4.6 Article

Non-Invasive Assessment of Dairy Products Using Spatially Resolved Diffuse Reflectance Spectroscopy

Journal

APPLIED SPECTROSCOPY
Volume 69, Issue 9, Pages 1096-1105

Publisher

SAGE PUBLICATIONS INC
DOI: 10.1366/14-07529

Keywords

Non-invasive spectroscopy; Oblique incidence reflectometry; Diffuse reflectance; Absorption; Reduced scattering; Turbid media; Milk; Yogurt

Funding

  1. Centre for Imaging Food Quality project
  2. Danish Council for Strategic Research within the Program Commission on Health, Food, and Welfare [09-067039]

Ask authors/readers for more resources

The quality of a dairy product is largely determined by its microstructure which also affects its optical properties. Consequently, an assessment of the optical properties during production may be part of a feedback system for ensuring the quality of the production process. This paper presents a novel camera-based measurement technique that enables robust quantification of a wide range of reduced scattering coefficients and absorption coefficients. Measurements are based on hyperspectral images of diffuse reflectance in the wavelength range of 470 to 1020 nm. The optical properties of commercially available milk and yogurt products with three different levels of fat content are measured. These constitute a relevant range of products at a dairy plant. The measured reduced scattering properties of the samples are presented and show a clear discrimination between levels of fat contents as well as fermentation. The presented measurement technique and method of analysis is thus suitable for a rapid, non-contact, and non-invasive inspection that can deduce physically interpretable properties.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Multidisciplinary Sciences

Using virtual reality for anatomical landmark annotation in geometric morphometrics

Dolores Messer, Michael Atchapero, Mark B. Jensen, Michelle S. Svendsen, Anders Galatius, Morten T. Olsen, Jeppe R. Frisvad, Vedrana A. Dahl, Knut Conradsen, Anders B. Dahl, Andreas Baerentzen

Summary: Utilizing virtual reality for annotating 3D models shows potential advantages in geometric morphometrics, improving annotation precision. While annotation in VR may not necessarily be faster than on desktop, it is more accurate.

PEERJ (2022)

Article Computer Science, Software Engineering

Progressive Denoising of Monte Carlo Rendered Images

Arthur Firmino, Jeppe Revall Frisvad, Henrik Wann Jensen

Summary: In this paper, a progressive denoising technique is proposed to improve image denoising by combining deep learning and statistical methods.

COMPUTER GRAPHICS FORUM (2022)

Editorial Material Biochemical Research Methods

Perspectives in Biophotonics: a special issue in honor of the International Graduate Summer School on Biophotonics

Stefan Andersson-Engels, Peter E. Andersen

JOURNAL OF BIOMEDICAL OPTICS (2022)

Article Chemistry, Multidisciplinary

Pedestal High-Contrast Gratings for Biosensing

Leonid Yu. Beliaev, Peter Groth Stounbjerg, Giovanni Finco, Ada-Ioana Bunea, Radu Malureanu, Lars Rene Lindvold, Osamu Takayama, Peter E. Andersen, Andrei V. Lavrinenko

Summary: High-contrast gratings (HCG), specifically pedestal HCG (PHCG), show enhanced performance compared to conventional HCG for label-free detection of biomarkers. PHCG demonstrated an improvement of 11.2% in bulk refractive index sensitivity and 10.5% in surface sensitivity. For the detection of avidin as a model analyte, PHCG achieved a lower limit of detection (LoD) of 2.1 ng/mL and a lower limit of quantification (LoQ) of 85 ng/mL, significantly better than the values obtained with conventional HCG.

NANOMATERIALS (2022)

Article Acoustics

360° optoacoustic capsule endoscopy at 50 Hz for esophageal imaging

Zakiullah Ali, Christian Zakian, Qian Li, Jerome Gloriod, Sophie Crozat, Francois Bouvet, Guillaume Pierre, Vassilis Sarantos, Massimiliano Di Pietro, Krzysztof Flisikowski, Peter Andersen, Wolfgang Drexler, Vasilis Ntziachristos

Summary: A 360-degree, 50 Hz frame rate scanning capsule optoacoustic endoscope for human gastrointestinal tract imaging is reported in this study. The imaging penetration depth and translational potential of the instrument were validated using an intralipid solution to simulate light scattering in human esophageal tissue and a pig esophagus.

PHOTOACOUSTICS (2022)

Article Engineering, Environmental

Revealing the complex spatiotemporal nature of crystal growth in a steel pipe: Initiation, expansion, and densification

Isaac Appelquist Loge, Peter Winkel Rasmussen, Henning Osholm Sorensen, Stefan Bruns, Tamadur AlBaraghtheh, Anders Nymark Christensen, Anders Bjorholm Dahl, Philip Loldrup Fosbol

Summary: Crystallisation fouling is a challenge in various applications and understanding the basic mechanisms is crucial in mitigating fouling. In this study, we conducted in situ investigation of dynamic effects using X-ray micro-computed tomography (mu CT) to analyze the fouling process in a steel pipe. Advanced segmentation techniques were employed to quantify the evolving fouling based on 4D images. Computational fluid dynamic simulations were performed using experimental geometries to understand the impact of pipe interface structure on reactive transport. The study identified three growth phases: initiation, expansion, and densification.

