.
Fourier transform infrared spectral data as a tool to predict energy balance, energy- and dry matter intake in lactating dairy cows
Journal of dairy research (2020) 1-8 - Knutsen T.M., Olsen H.G., Tafintseva V., Svendsen M., Kohler A., Kent M.P., Lien S.
Unravelling genetic variation underlying de novo-synthesis of bovine milk fatty acids.
Scientific reports 8 (2018) 2179. - Nørstebø H., Rachah A., Dalen G., Rønningen O., Whist A.C., Reksen O.
Milk-flow data collected routinely in an automatic milking system: an alternative to milking-time testing in the management of teat-end condition?
Acta Veterinaria Scandinavica 60:2 (2018) doi: 10.1186/s13028-018-0356-x. - Dalen G., Rachah A., Nørstebø H., Schukken Y.H., Gröhn Y.T., Barlow J.W., Reksen O.
Transmission dynamics of intramammary infections caused by Corynebacterium species.
Journal of Dairy Science 101 (2018) 472. - Rachah A., Dalen G., Reksen O., Nørstebø H., Barlow J.W.
Modelling and dynamics of intramammary infections caused by Corynebacterium species.
IEEE Xplore, 2017. doi:10.1109/ICMSAO.2017.7934858 - Olsen H.G., Knutsen T.M., Kohler A., Svendsen M., Gidskehaug L., Grove H., Nome T., Sodeland M., Sundsaasen K.K., Kent M.P., Martens H., Lien S.
Genome-wide association mapping for milk fat composition and fine mapping of a QTL for de novo synthesis of milk fatty acids on bovine chromosome 13.
Genetics Selection Evolution, 49:20 (2017) doi:10.1186/s12711-017-0294-5 - Martin A.D., Afseth N.K., Kohler A., Randby Å., Eknæs M., Waldmann A., Dørum G., Måge I., Reksen O.
The relationship between fatty acid profiles in milk identified by Fourier transform infrared spectroscopy and onset of luteal activity in Norwegian dairy cattle.
Journal of Dairy Science 98 (2015) 1. - Afseth N.K., Martens H., Giskehaug L., Narum B., Jørgensen K., Lien S., Haug A., Kohler A.
Predicting fatty acid composition of milk - A comparison of two FTIR sampling techniques.
Applied Spectroscopy 64 (2010) 700. - Martens H., Kohler A., Afseth N.K., Wold J.P., Hersleth M., Berget I., Ådnøy T., Skaugen M., Isaksson T., Vegarud G., Criscione A., Frøst M.B., Randby Å., Prestløkken E., Berg P., Kent M., Lien S., Omholt S.W.
High-throughput measurements for functional genomics of milk.
Journal of Animal and Feed Sciences 16 (2007) 172.
- Knutsen T.M., Olsen H.G., Ketto I.A., Sundsaasen K.K, Kohler A., Tafintseva V., Svendsen M., Kent M.P., Lien S.
- PHOTONFOOD - Flexible Mid-Infrared Photonic Solution for Rapid Farm-to-Fork Sensing of Food Contaminants
European Commision (H2020-ICT-2020-2, Project Nº 101016444). Coordinator: Achim Kohler. - DigiFoods - Digital Food Quality
Research Council of Norway SFI project Nº. 309259). Coordinator: Nofima. - Genome-based improvement of bovine milk fat composition
Research Council of Norway, Project Nº 225173. Coordinator: BIOVIT, NMBU. - AMS - New approaches for management and breeding of dairy cows, in automatic milking systems
Research Council of Norway, Project Nº 244231. Coordinator: VET, NMBU.
- PHOTONFOOD - Flexible Mid-Infrared Photonic Solution for Rapid Farm-to-Fork Sensing of Food Contaminants
BioSpec publications
- Kong B., Brandsrud M.A., Heitmann Solheim J., Nedrebø I., Blümel R., Kohler A.: Effects of the coupling of dielectric spherical particles on signatures in infrared microspectroscopy. Scientific Reports 12 (2022) 13327
- Storaker Myrbråten I., Stamsås G.A., Chan H., Morales Angeles D., Mathiesen Knutsen T., Salehian Z., Shapaval V., Straume D., Kjos M.: SmdA is a Novel Cell Morphology Determinant in Staphylococcus aureus. mBio 13 (2022) e03404-21
- Akulava V., Miamin U., Akhremchuk K., Valentovich L., Dolgikh A., Shapaval V.: Isolation, Physiological Characterization, and Antibiotic Susceptibility Testing of Fast-Growing Bacteria from the Sea-Affected Temporary Meltwater Ponds in the Thala Hills Oasis (Enderby Land, East Antarctica). Biology 11 (2022) 1143
- Knutsen T.M., Olsen H.G., Ketto I.A., Sundsaasen K.K, Kohler A., Tafintseva V., Svendsen M., Kent M.P., Lien S.: Genetic variants associated with two major bovine milk fatty acids offer opportunities to breed for altered milk fat composition. Genetics Selection Evolution 54 (2022) 35
- Smirnova M., Tafintseva V., Kohler A., Miamin U., Shapaval V.: Temperature-and Nutrients-Induced Phenotypic Changes of Antarctic Green Snow Bacteria Probed by High-Throughput FTIR Spectroscopy.
