scholarly journals Diagnostic Potential of FT-IR Fingerprinting in Botanical Origin Evaluation of Laurus nobilis L. Essential Oil is Supported by GC-FID-MS Data

Molecules ◽  
2020 ◽  
Vol 25 (3) ◽  
pp. 583 ◽  
Author(s):  
Stella A. Ordoudi ◽  
Maria Papapostolou ◽  
Stella Kokkini ◽  
Maria Z. Tsimidou
Keyword(s):  
Model Performance ◽  
Principal Component ◽  
Cost Effective ◽  
Species Variation ◽  
Laurus Nobilis ◽  
Analytical Technique ◽  
Spectral Bands ◽  
Diagnostic Potential ◽  
Production History ◽  
Ft Ir

The last years, non-targeted fingerprinting by Fourier-transform infrared (FT-IR) spectroscopy has gained popularity as an alternative to classical gas chromatography (GC)-based methods because it may allow fast, green, non-destructive and cost-effective assessment of quality of essential oils (EOs) from single plant species. As the relevant studies for Laurus nobilis L. (bay laurel) EO are limited, the present one aimed at exploring the diagnostic potential of FT-IR fingerprinting for the identification of its botanical integrity. A reference spectroscopic dataset of 97 bay laurel EOs containing meaningful information about the intra-species variation was developed via principal component analysis (PCA). This dataset was used to train a one-class model via soft independent modelling class analogy (SIMCA). The model was challenged against commercial bay laurel and non-bay laurel EOs of non-traceable production history. Overall, the diagnostic importance of spectral bands at 3060, 1380–1360, 1150 and 1138 cm−1 was assessed using GC-FID-MS data. The findings support the introduction of FT-IR as a green analytical technique in the quality control of these often mislabeled and/or adulterated precious products. Continuous evaluation of the model performance against newly acquired authentic EOs from all producing regions is needed to ensure validity over time.

scholarly journals Pendugaan Kadar Air Beras Ketan Putih Dengan Teknologi NIRS Menggunakan Metode Principal Component Regression (pretreatment De-Trending, Derivative-2, dan Standart Normal Variate)

2020 ◽  
Vol 4 (4) ◽  
pp. 502-511
Author(s):  
Mardiantono Mardiantono ◽  
Fachruddin Fachruddin ◽  
Zulfahrizal Zulfahrizal
Keyword(s):  
Water Content ◽  
Model Performance ◽  
Principal Component Regression ◽  
Principal Component ◽  
Standard Normal Variate ◽  
Glutinous Rice ◽  
Standard Normal ◽  
Ft Ir ◽  
Pcr Method ◽  
Rice Water

