Multivariate NIR studies of seed-water interaction in Scots Pine Seeds (Pinus sylvestris L.)

This thesis describes seed-water interaction using near infrared (NIR) spectroscopy, multivariate regression models and Scots pine seeds. The presented research covers classification of seed viability, prediction of seed moisture content, selection of NIR wavelengths and interpretation of seed-water interaction modelled and analysed by principal component analysis, ordinary least squares (OLS), partial least squares (PLS), bi-orthogonal least squares (BPLS) and genetic algorithms. The potential of using multivariate NIR calibration models for seed classification was demonstrated using filled viable and non-viable seeds that could be separated with an accuracy of 98-99%. It was also shown that multivariate NIR calibration models gave low errors (0.7% and 1.9%) in prediction of seed moisture content for bulk seed and single seeds, respectively, using either NIR reflectance or transmittance spectroscopy. Genetic algorithms selected three to eight wavelength bands in the NIR region and these narrow bands gave about the same prediction of seed moisture content (0.6% and 1.7%) as using the whole NIR interval in the PLS regression models. The selected regions were simulated as NIR filters in OLS regression resulting in predictions of the same quality (0.7 % and 2.1%). This finding opens possibilities to apply NIR sensors in fast and simple spectrometers for the determination of seed moisture content. Near infrared (NIR) radiation interacts with overtones of vibrating bonds in polar molecules. The resulting spectra contain chemical and physical information. This offers good possibilities to measure seed-water interactions, but also to interpret processes within seeds. It is shown that seed-water interaction involves both transitions and changes mainly in covalent bonds of O-H, C-H, C=O and N-H emanating from ongoing physiological processes like seed respiration and protein metabolism. I propose that BPLS analysis that has orthonormal loadings and orthogonal scores giving the same predictions as using conventional PLS regression, should be used as a standard to harmonise the interpretation of NIR spectra

Application of Infrared Spectroscopy and Chemometrics to the Cocoa Industry for Fast Composition Analysis and Fraud Detection

