scholarly journals Prototype of the Near-Infrared Spectroscopy Expert System for Particleboard Identification

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Anna Sandak ◽  
Jakub Sandak ◽  
Dominika Janiszewska ◽  
Salim Hiziroglu ◽  
Marta Petrillo ◽  
...  
Keyword(s):  
Quality Control ◽  
Expert System ◽  
Near Infrared ◽  
System Development ◽  
Nir Spectroscopy ◽  
Original System ◽  
Adhesive System ◽  
Type Composition ◽  
Wide Range ◽  
Panel Type

The overall goal of this work was to develop a prototype expert system assisting quality control and traceability of particleboard panels on the production floor. Four different types of particleboards manufactured at the laboratory scale and in industrial plants were evaluated. The material differed in terms of panel type, composition, and adhesive system. NIR spectroscopy was employed as a pioneer tool for the development of a two-level expert system suitable for classification and traceability of investigated samples. A portable, commercially available NIR spectrometer was used for nondestructive measurements of particleboard panels. Twenty-five batches of particleboards, each containing at least three independent replicas, was used for the original system development and assessment of its performance. Four alternative chemometric methods (PLS-DA, kNN, SIMCA, and SVM) were used for spectroscopic data classification. The models were developed for panel recognition at two levels differing in terms of their generality. In the first stage, four among twenty-four tested combinations resulted in 100% correct classification. Discrimination precision with PLS-DA and SVMC was high (>99%), even without any spectra preprocessing. SNV preprocessed spectra and SVMC algorithm were used at the second stage for panel batch classification. Panels manufactured by two producers were 100% correctly classified, industrial panels produced by different manufacturing plants were classified with 98.9% success, and the experimental panels manufactured in the laboratory were classified with 63.7% success. Implementation of NIR spectroscopy for wood-based product traceability and quality control may have a great impact due to the high versatility of the production and wide range of particleboards utilization.

scholarly journals A fast and low-cost approach to quality control of alcohol-based hand sanitizer using portable near infrared spectrometer and chemometrics

2021 ◽  
pp. 096703352098731
Author(s):  
Adenilton C da Silva ◽  
Lívia PD Ribeiro ◽  
Ruth MB Vidal ◽  
Wladiana O Matos ◽  
Gisele S Lopes
Keyword(s):  
Quality Control ◽  
Discriminant Analysis ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Chemical Components ◽  
Linear Discriminant ◽  
Hand Sanitizer

The use of alcohol-based hand sanitizers is recommended as one of several strategies to minimize contamination and spread of the COVID-19 disease. Current reports suggest that the virucidal potential of ethanol occurs at concentrations close to 70%. Traditional methods of verifying the ethanol concentration in such products invite potential errors due to the viscosity of chemical components or may be prohibitively expensive to undertake in large demand. Near infrared (NIR) spectroscopy and chemometrics have already been used for the determination of ethanol in other matrices and present an alternative fast and reliable approach to quality control of alcohol-based hand sanitizers. In this study, a portable NIR spectrometer combined with classification chemometric tools, i.e., partial least square discriminant analysis (PLS–DA) and linear discriminant analysis with successive algorithm projection (SPA–LDA) were used to construct models to identify conforming and non-conforming commercial and laboratory synthesized hand sanitizer samples. Principal component analysis (PCA) was applied in an exploratory data study. Three principal components accounted for 99% of data variance and demonstrate clustering of conforming and non-conforming samples. The PLS–DA and SPA–LDA classification models presented 77 and 100% of accuracy in cross/internal validation respectively and 100% of accuracy in the classification of test samples. A total of 43% commercial samples evaluated using the PLS–DA and SPA–LDA presented ethanol content non-conforming for hand sanitizer gel. These results indicate that use of NIR spectroscopy and chemometrics is a promising strategy, yielding a method that is fast, portable, and reliable for discrimination of alcohol-based hand sanitizers with respect to conforming and non-conforming ethanol concentrations.