CHEMICAL ENGINEERING JOURNAL (2023)

Review Automation & Control Systems

Surface roughness of as-printed polymers: a comprehensive review

Ali Payami Golhin, Riccardo Tonello, Jeppe Revall Frisvad, Sotirios Grammatikos, Are Strandlie

Summary: This review article summarizes recent advances in the role of processing on the surface roughness of AM-printed polymers and provides a benchmark for surface quality improvement in AM processes. The impact of four AM techniques (FFF, SLS, VPP, MJT) on the surface roughness of polymeric parts is discussed by analyzing key processes and printing parameters. Comparable research summaries are provided to assist in selecting the most appropriate method of 3D printing, and a detailed survey of current techniques, process parameters, roughness ranges, and their applicability in achieving surface quality improvement in as-printed polymers is presented.

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY (2023)

Article Materials Science, Multidisciplinary

Noninvasive material anisotropy estimation using oblique incidence reflectometry and machine learning

Lezhong Wang, Siavash Arjomand Bigdeli, Anders Nymark Christensen, Milena Corredig, Riccardo Tonello, Anders Bjorholm Dahl, Jeppe Revall Frisvad

Summary: This study aims to assess the material anisotropy noninvasively with as few measurements as possible. We evaluate different methods for detecting anisotropy using sample rotations, perpendicular planes of incidence, and single observation. Anisotropy is estimated by fitting ellipses to diffuse reflectance isocontours, and the robustness of this method is assessed as the number of observations is reduced. Additionally, a machine learning model is proposed to support the validity of the ellipse fitting method for estimating material anisotropy.

OPTICAL MATERIALS EXPRESS (2023)

Review Oncology

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: a report of the international immuno-oncology biomarker working group

Jeppe Thagaard, Glenn Broeckx, David B. Page, Chowdhury Arif Jahangir, Sara Verbandt, Zuzana Kos, Rajarsi Gupta, Reena Khiroya, Khalid Abduljabbar, Gabriela Acosta Haab, Balazs Acs, Guray Akturk, Jonas S. Almeida, Isabel Alvarado-Cabrero, Mohamed Amgad, Farid Azmoudeh-Ardalan, Sunil Badve, Nurkhairul Bariyah Baharun, Eva Balslev, Enrique R. Bellolio, Vydehi Bheemaraju, Kim R. M. Blenman, Luciana Botinelly Mendonca Fujimoto, Najat Bouchmaa, Octavio Burgues, Alexandros Chardas, Maggie U. Cheang, Francesco Ciompi, Lee A. D. Cooper, An Coosemans, German Corredor, Anders B. Dahl, Flavio Luis Dantas Portela, Frederik Deman, Sandra Demaria, Johan Dore Hansen, Sarah N. Dudgeon, Thomas Ebstrup, Mahmoud Elghazawy, Claudio Fernandez-Martin, Stephen B. Fox, William M. Gallagher, Jennifer M. Giltnane, Sacha Gnjatic, Paula Gonzalez-Ericsson, Anita Grigoriadis, Niels Halama, Matthew G. Hanna, Aparna Harbhajanka, Steven N. Hart, Johan Hartman, Soren Hauberg, Stephen Hewitt, Akira Hida, Hugo M. Horlings, Zaheed Husain, Evangelos Hytopoulos, Sheeba Irshad, Emiel A. M. Janssen, Mohamed Kahila, Tatsuki R. Kataoka, Kosuke Kawaguchi, Durga Kharidehal, Andrey Khramtsov, Umay Kiraz, Pawan Kirtani, Liudmila L. Kodach, Konstanty Korski, Aniko Kovacs, Anne-Vibeke Laenkholm, Corinna Lang-Schwarz, Denis Larsimont, Jochen K. Lennerz, Marvin Lerousseau, Xiaoxian Li, Amy Ly, Anant Madabhushi, Sai K. Maley, Vidya Manur Narasimhamurthy, Douglas K. Marks, Elizabeth S. McDonald, Ravi Mehrotra, Stefan Michiels, Fayyaz ul Amir Afsar Minhas, Shachi Mittal, David A. Moore, Shamim Mushtaq, Hussain Nighat, Thomas Papathomas, Frederique Penault-Llorca, Rashindrie D. Perera, Christopher J. Pinard, Juan Carlos Pinto-Cardenas, Giancarlo Pruneri, Lajos Pusztai, Arman Rahman, Nasir Mahmood Rajpoot, Bernardo Leon Rapoport, Tilman T. Rau, Jorge S. Reis-Filho, Joana M. Ribeiro, David Rimm, Anne Roslind, Anne Vincent-Salomon, Manuel Salto-Tellez, Joel Saltz, Shahin Sayed, Ely Scott, Kalliopi P. Siziopikou, Christos Sotiriou, Albrecht Stenzinger, Maher A. Sughayer, Daniel Sur, Susan Fineberg, Fraser Symmans, Sunao Tanaka, Timothy Taxter, Sabine Tejpar, Jonas Teuwen, E. Aubrey Thompson, Trine Tramm, William T. Tran, Jeroen van Der Laak, Paul J. van Diest, Gregory E. Verghese, Giuseppe Viale, Michael Vieth, Noorul Wahab, Thomas Walter, Yannick Waumans, Hannah Y. Wen, Wentao Yang, Yinyin Yuan, Reena Md Zin, Sylvia Adams, John Bartlett, Sibylle Loibl, Carsten Denkert, Peter Savas, Sherene Loi, Roberto Salgado, Elisabeth Specht Stovgaard

