ms alakalı 2
TRANSCRIPT
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EEGGEE UUNNIIVVEERR SSIITTYY
MASTER THESIS
DETERMINATION OF METAL CONTENTS OFHONEY, GRAPE SYRUP, VINEGAR AND FRUIT
JUICES PRODUCED IN TURKEY BY ICP-MSMETHOD
Levent ELBOL
Supervisors : Prof. Dr. F. Nil ERTA
Assist. Prof Dr. Hasan ERTA
Department of Chemistry
Code of Discipline : 405.03.01Date of Presentation : 04.12.2009
Bornova-ZMR2009
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EGE UNIVERSITYGRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
(MASTER THESIS)
DETERMINATION OF METAL CONTENTS OF HONEY,GRAPE SYRUP, VINEGAR AND FRUIT JUICES PRODUCED
IN TURKEY BY ICP-MS METHOD
Levent ELBOL
Supervisors : Prof. Dr. F. Nil ERTA
Assist. Prof. Dr. Hasan ERTA
Department of Chemistry
Code of Discipline : 405.03.01Date of Presentation : 04.12.2009
Bornova-ZMR
2009
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Levent ELBOL tarafndan Yksek Lisans tezi olarak sunulan Trkiyede
retilen Bal, Pekmez, Sirke Ve Meyve Suyu rneklerinin Metal eriklerinin
ICP-MS le Analizlenerek ncelenmesi balkl bu alma E.. Lisansst
Eitim ve retim Ynetmelii ile E.. Fen Bilimleri Enstits Eitim ve
retim Ynergesinin ilgili hkmleri uyarnca tarafmzdan deerlendirilerek
savunmaya deer bulunmu ve 04.12.2009 tarihinde yaplan tez savunma
snavnda aday oybirlii/oyokluu ile baarl bulunmutur.
Jri yeleri: mza
Jri : Prof. Dr. F. Nil ERTA .................................
Bakan
Raportr : Prof. Dr. mran YKSEL .................................
ye
ye : Prof. Dr. Ali ELK .................................
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ZET
TRKYEDE RETLEN BAL, PEKMEZ, SRKE VE
MEYVE SUYU RNEKLERNN METAL ERKLERNN
ICP-MS LE ANALZLENEREK NCELENMES
ELBOL Levent
Yksek Lisans Tezi, Kimya Blm
Tez Yneticisi: Prof. Dr. Nil ERTA
Aralk 2009, 50 sayfa
Bu tezde Trkiye'de retilen sirke, pekmez, bal ve meyve suyu rneklerinin
metal iyonu ieriklerinin indktif elemi plazma-ktle spektrometresi (ICP-MS)
sistemi ile analizi amalanmtr. Bu tr eker ierikli gda maddelerine hile
amal katmlar yaplarak piyasaya arzedildii bilinen bir gerektir. Bu gdamaddelerinin kalitesinin yansra orjinalitesinin snanmasna ynelik varolan
gelitirilmi yntemlere seenek oluturabilecek doru ve duyarl yntem
gelitirilmesi konusunda almalar srmektedir.
Bu tez almasnn ana hedefi bu gda matrikslerinin metal ieriklerinin
gnmzn bu alanda en gelimi yntemi saylan ICP-MS sistemi ile
saptanmasdr. Bu amala rneklerin analize hazrlanmas, bozundurulmas,
lm, verilerin istatistiksel deerlendirilmesi ve sonularn dier bulgularla
kyaslanmas aamalarnda varolan altyap kullanlarak gerekli eksik malzemelerin
bu projeden temini ile bu amaca hzla ulalmas hedeflenmitir.
Pekmez, sirke, bal ve meyve suyu gibi gda maddelerine hile amal
katmlar yaplarak piyasaya arz edildii bilinen bir gerektir. Her ne kadar bu gda
maddelerinin safln tespit etmek iin gelitirilmi farkl yntemler olsa da bu
yntemler her zaman kesin sonu verememektedir. Bu nedenle bu gda maddeleri
iin gelitirilmi yntemlere alternatif ve destekleyici olabilmesi asndan
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ierdikleri metal bileimi tespit edilerek matrikslerin saflna ilikin yeni
parametreler oluturulmas amalanmaktadr. Ayn zamanda bir dier hedef de bu
maddelere evreden bulaabilen yada retim aamasnda prosesten
kaynaklanabilen metalik kirliliklerin saptanmasdr. Bu kontaminasyonlar iin
verilen maksimum tolerans snrlar ok dk olduundan analizde olduka duyar
ve tekrarlanabilir dolays ile de gvenilir tekniklerin gelitirilmesine gereksinim
vardr.
Gnmzde bal, pekmez, sirke ve meyve sularnn saflk analizlerinde genel
olarak izotop oranlar ktle spekktroskopisi yntemi kullanlmaktadr. Buna ek
olarak, eker bileenlerinin, refraktif indeks dedektrl yksek basn sv
kromatografisi HPLC- RI yntemi ile analizi, bal iin prolin ve polen analizi,meyve sular iin kat madde tayini gibi yntemler de kullanlmaktadr. Bu tez
almas kapsamnda bu analizlere ek olarak ICP-MS cihaznda bu gda
maddelerinin metal bileimleri tespit edilerek, bu maddelere zg yeni
parametrelerin oluturulmasna allacaktr. Bunun iin rnekler mikro dalga
bozundurma sistemi kullanlarak bozundurma ilemine tabi tutulacak ve bu yolla
analize hazrlanacaktr. Ardndan kalibrasyonu ve validasyonu yaplm olan ICP-
MS yntemi kullanlarak metal iyonlarnn deriimleri saptanacaktr. te yandan
her zaman analizine bavurulmayan kimileri insan vcudu iin esansiyel olan
metal iyonlarnn da analizi gerekletirilerek, bu tr eker ierikli gdalarn metal
ieriine farkl bir bak kazandrlacaktr.
Anahtar Szckler: Ar metal, bal, meyve suyu, ICP-MS, Mikrodalga ile
bozundurma
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ABSTRACT
DETERMINATION OF METAL CONTENTS OF HONEY,
GRAPE SYRUP, VINEGAR AND FRUIT JUICES PRODUCED IN
TURKEY BY ICP-MS METHOD
ELBOL Levent
Master Thesis in Chemistry
Supervisor: Prof. Dr. Nil ERTA
December 2009, 50 pages
In this study, to develop a method for revealing the adultery in food samples
namely fruit juices, honey, grape syrups and vinegar was aimed. For this purpose,
ICP-MS measurements were used to discriminate the real and fake samples. This
is a part of a main project together with the 13C measurements of these sugar
containing foods. Overall results will overlook the average composition of these
foods for deciding any adultery.
In the course of the study, the comparison of the sample preparation
techniques and validation of the methods was also accomplished. The method was
developed for food samples and overall data was evaluated to find a pattern to
help to discriminate the real and fake samples
It is known that honey, grape syrup, vinegar and fruit juices are exposed to
adulteration before marketing. Although there are a number of methods developed
for authencity of these products, reliable methods are always needed for accurate
analysis. Therefore, it was planned to develop an alternative of supportive method
to those methods already used. Metal content of these samples will be analyzed to
perceive the possibility of establishing another parameter specific to these sample
or to reveal the contamination of heavy metal impurities as well.The maximum
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tolerance limits are very low for these contaminations. So very sensitive,
repeatable and reliable methods should be developed.
Recently, the authencity of honey, grape syrup, vinegar and fruit juices are
usually searched by isotope ratio method and HPLC-RI method for sugarcontents. Besides, proline and pollen analysis for honey, brix analysis for fruit
juice are also required for reliable results. In the context of this thesis, in addition
to those developed methods for authenticity, the metal content of these samples
will be determined by means of ICP-MS method to perceive the possibility of
establishing another parameter specific to these sample or to reveal the
contamination of heavy metal impurities as well. The samples will be decomposed
in microwave digestion system before the analysis.Then the concentrations ofmetal ions will be determined with calibrated and validated ICP-MS method that
has a wide range.
Keywords: Heavy metal, honey, fruit juice, ICP-MS, microwave digestion
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ACKNOWLEDGMENT
I would like to present my gratitude to my supervisors, Prof. Dr. F. Nil
ERTA and. Do. Dr. Hasan ERTA for their precious suggestion, support, and
patience, and for enlightening me via their deep knowledge and experience. I also
thank to all of the members of the Ege University Center for Drug Research &
Development and Pharmacokinetic Applications Contract Research Organization
(ARGEFAR) especially to the assistant director Ercment KARASULU for
providing the precious conditions and support throughout my studies.
I would like to thank to my friend Bar GMTA who have
encouraged and helped me throughout this work.
I would like to thank and present my gratitude to my family for their,
understanding, support and patience.
