Review
Green & Sustainable Science & Technology
Wei Peng, Giovanni Beggio, Alberto Pivato, Hua Zhang, Fan Lue, Pinjing He
Summary: Near-infrared spectroscopy and hyperspectral imaging techniques combined with chemometric method have been applied to address challenges in anaerobic digestion plants, and can be used for monitoring and optimizing process parameters and evaluating quality.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Multidisciplinary Sciences
Krishna C. Polavaram, Nishant Garg
Summary: A newly developed Raman imaging protocol is capable of mapping unpolished samples with an auto-focusing Z-mapping feature for direct fingerprinting of different polymorphs. The methodology for generating high-fidelity phase maps using characteristic peak intensity ratios can be extended to any multi-phase, heterogenous system. These enhancements allow rapid mapping of unpolished granite specimens with high accuracy and fine spatial resolution.
SCIENTIFIC REPORTS
(2021)
Article
Optics
Farid Ullah Khan, Aldo Moreno-Oyervides, Oscar Elias Bonilla-Manrique, Pedro Martin-Mateos
Summary: High-performance hyperspectral imaging is in high demand due to its wide range of capabilities. However, traditional systems have limitations in resolving narrow spectral features. In this study, we introduce the first hyperspectral dual-comb imaging system with sub-GHz optical resolutions and fast acquisition rates in the mid-infrared region.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Jinghua Wang, Lei Yan, Fan Wang, Shanshan Qi
Summary: This paper proposes a synthesized classification method based on multisensor hyperspectral imaging to assess the vitality of corn seeds. Various preprocessing techniques and feature selection algorithms were employed, and SVM classification models were established, achieving high accuracy.
JOURNAL OF SENSORS
(2022)
Article
Food Science & Technology
Antoine Laborde, Francesc Puig-Castellvi, Delphine Jouan-Rimbaud Bouveresse, Luc Eveleigh, Christophe Cordella, Benoit Jaillais
Summary: This study successfully detected peanut flour adulteration in chocolate powder using NIR hyperspectral imaging and chemometrics, with adulterated pixel detection rates ranging from 0% to 17% in mixed samples.
Article
Plant Sciences
Julio Nogales-Bueno, Berta Baca-Bocanegra, Jose Miguel Hernandez-Hierro, Raquel Garcia, Joao Mota Barroso, Francisco Jose Heredia, Ana Elisa Rato
Summary: Persian walnut is rich in bioactive compounds and consuming it can protect against cardiovascular, carcinogenic, and neurological disorders. This study used near infrared hyperspectral imaging to screen fatty acids in walnuts, showing that imaging technology could be a reliable tool for this purpose.
FRONTIERS IN PLANT SCIENCE
(2021)
Article
Ecology
Paul D. Zander, Stefanie B. Wirth, Adrian Gilli, Sandro Peduzzi, Martin Grosjean
Summary: Pigments produced by anoxygenic phototrophic bacteria are valuable proxies for past anoxia in lacustrine and marine environments. In this study, in situ hyperspectral imaging (HSI) core scanning was used to rapidly and non-destructively document high-resolution changes in oxygenic and anoxygenic phototrophic communities in Lake Cadagno, Switzerland. The HSI method successfully detected three distinct groups of pigments in the lake sediments, representing different phototrophic communities: oxygenic phototrophs, purple sulfur bacteria (PSB), and green sulfur bacteria (GSB). The results were validated by pigment measurements using spectrophotometer and high-performance liquid chromatography (HPLC). This study demonstrates the potential of HSI as a rapid tool to study samples containing pigments of both oxygenic and anoxygenic phototrophs.
Article
Food Science & Technology
Y. Dixit, M. Al-Sarayreh, C. R. Craigie, M. M. Reis
Summary: This study demonstrates a novel approach to develop global calibration models for predicting intramuscular fat (IMF) and pH across various red meat species and muscle types. These prediction models, developed using Partial Least Squares Regression (PLSR) and Deep Convolutional Neural Networks (DCNN), showed high accuracy in predicting pH and IMF values in red meat samples.
Article
Agronomy
Maylin Acosta, Isabel Rodriguez-Carretero, Jose Blasco, Jose Miguel de Paz, Ana Quinones
Summary: Visible and near-infrared hyperspectral imaging was used to determine the nutrient contents in persimmon leaves. The models based on partial least square regression achieved satisfactory results for nitrogen, phosphorous, calcium, magnesium, and boron, but lower prediction rates were attained for potassium, iron, copper, zinc, and manganese.
