IDENTIFICATION OF COFFEE BEANS USING FTIR-SPECTROSCOPY AND MULTIVARIATE ANALYSIS

2021 ◽  
Author(s):  
Д.А. МЕТЛЕНКИН ◽  
Ю.Т. ПЛАТОВ ◽  
Р.А. ПЛАТОВА ◽  
А.Е. РУБЦОВ ◽  
А.М. МИХАЙЛОВА
Keyword(s):  
Multivariate Analysis ◽  
Discriminant Analysis ◽  
Ir Spectra ◽  
Ftir Spectroscopy ◽  
Spectral Data ◽  
Calibration Model ◽  
Absorption Bands ◽  
Coffee Beans ◽  
The Matrix ◽  
Decaffeinated Coffee

Для идентификации кофе используют методы газовой и жидкостной хроматографии, которые дают точную и подробную информацию о его химическом составе, однако трудоемки, сложны по пробоподготовке и непригодны для оперативного мониторинга качества. Цель настоящего исследования – разработка и апробация метода идентификации кофе по ботаническому виду, географическому месту произрастания и обжарке с применением Фурье-ИК-спектроскопии и многомерного анализа. В качестве объектов исследования были образцы кофе в зернах, различающиеся по ботаническому виду (арабика/робуста), географическому месту произрастания (Азия/Америка/Африка) и обжарке (жареный/нежареный). Для разработки моделей идентификации кофе в зернах была сформирована база спектральных данных и применены методы многомерного анализа – метод главных компонент (МГК) и дискриминантный анализ (ДА). ИК-спектры образцов кофе регистрировали с помощью Фурье-ИК-спектрометра Bruker ALPHA с алмазным модулем НПВО в диапазоне 4000–400 см–1 при разрешающей способности спектрометра 2 см–1. Спектральные данные были экспортированы из встроенного программного обеспечения OPUS 7.3.5.0 в Excel. При анализе матрицы спектральных данных выявлены наиболее интенсивные полосы поглощения ИК-спектра, приписываемые наличию функциональных групп воды, липидов, полисахаридов, кофеина и хлорогеновой кислоты в кофе. При сравнении ИК-спектров образцов кофеина, декофеинизированного кофе и кофе в зернах выявлены полосы поглощения спектра, которые можно использовать для построения калибровочной модели содержания кофеина в составе кофе в зернах. По спектральным данным МГК построена многомерная модель градации образцов кофе в зависимости от ботанического вида и наличия обжарки. По матрице факторных нагрузок выявлены полосы поглощения спектра, объясняющие различия образцов по ботаническому виду и обжарке и вносящие наибольший вклад в разделение образцов кофе на группы. Методом ДА по 19 переменным – коэффициентам поглощения на волновых числах спектра разработана система классификационных функций градации образцов кофе по географическому месту произрастания. Доказано, что сочетание Фурье-ИК-спектроскопии с методами многомерного анализа можно использовать как быстрый и неразрушающий инструмент для идентификации кофе в зернах. Gas and liquid chromatography methods are used to identify coffee. They provide accurate and detailed information about its chemical composition; however they are time-consuming, complex in sample preparation and unsuitable for operational quality monitoring. The purpose of this study is to develop and test a method for identifying coffee by botanical species, geographical place of growth and roasting using FTIR-spectroscopy and multivariate analysis. Samples of coffee beans were selected as objects of research, differing in botanical type (Arabica/Robusta), geographical place of growth (Asia/America/Africa) and roasting (roasted/not roasted). To develop models for the identification of grain coffee, a spectral database was formed and the methods of multivariate analysis were applied: principal components analysis (PCA), discriminant analysis. The IR-spectra of coffee samples were recorded using a Bruker ALPHA FTIR-spectrometer with a diamond module in the range of 4000–400 cm–1 with a resolution of the spectrometer of 2 cm–1. Spectral data were exported from the OPUS 7.3.5.0 embedded software to Excel. During analysis the matrix of spectral data, the most intense absorption bands of the IR-spectrum were revealed, attributed to the presence of functional groups of water, lipids, polysaccharides, caffeine and chlorogenic acid in grain coffee. By comparison the IR spectra of the samples: caffeine, decaffeinated coffee and grain coffee, absorption bands of the spectrum were revealed, which can be used to build a calibration model of the caffeine content in the composition of coffee beans. Using PCA based on the spectral data, a multivariate model of the gradation of coffee by botanical type and depending on the roast was build. According to the matrix of factor loadings, absorption bands of the spectrum were revealed, explaining the differences between the samples in botanical type and roasting and making the greatest contribution to the division of coffee samples into groups. By the method of discriminant analysis using 19 variables – absorption coefficients at the wave numbers of the spectrum – a system of classification functions for the gradation of grain coffee samples according to the geographical place of growth has been developed. It is proved that the combination of FTIR-spectroscopy with multivariate analysis methods can be used as a fast and non-destructive tool for identifying coffee beans.

