Faculty of Bioscience engineering

Academic year 2015 – 2016

Biogenic amines in food products on the Belgian market

Lisa Miclotte

Promotoren: Prof. dr. ir. Liesbeth Jacxsens & Frank Devlieghere

Tutor: Markus Eriksson

Master thesis submitted in partial fulfillment of the requirements for the

degree of Master of Science in bio-engineering - Food Science and

Nutrition

ACKNOWLEDGEMENTS

At the start of this master thesis, I was still a full blown student, in the sense that I knew how to

decipher courses and how to make sure I controlled the material completely by the time the exams

began. During the past year, however, I've had to learn to do so much more than to study courses.

This master thesis taught me so many aspects of what it means to be a researcher and it gave me a

glimpse of what an adult’s working life looks like. I have grown in so many different ways during the

course of this master thesis and have come into contact with so many expertized people, to whom I

owe my thanks.

First of all, I wish to thank my promotor professor Liesbeth Jacxsens, who has been a competent

mentor with great expertise in terms of risk assessment and food safety. She proposed the structure

of this thesis, gave constructive pieces of advice concerning lab experiments, presentations and

reporting and was always present to answer questions and give feedback on my writings. Equally, I

wish to thank professor Frank Devlieghere and Bruno Demeulenaere for their support of this project

and their fruitful cooperation.

Special and explicit thanks also to my tutor Markus Eriksson, who has been a more than competent

mentor and partner in the lab and whom I could always turn to for advice. I would always receive

more detailed explanations than I could ever have hoped or wished for. On the other hand, working

together in the lab frequently turned into tease and laughter, making it an enjoyable experience for

me and even my fellow thesis students. I consider you as a friend, Markus, and I wish you the best

with your new job, your wife and your soon-to-be-born first child.

I would also like to thank Emmanuel Abatih for lending me his time and his expertise in the field of

statistical analysis using R. Our frequent meetings at the close of this thesis resulted in valuable

outcomes, without which my dissertation would not have been complete. Moreover, his calm and

friendly character and his multicultural approach of work and life have resulted into very pleasant

conversations. Thank you, Emmanuel.

Furthermore, I also thank all members of staff in the chemical and microbial lab for their patience

with the clumsiness that is typical of all thesis students, for their help in finding lab materials, for

their advice and for the many interesting conversations, which were always proof of their support.

And lastly, I thank my friends and family for their continuous support throughout this year. They

listened to my nagging and my joys, they advised me where they could and encouraged me in all my

endeavours, within and outside of this thesis. Moreover, I thank my parents for making this 5-year

journey of study possible by supporting me both financially and morally. I can never thank them

enough.

Table of contents LIST OF ABREVIATIONS ............................................................................................................................. i

GLOSSARY .................................................................................................................................................ii

SUMMARY ................................................................................................................................................ v

SAMENVATTING ..................................................................................................................................... vii

1. INTRODUCTION ............................................................................................................................... 1

2. LITERATURE STUDY .......................................................................................................................... 4

2.1 BIOGENIC AMINES ................................................................................................................... 4

2.1.1 Occurrence in food .......................................................................................................... 4

2.1.2 Production by microorganisms........................................................................................ 5

2.1.3 Detection methods .......................................................................................................... 6

2.2 TOXICOLOGY ............................................................................................................................ 6

2.2.1 General ............................................................................................................................ 6

2.2.2 Detoxification .................................................................................................................. 6

2.2.3 Histamine ......................................................................................................................... 7

2.2.4 Tyramine and trace amines ............................................................................................. 8

2.2.5 Putrescine, cadaverine and polyamines .......................................................................... 9

2.3 QUALITY INDICATOR .............................................................................................................. 11

2.4 FORMATION OF EXOGENIC BIOGENIC AMINES .................................................................... 12

2.4.1 Substrate availability ..................................................................................................... 12

2.4.2 Presence of microorganisms ......................................................................................... 13

2.5 Conditions affecting MO-growth, decarboxylase production and decarboxylase activity ... 13

2.5.1 Temperature .................................................................................................................. 13

2.5.2 pH .................................................................................................................................. 14

2.5.3 Other factors ................................................................................................................. 14

2.6 CONTROL OF BA-CONTENTS .................................................................................................. 15

2.6.1 Raw material handling ................................................................................................... 16

2.6.2 Fermentation process.................................................................................................... 16

2.7 EXPOSURE AND RISK ASSESSMENT ....................................................................................... 17

3. MATERIALS AND METHODS .......................................................................................................... 20

3.1 EXPERIMENTAL OUTLINE ....................................................................................................... 20

3.1.1 Storage tests .................................................................................................................. 20

3.1.2 Screening tests .............................................................................................................. 21

3.2 EXPERIMENTAL ANALYSES ..................................................................................................... 23

3.2.1 Free amino acids ............................................................................................................ 23

3.2.2 Biogenic amines ............................................................................................................. 25

3.2.3 Microbiology .................................................................................................................. 28

3.3 STATISTICAL ANALYSES .......................................................................................................... 30

3.3.1 Objectives ...................................................................................................................... 30

3.3.2 Preparation of the database.......................................................................................... 30

3.3.3 Part 1: T-tests fermented vs. non-fermented and animal vs. plants ............................ 31

3.3.4 Part 2: ANOVA-tests for difference between food groups ............................................ 32

3.3.5 Part 3: Correlation analysis ............................................................................................ 32

4. RESULTS AND DISCUSSION ............................................................................................................ 34

4.1 INTRODUCTION ..................................................................................................................... 34

4.2 POTENTIAL FOR BA-FORMATION IN TUNA AND MARINATED PORK .................................... 35

4.2.1 Storage test tuna ........................................................................................................... 36

4.2.2 Storage test marinated pork ......................................................................................... 39

4.3 STORAGE TEST OF DIFFERENT TYPES OF MARINATED MEAT................................................ 43

4.4 SCREENING OF MEAT PRODUCTS AND PREPARATIONS FROM THE BELGIAN MARKET........ 47

4.4.1 Salami and dried sausages ............................................................................................. 47

4.4.2 Cooked hams ................................................................................................................. 50

4.4.3 Raw hams (dried and cured) ......................................................................................... 52

4.4.4 Meat preparations ......................................................................................................... 54

4.4.5 Concluding remarks on fresh meat, meat preparations and meat products ................ 56

4.5 DESCRIPTION OF BA-DATA ASSEMBLED FOR OTHER FOOD GROUPS ................................... 56

4.5.1 Fruit and vegetables ...................................................................................................... 57

4.5.2 Chocolate ....................................................................................................................... 57

4.5.3 Beer ............................................................................................................................... 57

4.5.4 Meat products and preparations .................................................................................. 58

4.5.5 Dairy .............................................................................................................................. 58

4.6 STATISTICAL ANALYSIS ........................................................................................................... 59

4.6.1 PART 1: T-tests fermented vs. non-fermented and animal vs. plants ........................... 59

4.6.2 PART 2: ANOVA-tests for difference between food groups .......................................... 61

4.6.3 PART 3: Correlation analysis .......................................................................................... 64

5. CONCLUSIONS ............................................................................................................................... 67

6. FUTURE INVESTIGATIONS .............................................................................................................. 69

7. REFERENCES .................................................................................................................................. 70

8. APPENDICES ................................................................................................................................... 74

Appendix 1: Design of the 9-day storage test for marinated pork................................................ 74

Appendix 2: Design of the 9-day storage test for 3 types of marinated meat, stored at 7°C and

MAP-packaged (70/30 O2/CO2). .................................................................................................... 74

Appendix 3: Reagents used during the chemical analyses. ........................................................... 75

Appendix 4: Materials and Machines used for the chemical analyses. ........................................ 76

Appendix 5: Tables required during the calculation of the BA-concentrations. ........................... 77

Appendix 6: Materials used during the microbial analyses. ......................................................... 78

Appendix 7: Pictures of tuna samples during 6-day storage test. ................................................. 80

Appendix 8: BA-concentrations on the last day of analysis of the storage test for marinated

pork:. Mean values of the two samples on the last day of analysis for each condition and each

BA are plotted. .............................................................................................................................. 82

Appendix 9: Pictures of marinated pork during the 9-day storage test. ....................................... 83

Appendix 10: Results of the screening tests on salami’s and dried sausages. .............................. 85

Appendix 11: Results of the screening tests on cooked hams. ..................................................... 87

Appendix 12: Results of the screening tests on raw dried and cured hams and beef products. .. 90

Appendix 13: Results of the screening tests on meat preparations. ............................................ 93

Appendix 14: Preparation methods of cooked and raw dried and cured ham samples as

designated on the package. .......................................................................................................... 97

Appendix 15: Overview of the BA-concentrations in different food groups and their subgroups.

....................................................................................................................................................... 99

Appendix 16: Box-plots of BA-concentrations belonging to Part 1 of the statistical analysis. ... 107

Appendix 17: Tables representing the p-values resulting from the mean comparisons (ANOVA) of

the BA-concentrations in the different food groups. .................................................................. 112

Appendix 18: Correlation triplots resulting from redundancy analyses (RDA) executed to analyze

the correlations between BA, FAA and microbial concentrations. ............................................. 115

Appendix 19: Results of the multiple linear regressions (MLR) executed during the analysis of the

correlations between FAA, BA and microbial counts. ................................................................. 123

i

LIST OF ABREVIATIONS

AA Amino acids

ACN Acetonitrile

AO Amino oxidase

BA Biogenic amines

BAI Biogenic amine indicator

CCP Critical control point

CE Capillary Elektrophoresis

DAO Diamino oxidase

FAA Free aminoacids

FSMS Food Safety Management System

GC Gas Chromatography

GHP Good Hygiene Practices

Gr +/- Gram positive /negative

GMP Good Manufacturing Practices

HACCP Hazard Analysis Critical Control Points

HPLC High Pressure Liquid Chromatography

LOD Limit Of Detection

LOQ Limit Of Quantification

MAO Monoamine oxidase

MAOI Monoamine oxidase inhibitors

MAP Modified atmosphere packaging

MLR Multiple linear regression

MO Microorganisms

MRS De Mann, Rogosa and Sharpe agar

MSA Mannitol Salt Agar

NOAEL No Observable Adverse Effect Level

OPA Ortho-Phtalic aldehyde

PA Pseudomonas Agar

PCA Plate Count Agar

PRP Prerequisite Program

RDA Redundancy analysis

RE Rapid Enterobacteriaceae agar

SB Slanetz and Bartley agar

SMS Safety management system

TLC Thin Layer Chromatography

VRBG Violet Red Bile Glucose agar

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GLOSSARY

24h-recall

Quantitative research method used in nutritional assessment in the form of an interview, in which individuals are asked to recall all foods and beverages they consumed in the twenty-four hours prior to the interview. It may be self-administered or administered by a trained professional.

Aminogenic Generating amino acids

Arrhythmia Cardiac arrhythmia is group of conditions in which the heartbeat is irregular, too fast, or too slow. It originates from a change from the normal sequence of electrical impulses.

Brachycardia A form of cardiac arrhythmia, in which the heartbeat is too slow (less than 60 beats per minute).

Brain hemorrhage A brain hemorrhage or cerebral hemorrhage is a type of stroke. It is caused by an artery in the brain bursting and causing localized bleeding in the surrounding tissues. This bleeding kills brain cells (= hemorrhagic stroke).

Bronchospasm Abnormal contraction of the smooth muscle of the bronchi, resulting in an acute narrowing and obstruction of the respiratory airways, which causes difficulty to breathe.

Catecholamines Organic compound containing a catechol (benzene with two hydroxyl side groups) and a side-chain amine. Examples are epinephrine (adrenaline), norepinephrine (noradrenaline), and dopamine, all of which are produced from phenylalanine and tyrosine

Cell proliferation The process that results in an increase of the number of cells, and is defined by the balance between cell divisions and cell loss through cell death or differentiation. Cell proliferation is increased in tumours.

Crohn's disease Crohn's disease is an inflammatory bowel disease (IBD). It causes inflammation of the lining of your digestive tract, which can lead to abdominal pain, severe diarrhoea, fatigue, weight loss and malnutrition. Inflammation caused by Crohn's disease can involve different areas of the digestive tract in different people.

Endogenous Originating or produced within an organism, tissue,or cell: endogenous hormones.

Exogenous Originating or produced from outside a cell, tissue,or organism: exogenous antioxidants.

Glucono-δ-lacton A food additive with the E-number E575, used as a sequestrant, an acidifier, or a curing, pickling, or leavening agent. GDL is neutral, but hydrolyses in water to gluconic acid which is acidic, adding a tangy taste to foods, though it has roughly a third of the sourness of citric acid.

Hypertensive crisis Hypertensive crisis is an umbrella term for hypertensive urgency and hypertensive emergency. These two conditions occur when blood pressure becomes very high (over 180 systolic or 110 diastolic), possibly causing organ damage.

Hypoxia Diminished availability of oxygen to the body tissues.

Immunomodulation Alteration of the body's immune response

Isoflavones Isoflavones are a type of often naturally occurring isoflavonoids, many of which act as phytoestrogens in mammals. Some are termed antioxidants because of their ability to trap singlet oxygen. Isoflavones are produced almost exclusively by the members of the Fabaceae (i.e., Leguminosae, or bean) family.

Lockjaw Trismus, or Lockjaw, refers to reduced opening of the jaws caused by spasm of the muscles of mastication, or may generally refer to all causes of limited mouth opening.

Lymphocytes A lymphocyte is one of the subtypes of white blood cell in a vertebrate's immune system. Lymphocytes include natural killer cells (NK-cells) which function in cell-mediated, cytotoxic innate immunity, T-cells (for cell-mediated, cytotoxic adaptive immunity), and B-cells (for humoral, antibody-driven adaptive immunity). They are the main type of cell found in lymph, which prompted the name lymphocyte.

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Mass spectrometry Mass spectrometry (MS) is an analytical technique that ionizes chemical species and sorts the ions based on their mass to charge ratio. In simpler terms, a mass spectrum measures the masses within a sample. Mass spectrometry is used in many different fields and is applied to pure samples as well as complex mixtures

Mast cell A type of white blood cell. Although best known for their role in allergy and anaphylaxis, mast cells play an important protective role as well, being intimately involved in wound healing, angiogenesis, immune tolerance, defence against pathogens, and blood–brain barrier function

Mesophilic A mesophile is an organism that grows best in moderate temperature, neither too hot nor too cold, typically between 20 and 45 °C (68 and 113 °F).

Oedema Oedema is the medical term for swelling. It is a general response of the body to injury or inflammation. Oedema results whenever small blood vessels become "leaky" and release fluid into nearby tissues. The extra fluid accumulates, causing the tissue to swell. Oedema can be isolated to a small area or affect the entire body. Medications, infections, pregnancy, and many medical problems can cause oedema.

Organoleptic Organoleptic properties are the aspects of food, water or other substances that an individual experiences via the senses—including taste, sight, smell, and touch.

Paresis Weak form of paralysis. It is condition typified by a weak or partial loss of voluntary movement or by impaired movement. When used without qualifiers, it usually refers to the limbs, but it can also be used to describe the muscles of the eyes (ophthalmoparesis), the stomach (gastroparesis), and also the vocal cords (Vocal cord paresis). Neurologists use the term paresis to describe weakness, and plegia to describe paralysis in which all voluntary movement is lost.

Pathogenesis The biological mechanism (or mechanisms) that lead to the diseased state.

Peripheral blood vessels

The peripheral vascular system consists of the veins and arteries not in the chest or abdomen (i.e. in the arms, hands, legs and feet). The peripheral arteries supply oxygenated blood to the body, and the peripheral veins lead deoxygenated blood from the capillaries in the extremities back to the heart.

Piperidine This heterocyclic amine consists of a six-membered ring containing five methylene bridges (-CH2-) and one amine bridge (-NH-).

Pyrrolidine Cyclic secondary amine, which is miscible with water and behaves alkalic.

Polycation Polymer whose repeating units contain at least one positive charge. DNA, as a polymer of nucleotides, is an example.

Potentiators Enhancers of a certain effect. In the context of biogenic amines: compounds which enhance the toxic effects of BA by enhancing their absorption and/or diminishing AO-activity.

Pruritus Itching

Psychrotropic Psychrotrophic bacteria are bacteria that are capable of surviving or even thriving in a cold environment.

Scombroid fish The Scombridae family of the mackerels, tunas, and bonitos includes many of the most important and familiar food fishes. Scombrids are generally predators of the open ocean. They contain a large amount of red muscle, which helps them maintain a high activity-level.

Sympathomimetic Sympathomimetic drugs are stimulant compounds which mimic the effects of agonists of the sympathetic nervous system such as the catecholamines (epinephrine (adrenaline), norepinephrine (noradrenaline), dopamine, etc.) Sympathomimetic drugs are used to treat cardiac arrest and low blood pressure, or even delay premature labor, among other things.

Tachycardia A form of cardiac arrhythmia, in which the heartbeat is too fast (more than 100 beats per minute).

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Ulcerative colitis A form of inflammatory bowel disease (IBD) that causes inflammation and ulcers in the colon. What sets it apart from Crohn's disease is that ulcerative colitis only affects the colon and rectum, rather than the whole GI tract.

Urticaria Commonly referred to as hives. It is a kind of skin rash notable for pale red, raised, itchy bumps. Hives may cause a burning or stinging sensation. It is frequently caused by allergic reactions, although there are also many non allergic causes.

Vasoconstriction Narrowing of the blood vessels resulting from contraction of the muscular wall of the vessels

Vasodilation Widening of blood vessels

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SUMMARY

Currently, several biogenic amines (BA) are known cause food intoxication after ingestion of food

products containing excessive amounts. As such, histamine-poisoning (aka "scombroid poisoning")

and tyramine-poisoning ("cheese reaction") are well documented and their concentrations in the

most hazardous products (fish, cheese and fermented meat products) have been investigated before.

Nevertheless, little is known on the concentration of these biogenic amines in other, uncharacteristic

food groups. Likewise, insufficient information is available on the concentration of other biogenic

amines in different types of food, nor is there enough information on their harmful effects (1; 2).

When EFSA decided in 2010 to perform a risk assessment on biogenic amines present in all types of

food, the Belgian government was asked to provide data on the concentration of several biogenic

amines in food products on the Belgian market. As such data was insufficiently available, the

BIOGAMI-project was started in October 2013, a project aiming to assess the health risks associated

with biogenic amines in products part of the Belgian food market, via an elaborated risk assessment.

During this master thesis, a contribution to this envisioned risk assessment was made. As such, in a

first part of the thesis, the currently available toxicological data were investigated, as a part of the

hazard characterization. Then, in order to perform an exposure assessment (the third step in a risk

assessment), data on the concentration of 6 BA in food products on the Belgian market was gathered

via screening tests, according to a predefined sampling plan. These screening tests had started in

October 2014 and have been finished in April (2016) and during the course of this mater thesis

screenings were performed on yoghurt, beer, cheeses and meat (fresh meat, meat products and

meat preparations). Next to the screening tests, also some in depth storage tests have been

performed on fish and marinated meat to provide a preliminary view on the biogenic amine profile in

these animal products and on the influence of several storage conditions on the BA-formation during

storage. Subsequent to all these experimental analyses, statistical analysis of the results of the entire

body of screening tests were executed. First, some exploratory comparisons of the BA-profile were

made between different food groups, between fermented and non-fermented foods and between

animal and plant-based products. Furthermore, redundancy analysis combined with multiple linear

regression was performed in R, looking for the possible correlations between BA-concentrations,

microbial counts and concentrations of free amino acids. These last two types of data were gathered

during the screening tests as well.

The exploratory results of the storage tests showed that in tuna, histamine is the most dominant BA,

occurring in toxic concentrations when the product is misused (stored at too high temperatures). In

marinated meats (pork as well as chicken, beef and lamb), cadaverine and tyramine were the most

prominent BA. It was also concluded that MAP-packaging and refrigeration are effective techniques

to limit BA-formation.

The results of the screening tests for different meat products and preparations showed that tyramine

is always the most predominant BA in these kinds of products. The content of other BA depended

strongly on the type of product and its production method.

Screenings of food products in other food categories resulted in a database containing information

on their biogenic amine and free amino acid concentrations and their microbial contamination.

Exploratory investigation of these BA- data showed that the BA-profile differed strongly between

different food groups. Also some indications were found to state that in animal-based and fermented

products BA are formed differently than in plant-based and non-fermented products respectively.

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The subsequent correlation analyses studying the relationships between biogenic amines, free amino

acids demonstrated that higher contents of FAA might indeed lead to higher level of BA, although

further, more detailed investigations are required to confirm this statement. And lastly, the

correlation analysis between microbial counts and BA-concentrations showed that these correlations

were not that strong and no type of bacteria stood out as being more strongly related to BA-

formation than the others.

vii

SAMENVATTING

Van verschillende biogene aminen (BA) is geweten dat ze voedselintoxicaties kunnen induceren bij

te hoge consumptielevels. Histamine, bijvoorbeeld, veroorzaakt scombroïde vergiftiging en tyramine

kan het zogenaamde kaassyndroom ("cheese reaction") veroorzaken, gepaard gaande met een

stijgende bloeddruk en hoofdpijn. Deze twee intoxicaties werden reeds grondig bestudeerd en de

concentraties van histamine en tyramine in de meest risicovolle producten (vis, kaas en

gefermenteerde worst) werden tevens uitvoerig onderzocht. Anderzijds is er nog slechts weinig

informatie beschikbaar over hun concentratie in levensmiddelen waar deze intoxicaties minder vaak

mee geassocieerd worden. Daarenboven is er nog onvoldoende informatie beschikbaar over andere

BA in verschillende voedselgroepen, noch is er voldoende info over hun mogelijke toxische effecten.

Toen men bij EFSA in 2010 het besluit nam om een risicoanalyse te starten om de gezondheidsrisico’s

aangaande biogene amines in te schatten, werd aan de Belgische overheid gevraagd om

concentratiedata over deze stoffen in voedsel op de Belgische markt te voorzien. Deze data bleek

echter in onvoldoende mate beschikbaar. Daarom werd in oktober 2013 het BIOGAMI-project

opgestart, een studie met het doel om de gezondheidsrisico’s omtrent de blootstelling aan biogene

aminen voor de Belgische bevolking in te schatten via een sterk uitgewerkte risicoanalyse.

Tijdens deze masterproef werd aan de beoogde risicoanalyse een bijdrage geleverd. In een eerste

deel van deze thesis werd namelijk de beschikbare toxicologische data uit de literatuur geraadpleegd

en uiteengezet, ter karakterisatie van het risico dat biogene aminen vormen. Vervolgens werd de

concentratie van 6 biogene aminen bepaald in levensmiddelen op de Belgische markt via screening

testen en een vooropgesteld sampling plan. Deze data zouden gebruikt worden in een

blootstellingsanalyse, de derde stap in een risicoanalyse. De screening testen werden opgestart in

oktober 2014 en werden in april (2016) afgerond. Binnen de termijn van deze thesis werden

screenings uitgevoerd op stalen bier, yoghurt, kazen en vlees (vers vlees, vleesproducten en

vleesbereidingen). Naast deze screening testen werden eveneens enkele bewaartesten uitgevoerd

op vis en gemarineerd vlees, met als doel om een eerste zicht te krijgen op de biogene amines in

deze dierlijke producten en op de invloed van enkele bewaarcondities (temperatuur en MAP-

verpakking).