Article
Chemistry, Analytical
Cassio Lima, Howbeer Muhamadali, Yun Xu, Mustafa Kansiz, Royston Goodacre
Summary: This study demonstrates the use of infrared spectroscopy to track the uptake of stable isotope-labeled compounds by bacteria at the single-cell level, providing insights into microbial systems. The development of a new far-field infrared imaging technique, optical photothermal infrared (O-PTIR) spectroscopy, allows for monitoring the metabolic activity of individual bacteria and predicting isotopic ratios simultaneously using spectral signatures.
ANALYTICAL CHEMISTRY
(2021)
Article
Biochemistry & Molecular Biology
Hongzhe Jiang, Yilei Hu, Xuesong Jiang, Hongping Zhou
Summary: The maturity stages of Camellia oleifera fruit can be assessed accurately using a hyperspectral imaging system. Principal component analysis and classification models can be used to accurately discriminate different maturity stages. Selecting the correct wavelengths can improve the prediction accuracy.
Article
Chemistry, Multidisciplinary
Yajun Yu, Yuchen Tang, Kaiqin Chu, Tingjuan Gao, Zachary J. Smith
Summary: This study introduces a new method called dynamic azo-enhanced Raman imaging (DAERI) for high-resolution low-power cellular imaging. Compared to traditional methods, DAERI offers higher sensitivity and spatial resolution, and enables multiplex visualization of organelles.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2022)
Article
Nanoscience & Nanotechnology
Kirill Kniazev, Evgenii Zaitsev, Shubin Zhang, Yang Ding, Loc Ngo, Zhuoming Zhang, Gregory V. Hartland, Masaru Kuno
Summary: Label-free, bond-selective imaging has new opportunities in chemistry, biology, and material science. However, issues such as low sensitivity, low spatial and temporal resolution hinder its application in studying spatially-congested specimens. In this paper, a widefield infrared photothermal heterodyne imaging technique (wIR-PHI) is introduced, which overcomes these issues and enables high-resolution imaging with hyperspectral capabilities and high sensitivity. The technique has potential for kinetic imaging and spectroscopic studies in important chemical, biological, and material processes in the future. Rating: 9/10.
Article
Chemistry, Applied
Abolfazl Dashti, Judith Mueller-Maatsch, Emma Roetgerink, Michiel Wijtten, Yannick Weesepoel, Hadi Parastar, Hassan Yazdanpanah
Summary: The performance of visible-near infrared hyperspectral imaging (Vis-NIR-HSI) and shortwave infrared hyperspectral imaging (SWIR-HSI) combined with different classification and regression multivariate methods for meat authentication was evaluated. In Vis-NIR-HSI, the SVM and ANN-BPN models achieved higher accuracies (96% and 94%) in the prediction set compared to SWIR-HSI (88% and 89%). In terms of coefficient of determination (R2p) and root mean square error in prediction (RMSEP), Vis-NIR-HSI outperformed SWIR-HSI for different meat combinations.
Article
Remote Sensing
Hamid Ghanbari, Dermot Antoniades
Summary: The particle size of lake sediments contains important environmental information and detecting its changes over time is crucial for understanding ecosystems and sedimentary processes. This study proposes a new method that utilizes a one-dimensional convolutional autoencoder and a one-dimensional convolutional neural network (CNN) for regression analysis, and successfully reconstructs particle size from hyperspectral images of lake sediment cores. The proposed CNN method outperforms the traditional random forest algorithm in terms of predictive accuracy.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Environmental Sciences
Kevin Jacq, Yves Perrette, Bernard Fanget, Pierre Sabatier, Didier Coquin, Ruth Martinez-Lamas, Maxime Debret, Fabien Arnaud
SCIENCE OF THE TOTAL ENVIRONMENT
(2019)
Article
Computer Science, Information Systems
Reda Boukezzoula, Didier Coquin, Kevin Jacq
INFORMATION SCIENCES
(2020)
Article
Geology
Kevin Jacq, Charline Giguet-Covex, Pierre Sabatier, Yves Perrette, Bernard Fanget, Didier Coquin, Maxime Debret, Fabien Arnaud
SEDIMENTARY GEOLOGY
(2019)
Article
Geography, Physical
Philippe Sorrel, Kevin Jacq, Antonin Van Exem, Gilles Escarguel, Benjamin Dietre, Maxime Debret, Suzanne McGowan, Jules Ducept, Emilie Gauthier, Hedi Oberhaensli
Summary: This study utilizes visible and near infrared (VNIR), and short-wave infra-red (SWIR) hyperspectral imaging combined with geochemical analyses to reconstruct the lake stratification history, redox status, and mixing conditions in Lake Son Kol over the last 8500 years. The research reveals multiple episodes of hypolimnetic anoxia coinciding with increased snowmelt and warmer temperatures, leading to the deposition of dark organic sediments in the lake. The disappearance of hypolimnetic anoxia in Lake Son Kol is linked to strengthened wind conditions and enhanced lake overturning, highlighting the potential for abrupt ecosystem changes even without anthropogenic climate change.
