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Proceedings of the 21st International Conference on Near Infrared Spectroscopy

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Über dieses Buch

Die Proceedings der 21st International Conference on Near Infrared Spectroscopy (NIR 2023 Innsbruck) präsentieren eine umfassende Sammlung von Beiträgen renommierter Forscher, Wissenschaftler und Fachleute aus der Industrie, die sich zusammengefunden haben, um ihre Expertise und Fortschritte auf der NIR 2023-Konferenz zu teilen. Dieser Band deckt ein breites Themenspektrum ab und spiegelt die herausragende Vielseitigkeit und praktische Bedeutung der starken Analysetechnik und ihrer zeitgenössischen Möglichkeiten wider. Die Vorträge fassen bahnbrechende Forschungsergebnisse, neuartige Instrumente und vielfältige Anwendungen im Bereich der NIR-Spektroskopie zusammen. Das Buch untersucht die neuesten Methoden, Techniken und Trends in der NIR-Spektroskopie, die auf der NIR 2023 vorgestellt und diskutiert wurden. Es untersucht die zugrunde liegende Grundlagenforschung, die Entwicklung innovativer Instrumente, Methoden sowie modernster Datenanalysetechniken und deren Anwendung in Schlüsselbereichen wie Pharmazeutika, Lebensmittelanalytik, Landwirtschaft, biomedizinischer Diagnostik und Umweltüberwachung. Jeder Artikel in diesem Band repräsentiert aktuelle Trends auf dem Gebiet der NIR-Spektroskopie und präsentiert originelle Forschungsergebnisse und praktische Erkenntnisse. Dieses Buch spiegelt die Themen der ersten NIR-Spektroskopiekonferenz wider und stellt eine unverzichtbare Ressource für Forscher, Praktiker und Studenten dar, die an vorderster Front der NIR-Spektroskopie bleiben wollen. Die Hoffnung ist, dass die Proceedings of NIR 2023 als Katalysator für weitere Exploration, Zusammenarbeit und Innovation im dynamischen Bereich der NIR-Spektroskopie dienen werden.

Inhaltsverzeichnis

Frontmatter
Good Vibrations, Smooth Contours: NIR 2023 Conference in Hindsight
Abstract
NIR 2023, the 21st meeting of the International Council of Near Infrared Spectroscopy (ICNIRS), took place from August 20–24, 2023, in Innsbruck, Austria. This was the first time ICNIRS was held in Austria, and with over 380 participants from 37 countries, this gathering marked a strong return to in-person events after the disruptions caused by COVID-19. As the top global conference in the area of NIR spectroscopy, its success confirmed the continuously evolving nature and growing importance of the technique and its applications.
Krzysztof Bec, Christian Huck
Near Infrared Spectroscopy: A “Restless” Analytical Technique for a Multiplicity of Applications
Abstract
This article is a highly personal assessment of the development, special features and current significance of NIR spectroscopy for quality and process control in the material and life sciences. The stunning evolution over the last five decades from hang-on to UV/VIS or MIR spectrometers via stand-alone laboratory instruments to their current use as light-fiber coupled process control tools, imaging spectrometers and miniaturized sensors in pocket-size finds few analogues in instrumental analytical chemistry. The initial organizational difficulties in implementing the NIR technique in industrial analytical laboratories are addressed as well as the gradual optimization of chemometric evaluation procedures and technical advancements that have contributed to its current importance as an analytical technique. From the perspective of a conservative spectroscopist, specific beneficial features of the NIR technique are highlighted and some myths that have unnecessarily delayed the rapid spread of the NIR technique are dispelled. The current potential of the technique for in-the-field and on-site measurements is emphasized in light of advances in miniaturization and special attention will be paid to possible applications that will allow a clientele that is not necessarily scientifically trained to solve quality control and authentication problems with this technology in everyday life. Finally, the danger is addressed not to fall into the exaggerated narrative of some direct-to-consumer companies, which has raised expectations with full-bodied promises, but has harmed the very valuable technology of NIR spectroscopy, rather than promoting its further development.