Tesis por compendio[ES] El cacao es un producto de alto valor, no únicamente por sus características sensoriales, sino porque también presenta un alto contenido en antioxidantes y alcaloides estimulantes con efectos saludables. Debido a la alta demanda, la industria del cacao en polvo tiene el desafío de asegurar la calidad de grandes volúmenes de producción de una manera rápida y precisa, evitando la presencia de contaminantes o adulterantes en la materia prima, ofreciendo productos donde se preserven las propiedades saludables. La espectroscopia del infrarrojo cercano (NIR) es una tecnología rápida y no destructiva útil en el análisis de productos alimentarios. La presente tesis doctoral se centra en evaluar el potencial uso del NIR como una herramienta de control de calidad con el fin de poder resolver problemas que se presentan en la industria del cacao en polvo. Los problemas a resolver incluyen la detección de materiales no deseados o adulterantes en el cacao en polvo, y la monitorización rápida y precisa del contenido de flavanoles y metilxantinas del cacao en polvo durante el proceso de alcalinización. El primer capítulo evalúa la viabilidad del NIR, en combinación con análisis quimiométricos, en la detección de la presencia de materiales no deseados o adulterantes como son cascarilla de cacao o harina de algarroba. Para ello, diferentes muestras de cacao en polvo natural y con diferentes niveles de alcalinización (suave, medio y fuerte) fueron mezcladas con distintas proporciones de cascarilla de cacao (con cacao natural) o harina de algarroba (con cacao natural y alcalinizado). Los resultados obtenidos indican que el NIR, combinado con modelos estadísticos tales como el análisis discriminante por mínimos cuadrados parciales (PLS-DA) y la regresión parcial de mínimos cuadrados (PLS), es un método rápido y eficaz para identificar cualitativa y cuantitativamente materiales no deseados o adulterantes como la cascarilla y la algarroba en cacao en polvo, independientemente del grado de alcalinización o el nivel de tostado de la harina de algarroba. En el segundo capítulo, el análisis composicional del cacao en polvo se orientó al control de los cambios producidos en el contenido de flavanoles y metilxantinas debidos al proceso de alcalinización al que se somete el caco en polvo. Se determinó el contenido de catequina, epicatequina, cafeína y teobromina mediante cromatografía líquida de alta resolución (HPLC), correlacionándose los contenidos obtenidos para cada uno de estos compuestos con las determinaciones NIR. Se obtuvieron buenos modelos para la predicción de los compuestos mediante regresión PLS con valores superiores a 3 para la relación entre el rendimiento y la desviación (RDP), lo cual demuestra que los modelos obtenidos pueden ser utilizados para la rápida y fiable predicción del contenido de flavanoles y metilxantinas en cacaos naturales y con diferentes niveles de alcalinización.[CA] El cacau és un producte d'alt valor, no sols per les seues característiques sensorials, sinó perquè també presenta un elevat contingut en antioxidants i alcaloids estimulants amb efectes saludables. A conseqüència a l'alta demanda, l'industria del cacau en pols té el desafiament d'assegurar la qualitat de grans volums de producció d'una manera ràpida i precisa, evitant la presència de contaminants o adulterants en la matèria cosina, oferint productes a on se preserven les propietats saludables. L'espectroscòpia de l'infrarroig proper (NIR) és una tecnologia ràpida i no destructiva útil en l'anàlisi de productes alimentaris. La present tesis doctoral se centra en avaluar el potencial ús del NIR com una eina de control de qualitat amb l'objectiu de poder resoldre problemes que es presenten en l'industria del cacau en pols. Els problemes a resoldre inclouen la detecció de materials no desitjats o adulterants en el cacau en pols, i la monitorització ràpida i precisa del contingut de flavanols i metilxantines del cacau en pols durant el procés d'alcalinització. El primer capítol avalua la viabilitat del NIR, en combinació amb anàlisis quimiométrics, en la detecció de la presència de materials no desitjats o adulterants com són pellofa de cacau o farina de garrofa. Per a això, diferents mostres de cacau en pols natural i amb diferents nivells d'alcalinització (suau, mig i fort) foren barrejades en distintes proporcions de pellofa de cacau (en cacau natural) o farina de garrofa (en cacau natural i alcalinisat). Els resultats obtinguts per a NIR, combinats amb models estadístics com l'anàlisi discriminant per mínims quadrats parcials (PLS-DA) i la regressió parcial de mínims quadrats (PLS), és un mètode ràpid i eficaç per identificar materials no desitjats o adulterants com la pellofa de cacau o la farina de garrofa, amb independència del grau d'alcalinització del cacau o de torrat de la farina de garrofa. En el segon capítol, l'anàlisi composicional del cacau en pols s'orientà al control dels canvis produïts en el contingut de flavanols i metilxantines a causa del procés d'alcalinització al que se sotmet el cacau en pols. Es va determinar el contingut de catequina, epicatequina, cafeïna i teobromina mitjançant cromatografia líquida d'alta resolució (HPLC), i es van correlacionar els continguts obtinguts per a cadascun d'estos composts amb les determinacions NIR. Es van obtindré bons models per a la predicció dels composts mitjançant regressió PLS amb valors superiors a 3 per a la relació entre el rendiment i la desviació (RDP), la qual cosa demostra que els models obtinguts poden ser emprats per a la ràpida i fiable predicció del contingut de flavanols i metilxantines en cacaus naturals o amb diferents nivells d'alcalinització.[EN] Cocoa is a product of high value, not only because of its sensory characteristics, but also because it has a high content of antioxidants and stimulating alkaloids with health effects. Due to the high demand, the cocoa powder industry has the challenge of ensuring the quality of large volumes of production in a fast and accurate way, avoiding the presence of contaminants or adulterants in the raw material, offering products where the healthy properties are preserved. The near infrared spectroscopy (NIR) is a rapid and non-destructive technology useful in the analysis of food products. The present doctoral thesis focuses on evaluating the potential use of NIR as a quality control tool in order to solve problems that arise in the cocoa industry powdered. The problems to solve include the detection of unwanted materials or adulterants in the cocoa powder, and the rapid and accurate monitorization of the flavanols and methylxanthines content in the cocoa powder during the alkalization process. The first chapter evaluates the viability of the NIR, in combination with chemometric analysis, in the detection of presence of unwanted materials or adulterants such as cocoa shell or carob flour. For this, different samples of natural cocoa powder and with different levels of alkalization (light, medium and strong) were mixed with different proportions of cocoa shell (with natural cocoa) or carob flour (with natural and alkalized cocoa). The results obtained indicate that the NIR combined with statistical models such as the partial least squares discriminant analysis (PLS-DA) and the partial least squares regression (PLS), is a fast and efficient method to identify qualitative and quantitative unwanted materials or adulterants such as shell and carob in cocoa powder, regardless of the degree of alkalization or level of roasting of carob flour. In the second chapter, the compositional analysis of cocoa powder was oriented to the control of the changes produced in the content of flavanols and methylxanthines due to the process of alkalization to which the cocoa powder is subjected. The content of catechin, epicatechin, caffeine and theobromine were determined by high performance liquid chromatography (HPLC), correlating the contents obtained for each of these compounds with the NIR determinations. Good models were obtained for the prediction of compounds by regression PLS with values above 3 for the ratio of performance to deviation (RDP), which shows that the obtained models can be used for the quick and reliable prediction of flavanol content and methylxanthines in natural cocoas and with different alkalization levels.This Doctoral Thesis has been carried out thanks to a doctoral studies scholarship granted by the Ministry of Higher Education, Science, Technology and Innovation (SENESCYT) of the Republic of EcuadorQuelal Vásconez, MA. (2019). Application of Infrared Spectroscopy and Chemometrics to the Cocoa Industry for Fast Composition Analysis and Fraud Detection [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/135258TESISCompendi

