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Laser-Induced Breakdown Spectroscopy Based Protein Assay for Cereal Samples Banu Sezer, Gonca Bilge, and #smail Hakki Boyaci J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.6b04828 • Publication Date (Web): 23 Nov 2016 Downloaded from http://pubs.acs.org on November 26, 2016
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Journal of Agricultural and Food Chemistry
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Laser-Induced Breakdown Spectroscopy Based Protein Assay for Cereal Samples
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Banu Sezer, Gonca Bilge, Ismail Hakki Boyaci*
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Department of Food Engineering, Hacettepe University, Beytepe 06800, Ankara, Turkey
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*Corresponding Author:
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Phone: +90 312 297 61 46
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Fax: +90 312 299 21 23
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e-mail:
[email protected] 12
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ABSTRACT
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Protein content is an important quality parameter in terms of price, nutritional value and
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labeling of various cereal samples. However, conventional analysis methods, namely Kjeldahl
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and Dumas have major drawbacks such as long analysis time, titration mistakes and carrier
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gas dependence with high purity. For this reason, there is an urgent need for rapid, reliable
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and environmentally friendly technologies for protein analysis. The present study aims to
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develop a new method for protein analysis in wheat flour and whole meal by using laser
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induced breakdown spectroscopy (LIBS), which is a multi-elemental, fast and simple
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spectroscopic method. Unlike the Kjeldahl and Dumas method, it has potential to analyze
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high number of samples in considerably short time. In the study, nitrogen peaks in LIBS
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spectra of wheat flour and whole meal samples with different protein contents were correlated
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with results of standard Dumas method with the aid of chemometric methods. Calibration
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graph showed good linearity with the protein content between 7.9-20.9%, and 0.992
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coefficient of determination (R2). Limit of detection was calculated as 0.26%. The results
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indicated that LIBS is a promising and reliable method with its high sensitivity for routine
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protein analysis in wheat flour and whole meal samples.
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Key words: LIBS; protein analysis, wheat flour, whole meal, nitrogen content.
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INTRODUCTION
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Proteins are the main functional components in various food products and have ability to
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support dietary needs. They have a significant role in determining the textural, sensory and
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nutritional properties of products. Protein content affects technological properties and
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determines nutritional quality of foods. Therefore, determination of protein is an important
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quantitative analysis in terms of quality control, accurate nutrition labeling, pricing, functional
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property investigation and biological activity determination,1 which makes it a subject of both
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economic and social interest. The market value of major agricultural products (cereal grains,
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legumes, flour, oil seed, milk, livestock feeds) is determined partly by their protein content. It
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is also important for wheat products. Protein content of wheat varies from 6% to 20%
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depending on geographical factors and soil properties. Also, it is a quality index for wheat
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flour in bread making industry.2 Overall, protein analysis has nutritional, legal, health and
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economic results for food industry.3
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The analytical techniques used for determining protein content of food products can be
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divided into several groups based on measured parameters such as determination of nitrogen,
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peptide bonds, aromatic amino acids, ultraviolet absorptivity, and light scattering properties.
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The most commonly used reference analytical methods are Dumas and Kjeldahl methods,1
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which were developed in 1831 and 1883, respectively. Different from other methods, these
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two methods analyze protein content directly by measuring the nitrogen and amino acid
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content. In the Kjeldahl method, the sample is first digested with strong sulphuric acid in the
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presence of catalyst, and amine nitrogen is converted to ammonium ions. Then, ammonium
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ions are converted to ammonia gas, heated and distillated, then ammonia gas is converted
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back to ammonium ions by trapping into a solution. Following this process, the trapped
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ammonium ions are determined by titration, and protein content is calculated with some
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conversion factors. Despite its widespread use, Kjeldahl method has serious drawbacks such
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as need for sample pretreatment, titration mistakes, use of corrosive and potentially toxic
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reagents and long analysis time. In addition, breakdown of all organic compounds by
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sulphuric acid and conversion of nitrogen to ammonium in sample preparation step should be
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performed properly, otherwise it causes erroneous results and poor precision. In Dumas
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method, on the other hand, sample is purged of any atmospheric gas and heated at about 1000
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°C and combusted in the presence of pure oxygen. Combustion products such as carbon
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dioxide, water and nitrogen as several oxides are passed on to hot copper to remove any
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oxygen and convert nitrogen oxides to molecular nitrogen. Then, the obtained signal from
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thermal conductivity detector is converted to total nitrogen content, and protein amount is
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calculated with conversion factors. However, high purity carrier gas and expensive equipment
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is required to complete the analysis.