H. W. Siesler
Combining Elastic and Inelastic Light Scattering Spectroscopy: The Hidden Champion in PAT Applications
Abstract
In the context of IIoT (industrial internet of things) or I40 (Industry 4.0), PAT is established now in industry as an enabling technology to control and monitor processes at the molecular level. Sensors based on optical spectroscopy can be used to record the chemical structure of molecules using the absorption spectra. In the case of opaque systems even the nanoscopic morphology of particles, cells or tissues can simultaneously be measured by their complex spectra of the elastic light scattering (ELS) features. To fully exploit these two fundamental information different strategies can be applied. This review starts with examples of single particle analysis resp. particle aggregates classification using optical spectroscopy at shorter wavelengths to demonstrate the power of ELS. Complex morphological structures of chromosomes or tissues can fast and accurately be classified using hyperspectral imaging technology. When multiple methods are used, e.g., the combination of Raman and UV-Vis-spectroscopy, multimodal optical spectroscopy offers several advantages, particularly when examining and characterizing biological materials with markers at low concentrations. The major advantage of using NIR spectroscopy instead of multimodal spectroscopy is however, that both, absorption and scattering spectra can be measured simultaneously with a single device. This feature saves time and costs especially in PAT applications. The purpose of this presentation is to demonstrate to the reader the potential of inline spectroscopy for the chemical and morphological characterization of materials through various examples.
Rudolf W. Kessler, Waltraud Kessler, Edwin Ostertag
Near Infrared Spectroscopy Explores Mysteries of Ancient and Modern Medicine – Plenary Opening Lecture
Abstract
Near Infrared Spectroscopy (NIRS) is a powerful technology used in many areas of medicine, including traditional and innovative medicine. In ancient medicine, NIRS has been used to gain insights into diseases and medical treatments of the past. For example, in traditional medicine, NIRS can be used to determine effects of acupuncture and the quality of herbal medicines. In modern medicine, NIRS is used to diagnose and monitor diverse conditions, including brain injuries, stroke, and cancer. Over the decades, the application of NIRS in neuroscientific and neurological research has gained importance, and the number of scientific studies has grown extensively. Within the current opening lecture, a short review and highlights from 1995 to 2023 from an interdisciplinary research team at the Medical University of Graz, Austria, Europe, was presented. Main topics are among others results from transcranial cerebral oximetry in the hyperbaric environment and the non-invasive assessment of oxygen metabolism using NIRS technology during high altitude trekking in the Nepal Himalayas. In addition, NIRS publications from intensive care medicine and needle and laser acupuncture are presented and discussed. NIRS could be a fruitful approach helping to explore deeper biological mysteries within the brain and the periphery. Overall, NIRS is a powerful tool that has the potential to unlock many mysteries of ancient and modern medicine. As technology continues to improve, it is likely that NIRS will become even more important in the diagnosis and treatment of a wide range of medical conditions.
Gerhard Litscher
The Lure of Curvature
Abstract
Some generic modelling- and interpretation- problems in multivariate calibration of multichannel instruments (chemometric “machine learning”) are addressed wrt extrapolation, interpolation and interpretation. Multi-wavelength high-speed diffuse spectrophotometry in e.g. the Near InfraRed (NIR) wavelength range are information rich but require “mathematical cleanup”: Whether they are measured as transmittance, interactance or reflectance, such high-speed real-world data are affected by several different types of variation. These combine to offer certain data modelling challenges, like multicollinearity, mixed additive-and-multiplicative effects and response curvature. Through a progression of linear and bilinear preprocessing and calibration steps, multivariate data modelling is shown to pick up and correct for these challenges, with a strong focus on statistical validation wrt overfitting and on linear extrapolation power. A particular focus is on how to handle curvature, implicitly and explicitly. The lure of curvature is that mathematically useful, but causally meaningless linear modelling effects of nonlinear curvature may be interpreted as “new and interesting spectral details”. This is illustrated with high-precision NIR transmittance spectra of powder mixtures, from an experiment especially designed to reveal the “dirty” effects of light absorption and scattering. A simulation example demonstrates the lure of curvature explicitly. Finally, a successful linear approximation of nonlinear curvature is illustrated conceptually, by the approximation of a curved (nonlinear) 3D banana by a flat (linear) 2D boomerang.
Harald Martens
Chemometrics is More Than Algorithms
Abstract
As ever more sophisticated calibration algorithms become the focus of interest, we must not lose sight of the fact that getting good spectra on a well-chosen training set as well as validating properly and understanding why the calibration works are at least as important as the choice of algorithm to a successful outcome. The AI-driven automated systems for NIR calibration that will soon become available need to take these factors into account and not simply focus on algorithms.