A Comparative Study of Benchtop and Portable NIR and Raman Spectroscopic Methods for the Quantitative Determination of Curcuminoids in Turmeric Powder

Turmeric consumption is continually increasing worldwide. Curcuminoids are major active constituents in turmeric and are associated with numerous health benefits. A combination of spectroscopic methods and chemometrics shows the suitability of turmeric for food quality control due to advantages such as speed, versatility, portability, and no need for sample preparation. Five calibration models to quantify curcuminoids in turmeric were proposed using benchtop and portable devices. The most remarkable results showed that Raman and NIR calibration models present an excellent performance reporting RMSEP of 0.44% w/w and 0.41% w/w, respectively. In addition, the five proposed methods (FT-IR, Raman, and NIR) were compared in terms of precision and accuracy. The results showed that benchtop and portable methods were in good agreement and that there are no significant differences between them. This study aims to foster the use of portable devices for food quality control in situ by demonstrating their suitability for the purpose

Changes in methylxanthines and flavanols during cocoa powder processing and their quantification by near-infrared spectroscopy

[EN] Variation in methylxanthines (theobromine and caffeine) and flavanols (catechin and epicatechin) was studied in a large set of cocoa powders (covering different origins, processing parameters and alkalisation levels). The content of these compounds was established by high-performance liquid chromatography (HPLC), whose results showed that the alkalisation process lowered the content of all analytes, whose loss was more evident in flavanols. Therefore, the determination of these analytes in a huge set of samples allowed not only better knowledge of the concentration variability in natural commercial cocoas from different origins, but also the understanding of the effect that industrial alkalisation has on these contents. The feasibility of reflectance near-infrared spectroscopy (NIRS) combined with partial least square (PLS) to non-destructively predict these contents, was also evaluated. All the analytes were generally well predicted, with predictions for methylxanthines (R-P(Z) 0.819-0.813 and RMSEP 0.068-0.022%, and bias 0.005 and 0.007 for theobromine and caffeine, respectively) and for flavanols (R-P(Z) 0.830-0.824; RMSEP 8.160-7.430% and bias - 1.440 and -1.034 for catechin and epicatechin, respectively). Thus NIRS could be an alternative fast reliable method for the routine assessment of these analytes in the cocoa industry.The authors would like to acknowledge the financial support of the Spanish Government and European Regional Development Fund (Project RTC-2016-5241-2). M. A. Quelal thanks the Ministry of Higher Education, Science, Technology and Innovation (SENESCYT) of the Republic of Ecuador for her PhD grant. Olam Food Ingredients Company is aknowledged for proving part of the cocoa samples used in the study.Quelal-Vásconez, MA.; Lerma-García, MJ.; Pérez-Esteve, É.; Arnau-Bonachera, A.; Barat Baviera, JM.; Talens Oliag, P. (2020). 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Near infrared spectroscopy as a new tool to determine cocoa fermentation levels through ammonia nitrogen quantification. Food Chemistry, 148, 240-245. doi:10.1016/j.foodchem.2013.10.005Humston, E. M., Knowles, J. D., McShea, A., & Synovec, R. E. (2010). Quantitative assessment of moisture damage for cacao bean quality using two-dimensional gas chromatography combined with time-of-flight mass spectrometry and chemometrics. Journal of Chromatography A, 1217(12), 1963-1970. doi:10.1016/j.chroma.2010.01.069Kongor, J. E., Hinneh, M., de Walle, D. V., Afoakwa, E. O., Boeckx, P., & Dewettinck, K. (2016). Factors influencing quality variation in cocoa (Theobroma cacao) bean flavour profile — A review. Food Research International, 82, 44-52. doi:10.1016/j.foodres.2016.01.012Krähmer, A., Engel, A., Kadow, D., Ali, N., Umaharan, P., Kroh, L. W., & Schulz, H. (2015). Fast and neat – Determination of biochemical quality parameters in cocoa using near infrared spectroscopy. 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Application of infrared spectral techniques on quality and compositional attributes of coffee: An overview