Bornova, 2009 Levent ELBOL
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CONTENTS
Page
ZET ................................................................................................................ V
ABSTRACT........................................................................................................VII
ACKNOWLEDGMENT ...................................................................................... X
LIST OF FIGURES ............................................................................................XV
LIST OF TABLES..........................................................................................XVIII
1.INTRODUCTION .............................................................................................. 1
1.1.Authenticity of Foods....................................................................................... 1
1.1.1.Fruit Juice...................................................................................................... 1
1.1.2.Honey............................................................................................................ 2
1.1.3.Grape Syrup .................................................................................................. 4
1.1.4.Vinegar.......................................................................................................... 5
1.2.Heavy Metals ................................................................................................... 6
1.3.Literature Survey on Determination of Heavy Metals in Foods...................... 7
1.4.The Aim of the Thesis.................................................................................... 10
1.5.ICP-MS .......................................................................................................... 10
1.5.1.Sample Introduction.................................................................................... 11
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CONTENTS (continue)
Page
1.5.2.Transfer of ions into Vacuum ..................................................................... 12
1.5.3.Ion Optics.................................................................................................... 12
1.5.4.Octopole Reaction System (ORS) .............................................................. 13
1.5.5.Plasma ......................................................................................................... 13
1.5.6.Plasma Generation ...................................................................................... 13
1.5.7.Advantage of Argon.................................................................................... 14
1.5.8.Elemental Analysis ..................................................................................... 15
1.6.Microwave Digestion..................................................................................... 15
1.6.1.Heating Mechanism .................................................................................... 16
1.6.2.Open Versus Closed Acid Digestion .......................................................... 17
1.7.Method Validation ........................................................................................ 18
2.EXPERIMENTAL............................................................................................ 21
2.1 Apparatus ....................................................................................................... 21
2.2 Chemicals and Reagents ................................................................................ 21
2.3 Analytical Procedures and ICP-MS Conditions ............................................ 21
3.RESULTS AND DISCUSSION ....................................................................... 23
3.1 Optimization Studies for Method Development ............................................ 23
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CONTENTS (continue)
Page
3.2 Validation Studies ..........................................................................................26
3.2.1 Linearity ......................................................................................................26
3.2.2 Repeatability ............................................................................................... 26
3.2.3 Sensitivity.................................................................................................... 27
3.2.4 Recovery ..................................................................................................... 27
3.2.5 Uncertainty .................................................................................................. 28
3.3 Comparison of thhe Developed Method with Direct Injection ......................29
3.4 Application of the Method to the Samles.......................................................30
3.4.1 Vinegar Results ...........................................................................................30
3.4.2 Grape Syrup Results....................................................................................30
3.4.3 Fruit Juice Results .......................................................................................33
3.4.4 Honey Results..............................................................................................45
4. CONCLUSION................................................................................................ 47
REFERENCES..................................................................................................... 48
CIRRICULUM VITAE........................................................................................ 50
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LIST OF FIGURES
Figure Page
1.1. Schematic representation of an ICP-MS ................................................11
1.2. Schematic of sample heating by microwaves.........................................17
1.3. Schematic representations of sample digestion systems .......................17
3.1. Typical ICP-MS results of Sc, V, Cr, Mn, Co, Ni, Cd, Cr, As, Mn, Cd,
In, Sb, Ba.....25
3.2. Typical ICP-MS results of Zn, Ge, Hg, Bi .............................................25
3.3. Typical ICP-MS results of Fe, Mg, K, Ca, Na .......................................25
3.4. Schematic representation of barium results of grape syrups, mulberry
and harnup syrups...................................................................................32
3.5. Schematic representation of iron results of grape syrups, mulberry and
harnup syrups..........................................................................................32
3.6. Schematic representation of manganese results of grape syrups,
mulberry and harnup syrups ................................................................32
3.7. Schematic representation of barium results of strawberry juices and
froudulent sample ...................................................................................35
3.8. Schematic representation of calcium results of strawberry juices and
froudulent sample ...................................................................................35
3.9. Schematic representation of potassium results of strawberry juices and
froudulent sample ...................................................................................35
3.10. Schematic representation of magnesium results of strawberry juices and
froudulent sample ...................................................................................36
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LIST OF FIGURES (continue)
3.11. Schematic representation of sodium results of strawberry juices and
froudulent sample .................................................................................. 36
3.12. Schematic representation of zinc results of strawberry juices and
froudulent sample .................................................................................. 36
3.13. Schematic representation of cupper results of apricot juices and
froudulent sample .................................................................................. 39
3.14. Schematic representation of iron results of apricot juices and froudulentsample .................................................................................................... 39
3.15. Schematic representation of potassium results of apricot juices and
froudulent sample .................................................................................. 39
3.16. Schematic representation of magnesium results of apricot juices and
froudulent sample .................................................................................. 40
3.17. Schematic representation of manganese results of apricot juices and
froudulent sample .................................................................................. 40
3.18. Schematic representation of sodium results of apricot juices and
froudulent sample .................................................................................. 40
3.19. Schematic representation of cupper results of pomegranate juices and
froudulent sample .................................................................................. 42
3.20. Schematic representation of magnesium results of pomegranate juices
and froudulent sample............................................................................ 42
3.21. Schematic representation of zinc results of pomegranate juices and
froudulent sample .................................................................................. 42
3.22. Schematic representation of barium results of cherry juices and
froudulent sample .................................................................................. 44
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LIST OF FIGURES (continue)
3.23. Schematic representation of iron results of cherry juices and froudulent
sample.....................................................................................................44
3.24. Schematic representation of potassium results of cherry juices and
froudulent sample ...................................................................................44
3.25. Schematic representation of sodium results of cherry juices and
froudulent sample ...................................................................................45
3.26. Schematic representation of barium results of honey samples, sugaradded sample and froudulent sample .....................................................46
3.27. Schematic representation of calcium results of honey samples, sugar
added sample and froudulent sample .....................................................46
3.28. Schematic representation of cupper results of honey samples, sugar
added sample and froudulent sample .....................................................47
3.29. Schematic representation of potassium results of honey samples, sugar
added sample and froudulent sample .....................................................47
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LIST OF TABLES
Table Page
1.1. Limits for metal and sugar content of several fruit juices (mg/kg) (AIJN,
2007)......................................................................................................... 3
1.2. Typical honey composition in percent (% g/g)............................................. 3
1.3. Microwave digestion procedures of fruit juice samples ............................... 8
2.1. Microwave digestion procedure.................................................................. 22
2.2. Optimized conditions for ICP-MS system.................................................. 22
2.3. Used isotopes of analyzed elements............................................................ 22
3.1. The effect of sample weight on the analysis by comparing the metal content
of the fruit juice sample .............................................................................. 23
3.2. The comparison of the metal content of the fruit juice sample digested at
various temperatures................................................................................... 24
3.3. The comparison of the metal content of the fruit juice sample digested at
various time ................................................................................................ 24
3.4. Regression coefficients for metals studied from calibration curves obtained
with ICP-MS measurements ....................................................................... 26
3.5. Relative Standard Deviations of metals ...................................................... 27
3.6. LOD LOQ values of metals (g/L)............................................................. 27
3.7. Recovery percentages of the metals studied with ICP-MS......................... 28
3.8. Relative uncertainty values of metals ......................................................... 28
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LIST OF TABLES (continued)
Table Page
3.9. Comparison of the developed microwave digestion method with direct
injection.......................................................................................................29
3.10. Metal compositions of grape vinegar (GV) and falsified alcohol
vinegar(FAV) ..............................................................................................30
3.11. Metal compositions of grape syrups and mulberry syrup............................31
3.12. Metal compositions of pear juices ...............................................................33
3.13. Metal compositions of strawberry juices .....................................................34
3.14. Metal compositions of apple juices .............................................................37
3.15. Metal compositions of apricot juices ...........................................................38
3.16. Metal compositions of pomegranate juices .................................................41
3.17. Metal compositions of cherry juices............................................................43
3.18. Metal compositions of honey .....................................................................45
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H2SO4 Sulfuric Acid
He Helium
Hg Mercury
HCl Hydrochloric Acid
HNO3 Nitric Acid
ICP-AES Inductively Coupled Plasma- Atomic Emission Spectrometer
ICP-MS Inductively Coupled Plasma-Mass Spectrometer
ICP-OES Inductively Coupled Plasma- Optic Emission Spectrometer
IRMS Isotope Ratio Mass Spectrometer
K Potassium
LOD Limit of Detection
LOQ Limit of Quantification
Mg Magnesium
Mn Manganese
Na Sodium
Ni Nickel
OCTP Octopole
ORS Octopole Reaction System
ABBREVIATIONS (continued)
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Pb Lead
QP Quadrupole
RF Radio Frequency
RSD Relative Standard Deviation
S/C Spray Chamber
Se Selenium
Sb Antimony
TSE Turkish Standard Institute
USA United States of America
V Vanadium
W Watt
Zn Zinc
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1.INTRODUCTION
1.1Authenticity of Foods
Foods like honey, molasses, fruit juices and vinegar known that they arehealty foods. Many people consume these foods are just as healthy. Unfortunately,
they are all not healthy or original. In many countries of the world including our
country, this is known that many manufacturers make froud to these foods to earn
more. For a chemist, even though many analytical techniques have developed, it is
very hard to determine that it is natural or not as the competition between analyst
and falsifier is going on. For this reason, it is very important to develop new
techniques and aspects to detect forgery. Metal analysis is important to find
forgery as well as detecting non-essential metal in foods.