Estimation of Eucalyptus delegatensis wood properties by near infrared spectroscopy

2001 ◽  
Vol 31 (10) ◽  
pp. 1671-1675 ◽  
Author(s):  
L R Schimleck ◽  
R Evans ◽  
J Ilic
Keyword(s):  
Large Scale ◽  
Near Infrared ◽  
Microfibril Angle ◽  
Nir Spectroscopy ◽  
Wood Properties ◽  
Raw Material ◽  
Modulus Of Rupture ◽  
Single Type ◽  
Wide Range ◽  
Eucalyptus Delegatensis

The use of calibrated near infrared (NIR) spectroscopy for the prediction of a range solid wood properties is described. The methods developed are applicable to large-scale nondestructive forest resource assessment and to tree breeding and silvicultural programs. A series of Eucalyptus delegatensis R.T. Baker (alpine ash) samples were characterized in terms of density, longitudinal modulus of elasticity (EL), microfibril angle (MFA), and modulus of rupture (MOR). NIR spectra were obtained from the radial–longitudinal face of each sample and used to generate calibrations for the measured physical properties. The relationships were good in all cases, with coefficients of determination ranging from 0.77 for MOR through 0.90 for EL to 0.93 for stick density. In view of the rapidly expanding range of applications for this technique, it is concluded that appropriately calibrated NIR spectroscopy could form the basis of a "universal" testing instrument capable of predicting a wide range of product properties from a single type of spectrum obtained from the product or from the raw material.

Nondestructive estimation of Pinus taeda L. wood properties for samples from a wide range of sites in Georgia

2005 ◽  
Vol 35 (1) ◽  
pp. 85-92 ◽  
Author(s):  
P D Jones ◽  
L R Schimleck ◽  
G F Peter ◽  
R F Daniels ◽  
A Clark III
Keyword(s):  
Pinus Taeda ◽  
Loblolly Pine ◽  
Near Infrared ◽  
Microfibril Angle ◽  
Nir Spectroscopy ◽  
Wood Properties ◽  
Small Sample ◽  
Dry Density ◽  
Wide Range ◽  
Pinus Taeda L

Preliminary studies based on small sample sets show that near infrared (NIR) spectroscopy has the potential for rapidly estimating many important wood properties. However, if NIR is to be used operationally, then calibrations using several hundred samples from a wide variety of growing conditions need to be developed and their performance tested on samples from new populations. In this study, 120 Pinus taeda L. (loblolly pine) radial strips (cut from increment cores) representing 15 different sites from three physiographic regions in Georgia (USA) were characterized in terms of air-dry density, microfibril angle (MFA), and stiffness. NIR spectra were collected in 10-mm increments from the radial longitudinal surface of each strip and split into calibration (nine sites, 729 spectra) and prediction sets (six sites, 225 spectra). Calibrations were developed using untreated and mathematically treated (first and second derivative and multiplicative scatter correction) spectra. Strong correlations were obtained for all properties, the strongest R2 values being 0.83 (density), 0.90 (MFA), and 0.93 (stiffness). When applied to the test set, good relationships were obtained (Rp2 ranged from 0.80 to 0.90), but the accuracy of predictions varied depending on math treatment. The addition of a small number of cores from the prediction set (one core per new site) to the calibration set improved the accuracy of predictions and importantly minimized the differences obtained with the various math treatments. These results suggest that density, MFA, and stiffness can be estimated by NIR with sufficient accuracy to be used in operational settings.

scholarly journals The Ability of Near Infrared (NIR) Spectroscopy to Predict Functional Properties in Foods: Challenges and Opportunities

Molecules ◽  
2021 ◽  
Vol 26 (22) ◽  
pp. 6981
Author(s):  
Daniel Cozzolino
Keyword(s):  
Functional Properties ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Chemical Compositions ◽  
Food Ingredients ◽  
Wide Range ◽  
Challenges And Opportunities ◽  
New Instrumentation ◽  
Novel Algorithms ◽  
Main Routine