Biology 11 (2022) 890 - Rehman H.U., Tafintseva V., Zimmermann B., Solheim J., Virtanen V., Shaikh R., Nippolainen E., Afara I., Saarakkala S, Rieppo L., Krebs P., Fomina P., Mizaikoff B., Kohler A.: Preclassification of broadband and sparse infrared data by multiplicative signal correction approach. Molecules 27 (2022) 2298
- Virtanen V., Tafintseva V., Shaikh R., Nippolainen E., Haas J., Afara I., Töyräs J., Kröger H., Solheim J., Zimmermann B., Kohler A., Mizaikoff B., Finnilä M., Rieppo L., Saarakkala S.: Infrared spectroscopy is suitable for objective assessment of articular cartilage health. Osteoarthritis and Cartilage Open 4 (2022) 100250
- Solheim J.H., Zimmermann B., Tafintseva V., Dzurendová S., Shapaval V., Kohler A.: The Use of Constituent Spectra and Weighting in Extended Multiplicative Signal Correction in Infrared Spectroscopy. Molecules 27 (2022) 1900
- Tafintseva V., Lintvedt T.A., Solheim J., Zimmermann B., Rehman H.U., Virtanen V., Shaikh R., Nippolainen E., Afara I., Saarakkala S, Rieppo L., Krebs P., Fomina P., Mizaikoff B., Kohler A.: Preprocessing Strategies for Sparse Infrared Spectroscopy: A Case Study on Cartilage Diagnostics. Molecules 27 (2022) 873
- Heitmann Solheim J., Borondics F., Zimmermann B., Sandt C., Muthreich F., Kohler A.: An automated approach for fringe frequency estimation and removal in infrared spectroscopy and hyperspectral imaging of biological samples. Journal of Biophotonics 14 (2021) e202100148
- Dzurendova S., Losada C.B., Dupuy-Galet B.X., Fjær K., Shapaval V.: Mucoromycota fungi as powerful cell factories for modern biorefinery. Applied Microbiology and Biotechnology 106 (2021) 101
- Carnovale G., Rosa F., Shapaval V., Dzurendova S., Kohler A., Wicklund T., Horn S.J., Barbosa M.J., Skjånes K.: Starch Rich Chlorella vulgaris: High-Throughput Screening and Up-Scale for Tailored Biomass Production. Applied Sciences 11 (2021) 9025
- Gaykawad S.S., Ramanand S.S., Blomqvist J., Zimmermann B., Shapaval V., Kohler A., Oostindjer M., Boccadoro C.: Submerged Fermentation of Animal Fat By-Products by Oleaginous Filamentous Fungi for the Production of Unsaturated Single Cell Oil. Fermentation 7 (2021) 300
- Figoli C.B., Garcea M., Bisioli C., Tafintseva V., Shapaval V., Gómez Peña M., Gibbons L., Althabe F., Yantorno O.M., Horton M., Schmitt J., Lasch P., Kohler A., Bosch A.: A robust metabolomics approach for the evaluation of human embryos from in vitro fertilization. Analyst 146 (2021) 6156
- Seim E., Kohler A., Lukacs R., Brandsrud M.A, Marstein E.S, Olsen E., Blümel R.
Wave chaos enhanced light trapping in optically thin solar cells
Chaos 31 (2021) 063136 - Dzurendova S., Shapaval V., Tafintseva V., Kohler A., Byrtusová D., Szotkowski M., Márová I., Zimmermann B.: Assessment of Biotechnologically Important Filamentous Fungal Biomass by Fourier Transform Raman Spectroscopy. International Journal of Molecular Sciences 22 (2021) 6710
- Tafintseva V., Shapaval V., Blazhko U., Kohler A.: Correcting replicate variation in spectroscopic data by machine learning and model-based pre-processing. Chemometrics and Intelligent Laboratory Systems 215 (2021) 104350
- Byrtusová D., Szotkowski M., Kurowska K., Shapaval V., Márová I.: Rhodotorula kratochvilovae CCY 20-2-26—The Source of Multifunctional Metabolites. Microorganisms 9 (2021) 1280
- Brandenburg J., Blomqvist J., Shapaval V., Kohler A., Sampels S., Sandgren M., Passoth V.: Oleaginous yeasts respond differently to carbon sources present in lignocellulose hydrolysate. Biotechnology for Biofuels volume 14 (2021) 124
- Blazhko U., Shapaval V., Kovalev V., Kohler A.: Comparison of augmentation and pre-processing for deep learning and chemometric classification of infrared spectra. Chemometrics and Intelligent Laboratory Systems 215 (2021) 104367
- Brandsrud M.A., Blümel R., Lukacs R., Seim E., Stensrud Marstein E, Olsen E., Kohler A.: Investigation of resonance structures in optically thin solar cells. Journal of Photonics for Energy, 11 (2021) 024501
- Brandsrud M.A., Blümel R., Heitmann Solheim J., Kohler A.: The effect of deformation of absorbing scatterers on Mie-type signatures in infrared microspectroscopy. Scientific Reports 11 (2021) 4675
- Dzurendova S., Zimmermann B., Kohler A., Reitzel K., Nielsen U.G., Dupuy--Galet B.X., Leivers S., Horn S.J., Shapaval V.: Calcium affects polyphosphate and lipid accumulation in Mucoromycota fungi. Journal of Fungi 7 (2021) 300
- Langseter A.M., Dzurendova S., Shapaval V., Kohler A., Ekeberg D., Zimmermann B.: Evaluation and optimisation of direct transesterification methods for the assessment of lipid accumulation in oleaginous filamentous fungi. Microbial Cell Factories 20 (2021) 59
- Virtanen V., Nippolainen E., Shaikh R., Afara I.O., Töyräs J., Solheim J., Tafintseva V., Zimmermann B., Kohler A., Saarakkala S., Rieppo L.: Infrared Fiber-Optic Spectroscopy Detects Bovine Articular Cartilage Degeneration. Cartilage (2021)
- Slaný O. , Klempová T., Shapaval V., Zimmermann B., Kohler A., Čertík M.: Animal Fat as a Substrate for Production of n-6 Fatty Acids by Fungal Solid-State Fermentation. Microorganisms 9 (2021) 170
- Smirnova M., Miamin U., Kohler A., Valentovich L., Akhremchuk A., Sidarenka A., Dolgikh A., Shapaval V.: Isolation and characterization of fast‐growing green snow bacteria from coastal East Antarctica. MicrobiologyOpen, 10 (2021) e1152
- Curtasu M.V., Tafintseva V., Bendiks Z., Marco M.L., Kohler A., Xu Y., Nørskov N.P., Nygaard Lærke H., Knudsen K.E.B., Hedemann M.S.: Obesity-Related Metabolome and Gut Microbiota Profiles of Juvenile Göttingen Minipigs—Long-Term Intake of Fructose and Resistant Starch. Metabolites 10 (2020) 456
