scholarly journals Biodegradable and Compostable Shopping Bags under Investigation by FTIR Spectroscopy

2021 ◽  
Vol 11 (2) ◽  
pp. 621
Author(s):  
Silvana Alfei ◽  
Anna Maria Schito ◽  
Guendalina Zuccari
Keyword(s):  
Principal Component Analysis ◽  
Ftir Spectroscopy ◽  
Principal Component ◽  
Poly Lactic Acid ◽  
Chemometric Methods ◽  
Industrial Sectors ◽  
Fresh Food ◽  
Extruded Films ◽  
Productive Process ◽  
Non Destructive

In the recent years, plastic-based shopping bags have become irregular and progressively replaced by compostable ones. To be marketed, these “new plastics” must possess suitable requirements verified by specific bodies, which grant the conformity mark, and the approved physicochemical properties are periodically verified. The fast, inexpensive, non-destructive, easy to use, and reproducible Fourier-Transform infrared (FTIR) spectroscopy is a technique routinely applied to perform analysis in various industrial sectors. To get reliable information from spectral data, chemometric methods, such as Principal Component Analysis (PCA), are commonly suggested. In this context, PCA was herein performed on 4, 5, and 21 × 3251 matrices, collecting the FTIR data from regular and irregular shopping bags, including three freshly extruded films from the Italian industry MecPlast, to predict their compliance with legislation. The results allowed us to unequivocally achieve such information and to classify the bags as suitable for containing fresh food in bulk or only for transport. A self-validated linear model was developed capable to estimate, by acquiring a single FTIR spectrum if, after the productive process, the content of renewable poly-lactic-acid (PLA) in a new produced film respect the expectations. Surprisingly, our findings established that among the grocery bags available on the market, irregular plastic-based shopping bags continue to survive.

Quality evaluation of tugaksheeree samples by ATR-FTIR spectroscopy using multicomponent analysis

2020 ◽  
Vol 10 ◽  
Author(s):  
Nikunj D. Patel ◽  
Niranjan S. Kanaki
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Quality Evaluation ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Attenuated Total Reflectance ◽  
Chemometric Methods ◽  
Total Reflectance ◽  
Fingerprint Region ◽  
Ftir Technique

Background: Numerous Ayurvedic formulations contains tugaksheeree as key ingredient. Tugaksheereeis the starch gained from the rhizomes of two plants, Curcuma angustifoliaRoxb. (Zingiberaceae) and Marantaarundinacea (MA) Linn. (Marantaceae). Objective: The primary concerns in quality assessment of Tugaksheeree occur due to adulteration or substitution. Method: In current study, Fourier transform infrared (FTIR) technique with attenuated total reflectance (ATR) facility was used to evaluate tugaksheeree samples. Total 10 different samples were studied and transmittance mode was kept to record the spectra devoid of pellets of KBR. Further treatment was given with multi component tools by considering fingerprint region of the spectra. Multivariate analysis was performed by various chemometric methods. Result: Multi component methods like Principal Component Analysis (PCA), and Hierarchical Cluster Analysis (HCA)were used to discriminate the tugaksheeree samples using Minitab software. Conclusion: This method can be used as a tool to differentiate samples of tugaksheeree from its adulterants and substitutes.

scholarly journals Remaining Useful Life Prediction of Broken Rotor Bar Based on Data-Driven and Degradation Model

2021 ◽  
Vol 11 (16) ◽  
pp. 7175
Author(s):  
Islem Bejaoui ◽  
Dario Bruneo ◽  
Maria Gabriella Xibilia
Keyword(s):  
Principal Component Analysis ◽  
Induction Motor ◽  
Life Prediction ◽  
Principal Component ◽  
Component Analysis ◽  
Remaining Useful Life ◽  
Degradation Model ◽  
Broken Rotor Bar ◽  
Industrial Sectors ◽  
Useful Life