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Principles of other protein analysis methods (Biuret, Nessler’s Reagent, Folin-Ciocalteau,
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Lowry, Bradford and bicinchoninic acid methods4) are based on interaction of protein and
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reactive or dye molecules. In these techniques, results are influenced by the presence of
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pigment molecules which absorb visible, UV or infrared light, thus some difficulties can be
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witnessed in food samples. Recently, spectroscopic methods have come to the fore because of
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their simplicity and short analysis time. Near Infrared Spectroscopy (NIR) is another method
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used for protein analysis, which is based on absorption of a wavelength of infrared radiation
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specific to peptide bond. NIR combined with chemometric methods has been developed due
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to the need for a rapid and simple protein analysis method. However, it is an indirect method
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to measure protein content of the sample. There are many studies which use NIR as a tool for
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determining protein content of food products.5-8 It is also preferred by food industry, and there
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are many commercial NIR analysis systems developed for determination of protein content. 4 ACS Paragon Plus Environment
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However, in NIR spectra, finger print spectrum cannot be seen as distinctly as in mid-infrared
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and far-infrared regions. The obtained overtones in NIR spectra is strongly affected by the
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matrix of sample. Therefore, regular calibration updates are necessary. Given all these
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disadvantages, it can be clearly seen that food industry urgently needs a new, rapid, in-situ,
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robust, accurate and sensitive method that will determine protein content of food products.
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Laser induced breakdown spectroscopy (LIBS) is a new, rapid and in-situ technique for
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elemental analysis.9, 10 LIBS is a laser based optical spectroscopy technique in which plasma
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is created by means of focusing the laser through a lens on the sample surface. Plasma
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contains free atoms, ions and electrons, and it emits plasma light which is characteristic of
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each element.11,
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spectrometer, and spectroscopic signals are produced. These signals are related to chemical
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compositions of the sample.11 LIBS does not require complex sample preparation step and is a
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rapid method which has been used for qualitative and quantitative measurements of the
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elemental composition of different matrices such as solid, liquid and gas.13 The application
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field of LIBS has been increasingly expanding, including studies on metallurgy, mining,
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environmental analysis and pharmacology.14-16 There are also several studies on food
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applications such as analysis of rice powder, unpolished-rice flour and starch17 and Ca in
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breakfast cereals,18 Na and NaCl analysis in bakery products,19 determination of whey
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adulteration in milk powder,20 identification of meat species,21 oil analysis,22 determination of
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biological contaminants on foods and food surfaces,10 effect of processing techniques on Mg
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content of green leafy vegetables23 and analysis of medicinal herbs rich in flavonoids.24
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The obtained light is collected with fiber optics and directed into the
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The aim of this study was to develop a new, rapid, in-situ and advanced method to
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determine protein content, related to nitrogen content, in the protein structure of cereal
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samples by using LIBS combined with multivariate data analysis technique such as partial
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least square (PLS). The study focuses on developing a relatively rapid, practical and 5 ACS Paragon Plus Environment
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economical method compared to the conventional ones. For this purpose, wheat flour and
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whole meal samples with different protein contents were analyzed with LIBS, and the spectra
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were correlated with the results of Dumas method by using chemometric methods.