Volgend op al deze experimentele analyses werden statistische analyses uitgevoerd op een database

van 425 gescreende producten in totaal. Deze testen omvatten in de eerste plaats enkele

verkennende vergelijkingen van gemiddelde BA-concentraties tussen gefermenteerde en niet-

gefermenteerde stalen, stalen van dierlijke en plantaardige oorsprong en tussen verschillende

voedselgroepen. Daarna werden redundantieanalyses en een meervoudige lineaire regressies

uitgevoerd in R om de correlaties tussen de concentraties aan biogene amines en vrije aminozuren

en de microbiële tellingen te onderzoeken. Deze laatste twee datatypes (vrije aminozuren en

microbiële analyses) werden tevens tijdens de screening testen verzameld.

Uit de bewaartesten op tonijn en gemarineerd vlees bleek dat histamine het meest prominente

biogeen amine was in vis, zelfs oplopend tot extreem toxische concentraties wanneer de vis onder te

hoge temperaturen werd bewaard. In het gemarineerde vlees (zowel varkensvlees als kip-, lam- en

rundsvlees) werden tyramine en cadaverine als meest belangrijke biogene amines gevonden. Tevens

kon uit deze bewaartesten ook geconcludeerd worden dat MAP-verpakking en koeling effectieve

technieken zijn om vorming van biogene amines tegen te gaan.

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De resultaten van de screeningtesten voor verschillende vleesproducten en -bereidingen toonden

vervolgens aan dat tyramine het meest dominante BA is in deze categorieën voedsel. Het gehalte aan

andere biogene aminen bleek echter sterk per subcategorie te verschillen.

De database die volgde uit de screening testen van alle voedselcategoriëen samen bevatte

informatie over hun gehaltes aan biogene aminen, vrije aminozuren en microbiële contaminatie.

Verkenning van deze BA-concentraties toonde aan dat het BA-profiel sterk verschilde tussen de

verschillende voedselgroepen en dat gefermenteerde en dierlijke voeding een verschillend BA-profiel

vormen dan niet-gefermenteerde en plantaardige voeding respectievelijk. Uit de daaropvolgende

correlatieanalyse bleek verder er een positieve correlatie zou kunnen bestaan tussen het gehalte aan

vrije aminozuren op het moment van aankoop en de BA-gehalten op einde houdbaarheid. De

microbiële correlatieanalyses toonden tenslotte aan dat de correlaties tussen microbiële

concentratie en BA-gehalten heel wat minder sterk waren en dat in elk geval geen enkele groep

bacteriën een sterkere relatie met BA vertoonde dan de anderen.

1

1. INTRODUCTION

These days, the safety of our food is under strict control. However, this has not always been the

case. After some major food crisis’s in the 90’s, food safety became a hot topic and the need for an

integrated control system that would cover the whole food chain (farm-to-fork) started to show in

the EU (3). Over the past decades, EFSA has, following the principles of risk-analysis determined by

the General Food Law, been trying to asses and optimize the safety and the shelf life of our food (4).

The subject of food safety covers roughly everything that concerns food and its components and that

could form a hazard for human health. It has been defined by (5) as “the condition of the foodstuffs

in all stages of production, processing and distribution, required to guarantee protection of

consumer’s health, also taking into account normal circumstances of use and information available

for the foodstuff concerned. Food safety thus means the absence of biological, chemical or physical

agents (hazards) in concentrations/ quantities that can cause adverse health effects.” Specifically,

some of those hazards can be bacterial pathogens like Salmonella spp. and Listeria monocytogenes,

foodborne viruses, residues of pesticides, mycotoxins, nanomaterials, etc. (6). Also biogenic amines

form a hazard in the safety of our food. These last components will be the subject of this master

thesis.

Biogenic amines are organic nitrogenous compounds. They occur in plants, as well as in animals and

microorganisms (MO), where they are formed by endogenous pathways and where they perform

functions like growth regulator, neurotransmitter or mediator of infections (7). Furthermore, they

can be found in all foods that contain protein and/or free amino acids. They appear for example in

fish- and meat products, dairy, fruit and vegetables, nuts, chocolate, etc. In food products, the

presence of biogenic amines will mainly be the result of decarboxylation of free amino acids by

microorganisms. In order for this process to occur, three conditions must be met. Firstly, the

precursors of the biogenic amines, namely free amino acids, must be present. These will mainly be

produced by proteolysis of the protein in the food product. Secondly, decarboxylase active

microorganisms must be present. Lastly, the environmental conditions like temperature, pH etc.

must allow growth of these microorganisms and the activity of their decarboxylases (8; 9; 10).

The most prominent biogenic amines in food products, and so the ones that will be of importance in

this master thesis, are histamine, tyramine, tryptamine, putrescine, β-phenylethylamine and

cadaverine. Because biogenic amines are mainly the result of microbial activity, the highest

concentrations will be found in fermented foods on the one hand and spoiled foods on the other (8;

7; 2).

Knowing the concentrations of several biogenic amines in foods and their producing microorganisms

is of importance for several reasons. Firstly, due to their microbial origin, biogenic amines could

serve as a food spoilage parameter. Secondly, they can also serve as parameter for the hygiene or

the careful execution of the production process, and thus be a process parameter. Lastly, at high

intake levels, certain biogenic amines are toxic for the human body.

Until quite recently, Belgium did not possess sufficient data on the contents of biogenic amines in the

range of foodstuffs on the Belgian market. There was only sufficient data for fish. That is why, after a

request of EFSA for this kind of data, the BIOGAMI-project was initiated in 2014 (8; 7; 2). The goal of

the research project BIOGAMI is to perform a risk assessment for the Belgian population concerning

several biogenic amines, by analysing certain food groups and using the Belgian consumption data. In

order to do this, first, a method needed to be optimized to extract, detect and quantify these amines

2

in the food matrices. This had already been completed at the start of this thesis. Then the laboratory

analysis of the selected food groups would follow, in order to gain a view on which biogenic amines

appear in which foods and in which concentration. Simultaneously, the concentrations of the free

amino acids which are the precursors of the biogenic amines were determined and microbial

analyses were performed in order to see if there might be a relationship between the growth of

certain microorganisms and the production of biogenic amines. These analyses would result in a

database, which, together with the most recent Belgian consumption data, would be used to assess

the exposure of the Belgian population to these biogenic amines and to perform a risk-assessment

(2).

This Master dissertation has contributed to the BIOGAMI-project by taking part in the lab- analyses,

more particularly the screenings of the food groups, and by assessing their toxicity qualitatively.

Figure 1 shows an overview of the tasks to be performed during the course of the dissertation.

The lab experiments have been focused on fish and meat-based products, and were started by

executing exploratory storage tests: one on tuna, one on marinated pork and one on other types of

marinated meat. Other lab analyses comprised screening of food products on the Belgian market,

particularly meat products and preparations.

Figure 1: Outline of this master dissertation.

Part 1: Screening of meat, fish and

meat products

1) Storage tests for tuna and marinated meat to compare the BA-profile

of these products.

2) Storage tests on meat products to determine

which products to analyse further.

Determination of biogenic amines, free amino acids

and microorganisms

3) Screening of meat, fish and meat products

Part 2: Statistical analysis

4) Statistical analysis of the results to find correlations

between biogenic amins, free amino acids and microorganisms

3

The research questions proposed for this master thesis follow the general outline depicted in figure 1

and are:

1. Storage tests a. Which biogenic amines are dominant in the fish and meat products used? b. Which is the influence of MAP-packaging and storage temperature profiles on the synthesis of biogenic

amines and the development of microorganisms in tuna on the one hand and marinated meat on the other?

c. Is there a link between free amino acids at the start of storage and the BA-profile? d. Is there a link between the BA-profile and the microbial counts detected on the samples? e. Can BA-formation and possible BA-intoxication be masked by preparing meat in a certain way?

2. Screening tests a. Which biogenic amines are the most abundant and in which meat- based products? b. Is there a difference in type of biogenic amines formed between different types of meat-based products?

3. Statistical analysis a. Do fermented food products contain different BA-profiles than non-fermented food products? b. Do animal products contain different BA-profiles than plant-based products? c. Is the BA-profile different in different food groups? d. Is there a correlation between the initial amount of free amino acids and the concentration of biogenic

amines detected? e. Is there a correlation between the detected microorganisms and the concentration of biogenic amines?

In addition to the above-mentioned project, a literature study needed to be written. This study starts

with an overall view on the chemistry, the origins and the metabolic production of biogenic amines.

Subsequently, the toxicology of these amines is explained in detail and their role as a quality

indicator is delineated. The next part discusses which factors have an influence on the occurrence

and the concentration of biogenic amines in food and which tactics can be used to limit their

formation. Lastly, some aspects of the risk assessment process are explained, as this technique will

be used during the second part of this thesis (vide supra).

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2. LITERATURE STUDY

2.1 BIOGENIC AMINES

Biogenic amines are low molecular weight organic nitrogen compounds. The structure of a biogenic

amine can be aliphatic (for putrescine, cadaverine, spermine and spermidine), aromatic (for tyramine

and phenylethylamine) or heterocyclic (for histamine and tryptamine) (11). These compounds are

part of the metabolism of plants, animals and microorganisms, where they play a role in growth

regulation (polyamines), neural transmission (catecholamines and histamine) and as mediators of

inflammation (histamine and tyramine) (7).

2.1.1 Occurrence in food

Any food product containing proteins or free amino acids (FAA) that is subjected to conditions that

favour microbial and/or biochemical activities, will contain BA (8). On the one hand, BA in food can

be of endogenous origin, which means that they were formed by metabolic pathways of the plant or

animal and are hence present in the raw material of the food. “Natural polyamines” (putrescine,

spermine and spermidine), for example, are formed by de novo polyamine synthesis (see further)

(12). Endogenous biogenic amines are usually present in low concentrations in unfermented foods

like fruits and vegetables, meat, fish and milk (7). On the other hand, when their origin is exogenous,

biogenic amines are the result of microbial decarboxylation (figure 2) of free amino acids and are

present in higher concentrations. The precursing amino acids are either the result of proteolysis of

protein or were already present in the raw materials (13). Being the result of microbial activity,

exogenous biogenic amines can be present in fermented foods, like yoghurt, dry sausages, chocolate,

olives, etc. on the one hand and in spoiled foods on the other hand (8; 11).

Figure 2: decarboxylation reaction of Histidine to Histamine(14).

The most frequently occurring biogenic amines in foodstuffs are histamine, tyramine, putrescine,

cadaverine, tryptamine, 2-phenylethylamine, which are products of histidine, tyrosine, ornithine,

lysine, β-phenylalanine respectively (7; 10; 12). Figure 3 shows the structures of these compounds.

5

Figure 3: Structure of the most important biogenic amines in food products(7).

2.1.2 Production by microorganisms

Biogenic amines can only be produced by MO that contain decarboxylase activity, which means they

can synthesize decarboxylases, the enzymes necessary for decarboxylation. Decarboxylase activity

has already been detected in strains of the genera Bacillus, Pseudomonas and Photobacterium, in

Enterobacteriaceae like Escherichia, Morganella morganii, Citrobacter, Salmonella, Shigella and

Proteus, in Micrococci like Micrococcus, Staphylococcus and Kocuria and in the lactic acid bacteria

Lactobacillus, Pediococcus, Leuconostoc and Streptococcus (8; 7; 10). Even some yeast strains are

believed to be able to produce these enzymes. It needs to be mentioned that the presence, the

activity, and the specificity of decarboxylases are strain-dependent characteristics and can thus differ

within one microbial species (10). This fact needs to be considered when trying to determine which

organism was responsible for the BA present in a certain food product.

The physiological role of biogenic amines in the producing microorganisms has not yet been fully

elucidated. According to some authors, BA-production could be some kind of defence mechanism

against stressing effects of temperature, acidic pH, salt or other biological and/or chemico-physical

factors (10). Other reasons for MO to carry out BA-production involve a contribution to energy-

generation and assistance in pathogenesis by promoting adhesion to host cells, by altering the hosts

physiology (vasodilating effect of histamine) or by promoting the production of a virulence factor (1).

6

2.1.3 Detection methods

As mentioned in the introduction, determination of BA-profiles of foods is important, because of

their toxicity and their possible role as spoilage indicators. For the qualitative and quantitative

detection of BA, various methods have already been developed. Most are based on some form of

chromatography like Thin Layer Chromatography (TLC), Gas Chromatography (GC), Capillary

Electrophoresis (CE) and High Performance Liquid Chromatography (HPLC). HPLC with pre- or post-

column derivatisation is the most frequently used technique. Detection has been performed by

mass spectrometry, electrochemical detection or fluorimetric detection, but usually, UV-detection

after derivatisation with dansyl chloride or ortho-phtalic aldehyde (OPA) is used (7). Figure 4 shows

how the UV-sensitive product of this derivatisation reaction is formed. It must be mentioned that the

extraction of the BA from the food matrix, preceding the HPLC-analysis is the most crucial step in the

procedure, because it is the most important cause of low recoveries (7).

Figure 4: Derivatisation reaction of biogenic amines with dansyl chloride (15).

2.2 TOXICOLOGY

2.2.1 General

The first reason why monitoring the BA-levels of food is important, is because excessive intake of

certain BA can have a toxic effect on the human body. Fish and cheese are the foods associated with

the highest number of BA-poisoning cases (12). Histamine is the BA causing the food poisoning most

frequently and histamine intoxication, posing allergy-like symptoms, is mostly associated with the

consumption of scombroid fish and cheese (1; 8). Tyramine intoxication is called “cheese reaction”

and is mainly associated with cheese and wine. Other biogenic amines, like putrescine, cadaverine,

spermine and spermidine, show only limited direct toxicity but can potentiate the toxicity of

histamine and tyramine (7; 1; 12).

Below, the overall detoxification mechanisms of BA will be discussed. Next, a discussion of the

toxicity of histamine, trace amines and polyamines will follow, as these are three groups with

distinctly different toxicity mechanisms.

2.2.2 Detoxification

The human body is able to detoxify BA, mainly by oxidation. Oxidation is carried out by specific

enzymes, called mono- (MAO) or diamine oxidases (DAO), depending on the number of amino

groups oxidized. Both MAO and DAO are present in the intestinal tract of mammals, where they

detoxify BA present in ingested foods (16; 13). Detoxification pathways might differ slightly between

different BA. Histamine, f.ex. is mainly detoxified by DAO, but tyramine detoxification is chiefly

carried out by MAO (17; 18). For histamine, another detoxifying pathway via methylation or

acetylation by histamine-N-methyltransferase (or -acetyltransferase) exists(18).

7

When the activity of these AO’s is suppressed, however, or when too high amounts of BA are

ingested, not all ingested BA will be detoxified and will be able to enter the blood stream, possibly

causing systemic effects (Figure 5). Several factors, called potentiators have been reported to

diminish AO-activity. Firstly, AO-activity depends on genetic factors and the health status of the host.

For example, certain gastro-intestinal diseases like Crohn’s disease or ulcerative colitis, will diminish

AO-activity (13; 16). Secondly, AO-activities can be inhibited by certain antidepressants and

isoflavones, which are then called monoamine oxidase inhibitors (MAOI). Lastly, tyramine,

putrescine, tryptamine, cadaverine and the polyamines spermine and spermidine have all been

shown to inhibit AO-activities. This effect might explain why histamine is more toxic in cheese or fish,

accompanied by other BA, than in aqueous solutions (8; 7). Additionally, putrescine, cadaverine,

spermine and spermidine have also been reported to enhance the intestinal absorption of toxic BA,

thereby also amplifying their toxicity (7). Alcohol or acetaldehyde have similar effects and act by

increasing the permeability of the intestinal wall (16).

Figure 5: Processing of BA in the human intestinal tract(16).

As all above mentioned factors play a role in the toxicity of BA, dose-response relationships of the

toxicity are generally quite hard to determine. By consequence, data on the actual toxic effects,

their mechanisms, dose-response relationships and the actual concentrations in foods, are

generally quite limited (1). This makes sure that defining legal limits for certain biogenic amines in

certain products as a risk management strategy is not an easy task (8; 7).

2.2.3 Histamine

As mentioned above, most cases of food intoxication with biogenic amines involve histamine, after

the consumption of histidine-rich foods like scombroid fish like tuna, mackerel and sardines, or

cheese (8; 1; 19; 7). It’s presence in foods, however, cannot be noticed organoleptically, even in high

concentrations, as it is tasteless (13). In the human body, histamine is a hormone and a

neurotransmitter synthesized out of the amino acid histidine with the aid of the enzyme L-histidine

decarboxylase. It occurs in a large variety of cells, among which in mast cells, which are part of the

immune system. In these cells, histamine is stored in vesicles and released upon stimulation, f.ex. by

allergens, complement proteins, hypoxia, certain foods, … (18). Histamine has the highest biological

activity of all the BA (19; 18). When histamine is released in the bloodstream it exerts its function by

binding to one of its four receptors (H1, H2, H3, H4), spread in several tissues. These bindings cause

8

various effects. As such, histamine plays a role in gastric acid secretion, immunomodulation, day-

night rhythm, cell growth and differentiation, attention and cognition (1; 18). Toxic symptoms,

however, are mainly the result of histamine binding causing intestinal smooth muscle cell contraction

and dilatation of peripheral blood vessels (1; 8).

Detoxification by DAO forms the main mechanism for histamine originating from foods. When high

amounts of histamine are ingested, DAO-detoxification is insufficient, and histamine intoxication

occurs, posing allergy-like symptoms like headaches, flushing, rashes, hypotension, bronchospasm,

tachycardia, arrhythmias, oedema, pruritus and asthma (8; 1; 13; 18). Incubation times range from a

few minutes to a few hours. Rapid reactions suggests that at least part of the amine can be absorbed

already in the mouth, where no detoxification system is present (8; 13).

The toxicity of histamine is dependent on its concentration in the blood. Concentrations of 0.3 to 1.0

ng/ml are considered normal. Table 1 shows which symptoms can be expected at several blood

concentrations.

Table 1: Effects of histamine on the human body according to its concentration in the blood (18)

Histamine level (ng/mL) Clinical effect

0-1 Reference

1-2 ↑ Gastric acid secretion ↑ Heart rate

3-5 Tachycardia, headache, flushing, urticaria, pruritus

6-8 ↓ Arterial pressure 7-12 Bronchospasm

≈ 100 Cardiac arrest

Parente et al (2001) have stated that intake levels of 8-40 mg, 40-100 mg and above 100 mg can

cause respectively slight, intermediate and severe poisoning (7). Also, EFSA has reported an NOAEL

of 50 mg. Some individuals, however, are histamine intolerant and have lower DAO-activity, either by

genetic predisposition or by the action of gastrointestinal diseases. Approximately 1% of the

population is believed to suffer from this condition (18; 1). For these individuals, NOAEL are below

the detection limits. Therapy of histamine intolerance consists of consumption of a histamine-free

diet or prescription of antihistamines (18). Finally, histamine is the only biogenic amine for which

legal limits exist. According to Regulation 2073/2005 a 3 class sampling plan with n = 9, c = 2, m =

100 mg/kg and M = 200 mg/kg, is used in control analyses for “fish species associated with high

amounts of histidine”(20). For other foods, the same levels are being suggested, while 2 mg/l is

suggested for alcoholic beverages (14).

2.2.4 Tyramine and trace amines

Tyramine, together with β-phenylethylamine and tryptamine, is part of a group of biologically active

amines called “trace amines”. They are functionally and structurally similar to catecholamines and

occur in the body only in trace amounts (nanomolar concentrations in the brain). Trace amines are

synthesized in the body by decarboxylation out of their earlier mentioned precursors. The highest

tyramine levels are mainly found in cheese and fermented meat products (hundreds of mg/kg are

possible). Especially in long-ripened cheeses made from raw milk, concentrations above 1000 mg/kg

can occur. Tyramine and β-phenylethylamine have also been associated with red wine and chocolate

(16; 17).

9

The physiological action of tyramine and the other trace amines is sympathomimetic. When entering

the vascular system, tyramine can be hydroxylated to octopamine, which subsequently displaces

noradrenaline in nerve cells. This release of noradrenaline causes vasoconstriction. Several recent

studies, however, state that the vasoconstricting effect of tyramine might also be partly due to its

binding to trace amine-associated receptors, located in the blood vessels. Lastly, tyramine also

causes a transient increase in blood pressure, by stimulating muscle contraction, thereby increasing

the cardiac output (16; 17).

Tyramine is metabolized by the action of MAO, located throughout the whole body. Toxic effects of

tyramine are mainly associated with consumption of tyramine-rich foods in combination with mono

amine oxidase inhibitory (MAOI) drugs. These MAOI-drugs inhibit MAO-activity not only in the

intestine, but throughout the whole body and as noradrenaline is also metabolized by MAO and

tyramine mediates its release, the resulting high amounts of noradrenaline in the blood can lead to a

life threatening situation, called a hypertensive crisis. Certain cases have been fatal due to brain

hemorrhage and heart failure. Less severe cases of tyramine intoxication, for example at high intake

levels or in a person with genetically lower MAO-activities, give rise to symptoms like headaches,

nausea and vomiting. Other trace amines, like β-phenylethylamine and tryptamine, have been

shown to exhibit similar effects (17).

Toxic levels of tyramine and trace amines are generally established by determining the tyramine

pressure response, i.e. the dose of amine to be administered in order to increase the blood pressure

by 30 mmHg (16). In healthy men, this dose has been reported to be 500 mg of orally administered

tyramine. As women appear more sensitive to tyramine, smaller doses might already give a similar

effect (16). NOAEL have been determined for tyramine and were established at 600 mg/meal for

healthy people, 50 mg/meal for persons taking third generation MAOI-drugs, but only 6 mg/meal for

individuals taking the classic MAOI-drugs. For phenylethylamine and tryptamine, insufficient data on

dose-response relationships are available (1). No legal limits have been set for the contents of

tyramine or the other trace amines in foods, but levels of 100 - 800 mg/kg for tyramine and 30 mg/kg

for phenylethylamine have been suggested as maximal allowable levels (7; 19).

2.2.5 Putrescine, cadaverine and polyamines

Cadaverine is derived from lysine by lysine-decarboxylase. The physiological role of this BA is not very

well known, but it has been shown to replace putrescine in some biological systems (1).

Putrescine (1,4-diaminobutane), together with spermine (N, N-bis-(3-aminopropyl)-1,4-

diaminobutane) and spermidine (N-(3-aminopropyl)-1,4-diaminobutane) is part of the group of the

polyamines. In the human body polyamines are either synthesized in human cells by de novo

polyamine synthesis, or they have been taken up from food products. Figure 6 shows the

biosynthetic pathways of these compounds. Putrescine can, firstly, be derived from ornithine by

decarboxylation by ornithine decarboxylase. A second pathway starts from arginine, which is first

decarboxylated to yield agmatine, and then further deaminated to putrescine (21; 7). In normal cells,

the level of polyamines is strictly regulated. Catabolism is carried out through acetylation and

subsequent oxidative deamination by DAO or PAO, the latter giving rise to the formation of H2O2

(22).