- Rachah A., Reksen O., Afseth N., Tafintseva V., Ferneborg S., Martin A., Kohler A., Prestløkken E.: Fourier transform infrared spectral data as a tool to predict energy balance, energy- and dry matter intake in lactating dairy cows. Journal of dairy research (2020) 1-8
- Almklov Magnussen E., Heitmann Solheim J., Blazhko U., Tafintseva V., Tøndel K., Liland K.H., Dzurendova S., Shapaval V., Kohler A.: Deep convolutional neural network recovers pure absorbance spectra from highly scatter‐distorted spectra of cells. Journal of Biophotonics (2020) e202000204
- Slaný O., Klempová T., Shapaval V., Zimmermann B., Kohler A., Čertík M.: Biotransformation of Animal Fat-By Products into ARA-Enriched Fermented Bioproducts by Solid-State Fermentation of Mortierella alpina. Journal of Fungi 6 (2020) 236
- Dzurendova S., Zimmermann B., Tafintseva V., Kohler A., Horn S.J., Shapaval V.: Metal and Phosphate Ions Show Remarkable Influence on the Biomass Production and Lipid Accumulation in Oleaginous Mucor circinelloides. Journal of Fungi 6 (2020) 260
- Dzurendova S., Zimmermann B., Tafintseva V., Kohler A., Ekeberg D., Shapaval V.: The influence of phosphorus availability and the nature of nitrogen on the biomass production and accumulation of lipids in oleaginous Mucoromycota fungi. Applied Microbiology and Biotechnology 104 (2020) 8065
- Kohler A., Heitmann Solheim J., Tafintseva V., Zimmermann B., Shapaval V.: Model-Based Pre-Processing in Vibrational Spectroscopy. Comprehensive Chemometrics, Second Edition (2020) 83
- Byrtusová D., Shapaval V., Holub J., Šimanský S., Rapta M., Szotkowski M., Kohler A., Márová I.: Revealing the Potential of Lipid and β-Glucans Coproduction in Basidiomycetes Yeast. Microorganisms 8 (2020) 1034
- Dzurendova S., Zimmermann B., Kohler A., Tafintseva V., Slany O., Certik M., Shapaval V.: Microcultivation and FTIR spectroscopy-based screening revealed a nutrient-induced co-production of high-value metabolites in oleaginous Mucoromycota fungi. PLoS ONE 15 (2020) e0234870
- Trukhan S., Tafintseva V., Tøndel K., Großerueschkamp F., Mosig A., Kovalev V., Gerwert K., Kohler A.: Grayscale representation of infrared microscopy images by Extended Multiplicative Signal Correction for registration with histological images. Journal of Biophotonics 13 (2020) e201960223
- Diehn S., Zimmermann B., Tafintseva V., Bağcıoğlu M., Kohler A., Ohlson M., Fjellheim S., Kneipp J.: Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains. Analytical and Bioanalytical Chemistry 412 (2020) 6459
- Meyer V., Basenko E.Y., Benz J.P., Braus G.H., Caddick M.X., Csukai M., de Vries R.P., Endy D., Frisvad J.C., Gunde‑Cimerman N., Haarmann T., Hadar Y., Hansen K., Johnson R.I., Keller N.P., Kraševec N., Mortensen U.H., Perez R., Ram A.F.J., Record E., Ross P., Shapaval V., Steiniger C., van den Brink H., van Munster J., Yarden O., Wösten H.A.B.: Growing a circular economy with fungal biotechnology: a white paper. Fungal Biology and Biotechnology 7 (2020) 5
- Sirovica, S., Heitmann Solheim J., Skoda, M.W.A., Hirschmugl C.J., Mattson E.C., Aboualizadeh E., Guo Y., Chen X., Kohler A., Romanyk D.L., Rosendahl S.M., Morsch S., Martin R.A., Addison O.: Origin of micro-scale heterogeneity in polymerisation of photo-activated resin composites. Nature Communications 11 (2020) 1849
- Kenđel A., Zimmermann B.: Chemical Analysis of Pollen by FT-Raman and FTIR Spectroscopies. Frontiers in Plant Science 11 (2020) 352
- Tafintseva V., Shapaval V., Smirnova M., Kohler A.: Extended multiplicative signal correction for FTIR spectral quality test and pre‐processing of infrared imaging data. Journal of Biophotonics 13 (2020) e201960112
- Diehn S., Zimmermann S., Tafintseva V., Seifert S., Bagcioglu M., Ohlson M., Weidner S., Fjellheim S., Kohler A., Kneipp J.: Combining chemical information from grass pollen in multimodal characterization. Frontiers in Plant Science 10 (2020) 1788
- Muthreich F., Zimmermann B., Birks H.J.B., Vila‐Viçosa C.M., Seddon A.W.R.:
Chemical variations in Quercus pollen as a tool for taxonomic identification: Implications for long‐term ecological and biogeographical research. Journal of Biogeography 47 (2020) 1298
- Szotkowski M., Byrtusova D., Haronikova A., Vysoka M., Rapta M., Shapaval V., Marova I.: Study of Metabolic Adaptation of Red Yeasts to Waste Animal Fat Substrate. Microorganisms 7 (2019) 578
- Sanden K.W., Kohler A., Afseth N.K., Böcker U., Rønning S.B., Liland K.H., Pedersen M.E.: The use of Fourier‐transform infrared spectroscopy to characterize connective tissue components in skeletal muscle of Atlantic cod (Gadus morhua L.). Journal of Biophotonics 12 (2019) e201800436
- Xiong Y., Shapaval V., Kohler A., Li J., From P.J.: A Fully Automated Robot for the Preparation of Fungal Samples for FTIR Spectroscopy Using Deep Learning. IEEE Access 7 (2019) 132763-132774
- Xiong Y., Shapaval V., Kohler A., From P.J.: A Laboratory-Built Fully Automated Ultrasonication Robot for Filamentous Fungi Homogenization. SLAS Technology (2019) 1-13
- Shapaval V., Brandenburg J., Blomqvist J., Tafintseva V., Passoth V., Sandgren M., Kohler A.: Biochemical profiling, prediction of total lipid content and fatty acid profile in oleaginous yeasts by FTIR spectroscopy. Biotechnology for Biofuels 12 (2019) 140
- Heitmann Solheim J., Gunko E., Petersen D., Grosserruschkamp F., Gerwert K., Kohler A.: An open source code for Mie Extinction EMSC for infrared microscopy spectra of cells and tissues. Journal of Biophotonics 12 (2019) e201800415
- Brandsrud M.A., Seim E., Lukacs R., Kohler A., Marstein E.S., Olsen E., Blümel R.: Exact ray theory for the calculation of the optical generation rate in optically thin solar cells. Physica E: Low-dimensional Systems and Nanostructures 105 (2019) 125 – 138.