Tom Fearn
Hyperspectral Imaging for Process Control in Coating, Printing and Finishing Technologies
Abstract
This contribution illuminates the potential of hyperspectral imaging for the characterization and permanent monitoring of web-like materials, which are produced or converted in continuous roll-to-roll processes such as coating, printing, lamination or finishing. It is shown that this experimental technique is a mighty process analytical tool, which is able to provide extensive information about the corresponding technical processes, which might be used for both quality assurance and control of the production process itself. A broad range of specific applications in the various converting technologies is presented in which parameters such as the degree of conversion, the application weight or the moisture content after drying are in the focus of interest. Moreover, it is discussed how hyperspectral imaging can be efficiently adapted to very wide widths (several meters) of the web.
Olesya Daikos, Tom Scherzer
NIRS—Aquaphotomics: New Integrative Science and Technology Platform
Abstract
Near Infrared Spectroscopy (NIRS) embodies a richly interdisciplinary domain, where the near infrared (NIR) spectra find multifaceted applications across various fields. Yet, despite its versatility, the NIR community may not fully grasp the spectrum’s manifold potentials within the systems under study. Numerous phenomena within NIR spectra, such as non-linearity, spectral components, light-scatter, and polarization effects, remain inadequately understood. A thorough understanding of NIR spectra is of fundamental importance for maximizing the use of its full potential.
Roumiana Tsenkova
NIR Spectroscopy Contributed to SDGs—From Viewpoint of Wood Science and Technology
Abstract
Wood science and technology contribute to the Sustainable Development Goals (SDGs) in many ways. For example, by promoting sustainable forestry, they help in the appropriate management and conservation of forest resources, directly contributing to the protection of biodiversity (SDG15) and enhancing mitigation and adaptation to climate change (SDG13). Increasing demand for wood and wood products can also increase income from sustainable forestry, contributing to the improvement of livelihoods for communities involved in forestry (SDG1, SDG8). Furthermore, as wood is a renewable resource obtained from properly managed forests, it plays a role as a sustainable building material (SDG11, SDG12). Several kinds of state-of-art technology is useful for this. Especially, spectroscopic and imaging method is a great method for examining organic compounds, often used with advanced data analysis techniques. We show how spectroscopic and imaging method can contribute to sustained food supply. Thanks to improvements in spectral imaging and data analysis, some devices can do more than ever before.
Satoru Tsuchikawa, Tetsuya Inagaki, Te Ma
Recent Results of Near Infrared Spectroscopy on the Way “from Farm to Fork” or Even Further
Abstract
Agri-food products undergo very complex journeys until they reach our kitchens. Initial challenges start on the farm and continue in processing, storage, transport, distribution and even consumption. Besides the origin of the raw materials, value chain processes influence the quality of our food and finally our health. Modern digitalization endeavors, however, provide great opportunities to ensure the quality and authenticity of agri-food products. Development of digital fingerprinting approaches enable on-the-spot examinations providing comprehensive information about the product. This study aims to provide insights about recent results of Near Infrared Spectroscopy (NIRS) supporting the monitoring of food supply “from farm to fork” – and beyond. Numerous studies have demonstrated in our work the efficacy of NIRS across different stages of the food supply chain in providing comprehensive insights into tested materials, which has proven that NIRS is one of the most comprehensive tools to evaluate the old saying, “you are what you eat”. The most recent findings in the field of nutritional neuroscience even enable the technique to move beyond the confines of food quality assessment to directly correlate nutrition and health.
Zoltan Kovacs, Matyas Lukacs, George Bazar, Zoltan Gillay, Juan Pablo Aguinaga Bósquez, Mariem Majadi, Flora Vitalis
Different Ways to Assess the Vitreousness of Durum Wheat Kernels Using NIR Spectroscopy
Abstract
The standard method used to grade the vitreousness of durum wheat (Triticum turgidum ssp. durum) kernels relies on a tedious visual inspection of sliced kernels. Four devices based on near-infrared (NIR) spectroscopy were tested for the assessment of kernel vitreousness: two benchtop spectrometers (XDS NIR rapid content analyzer and Infratec™ NOVA, FOSS, Denmark), a single-kernel analyzer (QSorter EXPLORER 2.0, QualySense AG, Switzerland) and a hyperspectral imaging system (FX17, Spectral Imaging Ltd., Finland). Partial least square (PLS) regression models were developed using the mean spectra of bulk samples measured on the XDS, NOVA and QSorter to predict vitreousness. Similar performances were obtained in validation with both benchtop instruments, but the best results were achieved with the single-kernel analyzer. The ratios of performance to deviation (RPD) were nevertheless >2 for all instruments. Classification models based on partial least squares discriminant analysis (PLS-DA) were developed at the kernel-level for the single-kernel analyzer and at the pixel-level with the imaging system. The implementation of the QSorter classification model on unsorted batches showed some errors but results are promising for optical sorting. The classification of non-vitreous kernels using hyperspectral imaging reached a sensitivity of 73.5% and a specificity of 92.4% in external validation. The assessment of durum wheat kernels vitreousness based on the kernels intrinsic characteristics using NIR spectroscopy showed its potential to replace the labor-intensive reference method. Despite differences in performances, each type of instrument may find its use in a different context.