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MATERIALS AND METHODS
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Sample Preparation. Totally 140 wheat flour and whole meal samples with different
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protein contents ranging between 7.9-20.9%, were obtained from Turkish Republic Ministry
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of Food, Agriculture and Livestock, General Directorate of Agricultural Research and Policies
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(Ankara, Turkey). Two mL deionized water were added into a 3 g sample and mixed to obtain
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a basic dough. After dough formation, the samples were placed into Glutork 2020 device
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(Perten Instruments, Hägersten, Sweden), also known as dry gluten tester, which provides
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cooking of dough as a sheet, then rested for 4 min at 150 °Ϲ. For LIBS analysis, three
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replicates were prepared from each sample. Ninety different flour samples and 50 different
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whole meal samples with different protein contents were analyzed to obtain data for
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calibration and validation graphs.
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Protein Analysis. Protein analysis was conducted using the Flash 4000
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Nitrogen/Protein Analyzer (Thermo Scientific, Cambridge, England). 500 mg of wheat flour
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and whole meal samples were weighed into tin copper capsule and introduced into a
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combustion reactor in automated equipment. The released nitrogen was carried by helium gas
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and quantitated by using thermal conductivity detector (TCD). Then, total nitrogen content
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was converted to protein content by using conversion factor.1 Protein content was calculated
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as in Equation 1.1
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% protein = % N × c
(Equation 1) 6 ACS Paragon Plus Environment
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Journal of Agricultural and Food Chemistry
Where c: conversion factor. In cereals, conversion factor may vary because of the 25
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composition difference.
Based on this differentiation, conversion factors were chosen as
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5.70 and 5.83 for wheat flour and whole meal analysis, respectively.
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LIBS Instrumentation. In the LIBS experiments Nano SG 150 mJ Nd:YAG laser
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(Litron Lasers, Warwickshire, England) which emits a laser pulse at 1064 nm and 5 channel
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Aurora LIBS spectrometer (Applied Spectra, Fremont, CA) which records the spectrum
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between 186-888 nm were used. Figure 1 shows the experimental setup of LIBS system.
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Laser was operated in Q-switched mode at a repetition rate of 8 Hz and 44.6 mJ/pulse, while
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spectrometer was operated at 650 ns gate delay and 1.05 ms integration time. Surfaces of the
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samples were scanned with laser at 50 different regions (three replicates for each sample) by
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using a rotary system which was operated at 1.33 rpm.
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Data Analysis. Determination of LIBS spectra is very difficult because of its high-
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dimensional, large and complex data, thus multivariate data analysis was performed to obtain
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quantitative data, which also provided elimination of laser fluctuations from shot-to-shot and
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physical/chemical matrix effect. Complexity of the study lies in the correlation of
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spectroscopic variables (wavelengths) and chemical differences between samples. PLS is
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frequently used for such type of analyses. It is a multivariate data analysis method used for
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data quantitation. To evaluate wide range spectrum and reduce matrix effect of the samples,
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samples with different protein contents were analyzed using PLS_Toolbox ver. 7.5.2
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(Eigenvector Research, Wenatchee, WA). In this study, 100 different flours with various
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protein contents were used for calibration data set; and 40 different samples with various
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protein contents were used for validation data set. Orthogonal Signal Correction (OSC) pre-
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processing method was used to obtain a global model for protein prediction in both of flour
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and whole meal samples. In order to evaluate measurement sensitivity and precision, relative
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standard deviation (RSD), relative error of prediction (REP) and relative accuracy (RA) 7 ACS Paragon Plus Environment
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values of PLS method were calculated using the following equations (Equation 2-4).26 Also,
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limit of detection (LOD) and limit of quantitation (LOQ) values were calculated based on a
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new approach in multivariate calibration, which takes into account IUPAC official
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recommendations and the latest development in error-in-variables for PLS.27
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ĉ
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REP% =
161
Where Nv : number of validation spectra; ci : true concentration; and ĉi : predicted
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concentration.