- Schofield A.J., Blümel R., Kohler A., Lukacs R., Hirschmugl C.J.: Extracting pure absorbance spectra in infrared microspectroscopy by modeling absorption bands as Fano resonances. Journal of Chemical Physics 150 (2019) 154124.
- Seddon A.W.R., Festi D., Robson T.M., Zimmermann B.: Fossil pollen and spores as a tool for reconstructing ancient solar-ultraviolet irradiance received by plants: an assessment of prospects and challenges using proxy-system modelling. Photochemical and Photobiological Sciences 18 (2019) 275.
- Seim E., Kohler A., Lukacs R., Brandsrud M.A, Marstein E.S, Olsen E., Blümel R.: Chaos: A new mechanism for enhancing the optical generation rate in thin-film solar cells. SPIE West 10913 (2019). Chaos 29 (2019) 093132
- Innes S.N., Arve L.E., Zimmermann B., Nybakken L., Melby T.I., Solhaug K.A., Olsen J.E., Torre S.: Elevated air humidity increases UV mediated leaf and DNA damage in pea (Pisum sativum) due to reduced flavonoid content and antioxidant power. Photochemical and Photobiological Sciences 18 (2019) 387.
- Konevskikh T., Lukacs R., Kohler A.: An improved algorithm for fast resonant Mie scatter correction of infrared spectra of cells and tissues. Journal of Biophotonics 11 (2018) DOI: 10.1002/jbio.201600307
- Tzimorotas D., Afseth N. K., Lindberg D., Kjørlaug O., Axelsson L., Shapaval V.:
Pretreatment of different food rest materials for bioconversion into fungal lipid-rich biomass. Journal of Bioprocess and Biosystems Engineering 41 (2018) 1039. - Kosa G., Zimmermann B., Kohler A., Ekeberg D., Afseth N.K., Mounier J., Shapaval V.: High-throughput screening of Mucoromycota fungi for production of low- and high value lipids. Biotechnology for Biofuels 11:66 (2018)
- Guoa S., Kohler A., Zimmermann B., Heinke R., Stöckel S., Rösch P., Popp J., Bocklitz T.: EMSC based model transfer for Raman spectroscopy in biological applications. Analytical Chemistry 90 (2018) 9787.
- Knutsen T.M., Olsen H.G., Tafintseva V., Svendsen M., Kohler A., Kent M.P., Lien S.: Unravelling genetic variation underlying de novo-synthesis of bovine milk fatty acids. Scientific reports 8 (2018) 2179.
- Diehn S., Zimmermann B., Bağcıoğlu M., Seifert S., Kohler A., Ohlson M., Fjellheim S., Weidner S., Kneipp J.: Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) shows adaptation of grass pollen composition. Scientific Reports 8 (2018) 16591.
- Kosa G., Vuoristo K., Horn S.J., Zimmermann B., Afseth N.K., Kohler A., Shapaval V.: Assessment of the scalability of a microtiter plate system for screening of oleaginous microorganisms. Applied Microbiology and Biotechnology 102 (2018) 4915.
- Zimmermann B.: Chemical characterization and identification of Pinaceae pollen by infrared microspectroscopy. Planta 247 (2018) 171.
- Vanek M., Mravec F., Szotkowski M., Byrtusova D., Haronikova A., Certik M., Shapaval V., Marova I.: Fluorescence lifetime imaging of red yeast Cystofilobasidium capitatum during growth. The EuroBiotech Journal 2 (2018) 114.
- Blümel R., Lukacs R., Zimmermann B., Bağcıoğlu M., Kohler A.: Observation of Mie ripples in the synchrotron FTIR spectra of spheroidal pollen grains. Journal of the Optical Society of America A 35 (2018) 1769.
- Tafintseva V., Vigneau E., Shapaval V., Cariou V., Qannari E.M., Kohler A.: Hierarchical classification of microorganisms based on high-dimensional phenotypic data. Journal of Biophotonics 11 (2018)
- Azarfar G., Aboualizadeh E., Walter N.M., Ratti S., Olivieri C., Norici A., Nasse M., Kohler A., Giordano M., Hirschmugl C.J.: Estimating and correcting interference fringes in infrared spectra in infrared hyperspectral imaging. Analyst 143 (2018) 4674.
- Zimmermann B., Bağcıoğlu M., Tafinstseva V., Kohler A., Ohlson M., Fjellheim S.: A high-throughput FTIR spectroscopy approach to assess adaptive variation in pollen quality. Ecology and Evolution 7 (2017) 10839.
- Olsen H.G., Knutsen T.M., Kohler A., Svendsen M., Gidskehaug L., Grove H., Nome T., Sodeland M., Sundsaasen K.K., Kent M.P., Martens H., Lien S.: Genome-wide association mapping for milk fat composition and fine mapping of a QTL for de novo synthesis of milk fatty acids on bovine chromosome 13.
Genetics Selection Evolution, 49:20 (2017) doi:10.1186/s12711-017-0294-5 - Marova I., Rapta M., Vanek M., Haronikova A., Szotkowski M., Shapaval V.: Use of high-throughput techniques to study simultaneous production of lipid metabolites in carotenogenic yeasts grown on waste animal fat. Journal of Biotechnology 256 (2017) 42.
- Kosa G., Kohler A., Tafintseva V., Zimmermann B., Forfang K., Afseth N.K., Tzimorotas D., Vuoristo K.S., Horn S.J., Mounier J., Shapaval V.: Microtiter plate cultivation of oleaginous fungi and monitoring of lipogenesis by high-throughput FTIR spectroscopy. Microbial Cell Factories 16:101 (2017).
- Forfang, K., Zimmermann B., Kosa, G. Kohler A., Shapaval V.: FTIR spectroscopy for evaluation and monitoring of lipid extraction efficiency for oleaginous fungi. PLOS One 12 (2017) e0170611.