Near infrared (NIR) spectroscopy is considered one of the main routine analytical methods used by the food industry. This technique is utilised to determine proximate chemical compositions (e.g., protein, dry matter, fat and fibre) of a wide range of food ingredients and products. Novel algorithms and new instrumentation are allowing the development of new applications of NIR spectroscopy in the field of food science and technology. Specifically, several studies have reported the use of NIR spectroscopy to evaluate or measure functional properties in both food ingredients and products in addition to their chemical composition. This mini-review highlights and discussed the applications, challenges and opportunities that NIR spectroscopy offers to target the quantification and measurement of food functionality in dairy and cereals.

scholarly journals The Quality Control of Tea by Near-Infrared Reflectance (NIR) Spectroscopy and Chemometrics

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Ming-Zhi Zhu ◽  
Beibei Wen ◽  
Hao Wu ◽  
Juan Li ◽  
Haiyan Lin ◽  
...  
Keyword(s):  
Quality Control ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Chemical Compositions ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Control Quality ◽  
Tea Quality ◽  
Instrumental Technique

Tea is known to be one of the most popular beverages enjoyed by two-thirds of the world’s population. Concern of variability in tea quality is increasing among consumers. It is of great significance to control quality for commercialized tea products. As a rapid, noninvasive, and nondestructive instrumental technique with simplicity in sample preparation, near-infrared reflectance (NIR) spectroscopy has been proved to be one of the most advanced and efficient tools for the control quality of tea products in recent years. In this article, we review the most recent advances and applications of NIR spectroscopy and chemometrics for the quality control of tea, including the measurement of chemical compositions, the evaluation of sensory attributes, the identification of categories and varieties, and the discrimination of geographical origins. Besides, challenges and future trends of tea quality control by NIR spectroscopy are also presented.

Comparison of Three near Infrared Spectrophotometers for Infestation Detection in Wild Blueberries Using Multivariate Calibration Models

2009 ◽  
Vol 17 (4) ◽  
pp. 203-212 ◽  
Author(s):  
Boyan N. Peshlov ◽  
Floyd E. Dowell ◽  
Francis A. Drummond ◽  
Darrell W. Donahue
Keyword(s):  
Wavelength Range ◽  
Near Infrared ◽  
Multivariate Calibration ◽  
System Development ◽  
Nir Spectroscopy ◽  
Insect Infestation ◽  
Signal To Noise ◽  
Wild Blueberries ◽  
Technical Specifications ◽  
Imaging Spectrograph

A near infrared (NIR) spectroscopy system for rapid, automated and non-destructive detection of insect infestation in blueberries is desirable to ensure high quality fruit for the fresh and processed markets. The selection of suitable instruments is the first step in system development. Three diode array spectrophotometers were evaluated based on technical specifications and capacity for larva detection in wild blueberries ( Vaccinium angustifolium) using discriminant partial least squares (PLS) regression models. These instruments, differing mainly in wavelength range and detector type, comprised two spectrophotometers with scanning wavelength ranges of 650–1100 nm and 600–1700 nm and an imaging spectrograph with the scanning range of 950–1400 nm. The assessed factors affecting predictions included signal-to-noise ratio, wavelength range, resolution, measurement configuration, spectral pre-processing and absorbance bands related to infestation. The scanning spectrophotometers demonstrated higher signal-to-noise ratios with infestation prediction accuracies of 82% and 76.9% compared to the imaging spectrograph with 58.9% accuracy. Resolution, spectral pre-processing and measurement configuration had a lesser effect on model accuracy than wavelength range. The 950–1690 nm bands were identified as important for infestation prediction. In general, NIR spectroscopy should be a feasible technique for rapid classification of insect infestation in fruit.