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RSD% =
164
Where Nconc : number of different concentrations in the validation set; ρ : number of spectra
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per concentration; and σ : Standard deviation.
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RA =
167
Where d: difference between LIBS measurement and reference method; S.D.: standard
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deviation of LIBS measurement; n: the number of measurement ; t0.95: t value at 2.5% error of
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confidence; and M: reference method result.
∑
!"#!
!"#! ∑(
$%& '&
(Equation 2)
with
,
σ'& ) = ∑
ĉ&*! + &
,
|/|01.3.× 45.67 /√:
(Equation 3)
(Equation 4)
;
170
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RESULTS AND DISCUSSION
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In this study, wheat flour and whole meal samples were analyzed by using LIBS. For the
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analysis, high power laser source was focused on the surface of cereal samples and absorbed
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energy rapidly was converted into heat. When local temperature reached between 8000-20000
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K, the value at which small portion of material vaporizes and turns into ionized gas, plasma
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formation occurred. In plasma formation, organic structure burns and molecular structure
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turns into elemental forms which emits characteristic light. These emissions can be analyzed
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quantitatively according to the intensity of peaks. In this study, full spectrum and major
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nitrogen peaks of wheat flour and whole meal are presented in Figure 2. LIBS spectra were
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recorded through laser-scanning of 50 shots for each flour sample, and triplicate
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measurements were performed with LIBS. Then, 150 spectra from triplicate measurements
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were used to obtain the average spectrum for that sample. In the literature, nitrogen peaks
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were located between 340-870 nm, and three major peaks were reported at 742, 744 and 746
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nm. 28, 29
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LIBS spectra were normalized to eliminate fluctuations of LIBS experiments such as
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laser energy variations shot-to-shot. Normalization was carried out by averaging the spectra
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over the number of measurements.
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were carried out by averaging the fully integrated peak intensity and normalizing the
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integrated continuum emission intensity (Figure 2). The method has been applied as a reliable
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analytical method
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lines and nitrogen content of wheat flour and whole meal.
31, 32
30
For each spectral line, peak to base (P/B) calculations
as it provides linear relation between intensities of atomic spectral
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LIBS can measure all elements in flour including nitrogen, which makes it applicable for
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measuring protein content representing the total nitrogen content. For this reason, the obtained
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LIBS spectra were correlated with the results of Dumas analysis by using PLS method. Figure
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3 demonstrates calibration and validation graphs of wheat flour and whole meal samples
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together. Low root mean square error of calibration (RMSEC) (0.33) and root mean square
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error of cross validation (RMSECV) (1.73) values were chosen to develop the calibration
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model, and high coefficient of determination value was observed (latent variable 3). In
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addition, root mean square error of prediction (RMSEP) value was observed as 0.93 for
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validation. 9 ACS Paragon Plus Environment
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In order to evaluate measurement sensitivity and precision, RSD, REP, LOD and LOQ
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values of PLS method were calculated.26, 27 The accuracy of LIBS compared to Dumas was
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evaluated with relative accuracy (RA) value. RA is calculated using Equation 4.26 RSD, REP,
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LOD and LOQ values were calculated as 4%, 4.5%, 0.26% and 0.77%, respectively; and
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these values indicate that LIBS is a reliable and sensitive method for protein analysis in wheat
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flour and whole meal samples and has good prediction ability. Also, Dumas results of the
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samples as a function of protein level showed low RA values at about 0.13, which means that
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LIBS is a quite acceptable technique for protein measurement in wheat flour and whole
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meal.33
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The present study is a novel study since it has made use of LIBS on food applications for
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protein analysis in wheat flour and whole meal samples. Besides, other experiments in the
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literature used only a standard calibration curve method which utilized only a single band. It
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was reported in a previous study that nitrogen calibration can be successfully accomplished
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following only 746 nm in the spectrum and it is not possible to use other lines of nitrogen in
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the calibration study.
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wavelength range between 340-888 nm (resolution: 0.07 nm) with the help of PLS. With this
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method, all lines of nitrogen in the sample made contribution to the calibration model.