Examinations of the Matrix Isolation Fourier Transform Infrared Spectra of Organic Compounds: Part XVI

1989 ◽  
Vol 43 (6) ◽  
pp. 1008-1016 ◽  
Author(s):  
W. M. Coleman ◽  
Bert M. Gordon
Keyword(s):  
Fourier Transform ◽  
Ir Spectra ◽  
Vapor Phase ◽  
Infrared Spectra ◽  
Condensed Phase ◽  
Matrix Isolation ◽  
Absorption Bands ◽  
Argon Matrix ◽  
The Matrix ◽  
The Impact

Information concerning the matrix isolation Fourier transform infrared spectra of a series of alkanes, esters, lactones, lactams, phenols, alcohols, amides, alkenes, and ketones is presented. A comparison between the characteristics of the spectra in two matrices (argon and xenon) as well as in the absence of any matrix (bare gold disk) is drawn. The impact of these matrices on the characteristics of the IR spectra is compared with the impact observed when spectra are gathered in the vapor phase as well as the condensed phase/solid state. For the majority of compounds studied, the major absorption bands of each class of compound fall between higher values for the vapor phase and lower values for the condensed phase when either argon or xenon is used as the matrix gas. The few exceptions are discussed. The absorption bands found in the xenon matrix are usually at a lower energy than are comparable bands in the argon matrix. In most all cases, the values of absorptions for compounds on the bare disk were lower than the comparable values found in the argon matrix. These results represent the first extensive study at 10 K of the effect of different matrix gas hosts and document the proposal that preconceptions of noble gases as inert hosts for the examination of FT-IR spectra at low temperature are not valid.

scholarly journals Spectrochemical differentiation in gestational diabetes mellitus based on attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy and multivariate analysis

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Emanuelly Bernardes-Oliveira ◽  
Daniel Lucas Dantas de Freitas ◽  
Camilo de Lelis Medeiros de Morais ◽  
Maria da Conceição de Mesquita Cornetta ◽  
Juliana Dantas de Araújo Santos Camargo ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Multivariate Analysis ◽  
Fourier Transform ◽  
Discriminant Analysis ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Ftir Spectroscopy ◽  
Total Reflection ◽  
Attenuated Total Reflection ◽  
Linear Discriminant

Abstract Gestational diabetes mellitus (GDM) is a hyperglycaemic imbalance first recognized during pregnancy, and affects up to 22% of pregnancies worldwide, bringing negative maternal–fetal consequences in the short- and long-term. In order to better characterize GDM in pregnant women, 100 blood plasma samples (50 GDM and 50 healthy pregnant control group) were submitted Attenuated Total Reflection Fourier-transform infrared (ATR-FTIR) spectroscopy, using chemometric approaches, including feature selection algorithms associated with discriminant analysis, such as Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA) and Support Vector Machines (SVM), analyzed in the biofingerprint region between 1800 and 900 cm−1 followed by Savitzky–Golay smoothing, baseline correction and normalization to Amide-I band (~ 1650 cm−1). An initial exploratory analysis of the data by Principal Component Analysis (PCA) showed a separation tendency between the two groups, which were then classified by supervised algorithms. Overall, the results obtained by Genetic Algorithm Linear Discriminant Analysis (GA-LDA) were the most satisfactory, with an accuracy, sensitivity and specificity of 100%. The spectral features responsible for group differentiation were attributed mainly to the lipid/protein regions (1462–1747 cm−1). These findings demonstrate, for the first time, the potential of ATR-FTIR spectroscopy combined with multivariate analysis as a screening tool for fast and low-cost GDM detection.