10

Figure 6: Biosynthetic pathway of putrescine, spermidine and spermine in mammals (ATP = adenosine triphosphate, MAT = methionine decarboxylase, AdoMetDC = S-adenolsymethionine carboxylase,ADC = arginine decarboxylase, ODC =

ornithine decarboxylase) (21).

Polyamines can be found in foods of both animal or plant origin. Foodstuffs of plant origin are usually

richer in spermidine compared to spermine, while the opposite is true for animal products (21). Also,

putrescine is usually the most abundant polyamine in foods of plant origin, at levels sometimes

higher than 40 mg/kg, while low levels (0-3 mg/kg) characterize animal products. The richest

polyamine source would be cheese, but certain fruits, meat, legumes, potatoes and vegetables may

also contain considerable amounts. Milk, eggs and yoghurt usually don’t contain very significant

amounts, but polyamines in human milk may still be of great importance for newborns (22).

Polyamines fulfil a variety of essential physiological roles. Most of their functions are related to the

fact that they are polycations at physiological pH and thus interact easily with negatively charged

molecules, like DNA and some membrane constituents (21). The most prominent function of

polyamines involves their participation in cell proliferation and growth, a role which they exhibit

through stabilization of DNA and cellular membranes, regulation of RNA transcription and protein

synthesis (8; 22). As such, high levels of polyamines have been reported in rapidly dividing cells and

they have been proven to play an important role in the development of the digestive system in

newborn animals, the maintenance of the epithelial barrier function in adults and in wound healing.

Several negative effects of polyamines, however, have also been described. As such, at high

concentrations, they have also been related to tumor development, which has made them subject of

rigorous medical and physiological studies (21). Furthermore, polyamines might be of importance in

the proliferation and differentiation of lymphocytes and the regulation of the inflammatory response

and thus regulate the immune system, preventing allergies or food intolerance (21; 22).

Toxic effects of polyamines and cadaverine are mainly indirect and generally much less potent than

those for histamine and tyramine. Symptoms which have been described are hypotension,

bradycardia, lockjaw and paresis of the extremities (23). Polyamines and cadaverine potentiate the

negative effects of histamine and tyramine on the human body, by impairing their oxidation by DAO

and MAO and by enhancing their adsorption by the intestinal tract (8).

Another way by which polyamines, cadaverine and also tyramine, might exert a toxic effect, is by

generation of nitrosamines (Figure 7). When subjected to heat, f.ex. during a cooking process for

11

cooked hams, these BA can form secondary amines. Cadaverine an putrescine, f.ex. form pyrrolidine

and piperidine upon heating (12). When these secondary amines interact with nitrosating agents

such as nitrite and nitrogen oxides during storage or cooking, they can give rise to the formation of

carcinogenic nitrosamines. This mechanism is of particular importance in some processed meat

products, to which nitrates and nitrites are added to preserve color (8; 12).

For polyamines, no legal limits in foods have been suggested. Toxic levels are difficult to pinpoint, as

there is a general absence of dose-response data for polyamines and cadaverine in food and studies

on humans. From studies on rats, however, the acute oral toxic levels of putrescine, spermine and

spermidine have been established at 2000, 600 and 600 mg/kg body weight per day. Similarly, NOAEL

were established at respectively 180, 83 and 19 mg/kg BW/day (1; 21). These exposure levels,

however, are way too high to be reached only by a normal consumption of food, because the normal

adult diet provides only between 350 and 500 micromoles per day ( = 31 – 44 mg putrescine or 36 –

51 mg cadaverine) (21; 22).

Figure 7: Mechanism of the formation of nitrosamine out of nitrite and an amine. In an acidic medium, a nitrosonium ion is formed, which reacts with an amine. In the case of biogenic amines, this last amine would be a secondary amine,

resultant from putrescine, cadaverine, spermine, spermidine or tyramine (24).

2.3 QUALITY INDICATOR

BA are not only important because of their toxicity, but also because, as they result out of growth

and metabolism of microorganisms, they can indicate the degree of spoilage of a food product, the

microbial quality of the raw materials or the hygiene of the production process (12). There is

evidence that, as the hygienic quality of a product decreases, the BA-contents increase (1).

During storage of food, the overall concentration of BA changes. In unfermented products, like f.ex.

fresh meat and fish, the levels of histamine, cadaverine and putrescine will typically increase. Levels

of spermine and spermidine, however, usually decrease. Microbial counts increase as well during

storage, thus the presence of BA could be linked to the presence of certain decarboxylase-positive

spoilage organisms. Indeed, good correlations have been found between microbial counts and, f.ex.,

the concentrations of putrescine and cadaverine. Therefore, a number of biogenic amine indexes

(BAI) have been suggested in order to determine the hygienic quality of a food product. The sum of

histamine, tyramine, putrescine and cadaverine has been used as an indicator of meat freshness by

Hernandez-Jover et al. (1996) (19; 9; 12). Table 2 gives a good view on which values of this index are

related to meat of good hygienic quality (9; 12). Other indexes have been based on just one biogenic

amine, or have been using combinations with other factors (1). One should note, however, that, as

not all spoilage organisms are able to produce biogenic amines (vide supra), the absence of biogenic

amines does not necessarily mean that a product is safe.

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Table 2: BAI-values (sum of histamine, tyramine, putrescine and cadaverine) in relation to meat quality for fresh meats (12).

BAI-value (mg/kg) Hygienic meat quality

< 5 Good

5 – 20 Acceptable

20 - 50 Initial spoilage signs

> 50 Spoiled

In fermented food products, the use of BA-contents as a quality index is limited, because although

these products do contain high counts of microorganisms and very variable BA-levels, these are most

likely part of the starter culture and thus not always indicative of a spoiled product (see further: 5.2)

(12).

2.4 FORMATION OF EXOGENIC BIOGENIC AMINES

As was previously pointed out, biogenic amines can occur in every product that contains proteins or

free amino acids(8). Figure 8 shows a clear overview of how biogenic amines are generally formed.

First, proteins are broken down by either autolytic or bacterial proteolysis, delivering free amino

acids. Subsequently these free amino acids are converted to biogenic amines by decarboxylation,

which means that the carboxyl moiety of the amino acid is removed (9; 12).

Figure 8: Overview of the formation of BA starting from proteins (12)

The main prerequisites for the formation and accumulation of BA are: 1) the presence of FAA, the

substrate for decarboxylation 2) the presence decarboxylase positive bacteria and 3) suitable

environmental conditions that favor growth of these microorganisms, their enzyme production and

sufficient enzyme activity. Hence, all factors which have an influence on these three requirements,

will influence the formation of BA (1).

2.4.1 Substrate availability

The amount of AA present in a food product will mainly be determined by the extent of proteolysis

happening during storage, production or fermentation (12). This process can occur through both the

13

action of endogenous and microbial enzymes and is influenced by pH and NaCl-concentration (10).

Accelerated or enhanced proteolysis has been related to higher amounts of BA (1). Which and how

many AA are available for decarboxylation will also depend on the composition of the food product,

more specifically its protein content and AA-composition (10). As such, products with higher protein-

contents are more likely to yield high amounts of AA, and thus BA (think about the high BA-

contents of spoilt fish versus low contents in fruit and vegetables)(19)(23).

Inhibiting proteolysis can be a strategy to limit BA-formation in food (10). However, in fermented

products like cheese and fermented sausages, proteolysis is a vital part of the production process

and thus cannot be eliminated.

2.4.2 Presence of microorganisms

MO act as providers of the decarboxylase enzyme and thus play a fundamental role in the formation

of BA. It has been shown that in sterile products, no BA are formed, showing that microbial activity

is essential for BA-formation (12). Presence of MO in food products can be due to their presence in

the raw material or their addition during the production process, either willingly as a starter culture,

or unwillingly as a contamination (1).

Factors concerning MO determining the final BA-contents of food products are the type of MO and

the microbial load (8; 10; 12). The type of MO is important because not all bacteria are

decarboxylase positive. Only decarboxylase positive MO will be able to generate BA. The type of

decarboxylases can differ between MO, making each bacteria produce a different range of BA. As

such, certain amines can be associated with some groups of organisms. Putrescine and cadaverine

production, for example, can be linked to the presence of Enterobacteriaceae, while tyramine can

mainly be linked to Enterococci. Also, as mentioned before, the production of decarboxylases is

dependent on the strain, rather than on the species of MO present (1).

The microbial load of a product will firstly depend on the initial MO-contamination, and secondly on

their ability to grow, which in its turn is influenced by many factors (see further). At higher microbial

loads, higher concentrations of BA will be found (12).

2.5 Conditions affecting MO-growth, decarboxylase production and decarboxylase

activity

2.5.1 Temperature

The combination of time and temperature during storage is widely considered as very determining

for the BA-contents of food (8; 10). Being a major determinant of the growth of MO, higher

temperatures and longer storage times yield higher amounts of BA (1; 10). Indeed, it has been

demonstrated that Klebsiella pneumonia produced more cadaverine at 20°C than at 10°C (8). For

mesophilic bacteria, BA-production is optimal between 10°C and 37°C, and can thus be inhibited by

storage at lower temperatures. Psychrotrophic bacteria like Photobacterium phosphoreum and

Morganella psychrotolerans, however, are able to grow at refrigerator temperatures and can provide

for the accumulation of BA even below 5°C (1). Nevertheless, in general, the levels of BA will be

lower in refrigerated food compared to foods that have undergone temperature abuse (10).

For fermented products, the fermentation temperature is another factor of influence. During

fermentation, relatively high temperatures (24°C) will mostly favor the growth of the starter culture,

which then overgrow amine-positive non-starter MO, leading to lower BA-contents (10). Maijala et

14

al. (1995), however, have reported that the effect of fermentation temperature is highly dependent

on the starter used (25).

2.5.2 pH

The pH-level of a food product has a dual effect on BA-formation. On the one hand, it is considered a

major determinant of decarboxylase production and activity, which are both higher at slightly acidic

pH-values. Optimal pH-values for decarboxylase activity generally lie between 4.0 and 5.5 (8). On

the other hand, acidic pH-values inhibit the growth of MO, thereby lowering BA-production

indirectly. The final equilibrium between both mechanisms will eventually determine the true BA-

contents and is product- and decarboxylase-dependent. As such, tyramine-production in cheese has

been proven to be optimal at pH 5.0(26), yet production of histamine in skipjack tuna has shown and

optimum pH of 4.0 . Finally, adjusting the pH of a product is possible to limit BA-formation. Addition

of glucono-δ-lacton, for instance, will lower pH (8).

2.5.3 Other factors

Firstly, several compositional features of a product are worth mentioning here. NaCl-concentration,

for instance, has been shown to have an effect on BA-formation, allegedly by inhibiting both MO-

growth and decarboxylase activity. Santos (1996) has reported BA-inhibiting effects proportional to

the brine concentration even at 25°C. Other studies, however, have also shown enhanced BA-

forming capacity in halotolerant bacteria like Staphylococcus (1), thus the effect of NaCl is strain-

specific. Increasing fat contents have also been negatively related to BA-concentrations, owing to

lower water-activities, which inhibit MO-growth (12). Glucose in a food product has a dual relation to

BA-contents. On the one hand it forms a nutritional source for MO, stimulating growth and thus

enhancing BA-formation (8). Glucose concentrations of 0.5 – 2.0 % are reported as ideal for bacterial

growth and BA-formation. Levels above 3%, however, have shown inhibiting effect (8; 12). On the

other hand, in fermented foods, glucose (or other fermentable carbohydrates) are mostly used by

starter cultures, acidifying the product and overgrowing other BA-producing bacteria. This then

results in lower BA-concentrations (10).

Oxygen content also has a marked impact on BA-contents, but the effects are not straightforward. As

such, putrescine production by Enterobacter cloacae is cut in half in anaerobic conditions compared

to aerobic conditions (19), but Bover-Cid et al. (2006) reported no effect at all on formation of

histamine, cadaverine and putrescine (1). Also, many studies have shown successful application of

MAP-conditions in limiting BA-formation, but it should be noted that these effects are strongly

dependent on both the type of product and the specific spoilage flora (27).

It should also be noted that all above mentioned factors are strongly interrelated, which makes it

difficult to determine their isolated effects. Moreover, all effects appear strongly product-specific

(1). It is the combination of all these factors that will eventually determine the type and

concentration of biogenic amines (12). A severely simplified model is given in figure 9, in which the

influence of different factors is shown.

15

Figure 9: Simplified model of the influence of different factors on the formation of BA (figure adjusted from(12)).

2.6 CONTROL OF BA-CONTENTS

It has been proven that BA are present in many parts of our diet (8; 19; 1) and are thus practically

impossible to avoid, consuming a balanced diet. This and the fact that consumers are increasingly

aware of the safety and healthy image of their food and adjust their consumer behavior accordingly,

makes sure that increased attention is being paid to the presence of BA in food products. In order to

comply with evolving consumer demands, industries are looking for new and improved technologies

that will produce high quality products with biogenic amines at nontoxic levels. There is, therefore,

increased interest in studies that examine the toxicity of certain BA and the factors which influence

their concentration in food (12). A better understanding of these mechanisms contributes to the

development of strategies to prevent toxic levels of BA-formation (8). These strategies can then be

implemented in the food safety management system (FSMS) of the company, by defining and

applying relevant prerequisite programs (PRP’s) and defining critical control points (CCP’s).

Currently, the main tactics for control of BA-accumulation are (1):

1) Prevention of contamination with decarboxylase-positive MO by guarding the hygienic

quality of the product during raw material handling and processing,

2) Applying environmental conditions or production techniques which:

a. Inhibit or eliminate decarboxylating MO

b. Limit BA-formation by controlling MO-growth, decarboxylase production and activity

Application of these tactics is mainly focused on the production stages of a food product, more

specifically the raw material handling and the fermentation process (if present). During storage, BA-

accumulation is also possible, but mainly depends on how these previous stages were carried out (1).

Destruction of formed BA has been attempted as well, but this approach is not according to the

current food safety policy, which aims at prevention rather than elimination of problems. Elimination

of BA by normal cooking is not possible, as they are quite heat-resistant (1; 8). The use of amino

oxidase positive MO as a starter culture has also been investigated (27; 28; 10). Application of such

techniques can, however, possibly mask improper hygienic and manufacturing practices (1).

16

2.6.1 Raw material handling

In raw or unfermented products, controlling the level of BA mainly comes down to controlling the

microbial load of the product. This means 1) limiting contamination, 2) eliminating contaminating

bacteria and/or 3) inhibiting their growth.

The main strategy to prevent contamination with decarboxylase positive MO is the conscientious

application of an elaborate food quality and safety (SMS) management system relying on HACCP. In

this respect, spreading or addition of decarboxylating MO should be inhibited by application of good

health and manufacturing practices (GHP/GMP) and proper cleaning and disinfection, starting at

primary production (1). Eliminating contaminating MO can be done by using thermal treatments,

e.g. pasteurization of milk in cheese production (29). Some products, however, like fresh fish or

meat, do not allow the use of thermal treatments, due to damage of the raw materials. For these

commodities, alternative techniques like irradiation or hydrostatic pressure are an option, although

further research is still needed (1). Finally, in terms of growth-inhibition, the time/temperature

combination is considered to be the most important factor, both during production and storage (vide

supra) (12).

2.6.2 Fermentation process

Controlling the amounts of BA in fermented food products is typically more difficult than in

unfermented foods, as fermentation usually provides for an ideal environment for BA-formation.

The obligatorily present MO, for instance, who carry out the fermentation, can also show aminogenic

activity. Moreover, proteolysis and acidification - unavoidable parts of a fermentation process - both

favor the decarboxylation reaction. Hence, fermented food products usually contain higher amounts

of BA than unfermented foods (1). Also, their BA-contents tend to show more and extensive

variability (12; 1). It has, however, been proven possible to generate fermented products with low

amounts of BA, by careful control of the fermentation process (1).

First and foremost, in order to control BA-contents, the above mentioned tactics for raw material

handling (SMS-system, time/temperature management, …) should be applied for fermented products

as well. In fermented meat products, for instance, the hygienic quality of the raw materials has been

related to the high variability in BA-contents of the end products (30). Further control of the

fermentation process usually comprises the careful selection of a starter culture together with

environmental parameters like the composition of the product (sugar, salt, spices, additives, …) and

processing parameters (temperature, product shape, …), all in function of the specific product which

is aimed at. Careful fine-tuning of these factors for each type of product is vital to obtain optimal BA-

inhibition. The aim is usually to favor the growth of the fermentative non-aminogenic MO and to

limit the growth of non-desired aminogenic MO (1).

The most important BA-determining factor is the starter culture (31). Fermentation based on the

naturally present microbial flora is also being applied, but generally gives rise to more variable and

less controllable BA-contents (8). A starter culture can be an axenic culture or a mixture of bacteria,

in which lactic acid bacteria usually play a leading role (10; 32). If well chosen, starter cultures can

decrease BA-accumulation in fermented products by shortening the fermentation time and by

overgrowing the amine producing background flora (9). They can cause a rapid pH-decrease in the

food product, which has been related to lower levels of BA (10). In order to optimally limit BA-

production, careful selection of the starter culture is vital and should take into account their safety,

17

their competitiveness and their ability to influence the organoleptic properties of the product.

Ideally, starter cultures are decarboxylase negative and dominant towards amine producing MO (1).

2.7 EXPOSURE AND RISK ASSESSMENT

After discussing the kind of hazard biogenic amines form and the importance of controlling their

concentrations in food products, it is of equal importance to define precisely where the hazard of

these compounds lies (which food products, which BA, which concentration, ...) and what is the

actual risk run by a population (in this case, the Belgian population). This can be estimated by a

process called risk assessment. In the context of food safety, risk assessment is defined as the

assessment of health risks from a variety of compounds that can be present in food (33). It is a

scientific process comprising 4 steps: hazard identification, hazard characterization, exposure

assessment and risk characterization. Its goal is to provide a scientific basis for the implementation of

measures aiming at risk-reduction (34). Hazards are defined as biological, chemical or physical agents

that are able to cause an adverse health effect. Risks, on the other hand, are defined as the

probability of the occurrence of an adverse health effect and its severity (35).

In short, during hazard identification, one identifies what is the cause of a certain known adverse

health effect. In this thesis, identification of the hazard is elaborated under 2.1. Biogenic amines.

Hazard characterization then comprises further characterization of the symptoms and mechanisms

of the adverse health effect and the determination of the dose-response relationship (see 2.2

toxicology). Next, exposure assessment is aimed at defining (quantitatively or qualitatively) to how

much of the hazard a person is exposed during a certain period. Finally, risk characterization

combines the exposure and dose-response data in order to estimate the probability and severity of

the problem. In each step, variability’s and uncertainties should be identified (34; 35). This

knowledge can then be used by the authorities to define policy measures, such as legal limits,

monitoring or measures at company level (33).

Risk assessments can be executed qualitatively or quantitatively. Quantitative risk assessment

comprises mathematical analysis of numerical data and is usually preferred. In case of limited data or

time, however, one must conduct a qualitative risk assessment, which is a descriptive technique.

Qualitative risk assessments can also be applied as a first estimate of the food safety issue, in order

to determine if further, more detailed analysis is warranted (34).

An exposure assessment is performed by combining concentration and consumption data, in order to

define the level of exposure (Figure 10). Consumption data collected on an individual level ideally

stems from dietary records (food diary’s) or 24h-recalls. Next to information on the types and

amounts of food eaten, it should also contain additional information about the food products

(brands, packaging, preparation) and the consumer (age, body weight, nationality, …). Concentration

data usually originate from National monitoring programs (36).

18

Figure 10: Probabilistic risk assessment: exposure assessment for one hazard and one food type (own figure).

Exposure assessments can either be performed deterministically, using only single values (e.g. mean

values or P95-values) or probabilistically, using a Monte-Carlo simulation and resulting in an

exposure distribution. Exposure distributions provide a view on both the likelihood and the range of

exposure values and also directly display uncertainty and variability, which makes probabilistic

modelling the method of choice (35; 34).

Traditionally, risk assessment usually focused on only one hazardous compound in a particular food

product (37; 38). Nowadays, however, attempts are made to assess the risks associated with more

complex (and more realistic) situations. As such, cumulative risk assessment estimates the risks

associated with exposure to multiple hazards (compounds) related to a single adverse health effect

or target (Figure 11). On the other hand, aggregated risk assessment, is concerned with the risk

associated with exposure to one hazard via multiple routes/sources/pathways (Figure 11). The

Euromix (39) and Acropolis Project (40) are both examples of this more complex view on risk

assessment. They are both research projects which aim at assessing the risk of exposure to mixtures

of chemicals.

Figure 11: Illustration of the principles of cumulative (left) and aggregated (right) risk assessment (41).

Also for the BIOGAMI-project, the aim is to perform a risk assessment for multiple BA in multiple

classes of food, which might comprise the following steps. Firstly, for each combination of BA and

food class, a separate exposure assessment can be executed. Each of these distributions can then be

compared to the specific toxic levels known for each BA (vide supra). Secondly, for each individual

BA, the total exposure per meal or per day could be calculated by summation of exposure data over

all food classes (aggregate exposure assessment)(40). This can be done based on a previously

19

calculated average consumption pattern per day, or, as not all people consume all sources of BA

every day, on individual daily consumption data (1). These values of total exposure can equally be

compared to toxic amine-levels. Analysing the exposure data will also reveal which food classes offer

the biggest exposure levels of a certain BA and thus, which kinds of food offer the biggest risk. Risk

managers can then target these food groups in their development of policy measures (1).

Lastly, a cumulative exposure assessment could also be performed. Cumulative risk assessments aim

to assess the combined risk associated with multiple stressors (38). In the scope of this project, that

would mean looking at the combined effect of all BAs within one food group, keeping the

interactions between the different BA in mind. Considering the limited amount of quantitative

information on these interactions, and since the toxic mechanisms and dose-response relationships

differ for each BA, it would be no use to add up the exposure values of BA within one food group. A

qualitative comparison of the BA-profiles of different food groups would still be possible, though.

20

3. MATERIALS AND METHODS

3.1 EXPERIMENTAL OUTLINE

As was previously stated, the experiments carried out for this thesis fall under the BIOGAMI-project.

They thus had the objective to characterize the biogenic amine content of several foods on the

market and to assess the toxic risks for the Belgian Population.

For this thesis, the focus lay on the analysis of meat and meat products and fish. The experiments

that were performed could be divided into two main parts. Firstly, three storage tests were carried

out. The first one on tuna, the second one on marinated pork and the third one on three types of

other marinated meat, namely chicken, lamb and beef. The second big part of the experiments

comprised screening of several commercially available food products, belonging to 6 predefined food

groups (see further). The goals and design of these experiments are discussed below.

Through each of these experimental parts, 3 major types of analyses were carried out. These are the

determination of the biogenic amine concentration in the products, the determination of free amino

acids and the microbiological analyses of the samples. These 3 methods will be discussed further on.

3.1.1 Storage tests

3.1.1.1 Storage tests tuna and marinated pork

The storage tests for tuna and marinated pork were carried out in order to get an insight on the

profiles of the biogenic amines that could be formed in the different products and under different

storage conditions. Both tests had a similar design. The products were bought in batch quantities at

their producing companies at the day of production (day 0) and packaged at the university, after

which they were stored until their expiration date plus one day (5+1 days for tuna and 8+1 days for

the pork meat). Half of the samples were MAP-packaged (70/30 O2/CO2), while the other half was

stored under air. The atmosphere under which the MAP-packages were stored was based on

measurements of atmospheres in commercial packages of tuna and pork meat. The amount of

sample to use per package and the ratio product/headspace were based on commercial packages as

well.