The compositions of various metals in different food types of various
countries have been the subject of many studies. Such data are not readily avaible
for most food in developing countries, such as Turkey. The objective of this thesis
is to provide a more detailed determination of the contents of the metals in fruit
juices, honey, vinegar and molases. Following sections give a brief explanation
about the composition of these materials.1.1.1 Fruit Juice
100% fruit juices are nutritious beverages that have been enjoyed by adults
and children for decades. 100% fruit juices can play an important role in a healthy
diet because they offer great taste and a variety of nutrients found naturally in
fruits. These juices are fat-free, nutrient-dense beverages that are rich in vitamins,
minerals and naturally occurring phytonutrients that contribute to good health.
Phytonutrients are compounds in fruits, vegetables and other plants that
researchers find have disease preventative and disease fighting properties.
The determination of juice authenticity is exceedingly complex and requires
cooperative efforts of well-informed, dedicated individuals from many disciplines
and involves many analytical methodologies (K.W. Barnes, 1999). Metal
determinations can resolve many issues and are typically performed to answer
three questions. First, how much of a nutrient metal (mineral) is present and is the
product labeled properly?
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Next, is the product what it claims to be and does it comply with trade laws?
Have authentic products been used, or has the product been adulterated? Finally,
is the product wholesome and safe to eat, is it contaminated, or has tampering
occurred?
To promote and maintain fair competition and commercial viability of fruit
juices, European Fruit Juice Association (AIJN) serves for over 40 years. AIJN
has been the representative association of the fruit juice industry in the E.U. It
represents the industry from the fruit processors to the packers of the consumer
products. One of the main activities of AIJN is the development of instruments
such as the reference guidelines, codes of practice, position papers, etc. for the
benefit of the whole fruit juice industry. These instruments complement the fruitjuice legislation. AIJN developed two very important tools for the industry; first
one is The Code of Practice for evaluation of fruit and vegetable juices which sets
absolute quality requirements and criteria for the evaluation of identity and
authenticity of 20 different fruit juices. The second one is The European Quality
Control System which aims at maintaining the good and healthy image of fruit
juice products and ensuring fair competition in the single European market.
More recently AIJN developed a guideline for the interpretation of the fruitjuice directive 2001/112 EC, a guideline for restoration aroma, a traceability
guideline as well as a revision of its hygiene Code. Turkey is an affiliated member
of AIJN and Turkish Fruit Juice Industry Association (MEYED) facilitates on this
subject (meyed.com.tr). According to AIJN, metal contents of several fruit juices
were reported and given in Table 1.1 (AIJN, 2008).
1.1.2. Honey
Honey possesses valuable nourishing, healing and prophylactic properties.
These properties result from its chemical composition (Przybylowski et al., 2005).
Honey production starts valuable nourishing, healing and prophylactic properties
which are produce by Hymenoptera collected from bees. Collected nourishes are
changed in body of bees and stores in comb eyes for maturation, as a result honey
bee that is dense and desert (Demirezen, 2005).
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Table 1.1 Limits for metal and sugar content of several fruit juices (mg/kg) (AIJN, 2007)
Metal Apple Apricot Pomegranate Strawberry Pear Cherry
As 0.1 0.1 0.1 0.1 0.1 0.1
Ca 30-120 85-200 50-120 80-300 35-130 80-240
Cd 0.05 0.05 0.05 0.05 0.05 0.05
Cu 5.0 5.0 5.0 5.0 5.0 5.0
Fe 5.0 5.0 5.0 5.0 5.0 5.0
Hg 0.01 0.01 0.01 0.01 0.01 0.01
K 900-1500 2000-4000 1300-3000 1000-2300 1000-2000 1600-3500
Mg 40-75 65-130 20-110 70-170 45-95 80-200
Na Max 30 Max 35 Max 30 Max 30 Max 30 Max 30
Pb 0.05 0.05 0.05 0.05 0.05 0.05
Sn 1.0 1.0 1.0 1.0 1.0 1.0
Zn 5.0 5.0 5.0 5.0 5.0 5.0F/G 2.0-3.3 0.4-1.0 1.0-1.2 1.0-1.3 Min 2.5 0.7-0.9
13C -27/ -24 - - - - -
Brix 11.2 11.2 15.0 13.5 11.9 7.0
Honey is a semi liquid product, which contains a complex mixture of
carbohydrates, mainly glucose and fructose; other sugars are present at trace
levels, depending on floral origin. Moreover, organic acids, lactones, amino acids,
minerals, vitamins, enzymes, pollen wax and pigments are present. Honey isproduced either from many flowers or from single flower pollens.
The quality criteria for honey are described as its contents. Typical honey
percent combination is given in Table 1.2. These contents are; acidity, sugar
component ratio, mineral content, diastase activity, hydroxymethylfurfural
content, prolin (amino acid). Thus, analytical methods have to overcome all the
honey matrix effects.
Table 1.2 Typical honey composition in percent (% g/g)
Content % Content %
Water 17 Acid 0.57
Fructose 38 Proteins 0.26
Glucose 31 Ash 0.17
Sucrose 1 Others* 12
*maltose, alkaloids, tannins, enzymes, vitamins, pollens
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Honey can named as natural with these analyses but this is not enough for
its quality. As food stuff used for healing purposes, honey must be free ofobjectionable contents. It should contain only small amounts of pollutants, such as
trace metals. Analysis of honey for trace elements content is necessary in food
quality control.
In addition, bee honey has been used as monitors of a variety of
environmental contaminants, including heavy metals, low level radioactivity and
pesticides. Heavy metals have an important function for environmental pollution.
Experiments carried out in Polandshow that, large amounts of heavy metals were
found in honeys from hives located near extra urban crossroad and steelworks
(Tuzen, 2005).The climate and rich vegetation in Turkey provide a very suitable
environment for apiculture which is in a state of expansion. Turkey was the third
largest country with 3,686,000 hives in 1993, following Russia and USA. The
production of honey was 59.207 tons in 1995 and increased to 80.000 tons in
1997. Recently, both international and Turkish studies have drawn attention to the
occurrence of the metal contents of honey (Tuzen, 2005).
1.1.3. Grape Syrups
Grape syrups are widely produced and consumed in Turkey. Searched for
adultery in food can be focused on grape syrups as they are potentially available
for adultery. On the other hand, molasses is a viscous byproduct of the processing
of sugar cane or sugar beets into sugar. The quality of molasses depends on the
maturity of the sugar cane or sugar beet, the amount of sugar extracted, and the
method of extraction. Sweet sorghum syrup is known in some parts of the United
States as molasses, though it is not true molasses.
Recently, adulteration of grape syrups is increasingly being recognized as a
problem in Turkey. Grape syrups are produced in two forms; solid and liquid.
Solid grape syrup, also called as Zile, is produced by simply adding starch, egg
white, powdered sugar, honey, milk powder and ripe raisin concentrate to grape
syrup and it is not considered for adulteration.
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According to regulations of Turkish Standard Institute (TS-3792), liquid
type should be produced only from fruit extract and should not contain any
additive material including Zile (TSE, 2008). In order to reduce cost, it is
however, easily and usually adulterated with cheaper carbohydrates such as
sucrose, high-fructose corn syrup and glucose syrup, which may be regarded as
rather harmless.
Furthermore, grape syrup is sometimes illegally mixed with second grade
fruit juice concentrates such as mulberry, fig and carob bean and often treated
with citric acid as preservative and caramel as coloring matter (imek et al,
2002).
1.1.4. Vinegar
Vinegar is an acidic liquid processed from the fermentation of ethanol in a
process that yields its key ingredient, acetic acid. It also may come in a diluted
form. The acetic acid concentration typically ranges from 4 to 8% by volume for
table vinegar (typically 5%) and higher concentrations for pickling (up to 18%).
Natural vinegars also contain small amounts of tartaric acid, citric acid, and other
acids. Vinegar has been used since ancient times and is an important element in
European, Asian, and other cuisines.
Vinegar is made from the oxidation of ethanol by acetic acid bacteria in
wine, cider, beer, fermented fruit juice, or nearly any other liquid containing
alcohol. Commercial vinegar is produced either by fast or slow fermentation
processes. Slow methods generally are used with traditional vinegars and
fermentation proceeds slowly over the course of weeks or months. The longer
fermentation period allows for the accumulation of a nontoxic slime composed of
acetic acid bacteria and soluble cellulose, known as the mother of vinegar.
The fraud in vinegar production is made by adding dilute acetic acid. This
can be easily detected by IRMS technique. But, if the vinegar made by ethyl
alcohol, it is important to determine acetic acid with IRMS. Therefore, metal
spectrum of natural vinegar will guide us to determine whether vinegar is made by
ethyl alcohol or diluted acetic acid.