28
However, in this work, calibration study was carried out by using a
219
In previous studies, emissions from nitrogen were observed when laser plasma was
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formed in air or on a solid surface in air, and it had an impact on the results. This influence
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can be eliminated by reducing atmospheric pressure, using vacuum conditions or using inert
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gases to remove the air influence. This difficulty is caused by occurrence of strong nitrogen
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emission lines after the first few microseconds following plasma formation.28, 29 However, in
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this study, data set was collected under the same atmospheric conditions which produced the
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same influence on the whole dataset. Nitrogen, and also oxygen and hydrogen interferences
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coming from the air have a background role, and PLS can eliminate this interference effect 10 ACS Paragon Plus Environment
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from all the collected data while obtaining a model. Therefore, atmospheric nitrogen does not
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cause negative effects on determination of protein content if calibration and validation data set
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were collected under the same atmospheric conditions. Protein analysis has a vital role for
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understanding the nutritional value and quality of the product to determine utilization field,
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which makes it indispensable for manufacturers. Therefore, protein analysis is a routine and
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important analysis in food industry. In this study, LIBS method combined with multivariate
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data analysis was used as a rapid method for protein analysis in food applications for the first
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time. The results of the study are very promising for food industry considering that
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conventional protein analysis methods are both expensive and time consuming, and have
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complex sample preparation steps. In contrast, the developed method is rapid, economical, in-
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situ and requires minimum sample preparation step, which makes it very appealing for food
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industry. Unlike conventional protein analysis methods, LIBS has potential to analyze wheat
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flour and whole meal samples only in a few seconds, thus much higher numbers of flour
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samples can be analyzed rapidly by using LIBS. Consequently, this study can be promising
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not only for flour and whole meal samples, but also for other food products.
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Therefore, this method seems to be a useful tool for quality control laboratories of flour mills and other food processing companies.
244 245
Acknowledgement
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The authors would like to thank to Turgay Sanal, General Directorate of Agricultural
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Research and Policies, Turkish Republic Ministry of Food, Agriculture and Livestock
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(Ankara) for his help in the sample collection and Prof. Durmus Ozdemir, Department of
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Chemistry, Izmir Institute of Technology (Izmir) for his contributions.
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References
253 254
(1)
Chang, S. K., Protein analysis. In Food analysis, Nielsen, S. S., Ed. Springer New York,
255
NY, 2010; pp 133-146.
256
(2)
257
Ankara, 2005; Vol. 737.
258
(3)
259
Chem. Soc. 1979, 56, 239-239.
260
(4)
261
Press: 2002; Vol. 118.
262
(5)
263
Wilson, J.; Chung, O., Predicting wheat quality characteristics and functionality using near-
264
infrared spectroscopy. Cereal Chem. 2006, 83, 529-536.
265
(6)
266
near-infrared transmittance spectroscopy. J. Agric. Food Chem. 2003, 51, 6335-6339.
267
(7)
268
starch and protein prediction in irradiated rice. Food Chem. 2011, 126, 1856-1861.
269
(8)
270
near infrared reflectance spectroscopy in diverse cereal food products. J. Near Infrared
271
Spectrosc. 2000, 8, 35-43.
272
(9)
273
liquids using laser induced breakdown spectroscopy by liquid-to-solid matrix conversion.
274
Spectrochim. Acta, Part B 2006, 61, 929-933.