C. Demoitié, D. Vincke, P.-Y. Werrie, A. Pissard, B. Godin, W. R. Meza Morales, J. A. Fernández Pierna, V. Baeten, P. Vermeulen
Predicting Fungal Infection Sensitivity of Sepals in Harvested Tomatoes Using Imaging Spectroscopy and Partial Least Squares Discriminant Analysis
Abstract
Tomatoes (Solanum lycopersicum L.) are a widely grown and globally traded vegetable, essential for both local consumption and international trade. However, approximately 30% of harvested tomato yields are lost due to fungal decay during postharvest handling. Timely disease identification is crucial to prevent such losses, but certain tomato varieties exhibit higher susceptibility to fungal infections than others. Additionally, there are variations in susceptibility among individual sepals, with unknown underlying causes.
Traditional methods for assessing fungal presence in plants have limitations, such as sample destruction and a focus on symptom detection rather than evaluating susceptibility to fungal infection. Hence, there is a need for a dependable, non-destructive method capable of swiftly predicting susceptibility to fungal infection. Our objective is to utilize Hyperspectral Imaging (HSI) with chemometric analysis to achieve this, a novel approach not previously explored in research.
In our study, we employed three tomato cultivars (‘Brioso,’ ‘Cappricia,’ and ‘Provine’). Hyperspectral images were captured on May 10th, followed by controlled fungal growth conditions. Ground truth assessments were conducted by three experts on May 12th and 13th, averaging severity scores assigned per sepal.
Our methodology involved extracting spectra from HSI images and calibrating and validating models using Partial Least Squares Discriminant Analysis (PLSDA), aiming to optimize model parameters for accurate predictions. The models are categorized into those developed using data from a single variety (intravariety) and those utilizing data from multiple varieties combined (global models).
The best-performing intravariety model was established using the Cappricia variety, achieving a balanced accuracy of 0.84. Conversely, a global model combining Cappricia and Provine varieties achieved a balanced accuracy of 0.70.
Overall, our research suggests that distinguishing between more and less susceptible sepals is feasible under controlled conditions.
Mercedes Bertotto, Hendrik de Villiers, Aneesh Chauhan, Esther Hogeveen-van Echtelt, Manon Mensink, Zeljana Grbovic, Dimitrije Stefanovic, Marko Panic, Sanja Brdar
Chemical Interpretation of Meaningful Variables in Chemometric Models by Theoretical Simulation: The Case of NIR Analysis of Pharmaceuticals
Abstract
Multivariate calibration methods are crucial in near-infrared (NIR) spectroscopy, enabling the extraction of chemically specific information from complex spectra. Conventional performance metrics provide a basic framework for assessing model accuracy, but they tend to oversimplify the inherently multidimensional nature of the problem, ignoring the detailed chemical information being processed underneath. In NIR spectroscopy, predictions are fundamentally based on molecular absorption characteristics, yet the interpretability of these models frequently poses challenges. The inherent complexity of NIR spectra complicates the interpretation of the relationships between absorption features and the variables in the calibration model. Recent advances in quantum chemical simulations hold promise for overcoming these difficulties. This paper presents a proof-of-concept for the use of spectra simulation in interpreting the meaningful variables in multivariate regression models, monitoring the spectral pretreatment quality, evaluating instrumental differences and enhancing the predictive power of the model itself. PLS-R models are obtained and examined for paracetamol, caffeine and cellulose in a model pharmaceutical mixture, with an extension to a comparative analysis of three NIR spectrometers: the Hefei SouthNest Technology nanoFTIR, Viavi MicroNIR 1700 ES, and the benchtop Büchi NIRFlex N-500. Additionally, the study highlights the importance of supervised feature selection and identifies specific signatures of model overfitting. The findings demonstrate the utility of incorporating interpreted data into analytical method development and show the potential for informed sensor selection tailored to the unique characteristics of the analytical problem at hand.