Unlocking the Secrets of Terminalia Kernels Using Near-Infrared Spectroscopy

2021 ◽  
pp. 000370282199213
Author(s):  
Eshetu Bobasa ◽  
Michael Netzel ◽  
Anh Dao Thi Phan ◽  
Heather Smyth ◽  
Yasmina Sultanbawa ◽  
...  
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Near Infrared Reflectance ◽  
Classification Rate ◽  
Potential Health ◽  
Wide Range ◽  
Fruit Samples ◽  
The Fourier Transform ◽  
Kakadu Plum

In recent years, the native food industry in Australia has increased in both value and volume due to the discovery of a wide range of phytochemicals (e.g., vitamin C, polyphenols) that have potential health benefits. Thus, plant organs and tissues of these native plants are used in a wide range of applications. In particular, the kernel of a native plum, the Kakadu plum ( Terminalia ferdinandiana, Combretaceae) is considered to be rich in lipids and other phytochemical compounds. The aim of this study was to evaluate the use of NIR spectroscopy to analyze and characterize kernel samples and tissues of wild harvest fruit samples. The Fourier transform near-infrared reflectance spectra of cracked kernels, seeds cover tissues, and dry powder Kakadu plum kernels were acquired. Both principal component analysis and partial least squares discriminant analysis were used to analyze and interpret the spectral data. A correct classification rate of 93%, 86%, and 80% was achieved for the identification of kernel provenance using all tissues, seed coats, and the whole nuts, respectively. The results of this study reported for the first time the analysis of Kakadu plum kernels and their tissues using NIR spectroscopy.

Identification of geographical origin of TPFD based on handheld NIR spectroscopy and PLSDA

NIR news ◽  
2020 ◽  
Vol 31 (5-6) ◽  
pp. 25-29
Author(s):  
Rita-Cindy Aye-Ayire Sedjoah ◽  
Bangxing Han ◽  
Hui Yan
Keyword(s):  
Quality Control ◽  
Near Infrared ◽  
Geographical Origin ◽  
Nir Spectroscopy ◽  
Analysis Model ◽  
First Order ◽  
Standard Normal Variate ◽  
Standard Normal ◽  
Infrared Spectrometer ◽  
Near Infrared Spectrometer

The present study is focused on the identification of geographical origin (Zhejiang, Yunnan and Anhui, China) of Dendrobium officinale’s dried stem called Tiepi fengdou by mean of the handheld near-infrared spectrometer. Raw data were preprocessed to reduce unwanted spectral variations by the first-order derivative followed by standard normal variate transformation, and partial least squares discriminant analysis model was developed for calibration. The results showed that more than 90% of the origins were identified. Therefore, it is possible to classify the geographical origin of Tiepi fengdou by the use of the handheld near-infrared spectrometer for effective quality control.

scholarly journals Historical Evolution and Food Control Achievements of Near Infrared Spectroscopy, Electronic Nose, and Electronic Tongue—Critical Overview

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5479
Author(s):  
Balkis Aouadi ◽  
John-Lewis Zinia Zaukuu ◽  
Flora Vitális ◽  
Zsanett Bodor ◽  
Orsolya Fehér ◽  
...  
Keyword(s):  
Electronic Nose ◽  
Fruits And Vegetables ◽  
Near Infrared ◽  
Electronic Tongue ◽  
Nir Spectroscopy ◽  
High Sensitivity ◽  
Food Control ◽  
Time Data ◽  
Production Chain ◽  
Wide Range

Amid today’s stringent regulations and rising consumer awareness, failing to meet quality standards often results in health and financial compromises. In the lookout for solutions, the food industry has seen a surge in high-performing systems all along the production chain. By virtue of their wide-range designs, speed, and real-time data processing, the electronic tongue (E-tongue), electronic nose (E-nose), and near infrared (NIR) spectroscopy have been at the forefront of quality control technologies. The instruments have been used to fingerprint food properties and to control food production from farm-to-fork. Coupled with advanced chemometric tools, these high-throughput yet cost-effective tools have shifted the focus away from lengthy and laborious conventional methods. This special issue paper focuses on the historical overview of the instruments and their role in food quality measurements based on defined food matrices from the Codex General Standards. The instruments have been used to detect, classify, and predict adulteration of dairy products, sweeteners, beverages, fruits and vegetables, meat, and fish products. Multiple physico-chemical and sensory parameters of these foods have also been predicted with the instruments in combination with chemometrics. Their inherent potential for speedy, affordable, and reliable measurements makes them a perfect choice for food control. The high sensitivity of the instruments can sometimes be generally challenging due to the influence of environmental conditions, but mathematical correction techniques exist to combat these challenges.

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