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1.2. Heavy Metals
Trace metals are important in daily diets, because of their essential
nutritious value and possible harmful effects. Trace metals are classified into three
classes based on their effects on life. The essential nutritive metals are Co, Cu, Fe,I, Mn and Zn. However, elements such as Cu and Zn have emetic action when
ingested in higher amounts. The non-nutritive non-toxic metals which are not
harmful when present in amounts not exceeding 100 ppm include Al, B, Cr, Ni
and Sn. However, the increasing chromium intake calls for concern. The non-
nutritive toxic metals which are known to have deleterious effects even at
amounts below 100 ppm are As, Sb, Cd, F, Pb, Hg and Se. For example, arsenic
exposure induces cardiovascular diseases, developmental abnormalities,neurologic and neurobehavioral disorders, diabetes, hearing loss, hematologic
disorders and various types of cancer .
Heavy metals may enter the human body through food, water, air, or
absorption through the skin when they come in contact with humans in agriculture
and in manufacturing, pharmaceutical, industrial or residential settings. Food is a
major source of human exposure to metals.
Potential sources of human exposure include consumer products and
industrial waste as well as the working environment. Cumulative poisoning occurs
due to ingestion of food containing metals such as lead and arsenic over a long
period. Some metals have detrimental effects on the quality or nutritive value of
food. For example, copper tend to destroy vitamin C in fruit products (Williams et
al, 2007). Heavy metals become toxic when they are not metabolized by the body
and they accumulate in the soft tissues.
The metabolism of the toxic metal may be similar to metabolically related
essential ones. Such is the case with effects of Pb and Ca in the central nervous
system and Pb, Fe and Zn in heme metabolism.
Human cells that are involved in the transport of metals such as gastro-
intestinal, liver or renal tubular cells are particularly susceptible to toxicity.
Factors such as age, diet, interactions and exposure to other toxic metals influence
the toxicity levels of metals in humans. Children and the elderly are believed to be
more susceptible to toxicity from metallic exposure.
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Trace metals are present in foods in amounts below 50 ppm and have some
toxicological or nutritional significance. While some inorganic elements such as
Na, K, Ca, P are essential for man, elements like Pb, Cd, Hg, As are found to
cause deleterious effects even in low levels of 1050 ppm (Williams et al,2007).
Hence, determination of both major and trace levels of metal contents in food is
important for both food safety and nutritional considerations.
The compositions of various metals in different food types have been the
subject of many studies (Iwegbue et al, 2008). Such data are readily available for
most food in developing countries.
1.3. Literature Survey on Determination of Heavy Metals in Foods
Recently, numerous instrumental methods are used to determine heavy
metals in many kinds of foods, mainly spectroscopic methods including
inductively coupled plasma with mass detector (ICP-MS), and optic emission
(ICP-OES) and Graphite Furnace Atomic Absorption Spectroscopy (GFAAS).
Changes in the quality of bee honey are also caused by the contamination
with micro-polluting agents, toxic to consumers. The honey used in a study was
harvested from beehives situated in an area where ecological unbalances induced
by the non-ferrous metal industry through pollution. For this purpose, 5.0 g of
honey was placed in a small container and heated until turned into caramel and
then placed on the flame and burned further until the sample stops smoking. The
container is then placed in an electric oven and heated to 700oC until calcinated
for 3 hours. The resulted ash is cooled to room temperature and then dissolved in
5 ml solution of nitric acid (1:6). The solution is then heated until evaporated to
half its volume prior to the quantization with AAS. The amounts of Pb, Cd and Zn
contained in the samples have been determined using an AAS. The results
suggested that honey could be used to detect contaminating agents from the
environment (Bratu, et al. 2005).
In a study carried out in our country, bee honey samples collected from 16
stations around Kayseri were weighted ca. 2.5 g and incinerated at 450oC and
then, dissolved in nitric acid. The contents of cadmium, lead, nickel, zinc and
copper in the samples were determined by ICP-OES. The results have revealed
that mean intake of heavy metals is generally tolerable (Demirezen et al, 2005).
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In another study, the trace metal contents in 15 different honey samples
collected from different farms in Middle Anatolia were determined by GFAAS
after microwave digestion. The contents of trace metals were found to be in the
range of 1.0~5.2 g/g, 0.25~1.10 g/g, 0.18~1.21 g/g, 1.1~24.2 g/g,17.6~32.1
g/kg and 10.9~21.2 g/kg for Fe, Cu, Mn, Zn, Pb and Cd, respectively (Tzen,
2005).
In another study carried out with vinegar, after weighting (0.5-1.0 g) and
mixing with 10 mL of nitric acid, samples were digested first at 50oC for 2-3
hours and then, at 90oC to dryness. Cooled digests were dissolved in 1 M nitric
acid and then, analyzed for their lead concentration by GFAAS or ICP-MS
(Ndungu et al, 2004).It is known that fruit juices contain trace metals. Therefore, the trace metal
contribution of juices should be considered; however, literature survey has
revealed that less attention was paid to their determination in fruit juices. In a
study with fruit juices, the samples were weighed about 10.0 g into the Teflon
PFA digestion vessels and 10 mL ultrapure nitric acid and 2 mL ultrapure
concentrated H2SO4 was added. Then, microwave digestion procedure given in
Table 1.3 was applied. Finally, the vessels were cooled for 5 minutes and dilutedto 100 mL with ultrapure water (K.W. Barnes, 1999).
Table 1.3 Microwave digestion procesures of fruit juice samples
Parameter Stage 1 Stage 2 Stage 3 Stage 4 Stage 5
Power (%) 10 20 0 15 0
Power (watt) 51 141 0 96 0
Pressure (psi) 20 50 20 80 0
Run Time (min) 2 5 2 15 5
Canned fruit juice samples were stored at almost idential conditions similar
to shops. In a study with canned fruit juices, 300 mL of the liquid samples was
heated in evaporating dish on a regulated hot plate. The caramelous mass was
formed in most cases was than digested with a mixture of perchloric and nitric
acid. The digest was diluted to 25 mL mark using 1 M nitric acid. The sample
solutions were subsequently analyzed for the metals using a GFAAS equipped
with D2 background correction devices (Chukwujindu et al, 2008).
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A multi-metal Standard solution of nine metals was prepared to give the
following concentrations: Cu 1.0 ppm, Zn 0.2 ppm, Ni 0.2 ppm, Cr 0.2 ppm, Mn
0.05 ppm, Pd 0.5 ppm, Cd 0.5 ppm, Co 0.2 ppm, Sn 0.2 ppm. In fruit juices, large
particles were first removed by centrifuging and interference from sugar was
compensated for by using standard method of additions. Fruit juices were
centrifuged for 15 min at 4,500 rpm to obtain pulp free liquid. Aliquots 0, 1, 2 and
3 ml of the multi-metal standard solution were added to 100 ml volumetric flasks
containing 3, 2, 1 and 0 ml of distilled water respectively and diluted to 100 ml
with clear juice. The prepared samples were aspirated directly into the atomic
absorption spectrophotometer. Carbonated beverages were analysed after the
removal of carbon (IV) oxide by aeration. Four 100 ml aliquot of carbonated
drinks were pipetted into 250 ml beakers containing 0, 1, 2 and 3 ml of multi-
metal standard solution respectively. After heating on a hot plate until the volume
was reduced to 75 ml, the samples were cooled and diluted to 100 ml and the
prepared samples were aspirated directly into the spectrophotometer (Williams et
al, 2007).
The fruit samples were cleaned, peeled (if necessary) and washed to obtain
edible parts prior to analysis, then homogenized. Samples were weighed (10-50 g)
in quartz crucibles, dried at 105C for 24 hours and subsequently ashed in a
muffle furnace at 400C. The juice samples (100 ml) were poured into quartz
crucibles and evaporated to dry residue at 100C, then ashed in a muffle furnace
like the fruit samples. Ash was dissolved in 1mol/l nitric acid and filled up in 50
ml volumetric flasks to the mark by the same acid. The content of Pb and Cd in
the mineralised sample was determined after extraction of the complexes with
APDC (1-pyrrolidindithiocarbamate ammonium) to MIBK (methyl-
isobuthylketon) phase using the flame atomic absorption spectrometry (F-AAS)
method. The content of Zn and Cu in the diluted sample solutions was determined
by the same method . All the instrumental conditions applied for metal
determinations were set in accordance to the general recommendations
(wavelengths for Pb, Cd, Zn and Cu: 283.3 nm, 228.8 nm, 213.9 nm and 324.8
nm, respectively) (Krejpcio et al, 2004).
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1.4. The aim of the Thesis
In this study, it was planned to develop a method for revealing the adultery
in food samples namely fruit juices, honey, grape syrups and vinegar. For this
purpose, ICP-MS measurements were used to find a pattern to help todiscriminate the real and fake samples. This is a part of a main project together
with the 13C measurements of these sugar containing foods. Overall results will
overlook the average composition of these foods for deciding any adultery.
In the course of the study, the comparison of the sample preparation
techniques and validation of the methods was also planned. Next section describes
the fundamentals of the analytical methods used in the thesis study.
1.5. ICP-MS
Inductively Coupled Plasma Mass Spectrometry (ICP-MS) is an analytical
technique used for elemental determinations. The technique was commercially
introduced in 1983 and has gained general acceptance in many types of
laboratories. ICP-MS has many advantages over other elemental analysis
techniques such as atomic absorption and optical emission spectrometry,
including ICP Atomic Emission Spectroscopy (ICP-AES), including: detection
limits for most elements equal to or better than those obtained by GFAAS, higher
throughput than GFAAS, the ability to handle both simple and complex matrices
with a minimum of matrix interferences due to the high-temperature of the ICP
source, superior detection capability than ICP-AES with the same sample
throughput and finally, the ability to obtain isotopic information.