Krzysztof Bec, Justyna Grabska, Alexandra Warzilek, Christian Huck
PAT Case Studies for Pharmaceutical Process Scale-Up and Optimization of Solid Dosage Forms
Abstract
The implementation of PAT tools in pharmaceutical manufacturing has shown great advantages and applications from development to routine production, covering process understanding, scale-up support, troubleshooting, minimizing process variability and enhancing the control strategy or for real-time release of the product. This goal can only be achieved by clearly understanding the manufacturing process and by implementing the suitable technology for manufacturing and for process control. Each unit operation brings challenges that need to be assessed to prevent compromising the quality of the final product. NIR spectroscopy, as one of the major PAT tools, has attracted a lot of attention from the pharmaceutical industry since it can analyze bulk solids without previous treatment, therefore reducing or eliminating wet chemistry analysis.
Three cases are presented on the real PAT applications during process development. One case considers the blending monitoring by means of a hybrid PLS model generated with data collected at different manufacture scales. Second case tackles the challenges of process development related to blending and tableting. The third case describes the monitoring of the moisture trajectories during spray granulation. PAT enables a lean evaluation of the product quality, better understanding and supports process transfer. NIR proved to be a versatile and valuable tool for the pharmaceutical development and manufacturing.
Lizbeth Martinez, Matthieu Clavaud
Insights into Anharmonicity and Local Environment of Liquid Phase Amides (N-Methylformamide and Di-N,N-Methylformamide) via NIR and MIR Carbonyl Stretching Bands
Abstract
This study explores the anharmonicity and intermolecular interactions of N-methylformamide (NMF) and di-N,N-methylformamide (DMF) in the neat liquid phase, with a focus on amide bands. We analyzed the vibrational spectra in the mid- (MIR) and near-infrared (NIR) regions (11,500–560 cm−1; 870–17,857 nm) including the complex refractive index. Using Classical Damped Harmonic Oscillator (CDHO) theory, we simultaneously modeled the real and imaginary components of the spectra, identifying band positions, oscillator strengths, and damping constants from the experimental data. This provided insights into vibrational energy dissipation and self-association in liquid amides. The identification of MIR and NIR bands was based on anharmonic GVPT2//B3PLYP/6–311 +  + G(d,p) calculations. The distinct self-association patterns of DMF and NMF were revealed in the MIR fingerprint region by the two components of the νC = O band, analogous to the Amide I band. These findings are further supported by structural information derived from NIR spectra. Additionally, the study examined the contribution of overtones and combination bands in the MIR spectra of amides. Our conclusions on the molecular interactions and structural dynamics of NMF and DMF enhance the understanding of how changes in the local environment affect the amide group.
Justyna Grabska, Krzysztof Bec, Jerzy P. Hawranek, Christian Huck
Near Infrared Spectroscopy as a Reliable Tool for the Control Analysis of Cannabis Sativa L
Abstract
Cannabis sativa L. is an ancient cultivar that has gained much attention due to its versatility in different industries, e.g., medicine, textile and food. The quality control of the plant and their active pharmaceutical ingredients (APIs) is mandatory to guarantee the safety and effectiveness of the pharmaceutical product. In this context, Near Infrared Spectroscopy (NIRS) has emerged as a powerful technique due to its multiple advantages, e.g., non-destructive, cost-effective and rapid. In this article, a handheld NIRS has been employed, in combination with chemometrics, for the development of seven predictive models to determine five cannabinoids, along with moisture and nitrogen content in Cannabis samples, affording values of coefficient of determination of cross validation (R2CV) in the range of 0.75–0.99. To evaluate the suitability of the models, cross validation was performed, which provided low standard error of prediction (SEP) values, alongside slope values close to or equal to 1. Additionally, residual predictive deviation (RPD) was calculated for each parameter, obtaining values in the range of 1.67–9.36. Finally, the performance of the predictive results obtained has been compared with those achieved in previous research to demonstrate the suitability of the handheld instrument compared to two robust NIRS benchtop devices. Several improvements were highlighted for the determination of different parameters in Cannabis samples.