Abtrak. Kadar Air merupakan salah satu komponen penting dalam beras ketan putih yang dapat mempengaruhi kualitas dari beras ketan putih. Penelitian ini bertujuan menguji dan mengevaluasi teknologi NIRS sebagai metode cepat dan tepat dalam memprediksi kadar air beras ketan dengan metode Principal Component Regression (PCR) serta menentukan metode koreksi spektrum yang terbaik dan akurat untuk memprediksi kadar air beras ketan dengan menggunakan pretreatment De- Trending, Derivative-2, dan Standart Normal Variate (SNV). Penelitian ini menggunakan beras ketan putih yang didapat dari pasar Rukoh Banda Aceh, yang berjumlah 35 sampel. Perlakuan yang diberikan adalah tanpa perendaman, dibasahi, dan perendaman selama 5, 10, 15, 20, dan 25 menit. Prediksi kadar air beras ketan dengan NIRS menggunakan alat self developed FT-IR IPTEK T-1516 dan metode referensi yang digunakan adalah metode gravimetri yang berdasarkan pada Association of Official Analytical Chemists (AOAC). Pengolahan data menggunakan Unsclambers sofware® X version 10.5. Hasil penelitian menunjukkan bahwa NIRS dengan metode PCR mampu menghasilkan model yang baik untuk pendugaan beras ketan. Penelitian ini menghasilkan empat model pendugaan kadar air beras ketan dimana satu model tergolong very good performance (RPD3) dan tiga model tergolong good model performance (RPD2) sehingga dapat dikatakan bahwa semua model yang dihasilkan layak dan baik untuk pendugaan kadar air beras ketan. Pretreatment terbaik pada penelitian ini adalah Standart Normal Variate (SNV) dengan nilai RPD 3,12, r sebesar 0,95, R2 sebesar 0,89, dan RMSEC sebesar 2,34.Estimation of White Gluttony Rice Rate With NIRS Technology Using Principal Component Regression Method (Pretreatment De-Trending, Derivative-2, dan Standart Normal Variate)Abstract. Water content is one important component in white glutinous rice which can affect the quality of white glutinous rice. This study aims to test and evaluate NIRS technology as a fast and precise method for predicting glutinous rice water content with the Principal Component Regression (PCR) method and determine the best and accurate spectrum correction method for predicting glutinous rice water content using the De-Trending, Derivative pretreatment -2, and Standard Normal Variate (SNV). This study uses white sticky rice obtained from the Rukoh market in Banda Aceh, which amounted to 35 samples. The treatment given is without soaking, soaking, and soaking for 5, 10, 15, 20, and 25 minutes. The prediction of glutinous rice moisture content with NIRS uses a self-developed FT-IR IPTEK T-1516 tool and the reference method used is the gravimetric method based on the Association of Official Analytical Chemists (AOAC). Data processing using Unsclambers software X version 10.5. The results showed that NIRS with the PCR method was able to produce a good model for estimating glutinous rice. This study produced four models of estimation of glutinous rice water content where one model was classified as very good performance (RPD 3) and three models were classified as good model performance (RPD 2) so that it could be said that all the models produced were suitable and good for estimating rice water content sticky rice. The best pretreatment in this study is the Standard Normal Variate (SNV) with an RPD value of 3.12, r of 0.95, R2 of 0.89, and RMSEC of 2.34. 

scholarly journals Physical–Chemical Characteristics of Cutin Separated from Tomato Waste for the Preparation of Bio-lacquers

2019 ◽  
Vol 11 (1) ◽  
pp. 33-45
Author(s):  
A. Cifarelli ◽  
I. M. Cigognini ◽  
L. Bolzoni ◽  
A. Montanari
Keyword(s):  
Alkaline Hydrolysis ◽  
Food Packaging ◽  
Scale Up ◽  
Principal Component ◽  
Cost Effective ◽  
Raw Material ◽  
Selective Precipitation ◽  
Environmentally Safe ◽  
Ft Ir ◽  
Hydrolysis Of

Green chemistry protocols are proposed to produce high-value chemicals from waste tomatoes. Long-chain hydroxy fatty acids (called cutin acids), in particular the 10,16-dihydroxyhexadecanoic acid and its oligomers, could be innovative building-block chemicals for the synthesis of novel bio-resins and lacquers suitable as internal protective coating for metal food packaging. However, these natural compounds are not currently commercially available. This study investigates the possibility of extracting cutin acids from tomato peels without the use of organic solvents and by an efficient, cost-effective, and environmentally safe method amenable to industrial scale-up. The first route investigated was based on alkaline hydrolysis of the tomato cuticle. The second involved the acid free-selective precipitation of cutin. Finally, cutin was isolated by hydrogen peroxide-assisted hydrolysis. GC-MS analysis revealed the main chemical compound isolated by all methods to be 10,16-dihydroxyhexadecanoic acid, the principal component of tomato cutin, with extraction yields ranging from 81 to 96%. Products are different in terms of appearance, solubility, the degree of crosslinking observed and molecular weight, as shown by GPC analysis. Furthermore, the products extracted were characterized by means of FT-IR spectroscopy and thermal analysis. The cutin obtained through alkaline hydrolysis results the best raw material for bio-resin preparation.