An ICP-MS combines a high-temperature ICP (Inductively Coupled
Plasma) source with a mass spectrometer. The ICP source converts the atoms of
the elements in the sample to ions. The ICP-MS instrument employs plasma as the
ionization source and a mass spectrometer analyzer to detect the ions produced. It
can simultaneously measure most elements in the periodic table and determine
analyte concentration down to the sub nanogram-per-liter (ng/L) or part-per
trillion (ppt) levels. It can perform qualitative, semi quantitative, and quantitative
analysis, and since it employs a mass analyzer, it can also measure isotopic ratios.
Figure 1.1 shows the main components of the ICP-MS system.
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Figure 1.1 Schematic representation of an ICP-MS (Agilent Technologies).
ICP-MS has many applications in food science and is used in the analysis of
a wide range of samples in the plough to plate food chain. Samples analyzed by
plasma spectrometry can vary from the relatively simple and well defined, for
example a single fruit or vegetable, through to complex, highly processed whole
meals, diets, digesta, excreta or other biological samples. The establishment of
routine automated analytical methods using ICP-MS have permitted multi-
element measurements of most elements in the Periodic Table (S. J. Hill, 2007).
1.5.1 Sample introduction
The first step in analysis is the introduction of the sample. This has been
achieved in ICP-MS through a variety of means. The most common method is the
use of a nebulizer. This is a device which converts liquids into an aerosol, and that
aerosol can then be swept into the plasma to create the ions. Nebulizers work best
with simple liquid samples. However, there have been instances of their use withmore complex materials like slurry.
Many varieties of nebulizers have been coupled to ICP-MS, including
pneumatic, cross-flow, Babington, ultrasonic, and desolvating types. The aerosol
generated is often treated to limit it to only smallest droplets, commonly by means
of a double pass or cyclonic spray chamber. Use of auto samplers makes this
easier and faster.
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1.5.2 Transfer of ions into vacuum
The carrier gas (usually argon) is sent through the central channel and into
the very hot plasma. The sample is then exposed to radio frequency which
converts the gas into the plasma. The high temperature of the plasma is sufficientto cause a very large portion of the sample to form ions. This fraction of
ionization can approach 100% for some elements (e.g. sodium), but this is
dependent on the ionization potential.
A fraction of the formed ions passes through a ~1mm hole (sampler cone)
and then a ~0.4mm hole (skimmer cone). The purpose of which is to allow a
vacuum that is required by the mass spectrometer.
The vacuum is created and maintained by a series of pumps. The first stage
is usually based on a roughing pump, most commonly a standard rotary vane
pump. This removes most of the gas and typically reaches a pressure of around
133 Pa. Later stages have their vacuum generated by more powerful vacuum
systems, most often turbomolecular pumps. Older instruments may have used oil
diffusion pumps for high vacuum regions.
1.5.3 Ion optics
Before mass separation, a beam of positive ions has to be extracted from the
plasma and focused into the mass-analyzer. It is important to separate the ions
from UV photons, energetic neutrals and from any solid particles that may have
been carried into the instrument from the ICP. Traditionally, ICP-MS instruments
have used transmitting ion lens arrangements for this purpose. Examples include
the Einzel lens, the Barrel lens and Omega Lens. Another approach is to use ion
guides (quadrupoles, hexapoles, or octopoles) to guide the ions into mass analyzer
along a path away from the trajectory of photons or neutral particles. The primary
role of the ion lenses is to transfer and focus the ions efficiently into the mass
filter. Recently, a compound or multi lens ion optic, for efficient ion focusing
across, was introduced into the mass spectrometer in the sampling/scimming
process. If these reach the detector, the background noise will increase, and
detection limits will suffer. Off-axis omega lens on the instrument eliminates
neutral species, ensuring very low backgrounds, enabling sub-ppt detection limits
for most elements.
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1.5.4 Octopole Reaction System (ORS)
The ORS features an off-axis reaction cell, which effectively removes
spectral interferences in most complex sample matrices. In order to analyze the
complicated and heterogeneous samples that can cause problems with
conventional instruments, the ORS-ICP-MS has been designed specifically to
handle high matrices and elements suffering from significant Ar-based (plasma
based) interferences such as Fe, Se, As etc. The ORS consists of an octopole ion
guide, mounted off-axis to minimize random background levels, inside a cell that
can be pressurized with a reaction gas (usually H2 or He).
Difficult polyatomic interferences such as Ar2, ArCl and MAr are
dissociated by collisions with the reaction gas within the cell, enabling otherwise
interfering analytes to be determined. Because the ORS employs simple reaction
gases, side reactions that would create new, unpredictable interferences are
eliminated, and the ORS can be operated in passive mode without a mass-filter.
1.5.5 Plasma
The plasma used in an ICP-MS is made by ionizing argon gas (Ar Ar+ +
e-). The energy required for this reaction is obtained by pulsing an electrical
current in wires that surround the argon gas. A complete description of plasma
generation is given in the following section. After injecting the sample, the
plasma's extreme temperature causes the sample to separate into individual atoms
(atomization). Next, the plasma ionizes these atoms (M M+ + e-) so that they
can be detected by the mass spectrometer.
1.5.6 Plasma Generation
An inductively coupled plasma (ICP) is sustained in a torch that consists of
three concentric tubes, usually made of quartz. The end of this torch is placed
inside an induction coil supplied with a radio-frequency electric current. A flow of
argon gas (usually 14 to 18 L/min) is introduced between the two outermost tubes
of the torch and an electrical spark is applied for a short time to introduce free
electrons into the gas stream. These electrons interact with the radio-frequency
magnetic field of the induction coil and are accelerated first in one direction, then
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the other, as the field changes at high frequency (usually 27.12 million cycles per
second).
The accelerated electrons collide with argon atoms, and sometimes a
collision causes an argon atom to part with one of its electrons. The releasedelectron is in turn accelerated by the rapidly-changing magnetic field. The process
continues until the rate of release of new electrons in collisions is balanced by the
rate of recombination of electrons with argon ions (atoms that have lost an
electron). This produces a fireball that consists mostly of argon atoms with a
rather small fraction of free electrons and argon ions.
1.5.7 Advantage of Argon
Making the plasma from argon has several advantages. First, argon is
abundant and therefore cheaper than other noble gases. Argon also has a higher
first ionization potential than all other elements except He, F, and Ne. Because of
this high ionization energy, the reaction (Ar+ + e- Ar) is more energetically
favorable than the reaction (M+ + e- M). This ensures that the sample remains
ionized (as M+) so that the mass spectrometer can detect it.
Argon can be purchased for use with the ICP-MS in either a refrigerated
liquid or a gas form. However it is important to note that whichever form of argon
purchased, it should have a guaranteed purity of 99.9% Argon at a minimum. It is
important to determine which type of argon will be best suited for the specific
situation. Liquid argon is typically cheaper and can be stored in a greater quantity
as opposed to the gas form, which is more expensive and takes up more tank
space.
If the instrument will be in an environment where it will get infrequent use,
then buying argon in the gas state will be most appropriate as it will be more than
enough to suit smaller run times and will remain stable for longer periods of time,
whereas liquid argon will suffer loss to the environment due to venting of the tank
when stored over extended time frames. However if ICP-MS will be used
routinely, then going with liquid argon will be the most suitable. If there are to be
multiple ICP-MS instruments running for long periods of time, then it will most
likely be beneficial for the laboratory to install a bulk or micro bulk argon tank
which will be maintained by a gas supply company, thus eliminating the need to
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change out tanks frequently as well as minimizing loss of argon that is left over in
each used tank as well as down time for tank changeover.
1.5.8 Elemental analysis
The ICP-MS allows determination of elements with atomic mass ranges 7 to
250. This encompasses Li to U. Some masses are prohibited such as 40 due to the
abundance of argon in the sample. Other blocked regions may include mass 80
(due to the argon dimer), and mass 56 (due to ArO), the latter of which greatly
hinders Fe analysis unless the instrumentation is fitted with a reaction chamber.
A typical ICP-MS will be able to detect in the region of ng/L to 10 or 100
mg/L or around 8 orders of magnitude of concentration units. Unlike atomic
absorption spectroscopy, which can only measure a single element at a time ICP-
MS has the capability to scan for all elements simultaneously. This allows rapid
sample processing.
Although ICP-MS and ICP-AES are powerful techniques, care is still
needed to ensure adequate quality control when performing measurements over a
wide concentration range and a thorough evaluation of the accuracy and precision
may be required for each element. Consequently, it can take considerable effort to
develop robust methods which account for all possible matrix and any associated
interferences while still being able to take advantage of the speed and sensitivity
offered by the approach.