Özkaya, H.; Özkaya, B., Öğütme teknolojisi. Gıda Teknolojisi Derneği Yayınları:
Tallent, W., Current developments in protein food regulations—labeling. J. Am. Oil
Owusu-Apenten, R., Food protein analysis: quantitative effects on processing. CRC
Dowell, F.; Maghirang, E.; Xie, F.; Lookhart, G.; Pierce, R.; Seabourn, B.; Bean, S.;
Miralbés, C., Prediction chemical composition and alveograph parameters on wheat by
Shao, Y.; Cen, Y.; He, Y.; Liu, F., Infrared spectroscopy and chemometrics for the
Kays, S. E.; Barton, I.; Franklin, E.; Windham, W. R., Predicting protein content by
Pace, D. D.; D'Angelo, C.; Bertuccelli, D.; Bertuccelli, G., Analysis of heavy metals in
12 ACS Paragon Plus Environment
Page 13 of 20
Journal of Agricultural and Food Chemistry
275
(10) Multari, R. A.; Cremers, D. A.; Dupre, J. A. M.; Gustafson, J. E., Detection of
276
biological contaminants on foods and food surfaces using laser-induced breakdown
277
spectroscopy (LIBS). J. Agric. Food Chem. 2013, 61, 8687-8694.
278
(11) Anabitarte, F.; Cobo, A.; Lopez-Higuera, J. M., Laser-induced breakdown
279
spectroscopy: fundamentals, applications, and challenges. ISRN Spectrosc. 2012, 2012.
280
(12) Choi, S.-J.; Lee, K.-J.; Yoh, J. J., Quantitative laser-induced breakdown spectroscopy of
281
standard reference materials of various categories. Appl. Phys. B 2013, 113, 379-388.
282
(13) Cho, H.-H.; Kim, Y.-J.; Jo, Y.-S.; Kitagawa, K.; Arai, N.; Lee, Y.-I., Application of
283
laser-induced breakdown spectrometry for direct determination of trace elements in starch-
284
based flours. J. Anal. At. Spectrom. 2001, 16, 622-627.
285
(14) Rusak, D.; Castle, B.; Smith, B.; Winefordner, J., Fundamentals and applications of
286
laser-induced breakdown spectroscopy. Crit. Rev. Anal. Chem. 1997, 27, 257-290.
287
(15) St-Onge, L.; Kwong, E.; Sabsabi, M.; Vadas, E., Quantitative analysis of
288
pharmaceutical products by laser-induced breakdown spectroscopy. Spectrochim. Acta, Part
289
B 2002, 57, 1131-1140.
290
(16) Tognoni, E.; Palleschi, V.; Corsi, M.; Cristoforetti, G., Quantitative micro-analysis by
291
laser-induced breakdown spectroscopy: a review of the experimental approaches.
292
Spectrochim. Acta, Part B 2002, 57, 1115-1130.
293
(17) Khumaeni, A.; Lie, Z. S.; Niki, H.; Kurniawan, K. H.; Tjoeng, E.; Lee, Y. I.; Kurihara,
294
K.; Deguchi, Y.; Kagawa, K., Direct analysis of powder samples using transversely excited
295
atmospheric CO2 laser-induced gas plasma at 1 atm. Anal. Bioanal. Chem. 2011, 400, 3279-
296
3287.
297
(18) Ferreira, E. C.; Menezes, E. A.; Matos, W. O.; Milori, D. M.; Nogueira, A. R. A.;
298
Martin-Neto, L., Determination of Ca in breakfast cereals by laser induced breakdown
299
spectroscopy. Food Control 2010, 21, 1327-1330.
13 ACS Paragon Plus Environment
Journal of Agricultural and Food Chemistry
Page 14 of 20
300
(19) Bilge, G.; Boyacı, Đ. H.; Eseller, K. E.; Tamer, U.; Çakır, S., Analysis of bakery
301
products by laser-induced breakdown spectroscopy. Food Chem. 2015, 181, 186-190.
302
(20) Bilge, G.; Sezer, B.; Eseller, K. E.; Berberoğlu, H.; Topçu, A.; Boyacı, Đ. H.,
303
Determination of whey adulteration in milk powder by using laser induced breakdown
304
spectroscopy. Food Chem. 2016, 212, 183-188.
305
(21) Bilge, G.; Velioglu, H. M.; Sezer, B.; Eseller, K. E.; Boyaci, I. H., Identification of meat
306
species by using laser-induced breakdown spectroscopy. Meat Sci. 2016, 119, 118-122.