Rotating machines such as induction motors are crucial parts of most industrial systems. The prognostic health management of induction motor rotors plays an essential role in increasing electrical machine reliability and safety, especially in critical industrial sectors. This paper presents a new approach for rotating machine fault prognosis under broken rotor bar failure, which involves the modeling of the failure mechanism, the health indicator construction, and the remaining useful life prediction. This approach combines signal processing techniques, inherent metrics, and principal component analysis to monitor the induction motor. Time- and frequency-domains features allowing for tracking the degradation trend of motor critical components that are extracted from torque, stator current, and speed signals. The most meaningful features are selected using inherent metrics, while two health indicators representing the degradation process of the broken rotor bar are constructed by applying the principal component analysis. The estimation of the remaining useful life is then obtained using the degradation model. The performance of the prediction results is evaluated using several criteria of prediction accuracy. A set of synthetic data collected from a degraded Simulink model of the rotor through simulations is used to validate the proposed approach. Experimental results show that using the developed prognostic methodology is a powerful strategy to improve the prognostic of induction motor degradation.

Effect of the chain length on near-infrared spectra of 1-alcohols from methanol to 1-decanol

NIR news ◽  
2019 ◽  
Vol 30 (3) ◽  
pp. 6-8
Author(s):  
Mirosław Antoni Czarnecki ◽  
Michał Kwaśniewicz
Keyword(s):  
Principal Component Analysis ◽  
Chain Length ◽  
Infrared Spectra ◽  
Near Infrared ◽  
Principal Component ◽  
Pure Liquid ◽  
Chemometric Methods ◽  
Near Infrared Spectra ◽  
Similarities And Differences ◽  
Self Association

This work shows the effect of the chain length on near-infrared spectra of 1-alcohols and is based on a recent paper by Kwaśniewicz and Czarnecki ( Appl Spectrosc 2018, 72: 288). Near-infrared spectra of 1-alcohols from methanol to 1-decanol in the pure liquid phase were recorded from 5200 to 9000 cm−1. The similarities and differences between the spectra were analyzed by the classical and chemometric methods (principal component analysis). The obtained results reveal that the near-infrared spectra of methanol, ethanol, and 1-propanol are appreciably different from the spectra of higher 1-alcohols. As shown, the degree of self-association of 1-alcohols decreases with the increase in the chain length.

On the rapid and non-destructive approach for wood identification using ATR-FTIR spectroscopy and chemometric methods

2020 ◽  
Vol 110 ◽  
pp. 103097
Author(s):  
Vishal Sharma ◽  
Jyoti Yadav ◽  
Raj Kumar ◽  
Daniela Tesarova ◽  
Adam Ekielski ◽  
...  
Keyword(s):  
Ftir Spectroscopy ◽  
Wood Identification ◽  
Chemometric Methods ◽  
Non Destructive

scholarly journals Detection of Cyanuric Acid and Melamine in Infant Formula Powders by Mid-FTIR Spectroscopy and Multivariate Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Edwin García-Miguel ◽  
Ofelia Gabriela Meza-Márquez ◽  
Guillermo Osorio-Revilla ◽  
Darío Iker Téllez-Medina ◽  
Cristian Jiménez-Martínez ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Ftir Spectroscopy ◽  
Least Squares ◽  
Infant Formula ◽  
Cyanuric Acid ◽  
Principal Component Regression ◽  
Predictive Ability ◽  
Principal Component ◽  
Infant Formulas ◽  
Chemometric Methods

Chemometric methods using mid-FTIR spectroscopy were developed in order to reduce the time of study of melamine and cyanuric acid in infant formulas. Chemometric models were constructed using the algorithms Partial Least Squares (PLS1, PLS2) and Principal Component Regression (PCR) in order to correlate the IR signal with the levels of melamine or cyanuric acid in the infant formula samples. Results showed that the best correlations were obtained using PLS1 (R2: 0.9998, SEC: 0.0793, and SEP: 0.5545 for melamine and R2: 0.9997, SEC: 0.1074, and SEP: 0.5021 for cyanuric acid). Also, the SIMCA model was studied to distinguish between adulterated formulas and nonadulterated samples, giving optimum discrimination and good interclass distances between samples. Results showed that chemometric models demonstrated a good predictive ability of melamine and cyanuric acid concentrations in infant formulas, showing that this is a rapid and accurate technique to be used in the identification and quantification of these adulterants in infant formulas.