AbstractDuring the last two decades, near and mid-infrared spectral analyses have emerged as a reliable and promising analytical tool for objective assessment of coffee quality attributes. The literature presented in this review clearly reveals that near and mid-infrared approaches have a huge potential for gaining rapid information about the chemical composition and related properties of coffee. In addition to its ability for effectively quantifying and characterising quality attributes of some important features of coffee such as moisture, lipids and caffeine content, classification into quality grades and determination of sensory attributes, it is able to measure multiple chemical constituents simultaneously avoiding extensive sample preparation. Developing a quality evaluation system based on infrared spectral information to assess the coffee quality parameters and to ensure its authentication would bring economical benefits to the coffee industry by increasing consumer confidence in the quality of products. This paper provides an overview of the recently developed approaches and latest research carried out in near and mid-infrared spectral technology for evaluating the quality and composition of coffee and the possibility of its widespread deployment

Development and application of spectroscopy techniques for monitoring hydrate and corrosion risks

Pipelines are used to transport hydrocarbons from production wells to different locations for various purposes (e.g. processing, refinery, power generation, etc.) and CO2-rich fluids from the emission sources for disposal in suitable geological storage sites. The presence of water in such hydrocarbon and/or CO2 transport pipelines may result in corrosion, ice and/or gas hydrate formation and even pipeline blockage, so the fluid system should meet certain dehydration and/or inhibition requirements. This work describes the development and application of different spectroscopic (UV-VIS and NIR) methods for identifying and controlling flow assurance issues relating to gas hydrate and corrosion. For hydrates, a Fourier Transform Near-Infrared (FTNIR) spectroscopy method using chemometric models was developed to measure the concentration of main hydrocarbon gases (Methane through butanes) under in-situ pressure (up to 13.8 MPa). This approach was then used for detecting initial signs of hydrate formation based on reduction in the concentration of some preferential components in the gas phase. Furthermore, injection of hydrate inhibitors based on the calculated/measured hydrate phase boundary, water cut, pressure and temperature conditions, and the amount of inhibitor lost to non-aqueous phases is a commonly used method for avoiding gas hydrates problems. Thus, it is crucial to monitor salt and inhibitor concentration in the fluids along the pipeline and/or downstream in order to optimise the injection rate. To address this requirement, a novel method was developed by combining UV and NIR spectra to predict the concentration of salt and hydrate inhibitors (THIs and KHIs) simultaneously in aqueous solutions. In the case of corrosion, the potential of visible spectroscopic technique was investigated for determining the pH in CO2/ CO2-rich mixtures saturated water, and CO2/ CO2-rich mixtures saturated NaCl solutions at pressures up to 15 MPa and temperature ranges from 293.15 to 323.15 K. Furthermore, we described and evaluated a model that uses a robust thermodynamic basis for describing the solubility of gases in the aqueous phase and Pitzer’s theory for determining the activity coefficients of the ionic species involved. The model was tested in concentrated NaCl solutions under CO2 pressure at realistic industrial operating temperatures. The developed spectroscopic techniques were experimentally evaluated at lab conditions. Results show that these techniques can be applied to detect initial signs of hydrate formation, to optimise hydrate inhibitor injection rate, and to measure the pH of CO2 saturated H2O/brine systems in the downhole/wellbore/pipeline region

Chemometrics Methods Applied to Non-Selective Signals in Order to Address Mainly Food, Industrial and Environmental Problems

Chemometrics is a chemical discipline that uses mathematical and statistical methods in order to extract useful information from multivariate chemical data. Moreover, chemometrics is applied to correlate quality parameters or physical properties to analytical instrument data such as calculating pH from a measurement of hydrogen ion activity or a Fourier transform interpolation of a spectrum. Aim of this thesis project is to develop chemometrical strategies for the elaboration and the interpretation of non-selective complex data in order to solve real problems in food, industry and environmental fields

Development of innovative analytical methods based on spectroscopic techniques and multivariate statistical analysis for quality control in the food and pharmaceutical fields.