Table 3 represents the design of the storage test for tuna. The design of the storage test for pork is

similar and given in appendix 1. As can be seen in table 3, storage was carried out using 3

temperature-profiles. One part of the samples was kept at 7°C for the whole storage time. A second

part was first kept at 22°C for 3 hours and was then stored at 7°C. The third part of the samples was

stored at room temperature (22°C) during the whole storage time. Storage at 7°C was carried out in a

lab refrigerator. Storage at 22°C was executed in a 22°C incubator. Also, all tests were carried out in

double, so for every condition on every day, two packages were available.

Several analyses were carried out during storage. Tuna samples were analysed on days 0, 3, 5 and 6

of storage. Pork samples were analysed on days 0, 3, 5, 8 and 9. On day 0, the analyses comprised

determination of BA, FAA and microbial load. On the other days, only biogenic amines and

microbiology were determined. Next to these main analyses, also pictures were taken each day of

analysis, the atmosphere in the packages was determined and the pH of the samples was measured.

Also, as the analyses were carried out, attention was paid to the sensorial aspects of the products –

odor and outlook – in order to assess whether or not a consumer would judge the product as being

21

spoilt or not. It was particularly expected that the marinade on the pork’s meat might be able to

camouflage spoilage to a certain extent.

Table 3: Design of the 6-day storage test for tuna.

Day 0 Day 3 Day 5 Day 6

Number of

samples Analyses

Number of

samples Analyses

Number of

samples Analyses

Number of

samples Analyses

7 °C

Pictures, atmosphere, pH, BA, FAA,

MO, Sensorial

Pictures, atmosphere, pH, BA, MO,

Sensorial

Pictures, atmosphere, pH, BA, MO,

Sensorial

Pictures, atmosphere, pH, BA, MO,

Sensorial MAP

2 2 2

AIR 2 2 2 2

22°C + 7°C Pictures,

atmosphere, pH, BA, MO,

Sensorial

Pictures,

atmosphere, pH, BA, MO,

Sensorial

Pictures,

atmosphere, pH, BA, MO,

Sensorial

MAP

2 2 2

AIR

2 2 2

22°C Pictures,

atmosphere, pH, BA, MO,

Sensorial

Pictures,

atmosphere, pH, BA, MO,

Sensorial

Pictures,

atmosphere, pH, BA, MO,

Sensorial

MAP

2 2 2

AIR

2 2 2

Total samples

2

12

12

12

3.1.1.2 Storage test marinated meats

The storage tests for the marinated chicken meat, lamb meat and beef had a different objective than

the previous ones: here, the goal was to study the differences between the different types of meat

concerning their biogenic amine profiles. The setup of the storage test (given in appendix 2) was

similar to the previous storage tests, although this time, the storage conditions were not varied.

Instead, one set of storage conditions, used in the previous storage tests, was chosen: MAP-

packaging (70/30 O2/CO2) and storage in the refrigerator at 7°C. These storage conditions were the

most representative of how it is advised to store fresh meat products. The samples were again stored

for 9 days (= TGT + 1 day) and analyses of biogenic amines and microbiology were carried out on days

0, 8 and 9. Free amino acids were only determined at day 0. Here, again, the sensorial features of the

products were assessed.

3.1.2 Screening tests

3.1.2.1 Objective

During the BIOGAMI-project, screening tests were performed in order to gain insight on the

concentration of several BA in products on the Belgian food market. These concentration data,

together with toxicological data on these BA, would then be used to assess the health risks

associated with BA for the Belgian population. The screenings started in October 2014 and ended in

April 2016. In total, a number of 476 products were screened over 6 different food groups in which

BA were expected to occur (due to microbial activity): fruit and vegetables (F&V), chocolate, beer,

meat and meat products, diary and fish and fish products. In each of these food groups certain

subgroups were defined (cfr. appendix 15).

22

3.1.2.2 Design

The design of a screening test is depicted in figure 12 and comprised 1) purchase of the products, 2)

analysis of biogenic amines, microbiology and FAA as quickly as possible, 3) storage until TGT + 1 day

or THT + 10% at 7°C in a refrigerator and 4) analysis of BA and microbiology at the end of the storage

period.

DAY 0 STORAGE (7°C) DAY X

Day of purchase or day after TGT + 1 day/ THT + 10% shelf life

FAA BA

BA MO

Figure 12: Design of a screening test, executed for the BIOGAMI-project.

The products to be analysed were purchased with the aim of comprising as much of the Belgian

market as possible, meaning that it was attempted to obtain products from all over Belgium and in

different types of shops. They were thus bought in supermarkets of all sorts as well as from small

producers and small facilities like groceries and butcheries. Each product was bought threefold, once

for day-0 analyses, one for end-of-storage analyses and one backup sample.

After purchase, the first analyses were executed as quickly as possible. At the start of the analyses,

the product was given a sample number, it was photographed and, next to the FAA and BA –

concentrations, gas concentrations of packed products were measured using a PDI-Dansensor and

pH-values were tested with Mettler Toledo pH-meter with an Inlab Solids electrode (details on these

apparatuses can be found in appendix 4).

Note also that for some products, only the analyses at day 0 were performed. This was done for

products for which no significant change in BA concentration was expected between the start and

the end of storage. As such, there were microbially stable products with a long shelf life (say: over 6

months), for instance raw dried hams, or fermented products like certain salami’s, cheeses and

sauerkraut. In these products it was expected that the major amount of biogenic amines were

already formed at purchase, by previous fermentation or ripening, and that as these products are

more or less microbially stable (meaning growth nor activity)(42), no further amine formation would

follow.

3.1.2.3 Focus of this thesis

Within the scope of this Master dissertation, several categories of meat products and preparations

were studied. According to EU-Directive 853/2004, meat products are defined as “processed

products resulting from the processing of meat or from the further processing of such processed

products, so that the cut surface shows that the product no longer has the characteristics of fresh

meat”. These products are ready-to-use products. In this category, hams and salami’s have been

analysed. On the other hand, meat preparations are defined as “meat that has foodstuffs,

seasonings or additives added to it or which has undergone a treatment that is insufficient to modify

the cellular structure of the meat and thus to cause the characteristics of the fresh meat to

disappear”, for example marinated pieces of pork and sausages. These kinds of products usually need

a cooking step at home. Moreover, the EU-definition of minced meat is “boned meat that has been

minced into fragments and contains less than 1 % salt”. Minced meat must have been prepared

23

exclusively from skeletal muscle (including adherent fatty tissues) that complies with the

requirements for fresh meat.

First, 25 samples of fermented sausages (salami’s and dried sausages) were analysed, followed by 44

types of non-fermented meat products (cooked hams, dried and cured hams and dried and cured

beef products). Lastly, screening of 40 samples of meat preparations (hamburgers, schnitzels,

sausages) was carried out. These were divided over 4 types of meat, namely pork, chicken, lamb and

beef (MAP-packaged products as much as possible) according to the results of the third screening

test.

3.2 EXPERIMENTAL ANALYSES

3.2.1 Free amino acids

3.2.1.1 Principle

FAA-concentrations were determined via reversed phase chromatography

on an Agilent 1100 series HPLC-apparatus (Figure 13). For identification and

quantification, both an internal standard (IS) and a calibration curve were

used. During the sample preparation, the FAA were first extracted from the

food matrix with trichloroacetic acid (TCA), which precipitates proteins, and

derivatized with o-phthalaldehyde (OPA) and 9-fluorenylmethyl

chloroformate (FMOC) in the injector of the HPLC. The FAA which were

determined were: alanine, arginine, asparagine, aspartic acid, glutamine,

glutamic acid, glycine, isoleucine, leucine, lysine, methionine, ornithine,

phenylalanine, proline, threonine, tryptophan and tyrosine. Materials used

for the FAA - protocol can be found in appendix 4.

3.2.1.2 Reagents

Reagent Extra Information

15% TCA

Dissolved in water 0.1M HCl

4 M HCl

10 M NaOH

Internal standard 10 nmol/µl sarcosine and norvaline in water Mobile phase A 100% MeOH Mobile phase B 50/50 ACN/H2O Mobile phase C NaH2PO4.10H2O (3.58g/L), Na2B4O7.10H2O (3.81 g/L) and NaN3 (0.33 g/L) in

water. pH adjusted to 8.2 with 25% HCl, then filtered over 0.45 µm filter Mobile phase D 45/45/10 ACN/MeOH/H2O 0.4 M Borate buffer pH 10.2 (adjusted with 10M NaOH) , filtered over 0.2 µm OPA – solution 25 ml flask: 250 mg o-phtalaldehyde + 250 mg 3-mercaptopropionic acid in

borate buffer FMOC – solution 10 ml flask: 25 mg 9-fluorenylmethylformate in HPLC-grade ACN Dilution solvent 100 ml mobile phase C + 0.4 ml H3PO4 AA1 standard solution 16 nmol/µl asparagine, glutamine, tryptophane and citrulline in H2O AA2 standard solution 1 nmol/µl alanine, arginine, aspartic acid, glutamic acid, glycine, histidine,

isoleucine, leucine, lysine, methionine, ornithine, phenylalanine, proline, serine, threonine, tyrosine and valine in 0.1 M HCl

100% hexane Only for fatty food products (> 30 w% fat)

For information on the producers and the product codes, see appendix 3.

Figure 13: Agilent 1100 Series HPLC-apparatus for FAA-determination.

24

3.2.1.3 Protocol

The procedure for FAA-determination was as follows. First, 3.5 g (± 0.5g) of sample was added to a

50ml falcon flask. If the structure of the sample was not homogenous or easy to transfer, the whole

sample was first mixed using a commercial immersion blender. After weighing, 30 ml of 15% TCA was

added, the sample was further homogenized using an Ultra Turrax and left to extract for at least 10

minutes. Next, the pH of the sample was adjusted to 2.2 with 10M NaOH and/or 4M HCl and filtered

over a nitrogen-free paper filter into a 15 ml falcon tube. To avoid deterioration of the FAA, the

extracts were kept at 4°C in the dark as much as possible between the analysis steps.

Note: when analyzing fatty food products (>30 w% fat), like cheese, fermented sausage and cured

hams, an extra step needed to be implemented. Because the apolar fats react with the C18-column,

giving rise to erroneous chromatograms (split peaks etc.), fats were extracted by addition of 10 ml

hexane just after pH-adjustment. Vigorous shaking allowed maximal extraction and centrifugation at

8000 g for 3 minutes was used to separate the hexane and TCA-layers. The upper layer (hexane)

would then be pipetted and discarded. This procedure was repeated once again, before continuing

with the normal protocol.

After paper filtration, the samples were filtered again over an HPLC filter (0.45 µm) in order to

remove small particles which could cause clogging of the HPLC-system. After that, the pH of the

extracts was controlled using pH-strips (aim: between 2 and 4) and an HPLC-vial was prepared with

950 µl of filtrate and 50 µl of IS. Per sample, a second vial with pure HPLC-water was prepared for

rinsing. Also, 7 vials containing a standard series of AA were prepared. Finally, 5 more vials were

prepared: one containing borate buffer, one with OPA, one with FMOC, one with 100% acetonitrile

(ACN) (rinsing) and one containing a dilution liquid for injection. The vials were placed on a tray in the

HPLC-machine.

For the internal standard, a stock solution of norvaline and sarcosine in water, both at 10 nmol/µl,

was used. The standard series was prepared using a standard solution AA1, which contained the

basic amino acids at 16 nmol/µl dissolved in water, and a standard solution AA2 containing the acidic

and neutral amino acids at 1 nmol/µl in 0.1M HCl. Table 4 shows how, starting from these stock

solutions, a standard series ranging from 0 to 800 pmol/l was made.

Table 4: Overview of how to prepare the standard series.

Dilutions for calibration curve of amino acids

AA1 dilutions

Conc. (pmol/l) 800 400 200 80 40 20 0 Volume H20 (µl) 200 300 180 190 390 Volume AA1 (µl) 50 200 100 20 10 10 Total Volume (µl) 50 400 400 200 200 400

=>Take 50 µl of these solutions to make the calibration curve

Calibration curve

Conc. (pmol/l) 800 400 200 80 40 20 0 Diluted AA1 (µl) 50 50 50 50 50 50 IS (µl) 50 50 50 50 50 50 50 AA2 (µl) 800 400 200 80 40 20 0.1 M Hcl (µl) 100 500 700 820 860 880 950

Total Volume (µl) 1000 1000 1000 1000 1000 1000 1000

25

Derivatization with OPA (primary AA) and FMOC (secondary AA) was carried out automatically in the

injector of the HPLC. The FAA were separated on a Zorbax Eclipse Plus C18 column (P/N 959963-902)

from Agilent Technologies. Also, a pre-column (P/N 820950-936) was used to protect the column

against impurities. For optimal separation, a gradient program was performed, which made use of 4

mobile phases. Mobile Phase A and B were used for rinsing. Mobile phase C (polar) and mobile Phase

D (apolar) were used to create the gradient by changing their ratio (Figure 14). De derivatized FAA-

compounds were detected using a fluorescence detector. Other conditions used were a column

temperature of 40°C, a flow rate of 1.5 ml/min and a ratio of mobile phases C/D of 95/5 at the start.

Figure 14: Illustration of the gradient program for the separation of FAA. Solvent A: mobile phase A; Solvent B: Mobile Phase B; Solvent C: mobile phase C; Solvent D: mobile phase D.

3.2.1.4 Calculation of FAA-concentration

After receiving the chromatogram, the original FAA-concentrations were calculated out of the peak

areas using a standard curve. The first step in these calculations was to express the retention times

and areas of each peak in relation to those of sarcosine (for proline quantification) and norvaline (for

all other FAA). Using the relative retention times, the peaks could be identified and the

corresponding relative areas were then converted to relative concentrations by use of the slope and

intercept of the standard curve (vide supra). Lastly, the following formula was used to perform the

final step, converting the relative FAA-concentration to the original concentration in the sample

(mg/kg).

CRel = CAZ/CIS; CIS = internal standard concentration in the HPLC-vial (mg/ml); CAZ = AA-concentration in the HPLC-vial

(mg/ml); MMAZ = molar mass of the AA (g/mol); Vextract = volume of the extract (ml); msample = weighed amount of sample

(kg)

3.2.2 Biogenic amines

3.2.2.1 Principle

Determination of BA-concentrations was again performed via reversed phase chromatography, this

time using UHPLC and detection via a diode array detector (DAD). Just like the FAA, the BA were

extracted from the food product using 15% TCA. In order to compensate for losses during sample

preparation, an internal standard (1,7-diaminoheptane) was added and dansyl chloride was used as a

derivatising agent. The BA of which the concentration was determined were: cadaverine, histamine,

β-phenylethylamine, putrescine, tyramine and tryptamine.

26

3.2.2.2 Reagents

Reagent Extra information

15% TCA 100% Acetone Dichloromethane 99.9% pure Internal standard 2 mg/ml 1,7-diaminoheptane in 15% TCA Na2CO3 (saturated solution) pH adjusted to 11,2 before use Dansyl chloride solution 5 mg/ml in acetone ACN/water 65/35 (HPLC grade)

For information on the producers and the product codes, see appendix 3.

3.2.2.3 Protocol

The extraction procedure for BA is similar to that for FAA, yet still slightly different. Weighing was

carried out similarly. After weighing, 60 µl of IS was added, before adding 30ml TCA and mixing with

the Ultra Turrax. After 10 minutes of extraction, the extract was again filtered. In this procedure, it

was equally important to keep samples, extracts and filtrates in the dark and at 4°C as much as

possible.

Derivatisation was then performed in glass test tubes with screw caps. In these tubes, 1 ml of filtrate

was added, together with 0.75 ml of saturated NaCO3-solution. Next, 1 ml of dansyl chloride solution

was added, the test tubes were vortexed and immediately placed in a hot water bath of 40°C for 1.5

hours. During this time, the test tubes needed to be shaken vigorously every 10 minutes, in order for

the dansyl chloride to come into contact with the biogenic amines. The rack in which the test tubes

were placed was wrapped in aluminum foil because the derivatized compounds are sensitive to light

(42).

After derivatization, extraction of the BA followed immediately. This was performed by adding 2 ml

dichloromethane (DCM), vortexing, letting the phases set and pipetting both phases in two other test

tubes. This procedure was repeated another two times, each time working with the watery phase

from the previous step. When separation did not happen fast enough (within 10 minutes) or was

incomplete because of formation of an emulsion, an alternative approach was used, in which 3 ml

DCM was added and emulsion was centrifuged at 8000g (in plastic falcons) for 3 minutes. This was

then only performed twice. After extraction, the organic phase (DCM) was dried under N2, after

which the tubes could be stored in the freezer (-20°C).

The dried residue was subsequently dissolved by adding 1 ml 65/35 ACN/H20 to the test tubes.

Vortexing and the use of an ultrasonic water bath made sure everything was dissolved. The samples

were then filtered through 0.45 µm HPLC-filters and added to HPLC-vials. These vials were placed in

the UHPLC-apparatus (Figure15) for BA-analysis.

27

Figure 15: UHPLC-apparatus: Dionex Ultimate 3000.

The UPLC apparatus consists of several units: 1) a pump, which is able to mix up to 4 different

solutions, 2) a sampler, 3) the column unit and 4) the detector. The UHPLC – column used in this

protocol was an Acclaim RSLC 120 C18 column (particle diameter of 2.2 µm, column diameter 2.1

mm and column length 150 mm) at a temperature of 40°C. During each sample run, the gradient

pump provided for a flow of 0.5 ml/min and a gradient in ACN/H2O (Figure16). Finally, the BA-

derivatives were detected with the DAD measuring at a wavelength of 225 nm.

Figure 16: Gradient in mobile phases during UPLC-analysis.

3.2.2.4 Determination of BA-concentration

The chromatograms, resulting from the UPLC-procedure, were used to calculate the original BA-

concentrations in the food samples. First, the peaks were identified using retention times, relative to

the internal standard. Next, relative areas were calculated and used to determine the original BA-

concentrations in the food product. In this calculation, corrections for the concentration of IS (CIS),

the volume of the sample (Vsample), the amount of sample weighed (msample) were required and

executed using the following formula.

28

Rel Conc: CBA in standard/CIS in standard; a = slope of calibration curve; b = intercept of the calibration curve; Vextract =

volume of the extract (ml); msample = weighed amount of sample (kg).

Correct quantification of BA in food products also required correcting for the effect of the food

matrix. The food matrix consists out of every component of the food product that is not a BA and

may give rise to higher or lower amounts of detected BA than are actually present. This means that

the ratio of the amount of BA detected and the true amount (i.e. the recovery value), does not equal

100%. Correction was carried out by dividing the calculated BA-concentrations by these recovery

values, which were already determined before the start of this master dissertation and are presented

in appendix 5, table 42. The calibration curves (one per BA) used in these calculations were already

determined as well and are presented in appendix 5 tables 43, together with the LOD and LOQ

values, calculated out of the slope and intercept of these calibration curves.

One last note here is that when excessive BA-concentrations were present in a food product, the

corresponding peak could be much higher than the IS-peak, making correct quantification impossible.

In this case, the extract was diluted and reanalysed and the dilution was included in the calculations

by supplementary dividing the BA-concentrations by the dilution factor.

3.2.3 Microbiology

3.2.3.1 Principle

Microbial analyses were carried out in order to be able to link the presence of BA with that of MO in

a food product or in other words, to establish a view on the possible BA-forming bacteria. Therefore,

the contamination by several groups of MO (total count, LAB, Enterobacteriaceae, Enterococci,

Pseudomonas, Clostridia and Staphylococci) was determined by means of plating on their

corresponding media. After incubation, colony forming units (CFU) were counted and the original

MO-concentration of the products was calculated. Also, for food products which demonstrated high

counts of BA (> 100 mg/kg), the MO of certain plates were further characterized, but these analyses

fell out of the scope of this thesis. Materials used during the microbial analyses can be found in

appendix 6.

3.2.3.2 Plating

Table 5 shows an overview of the types of media used during microbial analysis of the samples.

However, not every bacterial group was determined for every type of sample. Clostridia, for instance,

were only determined in fish and fishery products and Staphylococci only in meat-based products.

Total bacterial count, LAB, Enterobacteriaceae and Enterococci were plated for every sample. The

VRBG-medium also measured Enterobacteriaceae, but was phased out during the course of the

screening tests, due to a limited added value of the data it yielded. Finally, Pseudomonas counts

were only determined for non-fermented products, as in fermented products, Pseudomonas was

expected to be overgrown by the fermenting flora.

Plating was carried out in a sterile environment, i.e. within a range of 15 cm from a Bunsen flame.

Firstly, from the refrigerated sample, 25.0 ± 0.5 g was weighed out in a stomacher bag. This sample

was then diluted 10 times with PPS and homogenized in the stomacher for 1 minute. Then, out of

this first dilution, a dilution series was prepared by each time transferring 1 ml of a dilution in a test

tube containing 9 ml PPS. Subsequently, several of these dilutions (3 for each sample) were plated

out. Which dilutions were plated differed between food groups and between media and was initially

determined by experience and scientific literature on how many CFU would be present on a certain

29

sample after a certain time. The goal of this method was to end up with at least one countable plate

for each sample, which means 15 – 150 CFU/plate for streak plates and 30-300 CFU/plate for pouring

plates. Streak plates were made by transferring 0.1 ml of the desired dilution onto a prepared streak

plate. For pour plates, 1 ml of a dilution was added in an empty plate, after which it was covered with

the desired medium. Some media (MRS and RE) also required a second layer of medium, in order to

create a microaerophilic environment for the MO below.

During plating, pouring media were kept at 48°C in a hot water bath. After plating the streak plates

were left to dry and the pour plates were allowed to cool down and jellify for a few minutes. Then

the plates were incubated at the appropriate temperatures for a specific amount of days. Table 5

indicates clearly which media were used, how to prepare and incubate them and how to count the

bacterial colonies after incubation.

Table 5: Media used during microbial analysis of food samples. PCA = pate count agar; MRS = de Mann Rogosa and Sharpeagar; RE = Rapid Enterobacteriaceae; MSA = Mannitol Salt Agar; SB = Slanetz and Bartley agar; KAA = Kanamycin Esculin Azide agar; PA = Pseudomonas agar; RCA = Reinforced Clostridial agar, VRBG = Violet Red Bile Glucose agar)

Medium MO Type of plate Code Incubation Colonies

PCA Total aërobic count Pour OM13 22°C, 4-5d Count everything MRS Lactic acid bacteria Pour + cover OM4 + 0,9 ml/L

12M HCl 22°C, 4-5d Count everything

RE** Enterobacteriaceae Pour + cover OM68 37°C, 18-24h

Purple –pink colonies

VRBG * Enterobacteriaceae Pour + cover 37°C, 18-24h

Purple –pink colonies

MSA***** Staphylococci Streak OM41 37°C, 24+24h

Coag +: lichtgele zone, coag-: red/purple zone

SB** Enterococci Streak / 37°C, 4h; 44°C, 44h

Pink, dark red or bordeaux with whitish edge

KAA Enterococci Streak (bev.) + sup KAA before autoclaving

37°C, 48h Black colonies, black halo

PA*** Pseudomonas Streak + 5 mL glycerol, OM52 + OS4

30°C, 48h Everything (Often blue-green or brown pigmentation)

RCA**** Clostridia Pour + cover 22°C, 4-5d, anaerobic

Count everything

*: Cook without autoclaving; day of usage

**: Cook without autoclaving

***: Add supplement after autoclaving

****: Only fish samples *****: Only meat samples

After incubation, the countable plates were counted for each sample and the original concentration

of bacteria per gram of sample was calculated using the following formula:

If growth was detected on SB plates, colonies were picked from these plates and inoculated on KAA

plates for confirmation of their nature (Enterococci should result in a black halo). Only if a colony was

positive on both the SB and the KAA-plate, their growth was registered.