M. C. Díaz-Liñán, C. Ferreiro-Vera, M. T. García-Valverde
NIR Monitoring of Hemp Oil Shelf Life Stored in Different Materials and at Two Temperatures
Abstract
Recently there has been a renewed interest in hempseed oil (Cannabis sativa L.) in the food industry due to the beneficial properties provided by hemp seeds and oil. Hemp oil is extremely rich in linoleic (18:2 w6) and α-linolenic (18:3 w3) acids. Moreover, it is rich in antioxidants, such as tocopherols and phenolic compounds. The presence of high concentrations of unsaturated fatty acids in hemp oil determines its high sensitivity to oxidative and photo-oxidative degradation. These processes generate peroxides, dienes, and trienes that are at the basis of the phenomenon of rancidity. A batch of hemp oil was obtained by cold pressing Futura 75 seeds. The oil was then transferred and packed into 20ml vials made of polypropylene, clear glass, amber glass, and amber glass coated with aluminum foil. The samples were stored for 150 days at ambient temperature (T 25 ℃) under diffused light and refrigerated temperature (T 10 ℃) in dark conditions in order to simulate the common storage conditions. To monitor the stability of hemp seed oil, peroxide value determination and conjugated dienes and trienes were evaluated. The peroxide number (expressed as meq O2/kg) was determined using the iodometric technique, while spectrophotometer analysis was used to measure the conjugated dienes and trienes of fatty acids. NIR spectra were measured in transmission. The sample dataset of spectra was analyzed using ASCA in order to test the spectral significance of the experimental factors. Analysis of the ASCA model showed a significance with a confidence of 5% of all factors and of all the simple interactions.
Andrea Gasparini, Francesca Bonazza, Lucia Monti, Valeria Pelizzola, Milena Povolo, Stefania Bar-zaghi, Giovanni Cabassi
Near-Infrared (NIR) Spectroscopic Examination of Water Interaction with Polymer Matrices
Abstract
The interactions between water and polymers represents a research field of great interest. Interplay between water and biopolymers has a fundamental function in biochemical processes, as well as an influential characteristic in materials science and industry caused by the interaction of commercially used polymers with water. The investigation of the properties of water-polymer systems has often been performed using vibrational spectroscopy techniques (infrared or Raman). In contrast, the potential of near-infrared spectroscopy (NIRS, 12,500–4000 cm−1; 800–2500 nm) has received little attention in studying this problem. Although NIRS offers exclusive opportunities for the study of molecular structures and their interactions. Unique information from the overtones and combination bands is accessible with this technique. NIRS is also very well suited for the analysis of aqueous systems, as both the bands of water and the polymer can be reliably acquired in a range of concentrations, in a more straightforward manner than it is possible in MIR spectroscopy. In this study the polymer-water interactions of polymers with diverse hydrophilicity were investigated by NIRS. On the one hand, commercially used hydrophobic polymers: polytetrafluoroethylene (PTFE), polypropylene (PP), polystyrene (PS), polyvinylchloride (PVC), polyoxymethylene (POM), polyamide 6 (PA) and on the other hand biopolymers: lignin, chitin and cellulose, were analyzed. The polymer-water mixtures were examined in a mass concentration range of 1–10% water. Analysis and interpretation of the NIR spectra included cluster analysis methods, difference spectroscopy, Multivariate Curve Resolution (MCR) and Two-Dimensional Correlation Spectroscopy (2D-COS). This research revealed clearly visible trends in NIR spectra related to the increasing hydrophilicity and the chemical nature of the polymer. It has been shown that changes in the NIR spectrum of water are also observed upon the interaction with very hydrophobic polymers (e.g., PTFE). Moreover, it was found that in the presence of different polymers, the revealed spectral patterns of water varied between the two main bands (νs + νas and νas + δ) in the NIR spectrum of water.
Vanessa Moll, Krzysztof Bec, Christian Huck
Recent Developments in Aquaphotomics: Insights into Water Structure and Functionality
Abstract
Aquaphotomics, a new field of science established in 2005 by Roumiana Tsenkova, focuses on the exploration of the interaction between water and light across the entire range of the electromagnetic spectrum. Its primary aim is to comprehend the structure and functionality of water within aqueous and biological systems, ultimately seeking to understand the universe and unravel the essence of life itself. The results of the first systematization of aquaphotomics knowledge led to the identification of 12 wavelength regions within the first overtone of water in the near-infrared (NIR) spectrum, named WAMACS (Water Matrix Coordinates), which represent specific water molecular species recurring across various systems and associated with distinct functions. Recent developments in aquaphotomics have been focused on more in-depth investigations of how certain water structures are connected to the properties and functionality of the examined systems. These studies contributed to a more complete picture of water as a polyphasic system encompassing vapor, liquid, amorphous, liquid-crystalline, semi-crystalline, and crystalline phases. The result of the ongoing efforts of research across the world and time has resulted in refining the definitions of WAMACs and better delineating the initial 12 WAMACs, resulting in the current proposal of 20 tentative WAMACs, with the expectation of finding at least 4 or 5 more in the first overtone of water. With this effort completed, it can be expected that similar efforts will continue into other overtones including the ones of the combination bands of the NIR range, offering a more comprehensive understanding of water-light interaction and the information it can provide, as well as more knowledge about the NIR range itself. By elucidating the intricate relationship between water and life, aquaphotomics offers valuable insights that could pave the way for practical applications and transformative discoveries.