QUATERNARY SCIENCE REVIEWS
(2021)
Article
Chemistry, Applied
Sylvain Treguier, Kevin Jacq, Christel Couderc, Hicham Ferhout, Helene Tormo, Didier Kleiber, Cecile Levasseur-Garcia
Summary: Fast diagnostic tools like near infrared spectroscopy have gained interest for bacterial identification. A new procedure for bacterial screening directly on agar plates has been proposed to reduce nutrient medium bias. Results show that principal component analysis in transmission mode and extended multiplicative scatter correction can effectively discriminate between different genera of bacteria and reduce external bias.
JOURNAL OF NEAR INFRARED SPECTROSCOPY
(2021)
Article
Environmental Sciences
Kevin Jacq, Estelle Ployon, William Rapuc, Claire Blanchet, Cecile Pignol, Didier Coquin, Bernard Fanget
Summary: The article discusses a method of creating high-resolution ortho-images using metrically calibrated targets and its potential applications in sediment core image processing. By processing multiple raw images, clear and undistorted ortho-images can be obtained, which can play a significant role in paleoclimate and paleoenvironmental studies.
JOURNAL OF PALEOLIMNOLOGY
(2021)
Article
Archaeology
Claire Chanteraud, Emilie Chalmin, Matthieu Lebon, Helene Salomon, Kevin Jacq, Camille Nous, Jean-Jacques Delannoy, Julien Monney
Summary: Analysing the colouring matter used in prehistoric rock art is essential for understanding the techniques used. This study compared in-situ and laboratory analyses of materials from the Points cave in France, finding that current pXRF systems are unable to provide suitable data for elucidating the chaines operatoires of ferruginous colouring matter.
JOURNAL OF ARCHAEOLOGICAL SCIENCE-REPORTS
(2021)
Article
Environmental Sciences
Kevin Jacq, William Rapuc, Alexandre Benoit, Didier Coquin, Bernard Fanget, Yves Perrette, Pierre Sabatier, Bruno Wilhelm, Maxime Debret, Fabien Arnaud
Summary: This study compares several supervised classification algorithms to analyze sedimentary structures in lake sediments. The results show that the Short Wave Infrared (SWIR) sensor is the best choice for creating robust classification models with discriminant analysis, while the Visible Near-Infrared (VNIR) sensor is affected by surface reliefs and structures. The combined use of hyperspectral imaging and machine learning improves the characterization of sedimentary structures compared to conventional methods.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Review
Geosciences, Multidisciplinary
Kevin Jacq, Maxime Debret, Bernard Fanget, Didier Coquin, Pierre Sabatier, Cecile Pignol, Fabien Arnaud, Yves Perrette
Summary: Hyperspectral imaging is an emerging technology that can be used to extract environmental properties of sediment cores. This article presents the applications of hyperspectral imaging in sediment core analysis and the current research progress in this field.
Article
Geosciences, Multidisciplinary
Antonin Van Exem, Maxime Debret, Yoann Copard, Kevin Jacq, Charles Verpoorter, Stephane Marcotte, Benoit Laignel, Boris Vanniere
Summary: Tracking past primary productivity through hyperspectral imaging analysis of chlorophyll-a allows for quick determination of indices, but detrital organic matter and mineral phase in sediments can impact the results. Normalizing indices by sediment components helps reduce these impacts for more accurate assessment.
Article
Geology
William Rapuc, Kevin Jacq, Anne-Lise Develle, Pierre Sabatier, Bernard Fanget, Yves Perrette, Didier Coquin, Maxime Debret, Bruno Wilhelm, Fabien Arnaud
SEDIMENTARY GEOLOGY
(2020)
Proceedings Paper
Computer Science, Information Systems
Kevin Jacq, Didier Coquin, Bernard Fanget, Yves Perrette, Maxime Debret
2019 22ND INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION 2019)
(2019)