30

3.3 STATISTICAL ANALYSES

3.3.1 Objectives

When the screening tests were finished, statistical analyses were performed on the collected data in

order to answer all research questions mentioned in the introduction section. The central point of

these analyses were the BA-concentrations detected in each screened food product, which were

combined with the FAA-concentrations on day 0 (A-values) and the microbial counts at the expiry

date (B-values).

The questions to be answered during the statistical analysis were:

PART 1

1) Is there a significant difference in BA-concentrations between fermented and non-

fermented foodstuffs

a. … at day 0?

b. … at the expiry date?

c. … in the evolution between day 0 and the expiry date?

2) Is there a significant difference in BA-concentrations between animal products and products

of plant origin

a. …at day 0?

b. … at the expiry date?

c. … in the evolution between day 0 and the expiry date?

3) Is there a significant difference in BA-concentrations between fermented and non-

fermented foods within animal products and products of plant origin

a. …at day 0?

b. … at the expiry date?

c. … in the evolution between day 0 and the expiry date?

PART 2

4) For each of the six BA, is there a significant difference in concentration between the

different major food groups (F&V, chocolate, beer, dairy and meat products)?

PART 3

5) Is there a correlation between the FAA-concentrations at day 0 and

a. the BA-concentrations at the expiry date?

b. the evolution in BA-concentration?

6) Is there a correlation between the microbial counts and

a. the BA-concentrations detected at the expiry date?

b. the evolution in BA-concentration?

3.3.2 Preparation of the database

In the end, screening tests resulted in a database containing all collected information on 476 food

products: their BA- and FAA-concentrations, their microbial contamination, their pH, the atmosphere

in the packages and additional information (producer, product name, etc.). In preparation of the

statistical analysis, this raw database was condensed into a single datasheet containing all

information relevant for answering the questions above. The datasheet contained for each food

product its concentration of 6 BA (cfr. 3.2.2) and 7 FAA (cfr. 3.2.1) and the microbial counts

31

measured on for several bacterial groups (cfr. 3.2.3). Two binary variables, stating if the product was

fermented or unfermented and animal or plant based, were also included in this sheet, as well as a

categorical variable, stating which food group it belonged to. Table 6 shows the structure of this

datasheet.

Note that for the products for which no B-data (at the expiry date) were available, the BA-

concentrations at day 0 were used for both timepoints (both A and B), as in these products the BA-

concentrations were assumed fairly constant (see 3.1.2). Also, although 476 food products had been

screened, the summarizing datasheet comprised only 425 food products. First of all, the data for fish

products were left out (46 samples), because the analyses of this food group hadn’t been finished by

the time the statistical analyses were carried out. As literature already contains a considerable body

of information on BA in fish and their major toxic concern (scombroid fish poisoning) and as legal

limits have already been established for histamine in certain fish products, this decision was not

considered a flaw in the study (1; 19; 8; 16). Next, 2 more samples were left out because of

incomplete data and 3 more because the reason for their analysis fell out of the scope of this study.

Notice also that the elimination of the fish samples reduced the number of food groups from 6 to 5,

so only F&V, beer, chocolate, dairy ad meat products and preparations were left for analysis.

Table 6: Structure of the datasheet, used for the statistical analysis. (M = Agar medium)

Sample nr.

Food Group

Fermented/ Unfermented

Animal/Plant BA1 … BA6 FAA1 … FAA7 M 1 … M9

1 … 425

3.3.3 Part 1: T-tests fermented vs. non-fermented and animal vs. plants

In order to answer the first three questions under 3.3.1, mean comparisons using independent two-

sample tests were estimated to be most useful. Before execution of these t-tests however, some

preparatory steps were required. During a first step, out of the first raw datasheet mentioned above

only BA-data and the factors fermented/non-fermented and animal/plant were taken. These were

then condensed into 3 subset datasheets: one with BA-concentrations at day 0 (A-data), one with BA-

values collected after storage (B-data) and one with evolutionary data (B minus A). In order to be

able to produce clear graphs, all BA-concentrations were log-transformed using the following

formula: . Evolutionary data were generated by

subtraction of the log-transformed A-data from the log-transformed B-data.

It should also be mentioned that from the B-data (and by consequence also the evolutionary data)

the first 32 samples were deleted. These data did not originate from normal screening tests but from

extended storage tests, during which the samples were kept in the fridge until twice their shelf life.

The BA-concentrations of these products at the second day of analysis was thus presumably higher

than at the end of their shelf life, thus no meaningful evolutions could be generated.

After preparation of the datasheets, a first exploratory analysis comprised the generation of boxplots

using the ggplot-function in the ggplot2 package in R, in order to get an idea on the behavior of the

BA-data. Next, independent two-sample t-tests were performed in R using LIMMA to compare

fermented vs. non-fermented food products, animal vs. plant-based products and fermented vs. non-

fermented within animal or plant products. This analysis scheme was executed for the three above

32

mentioned subsets. Considering that erasing the first 32 samples from the B- and evolutionary data

meant removing all non-fermented plant-based food products, the comparison of fermented vs. non-

fermented foods within plants could not be executed for the B- and evolutionary data. As such,

instead of 12 t-tests, only 10 were performed. The influence of multiplicity on the p-values was

adjusted for using the Benjamini-Hochberg FDR procedure.

3.3.4 Part 2: ANOVA-tests for difference between food groups

For the comparison of the means of the BA-concentrations between all five food groups (question 4),

the aim was to use ANOVA-tests in SPSS, with a Bonferroni-correction for multiple comparison.

Homogeneity of variances was tested within the groups as well (using the Levene's test) and in case

of non-homogeneity, Welch F-tests and Games-Howell post hoc tests were used to replace ANOVA

and Bonferroni-tests respectively. This scheme was applied to the same three subsets mentioned in

part 1.

Next to these mean comparisons, graphs were produced in excel to function as a background during

the discussion. In these graphs, the mean BA-concentrations and the standard deviations in each

food group are presented.

3.3.5 Part 3: Correlation analysis

In order to determine the correlations mentioned in questions 6 and 7 under 3.3.1, redundancy

analysis and multiple regression were chosen as suitable techniques based on an article from

Desdevises et al (2011). Redundancy analysis is a direct gradient analysis (canonical ordination) which

allows to determine which proportion of the variance in the response variables (here the BA-

concentrations) can be explained by the variance in a set of explanatory variables (the FAA-

concentrations, the microbial data and the factors fermented/non-fermented and animal/plant). In

short it consists out of a series of multiple linear regressions carried out for the different response

variables, followed by a principle component analysis (43). The results of this type of analysis can be

presented in either a bi- or a triplot, based either on (Euclidean) distances between objects or on

correlations. In the current analyses, correlation-based triplots (displaying both response and

explanatory variables) were generated, which were then used for the qualitative description of the

correlations between BA, FAA and microbial data (44).

After the execution of the RDA, a multiple linear regression analysis (MLR) combined with an ANOVA-

test for significance provided for a more quantitative approach to the sought correlations. This

combination of analyses would select for each BA a set of explanatory variables significantly

contributing to its variance and thus correlating with it. The selection of variables was based on the

Akaike’s Information criterion (AIC).

The correlation tests were again performed in R. RDA was performed using the 'rda'-function in the

'vegan' library and MLR and ANOVA were executed using the 'lm'- function. Correlations between

BA-concentrations and FAA (question 6) were determined separately from those with microbial data

(question 7). Also, correlations were only determined for B- and evolutionary data, because the aim

was to study the development of BA during storage. As such, correlations between FAA and A-data

(BA-concentrations at day 0) would be meaningless, since they were both measured on the same

day. Likewise, determining the correlation of A-data with microbial data at the end of storage would

be meaningless, since microbial growth an BA-formation are still happening during storage. In

microbially stable products, like beer or chocolate for instance, these correlations could be

33

meaningful, as the majority of BA-formation has happened before purchase in these products, but as

stated before, no analysis after storage were performed on these products, making correlation

analysis impossible by lack of microbial data.

In preparation for the correlation analysis, again, new datasheets were prepared starting from the

raw datasheet mentioned under 3.3.2. For the correlation analyses with FAA, two sheets were

arranged: one containing (log-transformed) B-data and on containing (log-transformed) BA-

evolutions. In these sheets, all samples for which only day-0 analyses were performed were

removed, as analysis of B- or evolutionary data would not be possible. Further removal of samples

with missing FAA-concentrations lead to datasheets containing BA-data and FAA-data on 335

samples. For the microbial correlations, data-observation lead to the conclusion that 6 separate

sheets would be required, because of the use of different media for different types of products. As

such, both the sheets for the B-data and the evolutionary data were separated into a sheet for F&V,

one for dairy products and one for meat. Should the data not have been separated, then on several

media the microbial counts would have contained too many missing values, making valid and

efficient analysis impossible. After preparation of these six sheets, further cleaning comprised

removing data on media that contained too many missing values (more than 1/3 of the counts in the

particular subgroup) and subsequently removing some samples which contained missing values on

singular agar media. As such, the resulting design of these 6 datasheets is depicted in table 7.

Note also that in each of the above mentioned sheets, FAA and BA-concentrations were again log-

transformed in a similar manner as was done under 3.3.3.

Table 7: Description of the 6 datasheet (after cleaning) that were created to investigate the correlations between BA-concentrations and microbial counts. In the datasheets, log-transformed BA-concentrations were used.

Type of BA-data Subclass N (after cleaning) PCA MRS SB RE MSA PA

At expiry date (B-data) F&V 81 X X X X Dairy 81 X X X X Meat 102 X X X X Evolutionary data (B – A) F&V 81 X X X X Dairy 81 X X X X Meat 102 X X X X

34

4. RESULTS AND DISCUSSION

4.1 INTRODUCTION

During the discussion of the BA-concentrations detected in several products, some toxicological

judgments will be formulated, defining which values form a potential health risk and which do not.

As overall insufficient quantitative data is available on the toxicity of all but histamine and tyramine,

this toxicological discussion will mainly focus on these 2 BA, making use of the toxic intake values

mentioned in the literature study (table 8). Note that in the articles where these toxicological data

were found, no designation was made to the weight of the person to which these values are

applicable. As such, these values should be handled with scrutiny and only for a rough toxicological

assessment. It can be concluded that more accurate toxicological judgment of BA-concentrations in

the future will require renewed investigation of the dose-response relationships of these

compounds. For the following discussion, it was assumed that these toxicological cut-offs apply to

healthy adults (no longer growing individuals) with a healthy BMI (20-25).

Table 8: Guideline for toxicological interpretation of BA-concentrations: Toxic effect at certain intakes for Histamine and Tyramine and their corresponding concentrations in several portion sizes of food products. (Toxicological data: Histamine: Parente et al. 2001 and tyramine: EFSA 2011)

Histamine

Intake per meal (mg) Toxic effect Concentration in food product (mg/kg)

At consumption of 100g At consumption of 200g

Normal person

8 - 40 Light 80-400 40 – 200 40 - 100 Moderate 400-1000 200 - 500 >100 Severe >1000 >500

Sensitive person

NOAEL below LOD Any concentration Any concentration

Tyramine

NOAEL per meal (mg)

Concentration in food product (mg/kg)

At consumption of 50g At consumption of 100g At consumption of 200g

600 mg (healthy subject) 12000 6000 3000 50 mg (third gen. MAOI-

drugs 1000 500 250

6 mg (classical MOAI-drugs

120 60 30

In order to link the detected BA-concentrations with the intake levels in table 8, portion sizes were

required as well. Therefore, the following table shows which portions were considered during the

discussion of several types of food. These values were derived from international healthy eating

guidelines (the Belgian food pyramid) and from portion sizes mentioned on the food packaging. Note

that true portion sizes might and probably will differ from these recommended portions, leading to

different intake levels. These serving sizes were considered good guidelines nevertheless.

35

Table 9: Portion sizes for different types of food, as advised by health organizations or as designated on the packages.

Portion sizes

Fruit 1 piece (> 2 pieces a day)**** Olives 25 g **/ 30 g *** Vegetables 200 g (lunch or dinner)/ 300g a day**** Sauerkraut 200 g ** Chocolate 20-30 g ** / *** Beer 1 bottle (25 -33 cl) Meat 50-75 g */ 100g **** Salami/dried sausage 25 g ** Cooked/ dried cured ham 15 -30 g ** Fish 100 g * Yoghurt 125g */** Cheese 25-50g * *http://www.heart.org/HEARTORG/Caregiver/Replenish/WhatisaServing/What-is-a Serving_UCM_301838_Article.jsp#.VvgR_fmLSM8 **Delhaize direct: http://shop.delhaize.be/nl-be?cmpid=SEA_DD_Brand_NA_Text_Bel_Nl_NA_NA_HP_BrandPur_NA ***Collect and gohttps://www.collectandgo.be/cogostatic/static/nl/index.html ****Active food triangle: http://www.vigez.be/projecten/actieve-voedingsdriehoek

In the discussion of the results, an attempt was also made to link the microbial profile with the BA-

concentrations. Therefore, knowledge was required on which MO are associated with the formation

of which BA in each food product and if these MO were the most prominent bacteria in the product.

The following figure functioned as a guide for these discussions.

Figure 17: Overview of which microorganisms can be responsible for which BA (1; 8; 47) .

4.2 POTENTIAL FOR BA-FORMATION IN TUNA AND MARINATED PORK

Below the results of the storage tests for tuna and marinated pork will be discussed. These tests

were conducted in order to gain an overall insight on the BA-profiles in the meat versus fish and at

different storage conditions. The BA-profiles will be compared to the FAA-profiles and the

microbiological counts to see if any coherent patterns can be found.

Histamine

•GR+ and GR-

•Enterobacteriaceae (Hafnia, Morganella, klebsiella) and photobacterium (vibrionales) in fish

•LAB in fermented foods

Tyramine

•GR+

•Enterococci

•LAB

•Staphylococci

β-Phenylethylamine

•Mostly linked to tyramine-producing bacteria

•Enterococci

•LAB

•Staphylococci

Tryptamine

•Enterococci (Ansorena 2002)

•LAB (Streptococci, Lactococci, Leuconostoc)

•Staphylococci (Ansorena 2002)

Putrescine & Cadaverine

•GR- bacteria

•Enterobacteriaceae

•Pseudomonas

•Shewanella

•LAB

•Staphylococci

36

4.2.1 Storage test tuna

4.2.1.1 Biogenic amines in tuna

The results of the BA-analyses for the storage test on tuna can be found in table 10. From these

results, it’s immediately clear that tryptamine and β-phenylethylamine were not important BA in

tuna. On the contrary, the most important BA in tuna were clearly histamine and cadaverine. It is

also clear that the detected BA-levels were increasingly higher as storage was longer, no matter what

storage condition was applied. The velocity of BA-formation, however, was influenced by the storage

condition. As such, storage at 22°C was by far the most harmful condition to store tuna, giving rise to

excessive histamine concentrations at the end of storage, which were exceeding the reported

toxicological values (see table 8). Moreover, at 22°C, severely toxic levels of histamine were already

formed before the expiry date (already at day 3), making the product unfit for consumption. On the

other hand, refrigeration at 7°C proves to be an effective method to limit BA-production. These

samples only resulted in a maximum of 13 mg/kg of any BA, even at day 6. Properly refrigerated

samples can thus be considered to give rise to low risks of poisoning. Also, 3 hours of storage at 22°C

before refrigeration did not seem to have a big influence on the BA-concentration. Lastly, looking at

these data, it can be concluded that packaging under MAP-conditions does seems to diminish BA-

formation as well. This effect is the clearest for the data of the samples stored at 22°C. Both the

protective effect of MAP-packaging and refrigeration agree with previous findings described in

literature (1; 8; 27; 10).

Table 10: BA-concentrations (mg/kg) on tuna during 6-day storage test. Different storage conditions and packaging techniques were applied. For each storage condition on every day 2 samples were analysed.

Condition Tryptamine β-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

DAY 0

<LOQ <LOD <LOD <LOD <LOD <LOQ

<LOD <LOD <LOD 1 <LOQ <LOQ

DAY 3

7°C – MAP <LOD <LOD <LOD <LOQ <LOD <LOQ

<LOD <LOD <LOD <LOD <LOQ <LOD

22°C – MAP <LOD <LOD <LOQ 17 445 5

<LOD <LOD 2 70 32 <LOQ

3h 22°C + 7°C - MAP <LOD <LOD <LOD <LOD <LOQ <LOD

<LOD <LOD <LOD <LOD <LOQ <LOD

7°C – Air <LOD <LOD <LOD <LOD <LOQ <LOD

<LOD <LOD <LOD <LOD <LOD <LOD

22°C – Air <LOD <LOD 10 96 899 8

<LOD <LOD 9 92 564 5

3h 22°C + 7°C - Air <LOD <LOD <LOD <LOD <LOQ <LOD

<LOD <LOD <LOD <LOD <LOD <LOD

DAY 5

7°C – MAP <LOD <LOD <LOD 2 <LOD <LOQ

<LOD <LOD <LOD 2 <LOQ 2

22°C – MAP <LOD <LOD 2 9 122 4

<LOD <LOD 2 7 170 6

3h 22°C + 7°C - MAP <LOD <LOD <LOD <LOD <LOQ <LOQ

<LOD <LOD <LOD <LOD <LOQ 3

7°C – Air <LOD <LOD <LOQ <LOD <LOQ <LOQ

<LOD <LOD <LOD 1 3 <LOQ

22°C – Air <LOD <LOQ 27 186 2233 <LOQ

37

<LOD 10 85 355 1924 14

3h 22°C + 7°C - Air <LOD <LOD 2 1 2 <LOQ

<LOD <LOD 1 <LOD <LOQ <LOD

DAY 6

7°C – MAP <LOD <LOD <LOD 5 7 4

<LOD <LOD <LOD <LOD <LOQ <LOQ

22°C – MAP <LOD <LOQ 40 152 2357 51

<LOD <LOD 17 79 2699 42

3h 22°C + 7°C - MAP <LOD <LOD <LOD <LOD <LOQ <LOQ

2 <LOD <LOD <LOD <LOQ <LOQ

7°C – Air <LOD <LOD 2 <LOD 4 <LOQ

<LOD <LOD 1 1 4 <LOQ

22°C – Air <LOD 15 80 324 2553 2

<LOD 10 60 238 2199 21

3h 22°C + 7°C - Air <LOD <LOD 2 2 13 <LOQ

<LOD <LOD 3 <LOD 2 <LOD

4.2.1.2 Free amino acids in tuna

Table 11 shows the concentration of the FAA, which were measured on day 0 to provide a view on

the potential precursors for BA-formation. Looking at these data, it can be concluded that this FAA-

profile for tuna coincides nicely with its BA-profile, meaning that the links can be seen between the

BA and their precursors. As such, the highest values were found for histamine, followed by

cadaverine. This agrees with the FAA-concentrations found for histidine and lysine, which were also

the two highest among the BA. The other FAA are only present in small amounts, which agrees with

the lower (relative to the other BA) corresponding BA-values in table 10.

Table 11: FAA-concentrations (mg/kg) on tuna, measured on day 0. 2 samples were analysed.

Histidine Arginine Tyrosine Tryptophane Phenylalanine Ornithine Lysine

Sample A 6479 20 34 3 21 <LOD 129

Sample B 8137 28 45 5 25 <LOD 51

4.2.1.3 Microbiology of tuna

The microbiological counts of different types of bacteria on tuna, determined during the storage test,

can be found in table 12, presenting an overview of the spoilage flora and BA-producers. The highest

microbial counts were recorded on PCA, PA and RCA, indicating that Pseudomonas and Clostridium

spp. are important types of bacteria on tuna. RE-counts were equally high, implying also the

importance of Enterobacteriaceae. This microbial profile coincides with the classical image of fish

spoilage (45)). Also, many Enterobacteriaceae (Proteus in particular (45)) have been shown to be

responsible for histamine production in fish, while Pseudomonas species have been linked to

cadaverine (1). As such, a link with the BA-profile can be found. Note also that this does not exclude

BA-production by the other groups of MO.

Different storage conditions also generate different microbial profiles. Storage in air, for instance,

gives rise to higher microbial loads than storage under MAP-conditions, indicating that MO-growth

under air is quicker than under MAP conditions. MAP-packaging could thus help limit spoilage in

tuna. Moreover, packages stored at 22°C show higher microbial counts earlier in the storage period

than refrigerated samples. Indeed, it is widely known that cooling (0°C – 7°C) is an effective

technique to limit microbial growth (45).

38

Table 12: Log-values of microbiological counts (CFU/g) of different groups of bacteria during 6-day storage test for tuna. (VRBG = Violet Red Bile Glucose agar; RE = Rapid Enterobactiaceae agar).

Condition Total count

LAB Entero- Bacteriaceae

(VRBG)

Entero- Bacteriaceae

(RE)

Enterococci Pseudo-monas

Clostridium

DAY 0

4,81 1,30 3,53 3,63 <2 4,15 3,85

4,95 1,60 3,11 3,18 <2 4,94 3,65

DAY 3

7°C - MAP 3,98 1,00 1,00 <1 <2 2,00 2,87

6,15 2,11 2,26 2,68 <2 6,31 5,09

22°C - MAP 8,91 7,58 8,75 8,76 5,41 8,81 8,88

8,23 7,00 7,95 8,15 5,08 8,11 8,43

3h 22°C + 7°C - MAP 6,60 4,11 2,73 3,04 <2 6,59 6,08

4,23 2,36 1,00 1,00 <2 4,30 3,72

7°C - Air 6,86 1,60 1,70 2,08 <2 7,11 4,65

7,33 3,13 2,23 2,23 <2 3,26 5,04

22°C - Air 9,71 7,05 8,83 9,04 6,33 9,50 9,29

9,78 6,85 8,81 8,92 <4 9,47 9,19

3h 22°C + 7°C - Air 8,13 2,91 2,70 2,72 <2 8,15 6,41

7,75 3,35 1,85 2,18 <2 7,82 5,84

DAY 5

7°C - MAP 6,23 3,35 <3 <3 <2 6,64 8,76

6,46 1,85 <3 <3 <2 7,07 6,53

22°C - MAP 9,30 7,47 9,26 9,11 7,05 9,24 9,26

9,41 7,18 9,18 9,13 6,75 9,24 9,16

3h 22°C + 7°C - MAP 9,17 2,70 6,52 7,78 2,00 7,00 8,00

7,59 4,28 4,78 7,20 <2 7,91 7,85

7°C - Air 8,43 4,76 3,30 4,04 <2 8,77 7,09

8,79 <3 3,95 4,28 <2 8,88 7,18

22°C - Air 9,99 8,23 9,46 8,60 6,68 9,64 9,79

9,93 7,39 9,54 8,68 6,85 9,73 9,72

3h 22°C + 7°C - Air 9,18 4,40 7,40 7,00 9,19 8,67

9,54 2,24 6,78 4,48 2,48 9,57 8,11

DAY 6

7°C - MAP 7,85 3,95 <3 <3 <2 7,76 7,43

7,26 4,52 <3 <3 <2 6,18 6,26

22°C - MAP 9,00 7,27 9,39 8,66 5,95 9,25 9,36

9,05 7,58 8,74 9,08 5,95 8,99 9,12

3h 22°C + 7°C - MAP 8,78 7,43 6,18 7,51 <2 5,39 7,48

6,58 3,49 <3 5,78 <2 6,20 6,26

7°C - Air 9,56 6,52 4,28 4,95 3,00 9,47 7,92

8,77 5,53 3,95 3,60 <2 10,51 7,86

22°C - Air 9,89 8,72 9,75 9,94 6,71 10,00 9,09

9,79 8,18 9,53 9,60 9,53 9,78

3h 22°C + 7°C - Air 9,21 4,38 4,74 8,36 <2 9,11 8,96

9,57 6,64 7,15 7,08 2,48 4,67 8,17

4.2.1.4 Sensorial aspects of tuna

In table 13 several sensorial aspects, observed during the analysis of the tuna-samples, are described.