307
(22) Caceres, J. O.; Moncayo, S.; Rosales, J. D.; de Villena, F. J. M.; Alvira, F. C.; Bilmes,
308
G. M., Application of laser-induced breakdown spectroscopy (LIBS) and neural networks to
309
olive oils analysis. Appl. Spectrosc. 2013, 67, 1064-1072.
310
(23) Rai, D.; Agrawal, R.; Kumar, R.; Rai, A. K.; Rai, G. K., Effect of processing on
311
magnesium content of green leafy vegetables. J. Appl. Spectrosc. 2014, 80, 878-883.
312
(24) Andrade, D. F.; Pereira-Filho, E. R.; Konieczynskib, P., Comparison of ICP OES and
313
LIBS analysis of medicinal herbs rich in flavonoids from Eastern Europe. J. Braz. Chem. Soc.
314
2016, 00, 1-10.
315
(25) Jones, D. B., Factors for converting percentages of nitrogen in foods and feeds into
316
percentages of proteins. US Department of Agriculture Washington, DC: 1931.
317
(26) Gondal, M.; Seddigi, Z.; Nasr, M.; Gondal, B., Spectroscopic detection of health
318
hazardous contaminants in lipstick using laser induced breakdown spectroscopy. J. Hazard.
319
Mater. 2010, 175, 726-732.
320
(27) Allegrini, F.; Olivieri, A. C., IUPAC-consistent approach to the limit of detection in
321
partial least-squares calibration. Anal. Chem. 2014, 86, 7858-7866.
322
(28) Harris, R. D.; Cremers, D. A.; Ebinger, M. H.; Bluhm, B. K., Determination of nitrogen
323
in sand using laser-induced breakdown spectroscopy. Appl. Spectrosc. 2004, 58, 770-775.
14 ACS Paragon Plus Environment
Page 15 of 20
Journal of Agricultural and Food Chemistry
324
(29) Dong, D.; Zhao, C.; Zheng, W.; Zhao, X.; Jiao, L., Spectral characterization of nitrogen
325
in farmland soil by laser-induced breakdown spectroscopy. Spectrosc. Lett. 2013, 46, 421-
326
426.
327
(30) Castro, J. P.; Pereira-Filho, E. R., Twelve different types of data normalization for the
328
proposition of classification, univariate and multivariate regression models for the direct
329
analyses of alloys by laser-induced breakdown spectroscopy (LIBS). J. Anal. At. Spectrom.
330
2016, 31, 2005-2014.
331
(31) Windom, B.; Diwakar, P.; Hahn, D., Dual-pulse laser induced breakdown spectroscopy
332
for analysis of gaseous and aerosol systems: Plasma-analyte interactions. Spectrochim. Acta,
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Part B 2006, 61, 788-796.
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(32) Carranza, J. E.; Hahn, D. W., Sampling statistics and considerations for single-shot
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analysis using laser-induced breakdown spectroscopy. Spectrochim. Acta, Part B 2002, 57,
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779-790.
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(33) Gondal, M. A.; Hussain, T.; Yamani, Z. H.; Baig, M. A., On-line monitoring of
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remediation process of chromium polluted soil using LIBS. J. Hazard. Mater. 2009, 163,
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1265-1271.
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FIGURE CAPTIONS
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Figure 1. LIBS experimental setup.
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Figure 2. Full spectra of: (A) whole meal; (B) three major nitrogen peaks of the whole meal;
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(C) full spectra of the wheat flour; and (D) three major nitrogen peaks of the wheat flour.
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Figure 3. (A) PLS calibration; and (B) validation models of wheat flour and whole meal.
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Figure 1 177x84mm (300 x 300 DPI)
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Figure 2 304x203mm (300 x 300 DPI)
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Figure 3 177x93mm (300 x 300 DPI)
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For Table of Contents Only 83x47mm (300 x 300 DPI)
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