Jelena Muncan, Roumiana Tsenkova
What Is Hidden Underneath NIR Lineshape of Water?
Abstract
The vibrational spectrum of water attracts significant scientific interest, particularly in the mid-infrared (MIR) region, which is characterized by strong fundamental bands associated with OH stretching vibrations. However, the overtones and combination bands in near-infrared (NIR) spectrum, though less studied, offers valuable complementary insights into water structure and properties. Liquid water is characterized by highly convoluted vibrational bands, and considerable focus has been placed on gaining understanding of the structures that contribute to the observed spectra. Typically, the attempts to deconvolute the water band lineshape in NIR region were based on the assumption that full correspondence can be found in the better studied MIR bands. In this study, vibrational spectra were simulated using anharmonic quantum chemical methods applied to a range of water species up to a pentamer. The resulting lineshape accurately captured the characteristic NIR spectral profile of water. Notably, the spectral lines in the NIR and MIR regions exhibit differences due to anharmonic shifts between water species, leading to variations in the order and bandwidth of the contributing bands. Moreover, the NIR absorption curves of the contributing species demonstrated complex shapes. These findings demonstrate that the NIR spectrum delivers unique information on the structure and properties of water that is not redundant with fundamental bands of water located in the MIR region.
Justyna Grabska, Krzysztof Bec, Christian Huck
Influence of Milk Fat on Milk Coagulation Process: An Aquaphotomics Approach
Abstract
Several papers show that NIR technique is valuable auxiliary tool to aid the operator through the cheese-making process management. This capability relies mainly on the variations of the light scattering induced by the formation of the clot after the rennet addition to the milk. Light scattering and spectral baseline are also affected by fat globules that can interfere with the scope of the measurements: the aim of this study was to verify the actual influence of milk fat content on the spectral response, when monitoring the milk coagulation process, using an aquaphotomics approach. This study was conducted through an experimental design, in which different levels of fat and amounts of rennet were considered. Three different doses of calf rennet were added to a reconstituted powder cow milk previously acidified with natural starter whey. The NIR spectra of the milk with rennet, were collected in reflectance mode, every 5s during the coagulation, with a MicroNIR spectrometer, (VIAVI) at constant temperature. Evaluating the linear model calculated from the full factorial experimental design for predicting the clotting time it was verified that the fat content and the interaction “fat x calf rennet content” were not significant. Aquagrams were developed considering the absorbance values of wavelengths, in the first overtone of the O–H stretching band, which resulted significant in the exploratory PCA of the spectra. Linear models with interaction were calculated separately considering the spectra collected at each two-minute interval of the coagulation process, using the normalized absorbances of the most significant wavelengths as responses. It was verified that fat content has a certain influence on the spectral response, in the range of the first overtone, particularly in the early stages of the coagulation process.
Stefania Barzaghi, Nicolò Pricca, Giovanni Cabassi, Laura Marinoni
Nondestructive Estimation of Green Vegetable Freshness with Science-Based NIR Spectroscopy
Abstract
Vis-NIR spectroscopy is often used as a “black-box” without knowing its working mechanism to predict indicators. It is necessary to understand its working mechanism before it can be used reliably. First, Vis-NIR spectroscopy combined with PLSR analysis and the stepwise selectivity ratio (SWSR) method demonstrated the ability to accurately estimate the freshness of komatsuna and broccoli. The monitored cumulative CO2 production of komatsuna and the cumulative temperature of broccoli under different storage conditions were used as indicators of freshness, and the measured Vis-NIR spectra of komatsuna and broccoli were used as predictors. Based on the informative wavelengths (IWs) selected by the SWSR method, accurate predictive models of the freshness of komatsuna (R2p = 0.678) and broccoli (R2p = 0.753) were constructed through PLSR analysis. Then, NMR metabolomics analysis was used to measure the metabolites in the vegetable samples. Through the correlation analysis between the signals of informative NIR spectra selected at IWs and the signals of NMR spectra, four amino acids were commonly identified as candidate freshness markers of komatsuna and broccoli. These identified amino acids were negatively related to freshness, and protein absorption in NIR spectra. Protein degradation to amino acids owing to senescence during vegetable storage was detected as a change in the NIR spectral absorbance, which was chosen to build the predictive model for freshness estimation.