These were recorded in order to evaluate whether a product showing toxic values of BA also displays

sensorial changes severe enough to prevent a consumer eating it. Combining this table with the

39

pictures of the tuna samples during the storage test (appendix 7), it can be concluded that the only

samples which a consumer would likely consume are the refrigerated samples (both MAP and air-

packaged) on day 3, as these showed little deviation in color or texture and did not present an off-

odor. Combination with the BA-values listed in table 8 makes clear that for these refrigerated

samples, there is no danger of poisoning, as the BA-concentrations remained below the LOD. On the

other hand, any sample that did contain toxic levels of histamine or tyramine, showed spoilage to

some extent. It can thus be stated that any sample of tuna containing dangerous amounts of

histamine, will always show significant deviation in odor, texture or appearance, making sure to

prevent consumption by the consumer.

Table 13: Sensorial aspects of tuna during 6-day storage test.

Colour Odor Texture

DAY 0

- Dark purple/red - Fresh fish - Meat-like texture

DAY 3

- Refrigerated samples (condition 1 and 3) still red, a little paler than at the start.

- Samples under 22°C start to look green

- Off-odor increasingly worse from MAP to Air-packed and from 7°C to 22°C/7°C to 22°C.

- Refrigerated MAP-packed no off-odors.

- 22°C - Air: slimy - Rest: texture similar to start

DAY 5

- Refrigerated samples still red, but paler. Greenish spots visible on some samples under 22°C/7°C-condition.

- 22°C – MAP: clearly green, somewhat slimy.

- 22°C - air: overly slimy and green.

- All packages present at least a slight off-odor.

- Refrigerated samples only present slight off-odor.

- 22°C –samples: strong smell of rotten eggs.

- Refrigerated samples look desiccated.

- 22°C – air: slimy, clear microbial growth

DAY 6

- Refrigerated samples still red, but paler. Greenish spots visible on some samples under 22°C/7°C-condition.

- 22°C - MAP: clearly yellow (!) and pale.

- 22°C - air: overly slimy and green.

- Strong off-odor => rotten eggs.

- Refrigerated samples look Desiccated.

- 22°C - air: slimy, clear microbial growth

4.2.2 Storage test marinated pork

4.2.2.1 Biogenic amines in marinated pork

Table 14 presents an overview of the BA-concentrations in marinated pork measured during the

storage test. From these data, it can be concluded that cadaverine is the most important BA in pork,

followed by tyramine and putrescine. The graph in appendix 8 is provided as an illustration to the

following observations.

Just like for tuna, it is obvious that storage at 22°C is the least safe way of storing pork, giving rise to

the highest BA-values. It can also be seen that for pork, refrigeration seems a less effective way to

limit BA-formation, as BA-concentrations reached values as high as 73 mg/kg, while the maximum in

refrigerated tuna was 13 mg/kg (histamine). Next, it can again be concluded that at 22°C, MAP-

40

packaging did seem to limit BA-production. In refrigerated (7°C) samples, however, the effect of

MAP-packaging seemed minor. Also, storing the samples at 22°C for 3 hours before refrigerating

does not seem to have major increasing effect on BA-concentrations, compared to immediate

refrigeration. Statistical analysis of this difference, however, was not possible, as there are only 2

samples per condition on each day.

For toxicological analysis, a portion size of 100g can be assumed (cfr. table 9). Considering table 8, it

can be concluded that histamine will pose no toxicological threat. For tyramine, the threshold of

6000 mg/kg for symptoms in health people was never reached. Even values of 500 mg/kg, which

would cause symptoms in people taking third generation MAOI-drugs, were not recorded. In people

taking classical MAOI-drugs, however, symptoms can occur starting from concentrations of 60

mg/kg. Such values were reached already at day 3 for samples at 22°C and between day 8 and 9 for

refrigerated samples, making these samples possible health hazards for these people. Overall,

however, no major toxicological problems are to be expected.

Table 14: BA-concentrations (mg/kg) for marinated pork meat during 9-day storage test, during which different storage conditions and packaging techniques were applied. For each storage condition on every day, 2 samples were analysed.

Condition Tryptamine β-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

DAY 0

<LOD <LOD <LOD <LOD <LOD <LOD

<LOD <LOD <LOD <LOD <LOD <LOD

DAY 3

7°C - MAP 3 <LOD 6 23 1 12

2 <LOD 4 24 1 13

22°C - MAP 9 <LOD 48 93 3 68

10 1 52 99 3 73

3h 22°C + 7°C - MAP 2 <LOD 10 35 2 18

<LOQ <LOD 9 28 2 13

7°C - Air <LOQ <LOD 10 32 4 16

<LOD <LOD 10 32 5 <LOD

22°C - Air 12 1 50 103 8 70

10 2 51 112 8 74

3h 22°C + 7°C - Air <LOD <LOD 13 42 5 25

<LOQ <LOD 15 37 4 22

DAY 5

22°C - MAP 27 2 80 116 10 106

30 3 88 135 11 125

22°C - Air 32 8 117 282 20 144

42 13 125 409 24 181

DAY 8

7°C - MAP 6 <LOD 39 45 4 38

11 <LOD 47 53 6 47

3h 22°C + 7°C - MAP 10 <LOD 49 54 5 47

15 <LOQ 57 69 7 54

7°C - Air 12 <LOD 55 51 16 53

15 1 60 58 16 62

3h 22°C + 7°C - Air 15 1 59 65 21 59

12 1 50 56 21 49

DAY 9

7°C - MAP 13 <LOD 52 58 7 54

12 <LOD 48 54 6 50

41

3h 22°C + 7°C - MAP 14 1 58 68 6 60

15 <LOD 56 65 5 60

7°C - Air 17 2 60 58 17 67

15 1 57 58 16 60

3h 22°C + 7°C - Air 18 3 68 72 20 73

18 3 59 64 20 65

4.2.2.2 Free amino acids in marinated pork

Table 15 shows the FAA-concentrations detected in marinated pork on day 0 of the storage test,

providing a view on the BA-precursors. In tuna, the FAA-pattern agreed with the BA-concentrations

detected (see 4.1.1.2 ). In pork, however, such a coherence cannot be observed. The highest FAA-

concentrations were found for tryptophane and β-phenylalanine, from which would be expected that

tryptamine and β-phenylethylamine concentrations are equally the highest. Table 14 however,

shows that the contrary is true, tryptamine and β-phenylethylamine concentrations were the lowest

among the BA. On the other hand, arginine, tyrosine, ornithine and lysine are found in lower

concentrations, while their BA are found in the highest concentrations. This leads to the conclusion

that the FAA present at the beginning of storage are not a decisive factor determining the final BA-

concentrations in marinated fresh pork. BA might mostly originate from proteolysis and

decarboxylating activities during the storage, rather than before. As another explanation the

bacteria on pork might have a preference towards the production of cadaverine, tyramine and

putrescine, rather than tryptamine and β-phenylethylamine, generating a BA-profile not coherent

with the FAA-profile at the start.

Table 15: FAA-concentrations (mg/kg) in marinated pork, measured on day 0. Two samples were analysed.

Histidine Arginine Tyrosine Tryptophane Phenylalanine Ornithine Lysine

Sample A 20 <LOD 27 174 38 9 49

Sample B 21 <LOD 27 177 39 9 50

4.2.2.3 Microbiology of marinated pork

Table 16 shows the microbiological counts recorded during the storage test of marinated pork,

illustrating the spoilage flora and the possible BA-producers present. Table 16 clearly shows that the

highest counts were found for the total bacterial count, Lactic acid bacteria (LAB) and Pseudomonas.

Moreover, Enterobacteriaceae show lower counts here than in tuna. The predominant presence of

LAB and Pseudomonas agrees with the classical image of spoilage of packaged fresh meat (45). It also

agrees with the BA-profile detected, because LAB have been associated with tyramine, cadaverine

and putrescine and pseudomonas have been shown to produce cadaverine an putrescine as well.

Considering the evolution in time, just like for tuna, higher counts were detected at the end of

storage than at the start. Also just like for tuna, each storage conditions gives rise to different MO-

counts, with higher values for air-stored products versus MAP-packaged products and higher values

for samples at 22°C versus 7°C.

42

Table 16: Log-values of microbial counts (CFU/g) of different groups of bacteria during 9-day storage test of marinated pork. (VRBG = violet red bile glucose agar; Re = Rapid Enterobacteriaceae agar).

Condition Total count LAB Entero- Bacteriaceae (VRBG)

Entero- Bacteriaceae

(RE)

Enterococci Pseudomonas Staphylococci

DAY 0

4,20 3,85 <1 <1 <2 3,64 3,08 4,16 3,97 1,00 2,78 <2 3,88 2,85

DAY 3

7°C - MAP 5,96 5,75 2,15 2,26 2,00 4,41 3,34 6,05 5,62 2,11 1,90 2,00 4,42 3,59 22°C - MAP 9,13 9,12 4,76 5,19 <4 5,49 7,43 9,08 9,09 4,34 5,09 2,78 5,18 5,15 3h 22°C + 7°C - MAP

6,21 5,81 2,18 2,30 2,00 6,07 3,53

6,29 5,91 2,36 2,63 <2 5,93 3,61

7°C - Air 6,45 5,75 2,62 2,61 2,48 6,37 3,75 6,38 5,85 2,34 2,86 2,95 4,70 3,83 22°C - Air 9,62 9,26 7,02 7,35 <4 9,11 7,41 9,63 9,14 6,76 7,43 <4 9,13 7,38 3h 22°C + 7°C - Air

7,12 6,14 2,76 2,90 3,00 6,77 4,11

6,93 6,17 2,60 2,64 <3 6,43 3,92

DAY 5

22°C - MAP 9,22 9,19 3,30 4,36 <4 5,43 5,62 9,31 9,30 3,00 4,59 <4 5,35 5,68 22°C - Air 10,23 9,25 9,28 9,85 <4 9,82 8,16 10,20 9,32 9,00 9,08 8,15 9,71 9,07

DAY 8

7°C - MAP 8,62 8,76 2,20 2,59 2,00 4,23 3,04 8,68 8,76 2,60 2,87 <2 4,29 3,72 3h 22°C + 7°C - MAP

9,64 8,94 5,31 5,33 <2 9,36 5,73

8,59 8,80 2,18 2,71 <2 4,29 3,23

7°C - Air 9,41 8,95 4,52 4,60 <2 9,20 5,20 9,58 9,04 4,56 4,92 2,70 9,47 5,38 3h 22°C + 7°C - Air

9,56 8,89 5,45 5,49 <2 9,28 5,00

9,36 8,82 4,51 5,21 <2 9,29 4,60

DAY 9

7°C - MAP 8,51 8,72 2,63 2,38 <4 4,03 3,54 8,62 8,78 2,00 2,43 <4 4,07 3,08 3h 22°C + 7°C - MAP

8,59 8,72 2,18 2,63 <4 4,13 3,48

8,58 8,80 2,20 2,49 <4 4,23 3,38

7°C - Air 9,42 8,89 5,00 5,37 <4 9,27 5,53 9,36 9,02 4,56 4,75 <4 9,33 5,51 3h 22°C + 7°C - Air

9,54 9,07 5,45 5,78 <4 9,54 6,07

9,34 8,88 4,52 4,93 <4 9,31 5,54

4.2.2.4 Sensorial aspects in marinated pork

Table 17 gives a description of the color, odor and texture of the marinated meat during the storage

experiment. The evaluation of the sensorial aspects is more important here than for tuna, as the

marinade might camouflage spoilage of the product, misleading a consumer into thinking it is still

safe to eat. Although it was previously concluded that the BA-values in these products would not

pose a considerable health threat (see 4.1.2.1), this discussion might still be useful, as spoilage could

also be associated with the growth of pathogens.

43

Combining table 17 and the pictures in appendix 9, it can be concluded that toxic BA-concentrations

will mostly be visible enough to prevent a consumer from consuming the product. At day 3 for

example, the only products carrying toxic tyramine-concentrations (for people taking classical MAOI-

drugs) were the ones under 22°C. Judging from the pictures, however, it can be considered unlikely

that these products would still be consumed. At day 5, the same reasoning is applicable.

Looking at the data for day 8 and 9, however, careful consideration is obliged. The atmosphere under

which the samples were packed plays an important role here. As such, air-samples did not appear

consumable anymore, so these should not pose any toxicological problems. The MAP-packages,

however, show little observable signs of spoilage, while microbial counts and BA-values were similar

to the air-packaged products. Considering the sensorial aspects of these samples, it was concluded

that inattentive consumers or a person in a hurry could very well consume the MAP-packaged

products. When this regards a person taking classical MOAI-drugs, these samples are possibly

hazardous.

Table 17: Sensorial aspects of marinated pork during 9-day storage test.

4.3 STORAGE TEST OF DIFFERENT TYPES OF MARINATED MEAT

Here, the results of the storage tests on chicken meat, lamb meat and beef will be discussed. The BA-

profiles of the different meat-types will be compared in order to identify potential differences. Also,

the agreements between the BA-profiles and the FAA and microbiological profiles will again be

judged.

Color Odor Texture

DAY 0

- Colour of the marinade - Fresh marinated meat

DAY 3

- Samples at 22°C: marinade looks paler and has lost shine.

- Refrigerated samples: normal color.

- No off-odors - Marinade has thickened.

DAY 5 (only samples under 22°C)

- Strong off-odor on all samples: corpse smell

- Air-samples: meat and marinade stick together.

Day 8 (Only refrigerated samples)

- Samples still red (color of marinade) - Microbial growth visible only on air-samples

- No off-odors on MAP-samples

- Slight off-odor on air-samples.

- Marinade somewhat solidified

- Meat under MAP somewhat desiccated.

DAY 9 (Only refrigerated samples)

- Samples still red (color of marinade) - Microbial growth visible only on air-samples

- No off-odors on MAP-samples

- Slight off-odor on air-samples.

- Marinade somewhat solidified

- MAP-samples somewhat desiccated.

44

4.3.1.1 Biogenic amines in different types of meat

Table 18 shows the BA-concentrations measured during the storage test on marinated chicken meat,

lamb meat and beef. The BA-concentrations for marinated pork for the condition 7°C-MAP (vide

supra) were included as well, in order to be able to include pork in the following discussion. Study of

these data makes clear that the level of BA-formation depends on the type of meat and that some

meat types are more vulnerable to BA-formation than others. As such, the highest BA-concentrations

by far were found in chicken meat, followed by lamb meat, pork and beef. On the other hand, the

types of BA which were formed predominantly were quite similar in all types of meat. As such,

tyramine, cadaverine and tryptamine were the three principal BA.

Toxicologically, attention goes once again mainly to the tyramine-values, as histamine-values were

too low to cause any symptoms (see table 1). Again considering a portion of 100g of meat per meal,

it can be concluded that chicken and lamb contained concentrations that could cause toxicological

problems at the end of storage, but only in those taking MAOI-drugs. Normal people should not

experience any toxicological complaints from these products. Another remark is all BA-

concentrations seem to increase during the experiment. Unexpectedly, though, the putrescine

concentrations decrease from day 8 to day 9 in chicken meat, lamb meat and pork. No statement on

the possible breakdown of this BA can be made, however, because different samples were analysed

on each day.

Lastly, it should be noted that all meat types were marinated differently, which might have had an

effect on the development of the different BA-profiles. Differences in pH or ingredients of the

marinade, for instance, might have influenced microbial growth and activity, both proteolytic and

decarboxylating (see literature study). It is, however, impossible to state if and to which extent the

different marinades might have caused differences in BA-formation.

Table 18: BA-concentrations (mg/kg) in chicken meat, lamb meat and beef during 9-day storage test. Storage happened under MAP conditions and refrigeration (7°C).

Histamine Tyramine β-Phenylethylamine Tryptamine Putrescine Cadaverine

DAY 0

Chicken <LOD <LOD <LOD <LOQ <LOD <LOD

1 <LOD <LOD <LOQ <LOD <LOD

Lamb <LOD 6 <LOD 5 <LOD 1

<LOD 6 <LOD 6 <LOD <LOD

Beef <LOD 7 <LOD 4 <LOD 2

2 6 <LOD 2 <LOD 2

Pork <LOD <LOD <LOD <LOD <LOD <LOD

<LOD <LOD <LOD <LOD <LOD <LOD

DAY8

Chicken 3 168 <LOD 48 140 117

3 165 <LOD 44 137 105

Lamb <LOD 97 <LOD 14 33 43

<LOD 73 <LOD 12 31 36

Beef 3 24 <LOD 7 64 35

3 33 <LOD 9 76 39

Pork 6 <LOD 39 45 4 38

11 <LOD 47 53 6 47

DAY 9

Chicken 7 196 6 54 <LOD 167

6 187 5 47 <LOD 166

Lamb 1 111 <LOD 21 <LOD 68

2 105 <LOD 22 <LOD 56

Beef 6 34 1 10 <LOD 46

45

5 16 1 7 <LOD 40

Pork 13 <LOD 52 58 7 54

12 <LOD 48 54 6 50

4.3.1.2 Free amino acids in different types of meat

The concentrations of the FAA, precursing the BA, for the storage test on chicken meat, lamb meat

and beef are presented in table 19. The following observations can be mentioned: firstly, from the

predominant presence of tyramine, putrescine and cadaverine among the BA (table 18), it could be

expected that tyrosine, arginine and lysine would also show notable concentrations, which was

indeed observed. However, their importance relative to each other in the BA- or the FAA-profiles

respectively did not coincide. Also, starting from the FAA-profile, it would be expected that β-

phenylethylamine concentrations are somewhat comparable to those of tyramine (for chicken and

lamb meat) and histamine (for beef and pork). This was, however, not observed in the BA-profile.

Also, comparing the FAA-profiles between the different meat-types, it must be stated that on this

point, the BA- and the FAA-profiles do agree. In the BA-profile the values were the highest for

chicken meat and the lowest for beef, which is also the case here.

Overall it can thus be concluded that, although some agreement could be found, the FAA-patterns of

these meat types are not entirely reflected in their BA-patterns, which again leads to the conclusion

that there are oher important factors than only the FAA-concentration determining the BA-

concentrations at the end of the experiment. The same explanation as suggested for the marinated

pork counts: BA are probably more derived from AA formed by proteolysis during storage, then they

are formed out of FAA available at the beginning of storage.

Table 19: FAA-concentrations (mg/kg) in chicken meat, lamb meat and beef meat on day 0 of the storage test. For each type of meat, 2 samples were analysed. Storage happened under MAP conditions and refrigeration (7°C).

Histidine Tyrosine Phenylalanine Tryptophane Arginine Ornithine Lysine

Chicken 99 163 117 91 300 <LOD 313

103 170 122 94 304 <LOD 316

Lamb 78 102 116 <LOD 316 <LOD 224

74 98 108 <LOD 290 <LOD 121

Beef 39 25 34 <LOD 43 <LOD 18

33 7 28 <LOD 32 <LOD 21

Pork 20 <LOD 27 174 38 9 49

21 <LOD 27 177 39 9 50

4.3.1.3 Microbiology of different types of meat

In table 20, the microbiological counts for the storage test on chicken meat, lamb meat and beef can

be found, again representing the spoilage flora and possible BA-producers. The microbial data for

pork were also included in this table for comparison. First of all, comparing the different types of

meat, it can be observed that lamb meat and beef carried the highest initial microbial

contamination. Chicken meat started with lower contaminations, but by the end of the storage test

the microbial counts on chicken meat were comparable to these on lamb, suggesting rapid microbial

growth/activity. This might explain why the BA-values recorded for chicken meat were higher than

those on lamb meat, as BA-formation and microbial activity are linked (see literature study). The

microbial counts for pork were each time lower than on the other meat-types. For all meat types, the

microbial counts rose during storage.

46

Next, looking at which types of MO were the most predominant, the LAB-counts clearly stand out as

the highest microbial counts. The second highest values were observed for PA (Pseudomonas). The

same conclusion as for the storage test on pork counts: this is the classical spoiling flora of meat (45).

Now comparing this microbial profile with the BA-data, it can be concluded that these two agree

with each other. Figure 17 clearly suggests that the combined presence of LAB and Pseudomonas

gives rise to the formation of tyramine, cadaverine and putrescine. Again, it should be noted here

that the different marinades might have influenced the development of the microbial profiles.

Table 20: Log-values of microbial counts (CFU/g) of different groups of bacteria on chicken meat, lamb meat and beef during 9-day storage test. Storage happened under MAP conditions and refrigeration (7°C).

Total count LAB Staphylococci Enterobacteriaceae Enterococci Pseudomonas

DAY 0

Chicken 4,76 3,10 3,08 2,04 <2 3,90 4,80 3,13 3,34 2,20 <2 3,81 Lamb 7,17 4,84 2,78 3,77 <2 4,24 7,41 5,01 3,30 4,10 <2 4,72 Beef 7,04 7,09 3,46 3,45 <2 5,13 7,00 6,74 3,90 3,47 <2 5,35 Pork 4,20 3,85 3,08 <1 <2 3,64

4,16 3,97 2,85 2,78 <2 3,88

DAY 8

Chicken 8,77 8,81 3,00 3,90 <3 4,90 8,78 8,70 <3 3,90 <3 4,92 Lamb 9,12 9,11 <3 5,12 <3 5,72 8,89 8,91 <3 5,46 <3 5,96 Beef 8,73 8,83 3,30 3,00 <3 5,37 8,72 8,85 <3 4,00 <3 5,28 Pork 8,62 8,76 3,04 2,59 2,00 4,23

8,68 8,76 3,72 2,87 <2 4,29

DAY 9

Chicken 8,91 8,76 <3 4,53 <3 6,17 9,06 8,98 <3 4,11 <3 5,05 Lamb 9,11 8,94 <3 5,52 <3 5,99 9,07 9,12 <3 5,14 <3 5,60 Beef 8,68 8,74 <3 3,70 <3 5,28 8,58 8,71 <3 3,48 <3 5,32 Pork 8,51 8,72 3,54 2,38 <4 4,03

8,62 8,78 3,08 2,43 <4 4,07

4.3.1.4 Sensorial aspects of different types of meat

As previously discussed, only the presence of tyramine might pose any health risk in the analysed

samples of chicken meat, lamb meat and beef, and only for people taking MAOI-drugs. But although

no major toxicological problems are expected, discussion of the sensorial properties of these meats is

still considered useful, because the marinades can still camouflage spoilage.