Examinations of the Matrix Isolation Infrared Spectra of Organic Compounds: PART XIII

1989 ◽  
Vol 43 (2) ◽  
pp. 305-310 ◽  
Author(s):  
W. M. Coleman ◽  
Bert M. Gordon
Keyword(s):  
Ir Spectra ◽  
Organic Compounds ◽  
Matrix Isolation ◽  
Intramolecular Hydrogen Bonding ◽  
Double Bond Position ◽  
Absorption Bands ◽  
The Matrix ◽  
Carbon Substitution ◽  
Ft Ir ◽  
Intramolecular Hydrogen

Matrix isolation Fourier transform infrared (MI/FT-IR) spectra have been collected on a series of internal alkenes, a series of hydroxy-substituted ketones, and a series of hydroxy-substituted esters. Assignments of double bond position and geometry are possible in the alkenes, due to the resolution of absorption bands of very similar energies. The location of the absorption bands for the alkenes was found to be very similar to the values found for the vapor-phase and condensed-phase spectra. Multiple carbonyl absorptions have been found in the MI/FT-IR spectra of the hydroxy ketones and hydroxy esters. Trends in the multiplicity of the carbonyl absorption patterns for these compounds as a function of ring size and hydroxyl carbon substitution have been used to document the presence of extensive intramolecular hydrogen bonding. The argon matrix as a phase for the study of stable organic compounds has, again, with this information, been shown to be unique.

Detection of aflatoxins B1 in  peanut oil using ATR-FTIR spectroscopy combined with partial least squares discriminant analysis and support vector machine models

2021 ◽  
Author(s):  
Han Song ◽  
Feng Li ◽  
Peiwen Guang ◽  
Xinhao Yang ◽  
Huanyu Pan ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Discriminant Analysis ◽  
Ftir Spectroscopy ◽  
Spectral Data ◽  
Aflatoxin Contamination ◽  
Peanut Oil ◽  
Support Vector ◽  
Grid Search ◽  
Discriminative Models ◽  
Svm Algorithm

This study establishes a rapid and accurate method to identify aflatoxin contamination in peanut oil. Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy, combined with either partial least squares discriminant analysis (PLS-DA) or a support vector machine (SVM) algorithm, were used to construct discriminative models for distinguishing between uncontaminated and aflatoxin-contaminated peanut oil. Peanut oil samples containing various concentrations of aflatoxin B1 (AFB1) were subjected to spectroscopic examination using an ATR-FTIR spectrometer. Preprocessed spectral data were input to PLS-DA and SVM algorithms to construct discriminative models for aflatoxin contamination in peanut oil. SVM penalty and kernel function parameters were optimized using grid search, a genetic algorithm, and particle swarm optimization. Results demonstrated that with the PLS-DA model established using spectral data, with an accuracy of 94.64%, exhibited better discriminative capacities than models established based on preprocessed data. The SVM model established after data normalization and grid search optimization with a penalty parameter of 16 and kernel function parameter of 0.0359 displayed the best discriminative capacity, with 98.2143% accuracy. The discriminative models for aflatoxin contamination in peanut oil established by combining ATR-FTIR spectral data and nonlinear SVM algorithm were superior to the linear PLS-DA models.

Multivariate consumption profiling (MCP) for intelligent meter systems: a methodology to define categories and levels

2010 ◽  
Vol 10 (5) ◽  
pp. 710-720 ◽  
Author(s):  
J. L. Solanas ◽  
M. R. Cussó
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Multivariate Analysis ◽  
Discriminant Analysis ◽  
Reference Population ◽  
Statistical Analyses ◽  
Conceptual Schema ◽  
Data Variability ◽  
Water Companies ◽  
Analyse Data

Multivariate Consumption Profiling (MCP) is a methodology to analyse the readings made by Intelligent Meter (IM) systems. Even in advanced water companies with well supported IM, full statistical analyses are not performed, since no efficient methods are available to deal with all the data items. Multivariate Analysis has been proposed as a convenient way to synthesise all IM information. MCP uses Factor Analysis, Cluster Analysis and Discriminant Analysis to analyse data variability by categories and levels, in a cyclical improvement process. MCP obtains a conceptual schema of a reference population on a set of classifying tables, one for each category. These tables are quantitative concepts to evaluate consumption, meter sizing, leakage and undermetering for populations and groupings and individual cases. They give structuring items to enhance “traditional” statistics. All the relevant data from each new meter reading can be matched to the classifying tables. A set of indexes is computed and thresholds are used to select those cases with the desired profiles. The paper gives an example of a MCP conceptual schema for five categories, three variables, and five levels, and obtains its classifying tables. It shows the use of case profiles to implement actions in accordance with the operative objectives.