- Marova I., Szotkowski M., Vanek M., Rapta M., Byrrtusova D., Mikheichyk N., Haronikova A., Certik M., Shapaval V.: Utilization of animal fat waste as carbon source by carotenogenic yeasts – a screening study. The EuroBiotech Journal 1 (2017) 310.
- Bağcıoğlu M., Kohler A., Seifert S., Kneipp J., Zimmermann B.: Monitoring of plant-environment interactions by high throughput FTIR spectroscopy of pollen. Methods in Ecology and Evolution 8 (2017) 870-880.
- Kosa G., Shapaval V., Kohler A., Zimmermann B.: FTIR spectroscopy as a unified method for simultaneous analysis of intra- and extracellular metabolites in high-throughput screening of microbial bioprocesses. Microbial Cell Factories 16:195 (2017).
- Shapaval V., Møretrø T., Suso H-P., Schmitt J., Lilehaug D., Kohler A.: A novel library-independent approach based on FTIR spectroscopy for source tracking of moulds contamination in food. Letters in Applied Microbiology 64 (2017) 335.
- Colabella C., Corte L., Roscini L., Shapaval V., Kohler A., Tafintseva V., Tascini C., Cardinali G.: Merging FT-IR and NGS for simultaneous phenotypic and genotypic identification of pathogenic Candida species. PLoS One 12 (2017) e0188104
- Zimmermann B., Tafintseva V., Bağcıoğlu M., Høegh Berdahl M., Kohler A.: Analysis of allergenic pollen by FTIR microspectroscopy. Analytical Chemistry 88 (2016) 803-811.
- Hovde Liland K., Kohler A., Afseth N.K.: Model-based pre-processing in Raman spectroscopy of biological samples. Journal of Raman Spectroscopy (2016) DOI: 10.1002/jrs.4886.
- Konevskikh T., Lukacs R., Blümel R., Ponossov A., Kohler A.: Mie scatter corrections in single cell infrared microspectroscopy. Faraday Discussions 187 (2016) 235-257.
- Blümel R., Bağcıoğlu M., Lukacs R., Kohler A.: Infrared refractive index dispersion of polymethyl methacrylate spheres from Mie ripples in Fourier-transform infrared microscopy extinction spectra. Journal of the Optical Society of America A 33 (2016) 1687-1696.
- Li J., Shapaval V., Kohler A., Talintyre R., Schmitt J., Stone R., Gallant A.J., Zeze D.A.: A Modular Liquid Sample Handling Robot for High-Throughput Fourier Transform Infrared Spectroscopy. In Ding X., Kong X. & Dai S.J. (eds) Advances in Reconfigurable Mechanics and Robotics II (2015). Cham: Springer International Publishing
- Bağcıoğlu M., Zimmermann B., Kohler A.: A multiscale vibrational spectroscopic approach for identification and biochemical characterization of pollen. PLOS One 10 (2015) e0137899
- Zimmermann B., Bağcıoğlu M., Sandt C., Kohler A.: Vibrational microspectroscopy enables chemical characterization of single pollen grains as well as comparative analysis of plant species based on pollen ultrastructure. Planta 242 (2015) 1237-1250
- Konevskikh T., Ponossov A., Blumel R., Lukacs R., Kohler A. Fringes in FTIR spectroscopy revisited: understanding and modelling fringes in infrared spectroscopy of thin films. Analyst 140 (2015) 3969.
- Zimmermann B., Tkalčec Z., Mešić A., Kohler A. Characterizing aeroallergens by infrared spectroscopy of fungal spores and pollen. PLOS One 10 (2015) e0124240
- Lukacs R., Blümel R., Zimmermann B., Bağcıoğlu M., Kohler A.: Recovery of absorbance spectra of micrometer-sized biological and inanimate particles. Analyst 140 (2015) 3273-3284
- Karaman I., Nørskov N.P., Yde C.C., Skou Hedemann M., Bach Knudsen K.E., Kohler A.: Sparse multi-block PLSR for biomarker discovery when integrating data from LC-MS and NMR metabolomics. Metabolomics 11 (2015) 367.
- Shapaval V., Afseth N.K., Vogt G., Kohler A.: Fourier Transform Infrared Spectroscopy for the prediction of fatty acid profiles in Mucor fungi in media with different carbone sources. Microbial Cell Factories 4 (2014)
- Kohler A., Boecker U., Shapaval V., Forsmark A., Anderssion M., Warringer J., Martens H., Omholt S.W., Blomberg A.: High-throughput biochemical fingerprinting of Saccharomyces cerevisiae by Fourier transform infrared spectroscopy. PLOS One 10 (2014) e0118052
- Hovde Liland K., Kohler A., Shapaval V.: Hot PLS—a framework for hierarchically ordered taxonomic classification by partial least squares. Chemometrics and Intelligent Laboratory Systems 15 (2014)
- Zimmermann B., Kohler A.: Infrared spectroscopy of pollen identifies plant species and genus as well as environmental conditions. PLOS One 9 (2014) e95417
- Kohler A., Boecker U., Shapaval V., Forsmark A., Anderssion M., Warringer J., Martens H., Omholt S.W., Blomberg A.: High-throughput biochemical fingerprinting of Saccharomyces cerevisiae by Fourier transform infrared spectroscopy. PLOS One 10 (2014)
- Shapaval V., Schmitt J., Møretrø T., Suso HP, Skaar I., Åsli AW., Lilehaug D., and Kohler A.: Characerization of food spoilage fungi by FTIR spectroscopy. Journal of Applied Microbiology 114 (2013)
- Hassani S., Hanafi M., Qannari M., Kohler A.: Deflation strategies for multi-block principal component analysis revisited. Chemometrics and Intelligent Laboratory Systems. 120 (2013) 154–168.
- Karaman I., Qannari M., Martens H., Skou Hedemann M., Bach Knudsen K.E., Kohler A.: Comparison of Sparse and Jack-knife partial least squares regression methods for variable selection. Chemometrics and Intelligent Laboratory Systems. 122 (2013) 65-77.
- Eslami A., Qannari E.M., Kohler A., Bougeard S.: Analyses factorielles de données structurées en groupes d’individus (Multivariate data analysis of multi-group datasets). Journal de la Société Française de Statistique 44 (2013) 2102.