Monitoring effluent quality in hypertrophic wastewater reservoirs using remote sensing

1996 ◽  
Vol 33 (8) ◽  
pp. 23-29 ◽  
Author(s):  
I. Dor ◽  
N. Ben-Yosef
Keyword(s):  
Water Quality ◽  
Theoretical Model ◽  
Principal Component ◽  
Cost Effective ◽  
Operational Parameters ◽  
Effluent Quality ◽  
Optical Images ◽  
Routine Monitoring ◽  
Cost Effective Method ◽  
Wastewater Quality

About one hundred and fifty wastewater reservoirs store effluents for irrigation in Israel. Effluent qualities differ according to the inflowing wastewater quality, the degree of pretreatment and the operational parameters. Certain aspects of water quality like concentration of organic matter, suspended solids and chlorophyll are significantly correlated with the water column transparency and colour. Accordingly optical images of the reservoirs obtained from the SPOT satellite demonstrate pronounced differences correlated with the water quality. The analysis of satellite multispectral images is based on a theoretical model. The model calculates, using the radiation transfer equation, the volume reflectance of the water body. Satellite images of 99 reservoirs were analyzed in the chromacity space in order to classify them according to water quality. Principal Component Analysis backed by the theoretical model increases the method sensitivity. Further elaboration of this approach will lead to the establishment of a time and cost effective method for the routine monitoring of these hypertrophic wastewater reservoirs.

scholarly journals Development of the Statistical Model for Monitoring Salinization in the Mekong Delta of Vietnam Using Remote Sensing Data and In-Situ Measurements

Proceedings ◽  
2018 ◽  
Vol 2 (10) ◽  
pp. 565
Author(s):  
Nguyen Nguyen Vu ◽  
Le Van Trung ◽  
Tran Thi Van
Keyword(s):  
Statistical Model ◽  
Mekong Delta ◽  
Remote Sensing Data ◽  
Principal Component ◽  
Measured Data ◽  
In Situ Measurements ◽  
Landsat 8 ◽  
Spectral Bands ◽  
Component Band

This article presents the methodology for developing a statistical model for monitoring salinity intrusion in the Mekong Delta based on the integration of satellite imagery and in-situ measurements. We used Landsat-8 Operational Land Imager and Thermal Infrared Sensor (Landsat- 8 OLI and TIRS) satellite data to establish the relationship between the planetary reflectance and the ground measured data in the dry season during 2014. The three spectral bands (blue, green, red) and the principal component band were used to obtain the most suitable models. The selected model showed a good correlation with the exponential function of the principal component band and the ground measured data (R2 > 0.8). Simulation of the salinity distribution along the river shows the intrusion of a 4 g/L salt boundary from the estuary to the inner field of more than 50 km. The developed model will be an active contribution, providing managers with adaptation and response solutions suitable for intrusion in the estuary as well as the inner field of the Mekong Delta.

scholarly journals Spectroscopy as a useful tool for the identification of changes with time in post-mortem vitreous humor for forensic toxicology purposes

2021 ◽  
Author(s):  
Anna Wójtowicz ◽  
Agata Mitura ◽  
Renata Wietecha-Posłuszny ◽  
Rafał Kurczab ◽  
Marcin Zawadzki
Keyword(s):  
Ir Spectra ◽  
Forensic Toxicology ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Vitreous Humor ◽  
Attenuated Total Reflection ◽  
Glass Slides ◽  
Added Benefit ◽  
Ft Ir ◽  
Non Destructive

AbstractVitreous humor (VH) is an alternative biological matrix with a great advantage of longer availability for analysis due to the lack of many enzymes. The use of VH in forensic toxicology may have an added benefit, however, this application requires rapid, simple, non-destructive, and relatively portable analytical analysis methods. These requirements may be met by Fourier transform infrared spectroscopy technique (FT-IR) equipped with attenuated total reflection accessory (ATR). FT-IR spectra of vitreous humor samples, deposited on glass slides, were collected and subsequent chemometric data analysis by means of Hierarchical Cluster Analysis and Principal Component Analysis was conducted. Differences between animal and human VH samples and human VH samples stored for diverse periods of time were detected. A kinetic study of changes in the VH composition up to 2 weeks showed the distinction of FT-IR spectra collected on the 1st and 14th day of storage. In addition, data obtained for the most recent human vitreous humor samples—collected 3 and 2 years before the study, presented successful discrimination of all time points studied. The method introduced was unable to detect mephedrone addition to VH in the concentration of 10 µg/cm3. Graphic abstract

scholarly journals A Methodology Based on FT-IR Data Combined with Random Forest Model to Generate Spectralprints for the Characterization of High-Quality Vinegars