Characteristics and discrimination of five types of wood-plastic composites by FTIR spectroscopy combined with principal component analysis

Holzforschung ◽  
2010 ◽  
Vol 64 (6) ◽  
Author(s):  
Chia-Huang Lee ◽  
Tung-Lin Wu ◽  
Yong-Long Chen ◽  
Jyh-Horng Wu
Keyword(s):  
Principal Component Analysis ◽  
Ftir Spectroscopy ◽  
Principal Component ◽  
Core Layer ◽  
Component Analysis ◽  
Attenuated Total Reflection ◽  
Distribution Profile ◽  
Data Set ◽  
Wood Plastic Composites ◽  
Plastic Composites

Abstract The analytical potential of attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy has been tested on the following wood-plastic composites (WPCs): high and low density polyethylene (HDPE and LDPE), polypropylene (PP), polystyrene (PS), and a recycled plastic (rHDPE). The data set of ATR-FTIR spectra has been analyzed by principal component analysis (PCA) and the studied samples could be grouped according to their polymeric matrixes. Additionally, ATR-FTIR spectroscopy proved to be a useful tool for determining the distribution profile of wood and plastic materials within different types of WPCs. Accordingly, the plastic content of the surface layers of HDPE, rHDPE, and PP composites was significantly higher than that of the core layer, whereas homogenous dispersion was observed in the LDPE composite. Among all WPCs, the PS composite displayed the worst dispersion.

scholarly journals Detection of Lard in Ink Extracted from Printed Food Packaging Using Fourier Transform Infrared Spectroscopy and Multivariate Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Syazwani Ramli ◽  
Rosnita A. Talib ◽  
Russly A. Rahman ◽  
Norhazlin Zainuddin ◽  
Siti Hajar Othman ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Multivariate Analysis ◽  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Ftir Spectroscopy ◽  
Food Packaging ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Calibration Standards ◽  
Number Of Factors

Fourier transform infrared (FTIR) spectroscopy combined with chemometrics was utilised to discriminate the presence of lard in extracted ink of printed food packaging. Two spectral regions (full spectra, 3999–649 cm−1, and combination of two regions, 3110–2630 cm−1and 1940–649 cm−1) of lard, commercial gravure ink, and the blends of both were selected and used to develop a Soft Independent Modelling of Class Analogy (SIMCA) model. The score plots obtained from the Principal Component Analysis (PCA) revealed that the maximum number of factors (7 factors) was needed to explain 84% of the total variance. SIMCA was employed as the method to classify the samples into their specific groups.SiversusHiplots showed that the calibration standards can be classified as lard-containing standards. Sample 2 was deduced to have the highest possibility of containing lard, while only samples 5 and 7 cannot be classified as lard-containing samples. These results demonstrated that FTIR spectroscopy, when combined with multivariate analysis, can provide a rapid method with no excessive sample preparation to detect the presence of lard in ink of foodstuff packaging.

scholarly journals Rapid and Accurate Discrimination Between Pure and Adulterated Commercial Indian Honey Brands Using FTIR Spectroscopy and Principal Component Analysis

2021 ◽  
Author(s):  
Bipin Singh ◽  
Sanmitra Barman
Keyword(s):  
Principal Component Analysis ◽  
Ftir Spectroscopy ◽  
Principal Component ◽  
Component Analysis

<p>Four leading commercial Indian honey brands were investigated using FTIR spectroscopy and principal component analysis for a rapid and accurate differentiation of pure, mildly adulterated, and highly adulterated honey brand samples. This study is first of its kind investigating commercial Indian honey brands using FTIR and PCA, hence can be used for investigating adulterations in bulk commercial honey brand samples where sophisticated instrumentations and facilities are not available.</p>

scholarly journals Rapid and Accurate Discrimination Between Pure and Adulterated Commercial Indian Honey Brands Using FTIR Spectroscopy and Principal Component Analysis

2021 ◽  
Author(s):  
Bipin Singh ◽  
Sanmitra Barman
Keyword(s):  
Principal Component Analysis ◽  
Ftir Spectroscopy ◽  
Principal Component ◽  
Component Analysis

<p>Four leading commercial Indian honey brands were investigated using FTIR spectroscopy and principal component analysis for a rapid and accurate differentiation of pure, mildly adulterated, and highly adulterated honey brand samples. This study is first of its kind investigating commercial Indian honey brands using FTIR and PCA, hence can be used for investigating adulterations in bulk commercial honey brand samples where sophisticated instrumentations and facilities are not available.</p>

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