- Zimmermann B., Kohler A.: Optimizing Savitzky-Golay parameters for improving spectral resolution and quantification in infrared spectroscopy. Applied Spectroscopy 67 (2013) 892-902.
- Eslami A., Qannari E.M., Kohler A., Bougeard S.: General overview of methods of analysis of multi-group datasets. Revue des Nouvelles Technologies de l’information (RNTI) 25 (2013) 113.
- Shapaval V., Walczak B., Gognies S., Møretrø T., Suso HP, Åsli AW., Belarbi A., and Kohler A.: FTIR spectroscopic characterization of differently cultivated food related yeasts. Analyst 138 (2012)
- Hassani S., Martens H., Qannari M., Hanafi M., Kohler A.: Model validation and error estimation in multi-block partial least squares regression. Chemometrics and Intelligent Laboratory Systems 117 (2012) 42-53
- Hassani S., Martens H., Qannari M., Kohler A.: Degrees of freedom estimation in Principal Component Analysis and consensus principal component analysis. Chemometrics and Intelligent Laboratory Systems 118 (2012) 246-259
- Bassan P., Sachdevaa A., Kohler A., Hughes C., Henderson A., Boyle J., Shanks J.H., Brown M., Clarke N.W., Gardner P.: FTIR Microscopy of biological cells and tissue: data analysis using resonant Mie scattering (RMieS) EMSC algorithm. Analyst 137 (2012) 1370.
- Afseth N.K., Kohler A.: Extended multiplicative signal correction in vibrational spectroscopy, a tutorial. Chemometrics and Intelligent Laboratory Systems 117 (2012) 92.
- Hanafi M., Kohler A., Qannari M.: Connections between multiple co-inertia analysis and consensus principal component analysis. Chemometrics and Intelligent Laboratory Systems 106 (2011) 37-40.
- Shapaval V., Møretrø T., Suso HP, Åsli AW., Schmitt J., Lilehaug D., Martens H, Boecker U., and Kohler A. A high-throughput microcultivation protocol for FTIR spectroscopic characterization and identification of fungi. Journal of Biophotonics 3 (2010)
- Zimmermann B.: Characterization of pollen by vibrational spectroscopy. Appl. Spectrosc. 64 (2010) 1364-1373
- Hanafi M., Kohler A., Quannari, M.: Shedding new light on Hierarchical Principal Component Analysis. Journal of Chemometics 24 (2010) 703-709.
- Hassani S., Martens H., Qannari M., Hanafi M., Borge G.I., Kohler A.: Analysis of –omics data: Graphical interpretation- and validation tools in multi–block methods. Chemometrics and Intelligent Laboratory Systems 104 (2010) 140-153.
- Bassan P., Kohler A., Martens H., Lee J., Byrne H.J., Dumas P., Gazi E., Brown M., Clarke N., Gardner P.: Resonant Mie Scattering (RMieS) Correction of Infrared Spectra from Highly Scattering Biological Samples. Analyst 135 (2010) 268.
- Kohler A., Böcker U., Warringer J., Blomberg A., Omholt S.W., Stark E., Martens H.: Reducing inter-replicate variation in Fourier-transform infrared spectroscopy by extended multiplicative signal correction. Applied spectroscopy 63 (2009) 296.
- Kohler A., Sulé-Suso J., Sockalingum G.D., Tobin M., Bahrami F., Yang Y., Pijanka J., Dumas P., Cotte M., Martens H.: Estimating and correcting Mie scattering in synchrotron based microscopic FTIR spectra by extended multiplicative signal correction (EMSC). Applied Spectroscopy 62 (2008) 259.
- Martens H., Bruun S.W., Adt I., Sockalingum G.D., Kohler A.: Pre-processing in biochemometrics: correction for path-length and temperature effects of water in FTIR bio-spectroscopy by EMSC. Journal of Chemometrics 20 (2006) 402.
- Bruun S.W., Kohler A., Adt I., Sockalingum G.D., Manfait M., Martens H.
Correcting attenuated total reflection-Fourier transform infrared spectra for water vapour and carbon dioxide. Applied Spectroscopy 60 (2006) 1029. - Thennadil S., Martens H., Kohler A.: Physics-based Multiplicative Scatter Correction Approaches for Improving the Performance of Calibration Models. Applied Spectroscopy 60 (2006) 315.
- Kohler A., Kirschner C., Oust A., Martens H.: Extended multiplicative signal correction as a tool for separation and characterisation of physical and chemical information in Fourier transform infrared microscopy images of cryo-sections of beef loin. Applied Spectroscopy 59 (2005) 707.
- Johanne Heitmann Solheim: Modelling scattering and absorption in the vibrational spectroscopy of cells and tissues. NMBU, 2022.
- Simona Dzurendova: Sustainable fungal biorefineries : optimizing production of valuable metabolites in oleaginous Mucoromycota. NMBU, 2021.
- Maren Anna Brandsrud: Scattering and absorption in nano- and microstructured media. NMBU, 2020.
- Eivind Seim: Chaos enhanced light trapping in optically thin solar cells. NMBU, 2020.
- Gergely Kosa: High-throughput screening of filamentous fungi for single cell oil production by microplate cultivation and FTIR spectroscopy. NMBU, 2018.
- Claudia Colabella: NGS-based rDNA barcoding in fungal species identification and delimitation : limits, opportunities and relation to phenotypic HT FT-IR spectroscopy. NMBU, 2017.
- Tatiana Konevskikh: Modeling scattering and absorption in the infrared spectroscopy of cells and thin film. NMBU, 2017.
- Murat Bağcıoğlu: Multiscale vibrational spectroscopy of pollen. NMBU, 2016.
The following master's theses were conducted at the BioSpec group:
- Pål Rysdal Tveit: Development, Testing and Evaluation of the Second Generation of the Small-Scale Biodiesel Production Line “BioMax” (2020). Faculty of Science and Technology, NMBU, Ås, Norway
- Kai Fjær: Whole genome sequencing with Oxford Nanopore and de novo genome assemblies of lipid-producing fungi in phylum Mucoromycota (2020). Faculty of Science and Technology, NMBU, Ås, Norway.