Foods ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1411
Author(s):  
José Luis P. Calle ◽  
Marta Ferreiro-González ◽  
Ana Ruiz-Rodríguez ◽  
Gerardo F. Barbero ◽  
José Á. Álvarez ◽  
...  
Keyword(s):  
Random Forest ◽  
Raw Materials ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Raw Material ◽  
Support Vector ◽  
Protected Designation Of Origin ◽  
Ft Ir

Sherry wine vinegar is a Spanish gourmet product under Protected Designation of Origin (PDO). Before a vinegar can be labeled as Sherry vinegar, the product must meet certain requirements as established by its PDO, which, in this case, means that it has been produced following the traditional solera and criadera ageing system. The quality of the vinegar is determined by many factors such as the raw material, the acetification process or the aging system. For this reason, mainly producers, but also consumers, would benefit from the employment of effective analytical tools that allow precisely determining the origin and quality of vinegar. In the present study, a total of 48 Sherry vinegar samples manufactured from three different starting wines (Palomino Fino, Moscatel, and Pedro Ximénez wine) were analyzed by Fourier-transform infrared (FT-IR) spectroscopy. The spectroscopic data were combined with unsupervised exploratory techniques such as hierarchical cluster analysis (HCA) and principal component analysis (PCA), as well as other nonparametric supervised techniques, namely, support vector machine (SVM) and random forest (RF), for the characterization of the samples. The HCA and PCA results present a clear grouping trend of the vinegar samples according to their raw materials. SVM in combination with leave-one-out cross-validation (LOOCV) successfully classified 100% of the samples, according to the type of wine used for their production. The RF method allowed selecting the most important variables to develop the characteristic fingerprint (“spectralprint”) of the vinegar samples according to their starting wine. Furthermore, the RF model reached 100% accuracy for both LOOCV and out-of-bag (OOB) sets.

scholarly journals Semi-automated regional classification of the style of activity of slow rock-slope deformations using PS InSAR and SqueeSAR velocity data

Landslides ◽  
2021 ◽  
Author(s):  
Chiara Crippa ◽  
Elena Valbuzzi ◽  
Paolo Frattini ◽  
Giovanni B. Crosta ◽  
Margherita C. Spreafico ◽  
...  
Keyword(s):  
Rock Slope ◽  
Progressive Failure ◽  
Principal Component ◽  
Cost Effective ◽  
Displacement Rate ◽  
Machine Learning Classification ◽  
Management Perspective ◽  
Alpine Environments

AbstractLarge slow rock-slope deformations, including deep-seated gravitational slope deformations and large landslides, are widespread in alpine environments. They develop over thousands of years by progressive failure, resulting in slow movements that impact infrastructures and can eventually evolve into catastrophic rockslides. A robust characterization of their style of activity is thus required in a risk management perspective. We combine an original inventory of slow rock-slope deformations with different PS-InSAR and SqueeSAR datasets to develop a novel, semi-automated approach to characterize and classify 208 slow rock-slope deformations in Lombardia (Italian Central Alps) based on their displacement rate, kinematics, heterogeneity and morphometric expression. Through a peak analysis of displacement rate distributions, we characterize the segmentation of mapped landslides and highlight the occurrence of nested sectors with differential activity and displacement rates. Combining 2D decomposition of InSAR velocity vectors and machine learning classification, we develop an automatic approach to characterize the kinematics of each landslide. Then, we sequentially combine principal component and K-medoids cluster analyses to identify groups of slow rock-slope deformations with consistent styles of activity. Our methodology is readily applicable to different landslide datasets and provides an objective and cost-effective support to land planning and the prioritization of local-scale studies aimed at granting safety and infrastructure integrity.