Table 21 sets out the sensorial aspects of chicken, lamb and beef during the storage test. From this

table, it can be seen that beef seems most prone to show aberrant sensorial aspects. Combination of

the microbial data (table 20) with the microbiological criteria (46) counting for meat preparations

shows that by day 8, all meat-types were already spoiled, while only beef showed visible signs of

spoilage at that point. It took up till day 9 before actual discoloring appeared in all types of meat. This

47

leads to the conclusion that the marinades are able to camouflage spoilage and although the BA

might not form a threat, consumption of such products could still be dangerous for microbial reasons

(for instance, if vegetative pathogens were to be present).

Table 21: Sensorial aspects of marinated chicken, lamb and beef recorded during 9-day storage test.

Color Odor Texture

DAY 0

Normal Normal Normal

DAY 8

Chicken Not aberrant Not aberrant Not aberrant

Lamb Not aberrant Not aberrant Not aberrant

Beef Meat has become grey under marinade

Not aberrant Desiccated

DAY 9

Chicken Meat has become white under marinade; still pink on inside

Not aberrant No remarks

Lamb Meat has become grey under marinade; still red on inside

Not aberrant No remarks

Beef Meat has become grey under marinade

Off-odor Desiccated, baked outlook

4.4 SCREENING OF MEAT PRODUCTS AND PREPARATIONS FROM THE BELGIAN

MARKET

In this section, the results of the screening tests conducted for the group of meat products and

preparations, purchased in commercial stores, will be discussed. This will comprise discussion of the

BA-concentrations in salami’s and dried sausages, cooked hams, raw dried hams and meat

preparations, plus their toxicological importance. Also, a comparison of this BA-profile with the FAA-

concentrations and the microbial profile will be made.

4.4.1 Salami and dried sausages

4.4.1.1 Biogenic amines

In total, 17 types of dried sausages and 8 salami’s, purchased from diverse supermarkets, markets

and butchery shops in Belgium, were screened. At purchase, there was a specific search for the most

'traditional' sausages, instead of sausages from well established companies or retailers. The

distinction between salami’s and dried sausages was made on the basis of their ingredients: sausages

containing intentionally added ferments were categorized as salami, while those without were filed

as dried sausages. In these last ones, natural fermentation had occurred.

Table 22 represents the BA-concentrations detected in these products. It can be derived that

tyramine and putrescine were the most important BA in both salami and dried sausages, based on

their mean and maximal values. In dried sausages, also cadaverine reached values over 100 mg/kg,

while in salami, cadaverine was less important. Another observation is that the BA-values for

putrescine, cadaverine and tyramine varied widely between samples. In most dried sausages, for

instance, the putrescine and cadaverine concentrations were no higher than several mg/kg, but in

some sausages several hundreds of mg/kg were reached! Also, comparing dried sausages to salami

shows that dried sausages showed higher mean and maximal values on the most important BA

(putrescine, cadaverine, histamine and tyramine), an observation agreeing with previous studies (8).

48

The biggest absolute differences were found for cadaverine. Next, when comparing concentrations of

A (day 0) vs. B (expiry date), data shows that mean values were usually lower at the end of storage

than at the beginning. Looking at individual samples, however, this effect was not always consistently

displayed.

Toxicologically, considering a portion of 25g for salami/dried sausage (see table 9), it can be

concluded that histamine values in these products are of no concern. Even for tyramine, no health

hazard should occur, because at a consumption of 25 g per meal, concentrations of 24000 mg/kg

would be required to cause symptoms in healthy individuals. For people taking classical MAOI-drugs,

tyramine-values would have to exceed 240 mg/kg to cause any trouble, a value which was reached in

none of the samples. Hence, it can be concluded that neither histamine, nor tyramine will form a

health risk in salami or dried sausages.

Table 22: BA-concentrations (mg/kg) in dried sausages and salami’s collected during screening tests. For the calculation of means, standard deviations, minimal and maximal values, B-values were filled out when unavailable by copying the A-concentrations (see materials and methods)

Tryptamine B-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

DRIED SAUSAGE

Min A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

Mean A 9 4 45 21 5 79

B 7 6 30 18 5 75

Stdev A 13 6 84 41 14 77

B 11 7 49 40 14 68

P50 A 2 1 3 2 <LOD 71 B <LOD 4 9 2 <LOD 64

P90 A 32 10 145 64 11 180 B 27 13 105 50 12 171

Max A 33 24 307 158 54 226

B 33 24 156 158 54 205

SALAMI

Min A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

Mean A 4 4 34 3 2 65

B 4 3 28 9 2 48

Stdev A 11 5 51 2 4 56

B 11 4 49 19 4 53

P50 A <LOD 1 4 2 <LOD 63

B <LOD 2 6 3 <LOD 28

P90 A <LOD 5 59 3 2 103

B <LOD 5 22 4 2 78

Max A 31 12 141 7 13 153

B 31 10 136 57 13 134

Note: for concentrations in individual samples, see appendix 10

4.4.1.2 Free amino acids

Table 23 contains the FAA-concentrations detected in salami’s and dried sausages. Comparing the

FAA-profile to the BA-profile above, it can be concluded that the two profiles do not agree: where

tyramine, putrescine and cadaverine were the principal BA, the three most important FAA at the

beginning of storage were lysine, phenylalanine and histidine (based on the mean values). This non-

coherence is more logical here than for fresh meat products, because in these fermented products,

49

the major fraction of BA-formation will already have happened before purchase during the

fermentation process. The FAA measured at day 0 thus do not represent the precursors for BA-

formation anymore. Rather they represent what FAA were left after this process of proteolysis and

decarboxylation.

Table 23: FAA-concentrations (mg/kg) for salami's/dried sausages, measured on day 0.

Histidine Arginine Tyrosine Tryptophane Phenylalanine Ornithine Lysine

DRIED SAUSAGE

Min 18 9 <LOD <LOD 35 <LOD 85

Mean 109 90 80 24 189 72 361

Stdev 55 121 74 17 95 76 182

P50 99 34 60 23 187 56 329 P90 186 268 147 43 302 180 624 Max 220 405 272 55 379 266 688

SALAMI

Min 53 5 2 <LOD 97 39 133

Mean 99 17 63 23 158 113 309

Stdev 37 23 34 13 50 60 139

P50 114 10 69 24 165 119 335

P90 129 12 91 33 197 173 370

Max 137 73 98 37 222 174 553

Note: for concentrations in individual samples, see appendix 10

4.4.1.3 Microbiology

Table 24 shows the microbial counts on dried sausages and salami’s. In these products, these counts

should not be considered as spoilage flora, but rather as the fermenting flora, essential to the

production of these products (45). From table 24 it can be derived that LAB and Staphylococci are

the principal MO present on salami and dried sausages, which is not surprising, knowing that starter

cultures, used in salami-production, are traditionally composed of these MO (45). Also, in dried

sausages, where no starter culture was added, several techniques are applied in order to favor

growth of these organisms (47), which are naturally present on fresh meat. As such, also the lower

counts of Enterobacteriaceae and Enterococci can be explained by the suppressing effect of the

fermenting flora (45).

Comparing salami with dried sausage, it can be derived that microbial counts on dried sausage were

on average lower than in salami. This can be explained by the fact that starter cultures (used in

salami, but not in dried sausages) are carefully selected to be perfectly adapted to their fermentation

environment, resulting in optimal growth (1).

Lastly, when converging this microbial profile with the BA-concentrations, it can be concluded that

the fermenting LAB and Staphylococci are probably not the MO responsible for BA-production,

because the more controlled fermentation environment (with higher microbial counts) in salami’s

yielded lower average amounts of BA than the natural fermentation in dried sausages, with lower

microbial counts. Indeed, it is stated in literature that the use of starter cultures inhibits the

formation of BA in several ways (10; 48; 8). Moreover, the use of decarboxylase negative starter

cultures is an advised technique to suppress BA-formation (12; 48). The BA formed in these types of

products will thus have originated from the background flora, rather than the starter cultures,

which yielded the higher microbial counts.

50

Table 24: Log-values of microbial counts (CFU/g) of different groups of bacteria on salami/dried sausages. These values were calculated using an upper bound scenario.

Total count LAB Staphylococci Enterobacteriaceae Enterococci

DRIED SAUSAGE

Mean 7,89 7,97 6,24 0,30 3,99

Stdev 1,08 0,62 1,37 1,22 1,47

Min 4,56 6,76 3,60 <1 <3

P50 8,21 8,20 5,77 3,00 3,00 P90 8,60 8,56 7,70 3,00 5,83 Max 9,17 8,65 8,94 5,02 7,36

SALAMI

Mean 8,32 8,13 6,49 <3 3,58

Stdev 0,55 0,49 1,09 <3 1,00

Min 7,34 7,33 5,30 <3 3,00

P50 8,57 8,39 6,51 <3 3,00 P90 8,76 8,50 7,63 <3 5,02 Max 8,87 8,51 8,42 <3 5,19

Note: for concentrations in the individual samples, see appendix 10

4.4.2 Cooked hams

In this category, it was observed that the preparation method differed between different types of

cooked meat products. For instance, next to being cooked, many cooked hams were also smoked,

either by use of an additive or a smoking chamber. Additionally, some hams were also grilled. These

different preparation methods might have had different effects on the formation of BA during

storage, but the effect was not investigated here. The different preparations methods of the samples

are described in appendix 14.

4.4.2.1 Biogenic amines

Table 25 shows a summary of these BA-concentrations in cooked hams, from which the following

observations can be described. Firstly, overall, cooked hams contain only limited amounts of BA,

which can be explained by the cooking process, which serves as a pasteurization, killing most of the

present MO. It is also clear that tyramine is the most important BA, as it’s mean value is the highest

and it occurs in the largest number of samples. Other BA are insignificant in cooked hams. It can also

be noted that, except for in the first sample, the tyramine values are usually higher at the end of

storage (A-values) than at the start (B-values).

Toxicologically, it appears that these products can do no harm. Firstly, histamine-concentrations, just

like in fermented sausages, were too low to cause any trouble. Secondly, as these products are

meant to be consumed between a sandwich, the portion size of these products will usually only be a

couple of grams, which results in even higher tolerable concentrations in these products than given

in table 8. This leads to the conclusion that cooked hams will be of no significant health risk.

Table 25: BA-concentrations (mg/kg) in cooked hams. For the calculation of means, standard deviations, minimal and maximal values, B-values were filled out when unavailable by copying the A-concentrations (see materials and methods).

Tryptamine B-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

Mean A 1 <LOD 3 1 <LOD 10

B 1 <LOD <LOD 5 <LOD 26

Stdev A 2 1 12 1 1 24

B 1 <LOD 1 14 1 22

51

Min A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

P50 A <LOD <LOD <LOD <LOD <LOD <LOD B <LOD <LOD <LOD <LOD <LOD 25

P90 A 2 <LOD <LOD 2 <LOD 28

B 3 <LOD <LOD 9 2 60

Max A 6 3 47 5 2 86

B 4 <LOD 3 56 2 70

Note: for concentrations in the different samples, see appendix 11.

4.4.2.2 Free amino acids

Table26 presents the FAA-concentrations in cooked hams. Looking at the mean and max FAA-values,

lysine and arginine appeared the most prominent, which led to the expectation of putrescine and

cadaverine being the principal BA. This is not the case, however. Also, while tyramine was the most

important BA in cooked hams, tyrosine was only 4th in the ranking from high to low FAA-

concentrations. It can thus be concluded, and this agrees with all other meat products discussed

above, that the FAA-profile does not seem to correspond with the BA-profile of cooked hams. The

reason might be similar to the one stated in the discussion of the storage tests for marinated pork

and other meats.

Table 26: FAA-concentrations (mg/kg) in cooked hams.

Histidine Arginine Tyrosine Tryptophane Phenylalanine Ornithine Lysine

Mean 50 99 67 36 85 10 130 Stdev 25 48 24 16 31 27 51

Min <LOD 49 25 17 37 <LOD 60

P50 45 82 62 27 84 <LOD 148 P90 84 157 100 56 123 32 184 Max 94 230 107 57 138 91 217

Note: for concentrations in the different samples, see appendix 11.

4.4.2.3 Microbiology

In cooked hams, strictly speaking, the only bacteria that should be found are the ones that survive

the cooking process (some heat resistant LAB). However, post-contamination occurring after

pasteurization and before packaging can lead to the presence of other types of MO (45). The

following table, containing the microbiological counts in cooked hams, shows that LAB are the most

prominent in cooked hams. On the other hand, the microbial counts for staphylococci (MSA),

Enterobacteriaceae (RE) and Enterococci (SB) are very low, which indicates that in most hams post-

contamination was successfully inhibited. Also, these low counts are a probably the explanation for

the low BA-concentrations discussed above.

Table 27: Log-values of microbial counts (CFU/g) of different groups of bacteria in cooked hams.

Total count LAB Staphylococci Enterobacteriaceae Enterococci

Mean 8,07 8,14 0,63 <3 0,42

Stdev 1,03 0,92 1,85 <3 1,16

Min 5,92 6,05 <3 <3 <3

P50 8,60 8,49 3,00 <3 3,00

P90 8,89 8,81 3,15 <3 3,15

Max 9,00 9,03 6,85 <3 3,48

Note: for concentrations in the different samples, see appendix 11.

52

4.4.3 Raw hams (dried and cured)

In this category, a distinction has been made between raw dried meat products originating from pork

(“raw dried and cured hams”) and originating from beef or horsemeat (“raw dried and cured beef

products”). Just like in cooked hams, the preparation methods of raw hams sometimes differ

between different products. Raw hams were usually dried or ripened for variable amounts of time,

during which ripening occurs to a certain extent. Additionally, also smoking can be applied. Again, the

preparations methods of the samples which were analysed are given in appendix 14 but they are not

further discussed in terms of their relation to the BA-concentrations.

4.4.3.1 Biogenic amines

Table 28 shows the BA-concentrations found in raw dried and cured hams. In these products, as

opposed to cooked hams, BA occur more sporadically. Next to tyramine, which is again the most

important BA by occurrence and mean value, some hams also display high values of tryptamine,

putrescine and cadaverine. Overall, however, most raw ham samples carry only several mg/kg of BA

other than tyramine. Also, analogous to cooked hams, the BA-concentrations are usually higher at

the end of storage than at the beginning. The toxicology for these products is similar to that of the

cooked hams.

In table 28, next to BA-contents in some dried and cured beef products, also one sample of dried

horsemeat is included. These products are similar in production to the raw hams and thus also

contain a similar BA-pattern: tyramine is again the most important, while also detectable values for

tryptamine, cadaverine and putrescine occur. The mean BA-values in these products, however, are

consistently higher than those in raw hams (pork meat), which might mean that beef is more prone

to BA-formation than pork. Again, the toxicological discussion of these products is similar to the

cooked hams.

Table 28: BA-concentrations (mg/kg) in raw hams. For the calculation of means, standard deviations, minimal and maximal values, B-values were filled out when unavailable by copying the A-concentrations (see materials and methods).

Tryptamine B-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

RAW DRIED AND CURED HAM

Mean A 2 <LOD 3 5 <LOD 13

B 9 2 17 3 1 41

Stdev A 5 1 7 16 1 28

B 25 3 44 5 5 87

Min A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

P50 A <LOD <LOD 1 1 <LOD <LOD B <LOD <LOD 1 1 <LOD <LOD

P90 A 7 <LOD 6 5 1 54

B 30 7 38 11 <LOD 134

Max A 20 2 32 77 2 107

B 112 12 183 18 22 365

RAW DRIED BEEF

Mean A 14 1 1 15 2 69

B 34 1 10 36 2 151

Stdev A 25 2 1 21 2 97

B 47 2 11 79 3 90

Min A <LOD <LOD 1 <LOD <LOD 5

B <LOD <LOD <LOD <LOD <LOD 57

53

P50 A <LOD <LOD 1 <LOD 2 28

B 9 <LOD 3 <LOD 2 107

P90 A 39 3 2 39 3 168

B 86 3 22 107 5 250

Max A 59 5 3 44 4 238

B 109 4 23 177 7 265

*Horsemeat Note: for concentrations in the individual samples, see appendix 12

4.4.3.2 Free amino acids

FAA-concentrations in raw meat products are displayed in table 29. Compared to the FAA-

concentrations in cooked hams, these FAA-values were a lot higher (factor 10 or more). This might

be explained by the difference in production method, in which raw hams are not pasteurized but

undergo a stage of ripening/fermentation, undoubtedly favoring proteolysis. At the time of purchase,

the major BA-formation has thus already happened in dried hams, while this is not the case in

cooked hams.

When comparing the FAA- and the BA-profile for raw dried hams, similar observations can be made

as for the cooked hams and the overall conclusion is again that both profiles don’t agree. In raw

dried beef products, the relative importance of the different BA differs from that of raw hams, yet

still there is no agreement between the FAA- and the BA-profile of these products. Notice also that in

these dried products, as the major part of BA should already have been formed, the FAA measured at

day 0 are not the precursors for BA-formation. In that sense, these products are more similar to dried

sausages than to cooked hams, so a similarity with dried sausages would be expected. This is not the

case, however: the comparison between BA- and FAA-profile yields similar conclusions for cooked

and raw hams. This leads to the conclusion that the relationship between the BA-and FAA-profile

might be more characteristic of the type of product (raw material, production method, microbial

profile,…), rather than to depend on the timepoint in BA-production.

Table 29: FAA-concentrations (mg/kg) in raw ham (pork) and raw dried beef products.

Histidine Arginine Tyrosine Tryptophane Phenylalanine Ornithine Lysine

RAW DRIED AND CURED HAM

Mean 613 1348 763 191 988 120 2284

Stdev 450 990 509 135 677 101 1561

Min <LOD 36 23 19 98 <LOD <LOD

P50 613 1408 720 176 873 94 2391

P90 1299 2673 1405 370 1977 235 4452

Max 1533 3234 1940 516 2370 348 5167

RAW DRIED BEEF

Mean 338 351 264 96 563 158 949

Stdev 274 319 260 51 378 217 920

Min 66 114 27 36 164 <LOD 138

P50 373 127 114 87 679 72 634

P90 612 709 555 149 920 385 1967

Max 701 763 611 157 1001 527 2226

*Horsemeat Note: for concentrations in individual samples, see appendix 12

4.4.3.3 Microbiology

Looking at the microbiological counts in table 30, it can firstly be observed that the microbiological

counts for raw hams and beef products are lower than those for cooked hams. Considering the low

54

aw of these products (due to salting AND drying), this seems evident. It does contrast with the

observation, though, that the BA-concentrations in these products are higher than in cooked hams.

Apparently, the bacterial cultures on raw dried meat products are more prone to form BA than the

MO which survive on cooked hams after pasteurization. Another observation is that raw beef

products give rise to higher counts than raw hams, which indicates the influence of the type of meat

on the growth of MO. Next, it can be observed that raw hams and beef products contain only low

amounts of Enterococci (SB), Enterobacteriaceae (RE) or Pseudomonas (PA). LAB, on the other hand,

are present in significant amounts on both types of products. This is the typical microbial profile of

raw ham (45). Also, in raw dried beef products, Staphylococci also showed a notable presence, while

their counts on raw hams are several log’s lower.

Combining this microbial profile again with the BA-profile and table figure 17, it can be concluded

that the types of BA formed can be explained by the types of bacteria detected. Also, the fact that

BA-concentrations were on average higher in beef products than in dried pork, combined with the

fact that higher counts of microorganisms should give rise to higher amounts of BA, leads to the

conclusion that LAB and Staphylococci were probably the most BA-forming bacteria in these

products, because the counts of Enterobacteriaceae, Enterococci and Pseudomonas were each time

lower in beef products, while the BA-contents were higher in these products.

Table 30: Log-values of microbial counts(CFU/g) in raw hams (pork) and raw dried beef products.

Total count LAB Staphylococci Enterobacteriaceae Enterococci Pseudomonas

RAW DRIED AND CURED HAM

Mean 5,84 5,10 3,64 2,95 3,47 3,02

Stdev 2,17 2,20 1,32 0,21 1,47 0,08

Min <3 <3 <2 <3 <3 <3

P50 5,07 4,28 3,85 3,00 3,00 3,00

P90 8,45 8,31 4,57 3,00 3,80 3,00

Max 9,81 8,40 6,36 <3 9,30 3,30

RAW DRIED BEEF

Mean 7,70 6,86 4,57 2,80 3,00 3,00

Stdev 0,78 1,99 1,94 0,45 0,00 0,00

Min 6,75 3,60 3,00 <2 <3 <3

P50 8,12 8,02 3,48 3,00 3,00 3,00

P90 8,33 8,20 6,70 3,00 3,00 3,00

Max 8,34 8,24 6,78 <3 <3 <3

*Horsemeat Note: for concentrations in individual samples, see appendix 12

4.4.4 Meat preparations

As described before, meat preparations are products containing meat, to which several spices and

other ingredients can be added, but in which the structure of meat can still be recognized (EU

Regulation 853/2004). In this category, products such as sausages, burgers, schnitzels and marinated

meat were included.

4.4.4.1 Biogenic amines

The BA-concentrations displayed in table 31 show that in this type of product, tyramine is again the

most prominent BA, occurring in the highest mean values. Next to tyramine, putrescine and

cadaverine are also present. This BA-profile thus agrees with the one observed during the storage

tests (vide supra). Cadaverine also gives rise to the highest maximum value. Overall, however, meat

55

preparations seem to contain only low amounts of BA (judging from the P50). In many meat

preparations, many BA were even undetectable. Also, in most cases the BA-concentrations at the

expiry date (B-values) were higher than those on day 0 (A-values), agreeing with the idea that

spoilage occurs during storage.

The toxicological assessment here is similar to the one described for the storage test of marinated

meats. As such, histamine-concentrations were again in too low to be able to cause any health

problems (see appendix 13 for concentrations in individual samples). In terms of portion size, it

should be noted that, although portions of 100g of meat are advised (table 9), portion sizes in

commercial packages of for instance burgers, sausages, etc. are mostly larger, lying between 100 and

200 g (49; 50; 51). Combining these portion sizes with table 8 shows that, for tyramine, the same

conclusions count as for the storage tests of marinated meat, namely that only people taking classical

MAOI-drugs might encounter health problems after consumption of certain products.

Table 31: BA-concentrations (mg/kg) in several meat preparations. For the calculation of means, standard deviations, minimal and maximal values, B-values were filled out when unavailable by copying the A-concentrations (see materials and methods).