Additionally, large amounts of data can be generated (including isotopic
information in ICP-MS) which require careful processing and such procedures can
be very time-consuming. Regardless of the type of matrix, analysis of the samples
most frequently encountered in food science can be considered in a number of
discrete stages, namely sample collection and storage, preparation, pre-treatment,
quantification, quality control and reporting (S. J. Hill, 2007).
1.6 Microwave Digestion
Microwave ovens began to find widespread use in chemical laboratories in
the late 1980s. The use of laboratory microwave units has become increasingly
popular because of the significant improvement in chemical reaction rates that are
possible using microwave radiation. The aim of all digestion methods is totransfer the element(s) of interest into the final solution quantitatively and
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efficiently, preferably with total decomposition of the bulk matrix and removal of
potentially interfering species (S. J. Hill, 2007).
As a rule, acid digestion procedures are employed for the determination of
elements in solids subsequent to sampling and mechanical sample preparation inorder to completely transfer the analytes into solution so that they can be
introduced into the determination step (e.g., ICP-AES, ICP-MS, AAS or
polarography) in liquid form.
The goal of every digestion process is therefore the complete solution of the
analytes and the complete decomposition of the solid (matrix) while avoiding loss
or contamination of the analyte. A typical microwave acid digestion can be
completed in a matter of minutes, whereas the same conventional hot platedigestion can take hours. Microwave digestion usually involves placing a sample
in an acid solution and heating to high temperatures and pressures. These extreme
conditions will dissolve most materials, but is potentially hazardous. The goals of
microwave digestion techniques are; complete solution of the elements, complete
decomposition of the matrix, avoiding losses and contamination, reduction of
handling and process times.
For technicians, there is an additional need to ensure that the digestion is
safe, reproducible and simple, that is, that it can be performed without excessive
manual effort. Since sample preparation typically also consumes the largest share
of task time, this process also has economic significance.
1.6.1 Heating Mechanism
Liquids heat by two mechanism: dipole rotation and ionic conduction. Polar
molecules will tend to align their dipole moments with the microwave electric
field. Because the field is changing constantly, the molecules are rotated back and
forth, which causes them collide with other nearby molecules. Ions in solution
will tend to migrate in the presence of a microwave electric field. This migration
causes the ions to collide with other molecules. Heat is generated when molecules
or ions collide with nearby molecules or ions (Dean, 2004).
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Figure 1.2 Schematic of sample heating by microwaves
1.6.2 Open versus Closed Acid Digestion
Open acid digestions are performed either with a reflux system or in a
beaker on a laboratory hot plate. Common to both methods is the temperature
limitation as a consequence of the solutions boiling point and the risk of
contaminants from the air. Volatile elements such as mercury may be lost during
the digestion times of, typically 2-15 hours.
The temperature limitation can be overcome by working with a closed
pressure vessel. This rise in pressure results in a dramatic increase in the reaction
kinetics allowing acid digestions to be carried out in a matter of hours or, if
microwave heating is employed, in 20-40 minutes. However, this also makes it
clear that the temperature represents what is actually the most significant reaction
parameter. It is the ultimate determinant of the digestion quality, but also results
in a pressure increase in the vessel and therefore in a potential safety hazard.
Therefore, the pressure must ultimately also be considered.
(a) Hot plate (b) Closed vessel microwave digestionFigure 1.3 Schematic representations of sample digestion systems
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The advantage of closed procedure in comparison with open digestion in a
recycling device or with the traditional hot plate lies in the significantly higher
working temperatures which can be achieved. While operating temperatures in
open systems are limited by the boiling point of the acid solution, closed digestion
vessels typically allow temperatures in the range of 200-260oC to be reached. This
results in a dramatic increase in the reaction kinetics, allowing digestions to be
carried out in hours.
However, this also makes it clear that the temperature represents what is
actually the most significant reaction parameter. It is the ultimate determinant of
the digestion quality, but also result in pressure increase in the vessel and
therefore in potential safety hazard. Therefore, the pressure must ultimately alsobe considered.
1.7 Method Validation
Methods validation is the process of demonstrating that analytical
procedures are suitable for their intended use. The methods validation process for
analytical procedures begins with the planned and systematic collection by the
applicant of the validation data to support analytical procedures (Bliesner, 2006).
Fundamental terms of validation are given below;
Linearity: The linearity of an analytical method is its ability to elicit test
results that are directly proportional to the concentration of analytes in samples
within a given range or proportional by means of well-defined mathematical
transformations. Linearity may be demonstrated directly on the test substance (by
dilution of a standard stock solution) and/or by using separate weighing of
synthetic mixtures of the test product components, using the proposed procedure.
Linearity is determined by a series of 3 to 6 injections of 5 or more
standards whose concentrations span 80120 percent of the expected
concentration range. The response should be directly proportional to the
concentrations of the analytes or proportional by means of a well-defined
mathematical calculation. A linear regression equation applied to the results
should have an intercept not significantly different from 0. If a significant nonzero
intercept is obtained, it should be demonstrated that this has no effect on the
accuracy of the method.
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Repeatability is the variation experienced by a single analyst on a single
instrument. Repeatability does not distinguish between variation from the
instrument or system alone and from the sample preparation process. During the
validation, repeatability is performed by analyzing multiple replicates of an assay
composite sample by using the analytical method.
Limits of Detection and Quantification: The detection limit (DL) or limit
of detection (LOD) is the point at which a measured value is larger than the
uncertainty associated with it. It is the lowest concentration of analyte in a sample
that can be detected but not necessarily quantified. The limit of detection is
frequently confused with the sensitivity of the method. The sensitivity of an
analytical method is the capability of the method to discriminate small differencesin concentration or mass of the test analyte. In practical terms, sensitivity is the
slope of the calibration curve that is obtained by plotting the response against the
analyte concentration or mass.
The quantization limit (QL) or limit of quantization (LOQ) of an individual
analytical procedure is the lowest amount of analyte in a sample that can be
quantitatively determined with suitable precision and accuracy. The quantization
limit is a parameter of quantitative assays for low concentrations of compounds insample matrices and is used particularly for the determination of impurities. It is
usually expressed as the concentration of analyte in the sample.
The LOD and LOQ were determined on the basis of signal-to-noise ratio,
and formulated below where cminis the minimum concentration of the calibration
series, S (b): The signal count of the blank sample, S (s): The signal count of the
sample that known concentration;
)()(3 min
sSbScLOD =
)(
)(10 minsS
bScLOQ
=
Accuracy and Recovery:The accuracy of an analytical method is the extent
to which test results generated by the method and the true value agree. Accuracy
can also be described as the closeness of agreement between the value that is
adopted, either as a conventional, true or accepted reference value, and the valuefound.
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The true value for accuracy assessment can be obtained in several ways.
One alternative is to compare the results of the method with results from an
established reference method. This approach assumes that the uncertainty of the
reference method is known. Secondly, accuracy can be assessed by analyzing a
sample with known concentrations (e.g., a control sample or certified reference
material) and comparing the measured value with the true value as supplied with
the material. If certified reference materials or control samples are not available, a
blank sample matrix of interest can be spiked with a known concentration by
weight or volume.
After extraction of the analyte from the matrix and injection into the
analytical instrument, its recovery can be determined by comparing the responseof the extract with the response of the reference material dissolved in a pure
solvent. Because this accuracy assessment measures the effectiveness of sample
preparation, care should be taken to mimic the actual sample preparation as
closely as possible. If validated correctly, the recovery factor determined for
different concentrations can be used to correct the final results.
Uncertainty: In metrology, measurement uncertainty describes a region
about an observed value of a physical quantity, also called a measurand, which islikely to enclose the true value of that quantity. Uncertainty of a method
associated with the result of a measurement that characterizes the dispersion of the
values that could reasonably be attributed to the measurand. Assessing and
reporting measurement uncertainty is fundamental in chemistry.
In practice the uncertainty on the result may arise from many possible
sources, including examples such as incomplete definition, sampling, matrix
effects and interferences, environmental conditions, uncertainties of weights andvolumetric equipment, reference values, approximations and assumptions
incorporated in the measurement method and procedure, and random variation.
The measurement uncertainty tells us what size the measurement error mightbe.
The basis for the evaluation is a measurement and statistical approach, where the
different uncertainty sources are estimated and combined into a single value.
Basis for the estimation of measurement uncertainty is the existing knowledge.
Existing experimental data should be used quality control charts, validation,interlaboratory comparisons, CRM etc.
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EXPERIMENTAL
2.1 Apparatus
Agilent 7500ce ICP-MS system was used throughout the experiments.
Samples were digested in microwave oven (CEM Mars 5) prior to the analysis.
2.2 Chemicals and Reagents
Nitric acid (ultrapure) was supplied from Fluka. Water was obtained using a
USF Purelab and Millipore Elix & Rios Systems combined Milli-Q Synthesis
System, including UV radiation and ultra filtration units.
Standard solution of Fe, K, Ca, Na, Mg, Ag, As, Ba, Cd, Co, Cr, Cu, Hg,
Mn, Ni, Pb, Sb, Se, Tl, V, Zn (environmental calibration standard and multielement calibration standard) was purchased from Agilent. Internal standard mix
(Li, Sc, Y, Ge, In) was also purchased from Agilent. Tin standard was purchased
from High Purity Standard and boron standard solution puchased from JT Baker.