Xinyue Li
Measurement and Analysis of Papers, Inks, and Lamination Films Using Fourier-Transform Near-Infrared Hyperspectral Imaging System
Abstract
Visible and near-infrared hyperspectral imaging (HSI) has become instrumental in document examination, enabling authentication, tampering detection, and visualisation of obscured or faded samples. Utilising Si-CCD and Si-CMOS detectors operating in the 0.4–1.0 µm wavelength range, relatively inexpensive HSI systems can be constructed. On the other hand, longer-wavelength light detection requires detectors such as those made of InGaAs. In addition, HSI systems paired with spectrometers have been developed and commercialised. We adopt a near-infrared HSI system capable of detecting wavelengths from 1.0 to 2.35 µm to assess the spectral properties of various materials, including different types of paper, oil inks, and plastic cards. We evaluate the system capability to capture information that cannot be detected using conventional HSI operating in the 0.4–1.0 µm wavelength range. HSI systems are often equipped with dispersive or Fourier-transform spectrometers, each offering distinct advantages. The Fourier-transform spectrometer achieves superior light throughput compared with its dispersive counterpart, possibly increasing the instruments sensitivity for a given detector. Hence, we present measurement results obtained using a Fourier-transform HSI system.
Shigeru Sugawara, Ichiro Ishimaru
Nondestructive Single Seed Scale Phenomic Platform: Chickpea Quality Traits Based on SKNIR Spectroscopy
Abstract
There is a growing interest from breeders and producers in the development of single seed methodologies for quality analysis. Chickpea (Cicer arietinum) is one of the most important food legume crops with 13 million tons of global production and is consumed worldwide for its excellent carbohydrate, protein, minerals, dietary fiber, and vitamin content. This study explores the use of single kernel NIR (SKNIR) spectroscopy for rapid and nondestructive detection of chickpea seed composition and weight. Spectra were acquired from the diverse chickpea accessions with a single-seed based NIR spectrometer. Next, we developed partial least squares (PLS) regression models based on wet-lab reference data and spectra for protein, oil, and weight. For the protein model, the values for R2 and SEP were 0.85 and 1.56, respectively. For the oil model, the values for R2 and SEP were 0.80 and 10.37, respectively. For the weight model, the values for R2 and SEP were 0.835 and 0.06, respectively. The SKNIR spectroscopy technique was efficient in further predicting the oil and protein content of unseen cultivars. SKNIR spectroscopy coupled with PLS regression has revealed the feasibility of protein, oil, and weight prediction in single chickpea seeds. This study demonstrates the potential of SKNIR spectroscopy technique that should enable rapid screening of large number of chickpea genotypes. This research provides crop breeders and producers with a valuable tool for selecting chickpea varieties for their quality content.
Gokhan Hacisalihoglu, Paul Armstrong
Use of NIR Spectroscopy for the Monitoring and Control of Textile Dyeing Processes
Abstract
The textile industry poses a lot of environmental issues due to the number of resources it uses and the waste it produces, inspiring the constant search for technologic solutions that allow for the implementation of more sustainable and efficient industrial processes. Due to the flexibility of NIR spectroscopy, it presents itself as suitable for on-line monitoring and control of processes, by eliminating the need for sample preparation while accomplishing rapid non-destructive analysis. The objective of this work is to predict the point in which the desired color is achieved, in the textile dyeing process. NIR spectra of the dyeing operations were collected, and using chemometric techniques it was possible to develop prediction models and apply them at industrial scale. The integration of NIR spectroscopy for the on-line monitoring and control of textile dyeing will unlock the production of more sustainable and higher-quality products.
F. Marques, J. Martins, J. Santos, P. Magalhães, F. Magalhães, L. Carvalho
Backmatter
Metadaten
Titel
Proceedings of the 21st International Conference on Near Infrared Spectroscopy
herausgegeben von
Krzysztof Bec
Christian Huck
Copyright-Jahr
2025
Electronic ISBN
978-3-031-84794-3
Print ISBN
978-3-031-84793-6
DOI
https://doi.org/10.1007/978-3-031-84794-3