- Simen Rønnekleiv Eriksen: Mie Ripples and Wiggles in Infrared Spectroscopy of Cells and Tissues (2020). Faculty of Science and Technology, NMBU, Ås, Norway
- Ole Thorbjørn Ileby Eriksen: Production of microbial oil from animal fat: process design, mass- and energy balance (2019). Faculty of Science and Technology, NMBU, Ås, Norway
- Snorre Niklas Galaaen: Finding optimal parameters for transesterification with heterogeneous and homogeneous catalysts (2019). Faculty of Science and Technology, NMBU, Ås, Norway
- Simen Arne Kirkhorn: Seasonal variation in chemical composition of Chamerion angustifolium pollen as measured by Fourier-Transform Infrared Spectroscopy (2019). Faculty of Environmental Sciences and Natural Resource Management, NMBU, Ås, Norway
- Tiril Aurora Lintvedt: Preprocessing strategies for infrared spectral data with limited numbers of spectral channels (2019) (thesis with non-disclosure agreement, limited access). Faculty of Science and Technology, NMBU, Ås, Norway
- Elisabeth Tatjana Grothe Hauge: Theoretical upscaling of the fermentation process for the conversion of animal fat rest materials into high-value biomass (2018). Faculty of Science and Technology, NMBU, Ås, Norway
- Johanne Heitmann Solheim: Optimizing the iterative Mie scatter correction algorithm for retrieving pure absorbance spectra in FTIR spectroscopy of cells and tissues (2017). Faculty of Science and Technology, NMBU, Ås, Norway
- Kristian Frafjord: Ray Dynamics in Array of Disks investigating Light Management in Thin-Film Solar Cells (2017). Faculty of Science and Technology, NMBU, Ås, Norway
- Denis Tafintsev: Multivariate Classification Methods for Spectroscopic Data with Multiple Class Structure (2016). Department of Mathematical Sciences and Technology, NMBU, Ås, Norway
- Tor Einar Møller: Assessment of Sparse Multi-Block Partial Least Squares Regression Model Performance in Analysis of High-Dimensional Phenotypic Data (2016). Department of Mathematical Sciences and Technology, NMBU, Ås, Norway
- Marlene Wilhelmine Jensen: Evaluation of a combined production of bioplastics and biogas from sludge compared with traditional biogas production (2016). Faculty of Science and Technology, NMBU, Ås, Norway
- Ida Kristine Kirkeslett Nielsen: Produksjon av Omega3 fett syrer og evaluering av virkning mot hjerte-karsykdommer (2016). Faculty of Science and Technology, NMBU, Ås, Norway and Pronova Biopharma AS, Sandefjord, Norway
- Morten Moltubakk: Biokjemisk omdanning av biprodukter fra matindustrien (2016). Faculty of Science and Technology, NMBU, Ås, Norway
- Frida Helen Maria Torgersen: Whispering Gallery Resonances in Dielectric Disks (2016). Department of Mathematical Sciences and Technology, NMBU, Ås, Norway
- Maren Anna Brandsrud: Understanding Resonant Structures of Coupled Disks for Light Management in Photovoltaics (2015). Department of Mathematical Sciences and Technology, NMBU, Ås, Norway
- Maria Høegh Berdahl: PollenID – an automated method for pollen analysis (2014). Department of Mathematical Sciences and Technology, NMBU, Ås, Norway
- Nora Klevjer Thøgersen: Use of the Resonance Structure of Mie Scattering for Refractive Index Estimation (2014). Department of Mathematical Sciences and Technology, NMBU, Ås, Norway
- Kjersti Misfjord: Pollen chemical composition determined by infrared spectroscopy : species identification and environmental effects (2014). Faculty of Environmental Science and Technology, NMBU, Ås, Norway
- Ketil Breckan Thovsen: Evaluation of Mie scatter approximation formulas for the scattering of infrared light at biological cells (2013). Department of Mathematical Sciences and Technology, NMBU, Ås, Norway
Master theses conducted at Nofima
The following theses were the result of scientific research at Nofima under the supervision of Achim Kohler:
- Karen Wahlstrøm Sanden: Development of vibrational spectroscopic techniques for measuring quality-related parameters of connective tissue (2011). Institute of Chemistry, Biotechnology and Food Science (IKBM), Norwegian University of Life Sciences, Ås, Norway.
- Ingvild Sørhus: Genome wide phenotype characterisation of yeasts by FTIR spectroscopy (2007). Institute of Chemistry, Biotechnology and Food Science (IKBM), Norwegian University of Life Sciences, Ås, Norway.
- Audun Flåtten: Determination of C22:5 and C22:6 marine fatty acids in pork fat with Fourier transform mid-infrared spectroscopy (2002). Institute of Chemistry, Biotechnology and Food Science (IKBM), Norwegian University of Life Sciences, Ås, Norway.
- Annette Veberg: Model system and analytical methods for the study of amyloidosis in tissue (2002). Institute of Chemistry, Biotechnology and Food Science (IKBM), Norwegian University of Life Sciences, Ås, Norway.
- Even Bringsdal: Segmentation of multispectral images with fuzzy clustering (2001). Institute of Chemistry, Biotechnology and Food Science (IKBM), Norwegian University of Life Sciences, Ås, Norway.