Stock solutions of elements prepared in 5% of HNO3 and 2% of HCl with
deionized water. Standard solutions were prepared weekly by diluting stock
solutions in 2% of nitric acid and 1% of HCl.
Juices, vinegars, grape syrups and honey samples were collected fromvaious locations of Turkey and their 13C and sugar component analysis were
performed before their heavy metal analysis done. The samples known with their
natural origin were analyzed as their trace metal content. The fraud samples of
apple juice and pear juice could not be encountered. So their fraudulent samples
were prepared by adding fructose syrup and then analysed.
2.3 Analytical procedures and ICP-MS conditions
Sample preparation procedures are given below.
Step 1: Weight 0.3 g juice into Teflon PFA vessels.
Step 2: Add 5 mL HNO3 to the sample and cap the vessel.
Step 3: Digest following the procedure juice 1 in Table 2.1
Step 4: Cool for approximately 5 minutes and vent vessels.
Step 5: Transfer the samples into clean, acid washed volumetric flasks and dilute
to 30 mL with 18 M, distilled, ultrapure water.
Step 6: Transfer the samples into clean polyethylene bottles.
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Table 2.1. Microwave digestion procedure
Heating Program: Ramp to Temperature
Stage Max.Power (W)
% Power Ramp(min)
Pressure(psi)
Temperature(oC)
Hold (min)
1 600* 100 30:00 N.A 210 5:00* Power should be adjusted up or down with respect to the number of vessels. General guidelinesare as follows: 1-2 vessels (300 W), 3-6 vessels (600 W), 7 or more vessels (1200 W).
The optimized ICP-MS conditions are given in Table 2.2.
Table 2.2 Optimized conditions for ICP-MS system
Plasma conditions Ion Lenses Octopole Parametres
RF Power 1500 W Extract 1 -54.9 V Octp RF 180 V
RF Matching 1.8 V Extract 2 -120 V OCTP Bias -6 V
Sample Depth 8 mm Omega Bias -30 V Reaction Cell
Carrier Gas 0.91 L/min Omega Lens 0.2 V Reaction Mode On
Make up Gas 0.17 L/min Cell Entrance -20 V H2 Gas 0 mL/min
Nebulizer Pump 0.08 rps QP focus 5 V He Gas 1 mL/min
S/C temperature 2 oC Cell Exit -28 V Ar Gas 15 mL/min
Isotopes of each element used in method validation studies and sample
analysis are listed in Table 2.3.
Table 2.3 Used isotopes of analyzed elements
Metal isotope Metal isotope Metal isotope
As 75 Cu 63 Ni 60
B 11 Fe 56 Pb 208
Ba 137 Hg 202 Sb 121
Ca 40 K 39 Se 82
Cd 111 Mg 24 Sn 118
Co 59 Mn 55 V 51
Cr 53 Na 23 Zn 66
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3. RESULTS AND DISCUSSION
3.1. Optimization Studies for Method Development
The optimization of the method was considered as mainly two parts; first
part is the optimization of sample preparation step and second part is the
optimization of the detection system, i.e. ICP-MS. In the first part the parameters
related with the microwave digestion system were considered namely the mass of
the sample, the volume of nitric acid and digestion temperature and time. The
parameters were tested by using CRM of fruit juice. As no reference material is
available for honey and grape syrup, the optimized conditions were also applied
for these types of samples.
Initial studies were conducted by adopting the sample weights
recommended in the manual however; the use of 2.5 g of sample mixed with 10
mL of nitric acid has resulted in a severe inner pressure problem which causes
vessel deterioration. Therefore, the sample weight was reduced to 0.3 g and mixed
with 3 mL of nitric acid for safer digestion which also gives consistent values with
former procedure. Table 3.1 summarizes the results obtained with ICP-MS
procedure given in Experimental Section.
Table 3.1 The effect of sample weight on the analysis by comparing the
metal content of the fruit juice sample
Certificated value (Fapas-T0776)
Cd(ng/mL)
Fe(g/mL)
Sn(g/mL)
Pb(ng/mL)
63.928.1 10.02.2 100.716.1 43.619.2
Sampleweight
Nitricacid
volume(mL)
Determined value
2.5 10 68.1 9.71 106.4 54.1
1.5 10 69.0 10.1 92.8 47.4
1.0 7 60.8 10.3 102.1 44.4
0.5 5 64.5 9.82 103.1 44.6
0.3 3 67.0 9.96 99.5 43.9
As can be followed from the table above, 0.3 g of sample can be used safely
without compromising and this amount was chosen for further studies. Other
parameters were digestion temperature and time. The effect of digestion
temperature can be seen in Table 3.2.
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Table 3.2 The comparison of the metal content of the fruit juice sample
digested at various temperatures
Certificated value(Fapas-T0776)
Cd(ng/mL) Fe(g/mL) Sn(g/mL) Pb(ng/mL)
63.928.1 10.02.2 100.716.1 43.619.2
Temp.oC
Determinedvalue
190 59.8 9.4 96.2 49.6
200 60.8 10.3 102.1 44.4
210 64.4 10.3 99.6 46.1
According to above results, digestion procedure at three different
temperature values have resulted similar metal ion contents without statistically
significant difference however, 210oC was selected for better digestion. The effect
of digestion time can be seen in Table 3.3.
Table 3.3 The comparison of the metal content of the fruit juice sample
digested at various time
Certificated value(Fapas-T0776)
Cd(ng/mL)
Fe(g/mL)
Sn(g/mL)
Pb(ng/mL)
63.928.1 10.02.2 100.716.1 43.619.2
Ramp
(min)
Hold
(min)
Determinedvalue
10:00 10:00 52.5 8.26 86.8 33.6
20:00 5:00 60.9 9.4 88.7 41.7
30:00 5:00 64.1 10.3 100.1 44.2
As can be seen from table the most accurate values obtained with 30 minute
ramping time and 5 minute hold time.
The second stage was ICP-MS parameters. An optimum mass detector
condition was conducted by using a tune solution that includes Li, Y, Ce, Tl and
Co. Medium concentration (10 ng/mL) of tune solution has been injected to mass
detector. In addition, during the optimization process the nebulizer flow, tourch
position, spray chamber temperature and ion lenses were optimized. The
optimized ICP-MS conditions were given in Experimental Section.
Typical ICP-MS results of Sc, V, Cr, Mn, Co, Ni, Cd, Cr, As, Mn, Cd, In,
Sb, Ba are given in Figure 3.1. The system is used in helium mode for this
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analysis. Zn, Ge, Hg, Bi are determined in no-gas mode and results are given in
Figure 3.2. Fe, Mg, K, Ca, Na can be detected in alkaline method and results are
given in Figure 3.3. These different methods were chosen according to the
manual.
Figure 3.1. Typical ICP-MS results of Sc, V, Cr, Mn, Co, Ni, Cd, Cr, As, Mn, Cd, In, Sb,Ba
Figure 3.2. Typical ICP-MS results of Zn, Ge, Hg, Bi
Figure 3.3. Typical ICP-MS results of Fe, Mg, K, Ca, Na
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3.2. Validation Studies
Under the optimized conditions given above, the validation of the method
was accomplished by determining the linearity, repeatability, reproducibility,
accuracy and the detection and quantification limits of the method. Uncertainty ofthe measurements was also calculated.
3.2.1 Linearity
For calibration studies, 17 metals studied were divided into two groups. The
first group includes Na, K, Fe, Mg and Ca and the calibration range is 0.100 to
2.500 mg/kg. The second group includes As, B, Ba, Cr, Cd, Co, Cu, Hg, Mn, Mo,
Ni, Sb, Se, Sn, Pb, V and Zn and the calibration range is 1.00 to 25.00 g/kg. The
MS response was found linear in these concentration ranges. The calibration
standards were prepared in acid mixture containing 2% HNO3 and 0.1% HCl.
The linearity of the metod was assessed with five standard injections to ICP-
MS as three replicates. Linearity was verified using the value of regression
coefficient, R2. The calibration curves and equations with regression coefficient
are given Table 3.4.
Table 3.4 Regression coefficients for metals studied from calibration curves
obtained with ICP-MS measurements
Metal R2 Metal R2 Metal R2
As 0.9998 Cu 0.9988 Ni 0.9999
B 0.9997 Fe 0.9999 Pb 0.9995
Ba 0.9997 Hg 0.9983 Sb 0.9998
Ca 0.9998 K 0.9999 Se 0.9995
Cd 0.9998 Mg 0.9999 Sn 0.9999
Co 0.9996 Mn 0.9994 V 0.9997
Cr 0.9997 Na 0.9999 Zn 0.9996
3.2.2. Repeatability
The injection repeatability was calculated by five replicated injections of
1.00 mg/L for the first group and 5.00 g/L for the second group standard
samples. Injection repeatability for individual components as RSD % can be seen
in Table 3.5.
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Table 3.5 Relative standard deviations of metals.