The increasing demand on quality assurance and ever more stringent regulations in food and pharmaceutical fields are promoting the need for analytical techniques enabling to provide reliable and accurate results. However, traditional analytical methods are labor-intensive, time-consuming, expensive and they usually require skilled personnel for performing the analysis. For these reasons, in the last decades, quality control protocols based on the employment of spectroscopic methods have been developed for many different application fields, including pharmaceutical and food ones. Vibrational spectroscopic techniques can be an adequate alternative for acquiring both chemical and physical information related to homogenous and heterogenous matrices of interest. Moreover, the significant development of powerful data-driven methodologies allowed to develop algorithms for the optimal extraction and processing of the complex spectroscopic signals allowing to apply combined approaches for quantitative and qualitative purposes. The present Doctoral Thesis has been focused on the development of ad-hoc analytical strategies based on the application of spectroscopic techniques coupled with multivariate data analysis approaches for providing alternative analytical protocols for quality control in food and pharmaceutical sectors. Regarding applications in food sector, excitation-emission Fluorescence Spectroscopy, Near Infrared Spectroscopy (NIRS) and NIR Hyperspectral Imaging (HSI) have been tested for solving analytical issues of independent case-studies. Unsupervised approaches based on Principal Component Analysis (PCA) and Parallel Factor Analysis (PARAFAC) have been applied on fluorescence data for characterizing green tea samples, while quantitative predictive approaches as Partial Least Squares regression have been used to correlate NIR spectra with quality parameters of extra-virgin olive oil samples. HSI was applied to study dynamic chemical processes which occur during cheese ripening with the aim to map chemical and sensory changes over time. The rapid technical progress in terms of spectroscopic instrumentations has led to have more flexible portable systems suitable for performing measurements directly in the field or in a manufacturing plant. Within this scenario, NIR spectroscopy proved to be one of the most powerful Process Analytical Technologies (PAT) for monitoring and controlling complex manufacturing processes. In this thesis, two applications based on the implementation of miniaturized NIR sensors have been performed for the real-time powder blending monitoring of pharmaceutical and food formulation, respectively. The main challenges in blending monitoring are related to the assessment of the homogeneity of multicomponent formulations, which is crucial to ensure the safety and effectiveness of a solid pharmaceutical formulation or the quality of a food product. In the third chapter of this thesis, tailor made qualitative chemometric strategies for obtaining a global understanding of blending processes and to optimize the endpoint detection are presented

Application of near-infrared spectroscopy for determination of nutrient contents in manure

111 solid poultry layer, 95 solid poultry broiler litter, 39 swine solid hoop, 72 beef cattle, 85 swine slurry, and 88 swine liquid lagoon manure samples were collected from farms in three states. Samples were analyzed for total nitrogen (TN), ammonia nitrogen (NH3-N), phosphorus (P), and potassium (K) and total solids (TS) by traditional laboratory methods. The strong relationships of TN, NH3-N, P and K with TS were only found for K in swine lagoon manure and for P in swine slurry. Further, poor prediction performance was found in regression lines even with a strong relationship by using the ratio of standard deviation/standard error of prediction (RPD). These manure samples were also used to develop NIRS calibration models by using different mathematical data pretreatments. The R2 of the one-out cross validation for TS, TN, and NH3-N are between 0.80 and 0.97 for all manure samples. The R2 of the one-out cross validation for minerals range from 0.71 to 0.81, 0.50 to 0.78, 0.74 to 0.94, 0.66 to 0.91, 0.73 to 0.91, and 0.70 to 0.90 in poultry solid layer manure, poultry broiler litter, swine solid hoop, beef cattle, swine liquid lagoon, and swine slurry manure samples, respectively. The RPD values indicate NIRS can predict several minerals in certain manure samples, for example, P in beef cattle, swine lagoon, and swine slurry manure samples. Seventy-two beef cattle feedlot manure samples were scanned through the Foss NIRSystems 6500 (master) and the Foss NIRSystems 5000 (slave) instruments. Three standardization methods including cloning, direct standardization, and piece-wise direct standardization were used to transfer the master equations to slave spectra. The 72-sample data set was split into a 30-sample standardization set to generate standardized files and a 42-sample prediction set to test the accuracy of different standardization methods. The standard error of difference (SED) of the standardized slave spectra was much less than the corresponding SED of the unstandardized slave spectra. It was concluded that NIRS can determine TS, VS, TN, NH3-N, and possibly some minerals in manures rapidly and accurately, and the transfer of manure sample calibrations between instruments is possible

Application of Terahertz Technology in Biomolecular Analysis and Medical Diagnosis

Terahertz technology is a nondestructive technique, which has progressed significantly in the scientific research and gains highly attention in the analysis of biological molecular, cellular, tissues and organs. In this decade, some studies were reported on the application of terahertz technology in medical testing and diagnosis. Here, we summarize the terahertz characters, terahertz spectroscopy, and terahertz imaging technology combined with chemometrics. This chapter focuses on introducing the research progress on analyzing the tissues of cancers using terahertz spectroscopy and terahertz imaging technology. Furthermore, the problems should be solved, and development directions of terahertz spectroscopy and terahertz imaging technology are discussed