Comparative characterisation of two fulvic acids from East Lake and Liangzi Lake in central China

2015 ◽  
Vol 12 (2) ◽  
pp. 189 ◽  
Author(s):  
Jun Wang ◽  
Huijie Li ◽  
Yong Chen ◽  
Yuan Fang ◽  
Zongping Wang ◽  
...  
Keyword(s):  
Fluorescence Spectroscopy ◽  
Cost Effective ◽  
Fulvic Acids ◽  
Central China ◽  
Anthropogenic Activity ◽  
Cost Effective Method ◽  
Vis Spectroscopy ◽  
East Lake ◽  
Ft Ir ◽  
Eem Fluorescence

Environmental context Fulvic acids account for a large proportion of dissolved organic matter in aquatic environments and affect the transportation and bioavailability of organic and inorganic pollutants. The structural and spectroscopic characteristics of fulvic acids mainly depend on the sources, seasons and anthropogenic activity. We present an advanced approach using fluorescence spectroscopy as a rapid and cost-effective method to investigate the composition, properties and origins of fulvic acids. Abstract Fulvic acids (FAs) isolated seasonally from the sediments of East Lake and Liangzi Lake in central China were comparatively investigated. The structural features of the FAs were characterised using chemical and spectroscopic methods, including elemental analysis, UV-Vis spectroscopy, Fourier-transform infrared (FT-IR) spectroscopy, and three-dimensional excitation emission matrix (EEM) fluorescence spectroscopy coupled with parallel factor analysis (PARAFAC). The O/C, (O+N)/C and C/N ratios of FA extracted from Liangzi Lake (FAL) were higher than those of FA extracted from East Lake (FAE), indicating higher oxygen-containing functionality and polarity and less nutrient in FAL compared with FAE. The two FAs had similar UV-Vis spectra with different absorbance intensities. The FT-IR spectra showed that the two FAs had similar functional groups. The total fluorescence intensity and aromaticity of samples from Liangzi Lake were higher than those of East Lake except for those taken in the summer. The two FAs were largely terrestrially derived organic materials. Five fluorescent components, including four humic-like and two fulvic-like components, were identified by PARAFAC modelling of the EEM spectral data. The fluorescence was dominated by two components. The findings suggest that EEM fluorescence spectroscopy together with PARAFAC is a rapid and cost-effective method for understanding the characteristics and origins of FAs in natural water systems.

Photoacoustic FT-IR Spectroscopy of Natural Copper Patina

1995 ◽  
Vol 49 (10) ◽  
pp. 1516-1524 ◽  
Author(s):  
Alex O. Salnick ◽  
Werner Faubel
Keyword(s):  
Depth Distribution ◽  
Depth Profiling ◽  
Beam Deflection ◽  
City Hall ◽  
Spectral Bands ◽  
Special Sample Preparation ◽  
Ft Ir ◽  
Infrared Photoacoustic Spectroscopy ◽  
Ft Ir Spectroscopy

Fourier transform infrared photoacoustic spectroscopy (FT-IR/PAS) has proved to be a useful tool for nondestructive testing of copper corrosion layer (patina) formed in the atmosphere. The samples cut from a piece of the roof of the Stockholm City Hall were examined without any additional pretreatment. The components of the patina—brochantite Cu4(OH)6SO4, antlerite Cu3(OH)4SO4, and basic cupric carbonate Cu2CO3(OH)6 · H2O—as well as some other minerals were identified. The photothermal beam deflection (PBD) method was used for independent photoacoustic characterization of the samples. The depth profiling capability of FT-IR/PAS was used to determine the degree of photoacoustic saturation of the spectral bands and to evaluate the depth distribution of the main patina components. The technique thus compares favorably with more common approaches of patina examination which are more expensive and require special sample preparation.

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