Summary: The clinical significance of tumor-immune interaction in breast cancer has been established. Tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative and HER2-positive breast cancer. The use of machine learning (ML) to automatically evaluate TILs has shown promising results. However, there are challenges in implementing this in trial and routine clinical management, including technical slide issues, ML and image analysis aspects, data challenges, and validation issues.

JOURNAL OF PATHOLOGY (2023)

Article Neurosciences

Uncovering CNS access of lipidated exendin-4 analogues by quantitative whole-brain 3D light sheet imaging

Grethe Skovbjerg, Urmas Roostalu, Casper G. Salinas, Jacob L. Skytte, Johanna Perens, Christoffer Clemmensen, Lisbeth Elster, Camilla K. Frich, Henrik H. Hansen, Jacob Hecksher-Sorensen

Summary: Peptide-based drug development for CNS disorders is hindered by poor BBB penetrability. This study used LSFM to visualize the distribution of lipidated peptide drugs in the CNS. The results demonstrated that lipidation enhances the CNS accessibility of the peptide drug Ex4.

NEUROPHARMACOLOGY (2023)

Article Polymer Science

Surface Roughness and Grain Size Variation When 3D Printing Polyamide 11 Parts Using Selective Laser Sintering

Riccardo Tonello, Knut Conradsen, David Bue Pedersen, Jeppe Revall Frisvad

Summary: Selective laser sintering (SLS) is a well-established additive manufacturing technology. Efforts have been made to improve SLS by optimizing powder deposition, laser parameters, and temperature settings. This study evaluated the surface roughness and grain size differences of curved objects manufactured using a new SLS technology featuring two CO laser sources. Significant differences were found in some surface roughness and grain size measurements when varying build setup, presence of thin walls, and sample position on the powder bed.

POLYMERS (2023)

Article Multidisciplinary Sciences

Spatially offset optical coherence tomography: Leveraging multiple scattering for high-contrast imaging at depth in turbid media

Gavrielle R. Untracht, Mingzhou Chen, Philip Wijesinghe, Josep Mas, Harold T. Yura, Dominik Marti, Peter E. Andersen, Kishan Dholakia

Summary: The penetration depth of optical coherence tomography (OCT) is greater than conventional microscopy, but signal reduction with depth is a challenge. This study explores the role of multiple scattering in OCT image contrast and introduces a geometry that separates the incident and collection fields, enhancing contrast at depth. Theoretical and experimental results demonstrate a significant improvement in contrast, with a ninefold enhancement observed in biological samples.

SCIENCE ADVANCES (2023)

Article Imaging Science & Photographic Technology

Dot Off Dot Screen Printing with RGBW Reflective Inks

Alina Pranovich, Sergiy Valyukh, Sasan Gooran, Jeppe Revall Frisvad, Daniel Nystrom

Summary: This study investigates the angle-dependent gamut of RGBW primaries and dot gain in halftoned printing. It provides colorimetric data for the efficient application of interference RGBW pigments in practical applications.

JOURNAL OF IMAGING SCIENCE AND TECHNOLOGY (2023)

Article Imaging Science & Photographic Technology

Metal Artifact Reduction in Spectral X-ray CT Using Spectral Deep Learning

Matteo Busi, Christian Kehl, Jeppe R. Frisvad, Ulrik L. Olsen

Summary: Spectral X-ray computed tomography (SCT) is a promising technique for non-destructive imaging. The proposed correction method, based on spectral deep learning, efficiently reduces streaking artifacts in all energy channels. Additional information in the energy domain is crucial for restoring the quality of low-energy reconstruction affected by metal artifacts.

JOURNAL OF IMAGING (2022)

No Data Available