Metal RSD Metal RSD Metal RSD
As 1.2 Cu 1.6 Ni 1.5
B 2.6 Fe 0.5 Pb 3.2
Ba 3.1 Hg 3.7 Sb 2.3
Ca 0.4 K 4.6 Se 1.9
Cd 4.0 Mg 0.6 Sn 2.4
Co 2.1 Mn 2.2 V 2.0
Cr 3.0 Na 0.2 Zn 4.9
3.2.3. Sensitivity
The detection limits (LOD) and quantification limits (LOQ) were
determined on the basis of signal-to-noise ratio, LOQ and LOD for selected
metals for fruit juices matrices are listed in Table 3.6.
Table 3.6 LOD and LOQ values of metals (g/L)
Metal LOD LOQ Metal LOD LOQ Metal LOD LOQ
As
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3.2.5. Uncertainty
The uncertainty of measurement was calculated from quality control charts
of each element. The relative uncertainties are given in Table 3.8.
Table 3.7 Recovery percentages of the metals studied with ICP-MS
MetalLow Conc.
%Average Conc.
%High Conc.
%As 100 88 99
B 95 97 91
Ba 100 112 110
Ca 119 89 103
Cd 107 76 104
Co 93 77 98
Cr 95 80 105
Cu 110 103 101Fe 85 87 75
Hg 87 100 101
K 92 96 103
Mg 87 93 79
Mn 97 103 105
Na 91 81 81
Ni 97 88 104
Pb 103 92 98
Sb 96 103 106
Se 100 79 89Sn 98 86 93
V 100 87 117
Zn 86 91 84
Table.3.8 Relative uncertainty values of metals
Metal Uncertainty Metal Uncertainty Metal Uncertainty
As 0.08 Cu 0.25 Ni 0.32
B 0.24 Fe 0.23 Pb 0.16
Ba 0.34 Hg 0.22 Sb 0.27
Ca 0.40 K 0.32 Se 0.09
Cd 0.26 Mg 0.43 Sn 0.27
Co 0.16 Mn 0.66 V 0.16
Cr 0.16 Na 0.39 Zn 0.29
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3.3. Comparison of the Developed Method with Direct Injection
The method developed so far including microwave digestion and subsequent
ICP-MS measurements was compared with direct injection of simply diluted fruit
juices to the ICP-MS system. The table below shows the results of cherry andapricot juices with microwave digestion and direct injection to the ICP-MS
system.
Table 3.9 Comparison of the developed microwave digestion method with direct injection (mg/kg)
MetalMicrowave
(cherry)
Directinjection(cherry)
Microwave(appricot)
Directinjection(appricot)
As 0.072 0.022 0.035 0.006
B 16.22 10.95 9.98 8.71Ba 1.389 0.667 0.963 0.781
Ca 499.0 257.2 6743 365.5
Cd 0.017 0.002 0.010 0.001
Co 0.039 0.022 0.030 0.020
Cr 0.194 0.078 0.238 0.071
Cu 0.411 0.091 1.668 0.137
Fe 17.11 10.94 19.26 9.988
Hg 0.028 < LOQ 0.020 0.003
K 4418 2292 7290 4275
Mg 487.2 349.6 39.8 27.07
Mn 2.456 1.644 1.78 0.157
Na 132.2 48.83 86.49 68.95
Ni 0.756 0.456 0.973 0.127
Pb < LOD < LOD 0.020 0.020
Sb 0.067 0.004 0.025 0.004
Se 0.167 0.033 0.162 0.010
V 0.100 0.022 0.056 0.056Zn 3.583 2.156 3.448 0.963
It is evident from the table that there is a big gap between the results of two
methods. In the light of the data given above it can be clearly stated that digestion
method is required for and more reliable determination of the selected metal ions
in fruit juices. Further sections present the results obtained for several samples
including original and fake foodstuff.
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3.4. Application of the Method to the Samples
3.4.1. Vinegar Results
The metal compositions of vinegar made of grape and falsified samples
were given in Table 3.10.
Table 3.10 Metal compositions of grape vinegar (GV) and falsified alcohol vinegar (FAV) (mg/kg)
Metal GV FAV Metal GV FAV
As 0.012 0.017 Mg 83.12 13.04
Ba < LOD < LOD Mn 0.613 0.046
Ca 27.34 9.243 Na 187.9 7.738
Cd < LOD 0.005 Ni 0.019 0.021
Co < LOQ 0.040 Pb < LOD < LOD
Cr < LOD 0.007 Sb < LOD 0.007
Cu < LOD < LOD Se < LOD < LOD
Fe 2.750 0.559 V 0.050 0.023
Hg < LOD < LOD Zn < LOD < LOD
K 1281 347
Comparing to the results obtained for real and fake samples it can be clearly
said that the potassium, iron, calsium, magnesium, sodium and manganese valuesof grape vinegar is much more than its fake substitute. Therefore, the metal
composition of vinegar has a potential for establishing another parameter to detect
any fraud.
3.4.2. Grape Syrup Results
The metal compositions of nine grape syrups and a mulberry syrup are
given in Table 3.11. As can be seen from the table, similar results were obtained
for real and fake samples. Therefore it is hard to classify grape syrups according
to their metal compositions. But calcium, iron and potassium amounts of grape
syrup, harnup syrup and mulberry are substantially different from each other
indicating a possibility to distinguish the original samples.
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Table 3.11 Metal compositions of grape syrups, harnup and mulberry syrup (mg/kg)
As B Cd Co Cr Hg Ni Pb Sb V
Grape1 0.006 8.555 < LOD 0.031 < LOD < LOQ 0.367 < LOD 0.012 < LOD
Grape2 0.031 6.134 0.003 0.022 0.060 0.006 0.344 0.035 0.005 0.041
Grape3 0.075 8.146 0.003 0.026 0.114 0.006 0.246 0.008 0.004 0.056
Grape4 0.024 15.64 0.001 0.135 < LOD 0.048 0.472 0.026 0.006 0.003
Grape5 0.201 95.38 0.004 0.092 < LOD 0.009 0.472 0.025 0.021 < LOD
Grape6 0.189 46.33 0.003 0.089 < LOD 0.028 0.467 0.024 0.016 < LOD
Grape7 0.020 4.072 0.001 0.031 < LOD 0.014 0.217 0.008 0.004 < LOD
Grape8 0.021 8.156 0.003 0.038 < LOD < LOQ 0.346 0.025 0.012 < LOD
Grape9 0.019 11.14 0.001 0.025 < LOD 0.009 0.397 0.011 0.004 < LOD
Mean 0.065 22.62 0.002 0.054 0.019 < LOQ 0.370 0.018 0.009 0.011
Mullberry 0.114 91.95 0.002 0.057 0.007 < LOQ 0.671 0.045 0.011 < LOD
Harnup 0.062 45.71 0.003 0.037 < LOD 0.011 0.522 0.039 0.011 < LOD
Continued
Ba Ca Cu Fe K Mg Mn Na Se Zn
Grape1 0.396 373 0.452 16.95 4648 119.3 2.282 618.9 < LOD 0.888
Grape2 0.268 231 0.380 11.87 2841 114.6 1.702 401.1 0.018 0.902
Grape3 0.275 141 0.477 7.48 13050 1491 3.114 297.1 < LOD 0.338
Grape4 0.376 254 3.761 15.61 5068 498.6 3.362 475.5 0.020 2.916
Grape5 0.954 197 1.008 9.47 7237 271.5 3.380 155.7 0.008 1.226
Grape6 0.953 509 0.979 14.88 7085 427.3 3.352 996.1 0.005 1.193
Grape7 0.279 204 2.069 6.18 2229 113.3 1.003 683.9 0.006 0.508
Grape8 0.467 251 1.015 13.45 5168 496 3.626 568 0.006 2.246
Grape9 0.879 306 0.867 8.17 6158 298.1 3.915 601 0.011 1.216
Mean 0.539 274 1.223 11.56 4831 323.3 2.86 533 0.008 1.270Mullberry 0.918 130 0.394 35.71 11450 483 4.169 386 0.015 1.330
Harnup 1.151 352 2.329 28.91 8928 387.6 7.426 332.2 0.017 4.936
As you can see from the table above, the iron, barium and manganese
results of harnup and mulberry molasses are different from the values of grape
syrups. Figure 3.3, 3.4 and 3.5 gives the schematic representation of results above.
The upper and lower limits show the standard deviations of nine grape syrups.
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Figure 3.4. Schematic representation of barium results of grape syrups, mulberry andharnup syrups.
Figure 3.5. Schematic representation of iron results of grape syrups, mulberry and harnupsyrups
Figure 3.6. Schematic representation of manganese results of grape syrups, mulberry andharnup syrups
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3.4.3. Fruit Juice Results
The metal composition of pear juices are given in Table 3.12.
Table 3.12. Metal compositions of pear juices (mg/kg)
As B Cd Co Cr Hg Ni Pb Sb V
pear1 0.032 2.35 0.001 0.011 < LOQ < LOD 0.027 0.002 0.880 0.066
pear2 0.082 2.35 0.001 0.009 < LOQ 0.001 0.044 0.030 1.613 < LOQ
pear3 < LOQ 1.04 0.001 0.009 0.020 0.001 0.036 0.015 < LOD 0.004
pe