scholarly journals Effect of Water Leaching on Photodegraded Scots Pine and Spruce Timbers Monitored by FTIR Spectroscopy

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 833
Author(s):  
Edina Preklet ◽  
László Tolvaj ◽  
Eszter Visi-Rajczi ◽  
Tamás Hofmann
Keyword(s):  
Ftir Spectroscopy ◽  
Scots Pine ◽  
Uv Irradiation ◽  
Chemical Elements ◽  
Uv Light ◽  
Carbonyl Groups ◽  
Water Leaching ◽  
Absorption Bands ◽  
Chemical Changes ◽  
Absorption Increase

The goal of this research was the systematic study and comparison of the divided individual effects of UV light irradiation and water leaching during artificial weathering. Spruce (Picea abies Karst.) and Scots pine (Pinus sylvestris L.) samples were irradiated by ultraviolet (UV) light. Another sequence of samples was treated with the combination of UV irradiation and water leaching. The total extent of UV treatment was 20 days for both series of samples. Time relation of UV irradiation and water leaching was 2:1. The chemical changes were observed by FTIR spectroscopy. The difference spectrum was used for determination of the chemical changes. Degradation of lignin was greater for the leached samples than for the pure UV treated samples. Scots pine suffered greater lignin degradation than spruce, and produced higher absorption increase on the absorption region of unconjugated carbonyls. The unconjugated carbonyl groups were the most responsive chemical elements to leaching. Spruce was more susceptible to leaching of unconjugated carbonyl groups than Scots pine. Two absorption bands of unconjugated carbonyl groups at 1706 and 1764 cm−1 wavenumbers were produced by photodegradation. The absorption band at 1764 cm−1 was more sensitive to water leaching than the band at 1706 cm−1.

Identification and Quantification of Metamizole in Traditional Herbal Medicines using Spectroscopy FTIR-ATR combined with Chemometrics

2021 ◽  
pp. 4413-4419
Author(s):  
Dharmastuti Cahya Fatmarahmi ◽  
Ratna Asmah Susidarti ◽  
Respati Tri Swasono ◽  
Abdul Rohman
Keyword(s):  
Discriminant Analysis ◽  
Herbal Medicine ◽  
Ftir Spectroscopy ◽  
Herbal Medicines ◽  
Principal Component ◽  
Attenuated Total Reflection ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Precision Data

The study aims to develop an effective, efficient, and reliable method using Fourier Transform Infrared (FTIR) spectroscopy with Attenuated Total Reflection (ATR) combined with chemometric for identifying the synthetic drug in Indonesian herbal medicine known as Jamu. Jamu powders, Metamizole, and the binary mixture of Jamu and Metamizole were measured using FTIR-ATR at the mid-infrared region (4000-650 cm-1). The obtained spectra profiles were further analyzed by Principal Component Analysis, Partial Least Square Regression, Principal Component Regression, and Discriminant Analysis. Jamu Pegel Linu (JPL), Jamu Encok (JE), Jamu Sakit Pinggang (JSP), Metamizole (M), and adulterated Jamu by Metamizole were discriminated well on PCA score plot. PLSR and PCR showed the accuracy and precision data to quantify JPL, JE, and JSP, and each adulterated by M with R2 value > 0,995 and low value of RMSEC and RMSEP. Discriminant Analysis (DA) was successfully grouping Jamu and Metamizole without any misclassification. A combination of FTIR spectroscopy and chemometrics offered useful tools for detecting Metamizole in traditional herbal medicine.

Synthesis of Galactomannan Sulfate-Citrate

2022 ◽  
Vol 1049 ◽  
pp. 218-223
Author(s):  
Aleksandr S. Kazachenko ◽  
Yuriy N. Malyar ◽  
Anna S. Kazachenko
Keyword(s):  
Biological Activity ◽  
Ftir Spectroscopy ◽  
X Ray Diffraction ◽  
Absorption Bands ◽  
X Ray ◽  
Mixed Ester ◽  
First Time ◽  
Derivatives Of

Sulfated derivatives of polysaccharides have anticoagulant, hypolipedimic and other biological activity. In this work, a complex mixed ester of galactomannan, its sulfate-citrate, was obtained for the first time. The introduction of citrate and sulfate groups was proved by FTIR spectroscopy by the appearance of corresponding absorption bands. It was shown by X-ray diffraction that the introduction of the citrate group leads to the amorphization of the galactomannan structure.

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