BioSpec group members
- Murat Bağcıoğlu (PhD, biospectroscopy)
- Stine Brekke Vennemo (MSc, administrator)
- Claudia Colabella (PhD, microbiology)
- Darya Dubava (PhD student, biospectroscopy and biophysics)
- Kai Fjær (MSc, researcher in biochemistry and microbiology)
- Kristin Forfang (PhD student, biospectroscopy, microbiology and biorefinery processes)
- Evgeniy Gunko (PhD student, computer science and biospectroscopy)
- Johanna Karin Hillevi Blomqvist (PhD, researcher in microbiology and biotechnology)
- Tatiana Konevskikh (PhD, scattering in vibrational spectroscopy)
- Gergely Kosa (PhD, biospectroscopy, microbiology and biotechnology)
- Anne Marie Langseter (PhD, researcher in organic synthesis and analysis)
- Tiril Aurora Lintvedt (MSc, scattering in IR spectroscopy)
- Rozalia Lukacs (PhD, researcher in scattering physics, non-crsytalline solids and IR spectroscopy)
- Daria Markina (PhD, researcher in microbiology)
- Ellen Opsahl Mæhle (MA, project manager)
- Amira Rachah (PhD, researcher in multivariate data analysis)
- Simen Rønnekleiv Eriksen (MSc, scattering in IR spectroscopy)
- Eivind Seim (PhD, scattering in energy physics)
- Andreas Ulrich Nicolas Persch (PhD student, physics, biospectroscopy and data analysis)
- Hafeez Ur Rehman (PhD, researcher in spectroscopy and multivariate data analysis)
- Mehdi Andresen Belhaj (MSc, environmental physics and quantum information theory)
- Simona Dzurendová (PhD, researcher in biospectroscopy and biotechnology)
- Stanislau Trukhan (PhD student, computer science and biospectroscopy)
- Johanne Heitmann Solheim (PhD student, postdoc)
BioSpec research infrastructure
The Biospectroscopy and Data Modeling Group at the Faculty of Science and Technology has two laboratory facilities:
- Biospectroscopy Laboratory, with vibrational spectroscopy and gas chromatography instrumentation
- Microbiology Laboratory, with instrumentation for microbial cultivation
Storage of data in ongoing projects
- We store all our data daily on NMBU’s server, according to NMBU's guidelines and national guidelines
- Separate folders for each project
- Access to the data is restricted to selected project participants
- We have routines in place for master students and guests
Archiving of research data
- We archive our data at Zenodo, as suggested by NMBU's guidelines
- This is done when a paper is published
- It is the task of the first author in the BioSpec group
- We archive the data relevant for the paper
- Before we archive, we check if the data is ready
- This is done with the project manager and person generating the data
- We check to make sure we use correct names, that the data is structured properly, etc.
- At Zenodo, we connect data to the BioSpec Norway community, and reference our NRC/EU-projects
- In addition, the project manager must make a data management plan for the project
- After the end of the project period, the project manager has to make sure all relevant data are archived
- We follow the FAIR principles
Database for all data
- A spectral database called BIOSDATA is under development.
How to find BioSpec
Visiting address:
- Kajaveien 11, 1430 Ås, Norway
- Find us in Google Maps
Postal address:
- P.O. Box 5003 NMBU, NO-1432 Ås, Norway
Contact the Biospectroscopy and Data Modeling group:
Follow us on LinkedIn for news and updates
The NMBU campus is located in Ås, which is the neighbor town of Ski, and about a 30-minute trip from Oslo. You can easily get from Oslo to Ås either by train or by bus.
Train from Oslo (Oslo S) to Ås:
To get to Ås by train, take train L21. The train departs from both Oslo S and from Ski. The end station is Moss, and you should get off at Ås. The train station in Ås is 1.1 km from the BioSpec building (TF fløy3, see the map below). During rush hour, the train leaves every half hour, otherwise it leaves every hour.
Bus from Oslo Airport (Oslo Lufthavn) to Ås (Korsegården):
The most effective way to travel directly from the Oslo Airport to NMBU is to take a direct bus to Ås from the airport (Flybussen FB11 to Fredrikstad). The bus leaves at 10 minutes past the hour, approximately every one to two hours (every two hours on Saturday). The bus takes 55 minutes. The FB11 bus station in Korsegården is 2 km from the BioSpec building (TF fløy3, see the map below). If you do not want to walk to the BioSpec building, take bus 510 Drøbak - Frogn vgs. The bus stop is close to the petrol station (bus stop "Brønnerud Skole", see map below). The bus stop in Ås is called “Åsgård skole” (see map below). The bus takes 5 minutes.
Plan your travel from the airport to Ås online:
Departure station: Oslo Lufthavn
Arrival station: Korsegården (first stop)Arriving by bus from Oslo Airport Photo: Google The BioSpec group is located at NMBU campus, Ås, TF building, wing 3 (TF Fløy 3), second floor (see the map below). Enter the main entrance of TF Fløy3 (Kajaveien 11), go to the second floor, then turn left to the corridor next to the stairs, and then left to the meeting room TF201. Note that TF3 is a separate building from the main TF building (see the map below).
Car:
There is a large parking area at the TF building complex, including in front of TF3 building (see the map below). Pay attention to the marked parking spaces in order to avoid a parking fine. Send us your license plate number in advance in order to register your vehicle in the NMBU’s parking system.
Address: Kajaveien 11, 1430 Ås, Norway
Arriving at BioSpec Photo: Google NMBU REALTEK (TF building complex) Photo: Google Thon Hotel Ski
When visiting NMBU, the easiest place to stay is at Thon Hotel. Thon hotel is located in Ski, right next to the train station.
The most effective way to travel to Ski is by taking a plane to Oslo Airport, and from the airport, the fastest and easiest way to get to Ski is by train (approx. 1 h). You have to change train at Oslo central station (Oslo S).
Train from Oslo Airport (Oslo Lufthavn) to Ski:
From Oslo Lufthavn to Oslo S: take train R10, R11 or L12.
From Oslo S to Ski station: take train L2X, L2, L21, L22 or R10.Plan your travel from the airport to Ski online:
Departure station: Oslo Lufthavn
Arrival station: Ski
Check railway mapsTrain from Ski to Ås:
Take train L21 from Ski to Ås. The train station in Ås is 1.1 km from the BioSpec building (TF fløy3, see the map below). From Ski, the trains go every half hour (12 min past and 42 min past every full hour).Bus from Ski to Ås:
Take bus 510 Drøbak-Seiersten. The bus departs right besides Ski train station (bus stop "Ski Stasjon", see the Ski map above) every 10th minute in the morning. The bus stop in Ås is called “Åsgård skole” (see the map below). The bus takes 21 minutes.SiÅs
SiÅs offers guest accommodation to researchers, fellows, visitors and others associated to NMBU and the research institutions on Campus Ås. SiÅs’ guest accommodation is located in Utveien 6, approx. 300 m from the TF building. It consists of shared housing and studio apartments. To check for availability, send an e-mail to utleie@sias.no.
Open and free WiFi can be accessed via the “NMBU-guest” net or via “Eduroam” (for members of universities).

BioSpec summer school
BioSpec Norway, as part of the Norwegian University of Life Sciences, is organising an interdisciplinary summer school for Master and PhD students dedicated to analysis of biological data in infrared spectroscopy.
Read more and sign up for the summer school here