Tryptamine B-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

Mean A <LOD <LOD 4 2 <LOD 6 B 6 <LOD 6 15 2 29

Stdev A <LOD 1 25 4 1 17 B 16 1 26 45 5 45

Min A <LOD <LOD <LOD <LOD <LOD <LOD B <LOD <LOD <LOD <LOD <LOD <LOD

P50 A <LOD <LOD <LOD <LOD <LOD <LOD B <LOD <LOD 1 1 <LOD 5

P90 A <LOD <LOD 2 6 1 12

B 16 2 5 47 4 96

Max A <LOD 4 157 18 3 102 B 83 3 163 269 29 195

Note: for concentrations in individual samples, see appendix 13

4.4.4.2 Free amino acids

Starting from the BA-profile it can be expected that tyrosine should give rise to the highest FAA-

values (table 32) and that lysine and arginine and/or ornithine are the second and third most

prominent. This is not the case, however. Also, the mean value for phenylalanine lies between those

of tyrosine and arginine, while β-phenylethylamine (originating from phenylalanine) was usually not

even detectable. The conclusion is again that the BA- and FAA-profiles do not coincide, for the same

reason as stated in the discussion of the storage tests for marinated meat.

Table 32: FAA-concentrations (mg/kg) in meat preparations.

Histidine Arginine Tyrosine Tryptophane Phenylalanine Ornithine Lysine

Mean 56 119 61 23 74 19 126 Stdev 38 93 49 22 52 25 102 Min 14 <LOD 17 <LOD 25 <LOD 43 P50 47 92 61 22 69 <LOD 117 P90 108 228 122 57 165 43 317 Max 168 421 214 88 195 106 423

Note: for concentrations in individual samples, see appendix 13

56

4.4.4.3 Microbiology

Looking at the microbial profile in meat preparations (table 33) a similar pattern as viewed during the

storage tests for marinated meat is observed, which means a predominance of LAB and

Pseudomonas. The microbial counts are, however, lower than for the storage test, possibly due to

less post-contamination - the marinated meats originated from a butchers chop, while the meat

preparations were mostly industrially packed - and higher contents of conserving additives.

Table 33: Log-values of the microbial counts (CFU/g) in meat preparations at the end of storage.

Total count LAB Staphylococci Enterobacteriaceae Enterococci Pseudomonas

Mean 7,06 6,84 3,53 3,69 3,23 4,96 Stdev 2,16 2,15 0,86 1,46 0,54 1,96

Min <3 <3 <3 <3 <3 <3

P50 8,06 7,92 3,60 3,00 3,00 4,49 P90 8,86 8,72 4,61 5,72 4,03 7,57 Max 9,18 8,99 5,02 7,63 5,43 8,84

Note: for concentrations in individual samples, see appendix 13

4.4.5 Concluding remarks on fresh meat, meat preparations and meat products

When comparing the above mentioned products on their BA-content, FAA-content and MO-counts,

the following summarizing remarks can be made. Firstly, tyramine is present in all types of meat

products, mostly as the principal BA. Other types of BA which can show significant presence are

cadaverine, putrescine and sometimes tryptamine, but their presence depends strongly on the type

of product. Also, within one type of meat product, the BA-contents tend to vary considerably

between different samples (f. ex between different types of salami). As such, many BA in many

samples were undetectable, but sporadically, some samples carried excessive concentrations of

tyramine, cadaverine, putrescine or tryptamine.

Next, only limited agreements could be found between the FAA- and the BA-profile detected in the

same products, meaning that predominance of certain BA not always coincides with the

predominance of the precursor-FAA. This means that for meat-based products, the FAA-content at

the moment of purchase is not a good indicator for the BA-contents that will be registered at the end

of their shelf life. Apparently, too many other factors play a role in the development of the BA-profile

during storage (proteolysis f.ex., mainly for more perishable products) or the FAA at the moment of

purchase are not precursors anymore, as they are measured after the major BA-formation (f.ex. in

fermented sausages)

Finally, the microbial profiles on meat-based products could mostly be explained using knowledge of

their production methods. In fermented sausages, for instance, the starter culture is a defining

factor. In cooked hams, the cooking process is crucial in determining the microbial load. In dried and

cured hams the microbial profile can be explained by its low water activity and the microbial profile

in meat preparations is also as can be expected. Also, in all discussed types of meat-containing

products, the microbial profile could be linked with the BA-profile. It can thus be concluded that the

microbial profile forms a better indicator for the level of BA formed.

4.5 DESCRIPTION OF BA-DATA ASSEMBLED FOR OTHER FOOD GROUPS

As an introduction to the results of the statistical tests, first, the BA-concentrations in each food

group are described below. These food groups were not all analysed in the frame of this master

57

thesis, but are the BIOGAMI project. Appendix 17 provides an overview of several characteristics of

the BA-concentrations in each food group and subgroup, as well as the number of samples in each of

these categories. After this descriptional exposition, the results of the statistical analyses, executed

using the data resulting from the screening tests, will be discussed as well.

4.5.1 Fruit and vegetables

This category comprises 3 types of products, namely fresh fruit and vegetables (F&V) (non-

fermented), olives and sauerkraut (both fermented). It was observed that the BA-profiles differed

largely between all three of these food groups. Studying the BA-concentrations in fresh fruit and

vegetable products, it was observed that histamine and putrescine are the most characteristic BA.

Histamine occurred in the highest values (max of 39 mg/kg) and putrescine in the largest number of

samples. Other BA were usually undetectable.

Next, observing the BA-concentrations in olives reveals firstly that overall, only small amount of BA

were present in olives (P90 no higher than 2 mg/kg). Tryptamine was present in the highest

concentrations (maximum value of 41 mg/kg). Tyramine and β-phenylethylamine, on the other hand,

were never detected. Other BA, like putrescine, histamine and cadaverine sporadically occurred in

values of respectively 0 – 15, 0 – 5 and 0 – 12 mg/kg. Another peculiar observation was that the

average BA-values in olives were lower at the expiry date than on day 0, which indicates that BA

might be broken down during prolonged storage. This can, however, not be concluded with full

certainty, because two separate samples were used on the two timepoints of analysis.

Finally, the BA-concentrations in Sauerkraut clearly show that in this type of product much higher

BA-values occured than in olives. Putrescine was by far the most dominant BA in sauerkraut, as it

appeared in the highest concentrations (6 – 441 mg/kg) and in all samples. All other BA occurred in

considerably lower amounts and based on the mean values, BA-values diminished from tyramine to

cadaverine, histamine, β-phenylethylamine and tryptamine. As for the difference between the

timepoints of analysis: most mean values had not changed considerably at the end of storage

compared to day 0. For β-phenylethylamine, histamine and cadaverine, slight increases were

observed, while tyramine and putrescine have shown diminished BA-concentrations.

4.5.2 Chocolate

Both white, brown and dark chocolates were analysed. Brown and dark chocolate were both

categorized as “dark chocolate”. Looking at these BA-concentrations, it is clear that only brown and

dark chocolate seems prone to BA-formation. Samples of dark chocolate contained detectable

amounts or all BA, but all concentrations remained fairly low, with tyramine reaching the highest

values (0 – 29 mg/kg). White chocolate contained almost no detectable amounts of BA whatsoever

(only one sample showed detectable amounts).

4.5.3 Beer

In this food group, the aim was to analyse beers brewed by local breweries, as it was assumed that

larger industrial breweries already implement sufficient control measures in order to limit any health

hazards in their products. An overall view on BA-values in beer led to the impression that the

presence of BA decreased in the following sequence: tyramine > putrescine > histamine > cadaverine

> β-phenylethylamine > tryptamine. In general, BA-concentrations were low in beer, with a maximal

detected amount of 67 mg/kg for tyramine. Toxicologically, beer should thus be of no concern,

unless consumed in excessive amounts.

58

Further comparison of the different subcategories in beer gives interesting results. Firstly, in all

subcategories, putrescine was present in comparable amounts. The content of other BA, however,

differed. Firstly, in amber beers, except for putrescine, all other BA were undetectable (although one

sample contained histamine and tyramine). In light beers (or lagers), putrescine was again the most

widely present. Tyramine, histamine and cadaverine were also present in some samples, usually in

much higher amounts (13-67 mg/kg) than the average putrescine concentration (5 mg/kg). In dark

beers, the main presence next to putrescine was tryptamine, a BA unique for this subcategory.

Concentrations of tryptamine were comparable to those of putrescine when present. In home-

brewed beers, putrescine was the only BA detected. And lastly, fruitbeers contained the most varied

spectrum of BA. Not only were the putrescine values slightly higher in this subcategory, but it was

also no longer the principle BA in this class. On the contrary, tyramine, cadaverine and histamine

were widely present in this group, in values of 0 – 64, 0 – 52 and 0 – 29 respectively.

4.5.4 Meat products and preparations

These BA-concentrations have already been described under 4.3 Screening of meat products.

4.5.5 Dairy

4.5.5.1 Yoghurt

As can be seen from the mean BA-values in appendix 15, yoghurt contained practically no BA. The

maximum BA-value over all yoghurts was a concentration of 6 mg/kg, reported for tyramine.

4.5.5.2 Cheese

In contrast with yoghurt, the subgroup of cheese is much harder to describe. There are fewer clear

trends visible here than in other food groups. During the screenings of soft cheeses, usually only very

low or undetectable BA-concentrations were recorded (only 9 samples showed contents higher than

50 mg/kg). On the other hand, when detectable amounts of BA occurred, their values were

sporadically very high (904 mg/kg for cadaverine!). Generally, data showed that there was not really

one or 2 characteristic BA in soft cheese. Only tryptamine and β-phenylethylamine did not really

occur often in this subgroup. On the other hand, marked amounts of different BA are usually found in

the same samples, showing that BA-formation strongly depends on the type of cheese. Another

observation is that BA-contents were always higher at the end of storage (timepoint B) than at the

start (timepoint A), indicating that fermentation goes on during storage.

The subgroup of half-hard cheeses showed a slightly different BA-pattern than the soft cheeses. For

starters, the maximal concentrations were much higher in this class, indicating a further ripening

stage at purchase. Tyramine, in particular, reached some excessive values (726 and 1029 mg/kg!)

and also a larger fraction of samples contained more elevated BA-concentrations than in the soft

cheeses. Also, putrescine was less represented in this subgroup than in soft cheeses, but β-

phenylethylamine occured more in this class. High BA-concentrations are again mainly concentrated

per product and B-values are again higher than A-values.

When comparing the hard cheeses to the half-hard and the soft cheeses, it is again clear that a

longer ripening time results in higher BA-concentrations, as mean values were higher in hard cheeses

compared to the previous classes. In this subgroup, tyramine and cadaverine seemed most important

and one excessive histamine value (1025 mg/kg) was detected, which would undoubtedly cause

health problems. Looking at the evolution in time, in this subgroup it can no longer be said that BA-

59

concentrations were clearly higher at the end of storage. Apparently, when the ripening time is

sufficiently long, most BA are already formed at the moment of sale in the supermarkets and no

significant BA-formation occurs anymore during storage (similar statements have been made for

fermented sausages and dried and cured hams: vide supra).

The BA-concentrations in blue cheese were more concentrated around one BA, being tyramine.

Some extreme values were reached for this BA (5 in 16 samples > 300 mg/kg and 2 samples above

1000 mg/kg). Other BA were less important in this subgroup. Also, looking at the evolution of BA in

individual samples, no real conclusion can be drawn for this class. For some BA, the concentrations

were lower after storage, some others were higher.

Overall conclusions for cheese are that tyramine and histamine were the most important BA in terms

of concentration level. Furthermore, also cadaverine and putrescine sometimes came forward.

Generally speaking, cheese is a food group with a wide variety of BA, and quite high values compared

to the previously mentioned groups. Looking at the toxicity, the food groups described above never

really showed a high potential for causing health problems. In cheese, however, this story changes. In

terms of tyramine, there should only be a problem for people taking classical MOAI-drugs, which is

the same as described for the other food groups. Considering a portion size of 25 to 50 g of cheese,

values of at least 12000, 6000 and 120 mg/kg should be present to cause toxic symptoms for

tyramine in respectively healthy people, people taking new MOAI-drugs and those taking classical

MAOI-drugs. For histamine, however, considering the same portion size, concentrations of 160, 800

and 2000 can cause respectively light, moderate and severe toxic symptoms. In total, 3 cheeses (out

of 86) showed values higher than 160 mg/kg (and under 800 mg/kg) and one value over 800 mg/kg

was recorded, from which it can thus be concluded that in cheese, some toxicological risks may be

present. On the other hand, considering the amount of cheeses which were analysed, 4 cheeses with

potential for intoxication does not result in a very high risk, but compared to the other food groups,

in which no such risks seemed to exist, this is a big difference.

4.6 STATISTICAL ANALYSIS

4.6.1 PART 1: T-tests fermented vs. non-fermented and animal vs. plants

In this part, the p-values resulting from the independent t-tests comparing fermented and non-

fermented food products and animal or plant-based products will be discussed in order to see if any

significant difference could be detected. Table 34 gives an overview of how the food products were

distributed in the first summarizing datasheet (cfr. 3.3.2). Note again that for the analysis of B-data or

BA-evolutions, the 32 non-fermented plant-based products were excluded, yielding slightly different

distributions than the one depicted below.

Table 34: Distribution of the food products over the factors "fermented/non-fermented" and "animal/plant" for the t-tests on BA-data on day 0. A similar table can be generated for the B-data or the BA-evolutions by eliminating the 32 non-fermented plant samples.

Animal Plant Total

Fermented 127 182 309 Non-fermented 84 32 116

Total 211 214 425

The boxplots, generated for this part of the statistical analysis can be found in appendix 16. Next,

tables 35 to 38 below show the p-values resulting from the independent t-tests. Looking at table 35,

60

it can be seen that at day 0 (timepoint A) the concentrations of 3 BA (tryptamine, putrescine and

tyramine) differed significantly between animal and plant-based products. The corresponding

boxplot shows that, at this point in time, plant-based products usually showed higher BA-

concentrations than animal products. Next, at the end of storage (timepoint B), the pattern shifts

slightly and 4 BA were significantly different. In the boxplots it can be seen that the BA-

concentrations for animal products have increased during storage, which presumably caused the

shift in significant differences. The evolutionary boxplot for animal vs. plant, showing positive

evolutions for putrescine, cadaverine and tyramine, for animal products, supports this statement.

Also, overall, the evolutions in BA were larger in absolute value in animal products than in plant-

based products, which could be explained by the fact that animal products contain higher

percentages of protein (see literature study). A more likely explanation here, however, is that for the

evolutionary analyses, all plant-based products were stable products (after exclusion of 32 non-

fermented samples) for which little BA-evolution occurred. P-values presented in table 35 show that

the differences in evolutions were significant for all BA.

Table 35: Adjusted p-values for independent two-sample t-tests comparing animal vs. plant-based products (significance level of 5% was used). Significant p-values are expressed in bold.

Biogenic amine A B EV

p-value p-value p-value

Tryptamine 0.01 0.52 <0.001

Β-phenylethylamine 0.11 0.04 0.04

Putrescine <0.001 <0.001 <0.001

Cadaverine 0.08 0.01 <0.001

Histamine 0.07 0.52 0.03

Tyramine 0.01 <0.001 <0.001

Table 36 was used to study the differences in BA-profile between fermented and non-fermented

food products. From this table, it can be concluded that already at day 0 (timepoint A), all BA-

concentrations differed significantly between these classes, with fermented products containing

significantly higher values than non-fermented products (cfr. figure 24 in appendix 16). This seems

logical, knowing that fermentation yields BA. Next, at the end of storage (timepoint B), it can be seen

that several of the significant differences (for tryptamine, cadaverine and tyramine) have

disappeared. Again, this is no surprise, considering the BA-formation happening during spoilage of

fresh products (cfr. literature study), versus the assumingly stable BA-concentrations in fermented

products once fermentation has finished (cfr. 3.1.2). The boxplot at timepoint B and the evolutionary

boxplot confirm this reasoning, clearly depicting increasing BA-concentrations in non-fermented food

(tryptamine, cadaverine, putrescine and tyramine) and also showing significantly higher increases in

non-fermented versus fermented food products.

Table 36: Adjusted p-values for independent two-sample t-tests comparing fermented vs. non-fermented products (significance level of 5% was used). Significant p-values are expressed in bold.

Biogenic amine A B EV

p-value p-value p-value Tryptamine <0.001 0.17 0.01 Β-phenylethylamine <0.001 0.02 0.42 Putrescine <0.001 <0.001 0.27 Cadaverine <0.001 0.68 0.01 Histamine <0.001 <0.001 0.04 Tyramine <0.001 0.13 0.02

61

In table 37, the differences between fermented and non-fermented plant-based products are

represented. From these p-values, a different picture than from table 36 arises. As such, it can be

seen that only for tryptamine, the difference in concentration was significant, while when animal and

plant base products were analysed together, the concentrations of all BA were significantly different.

Table 37: Adjusted p-values for independent two-sample t-tests comparing fermented vs. non-fermented products within plant-based products (significance level of 5% was used). t-tests for the end-of-storage data and the evolutionary data could not be performed (cfr. 3.3.3). Significant p-values are expressed in bold.

Biogenic amine A

p-value

Tryptamine 0.03

Β-phenylethylamine 0.17

Putrescine 0.68

Cadaverine 0.17

Histamine 0.17

Tyramine 0.78

Lastly, some remarkable conclusions can be drawn from table 38, presenting the p-values for the

differences between fermented versus non-fermented animal products. As such, it can be seen that

within animal products, BA-concentrations nor evolutions in BA-concentrations differed significantly

between fermented and non-fermented foods, which again seems contradictory to the overall

conclusions on the comparison of fermented and non-fermented products (table 36). Apparently,

fermentation is a more important process in plant-based than in animal products in terms of causing

differences in BA-concentration.

Table 38: Adjusted p-values for independent two-sample t-tests comparing fermented vs. non-fermented products within animal products (significance level of 5% was used). Significant p-values are expressed in bold.

Biogenic amine A B EV

p value p Tryptamine 0.10 0.56 0.50 Β-phenylethylamine 0.39 0.16 0.50 Putrescine 0.39 0.56 0.82 Cadaverine 0.99 0.56 0.56 Histamine 0.39 0.56 0.50 Tyramine 0.10 0.16 0.82

4.6.2 PART 2: ANOVA-tests for difference between food groups

In this part, the results of the ANOVA-test, comparing different food groups on their BA-content are

presented. First of all, preliminary testing for homogeneity of variances showed that for all BA, the

variances within each food group were not homogenous (all p-values were <0.001). Therefore,

conclusions were based on the outcomes of the Welch F-tests and the Games-Howell tests, rather

than the ANOVA- and the Bonferroni-tests.

The Welch F-test, comparing the means among the five food groups resulted in p-values indicating

significant differences in BA-concentrations between the food groups for both the analysis on A-data

and B-data (at day 0 and the expiry date respectively). The Welch test for the evolutionary data did

not run, because of zero-variances for one of the food groups (beer). Therefore, to define differences

in BA-evolutions, only the results of the pairwise comparisons (Games-Howell) were consulted (see

further).

62

Now before discussing the results of these pairwise comparisons, figures 18 and 19 show the BA-

concentrations in the different food groups on day 0 and at expiry date respectively. At first sight,

both graphs do not seem to differ much. Nevertheless, looking closer, some slight differences can be

noticed, like for instance an increase in tyramine and putrescine for meat. Note that the mean BA-

concentrations of F&V should not be compared between these two figures to conclude on

evolutions, because in figure 19, F&V contained only olives and sauerkraut (32 fresh samples were

not included (see 3.3.3)) while in figure 18, the whole F&V-group is depicted. It can also be observed

in figures 18 and 19 that the BA-profile is clearly different in the different food groups. Another

observation, judging from the length of the error bars, is that the variability in BA-concentration is

quite substantial and often larger than the mean BA-value itself. This illustrates clearly the

importance of the mean comparison tests to indicate the significance of the differences in BA-

concentrations between the different food groups.

The p-values resulting from these mean comparisons for A- and B-data are represented in tables 61

and 62 in appendix 17. Combining these tables with figures 18 and 19 led to the following

observations. Firstly, as tryptamine and β-phenylethylamine were presented in significantly higher

concentrations in chocolate than in most other food groups, these BA can be considered

characteristic for chocolate (although some significances disappeared at the end of storage).

Secondly, putrescine is clearly characteristic for F&V, as this BA was significantly more present in this

food group and retained this property compared to all food groups (except for beer) until after

storage. A third observation is that the concentrations of cadaverine and tyramine did not differ

significantly between most food groups (most p-values were non-significant). Cadaverine was also

the most predominant in F&V and dairy. Histamine is also highly represented in F&V (and also in

dairy), but notice that if fish products were included in these analyses, it's mean histamine value

might have been important as well (consider the histamine-levels detected during these storage test

for tuna (see 4.2.1)). Lastly, studying the profile of tyramine among the food groups, it should be

noted that this profile is the most dynamic among the different BA. As such, at day 0, dairy and

chocolate contained the highest mean tyramine concentrations, but after storage, a rise in tyramine

concentration in and meat changed up the pattern of p-values and meat became the most prominent

food group for tyramine.

Figure 18: Comparison of the BA-concentrations in the different food groups at day 0 (A-data).

0,00

0,50

1,00

1,50

2,00

log(

BA

-co

nce

nra

tio

n +

1)

Fruit and Vegetables

Chocolate

Beer

Dairy

Meat

63

Figure 19: Comparison of the BA-concentrations in the different food groups at expiry date (B-data). As 32 non-fermented fruit and vegetable samples were eliminated when creating this graph, F&V contain only olives and sauerkraut.

Next, figure 20 shows the evolution in BA-concentration during storage in the different food groups.

For this figure, it should be noted that beer and chocolate were not included, because these products

were only screened at day 0. Also, again the evolutions for F&V depicted in this graph should not be

linked with the two graphs discussed above, as the non-fermented F&V were removed from the B-

and evolutionary data (vide supra).

Looking at figure 20, the overall the evolutions of the BA-concentrations can be judged very small

(amounting to only several mg/kg usually). The variability in evolutions, however, is again quite

substantial, compared to the mean evolutions. Next, it is clear that the evolution in BA-values clearly

differed between different food groups: in F&V (olives and sauerkraut) 4 of the 6 BA showed

decreasing mean values, dairy-products usually showed only slight positive evolutions and in meat

products all BA increased in concentration during storage. Moreover, these increases were far more

substantial than in dairy. Considering these observations, the results of the mean comparisons (table

63 in appendix 17) looking for significantly different evolutions, were as can be expected. Significant

differences in evolutions were only found for meat products compared to all other classes. For β-

phenylethylamine and histamine, no significant differences could be found. It should also be noted

that, although decreasing evolutions are presented in figure 20for F&V, the BA-concentrations in the

excluded fresh samples did increase. And finally, it can also be stated that the sharp positive

evolution in tyramine for meat products agrees with the previous observation in figures 18 and 19.

0,00

0,50

1,00

1,50

2,00

2,50 lo

g(B

A-c

on

cen

trat

ion

+ 1

) Fruit and Vegetables

Chocolate

Beer

Dairy

Meat

64

Figure 20: Evolution of the BA-concentrations in several food groups during storage. As 32 non-fermented fruit and vegetable samples were eliminated when creating this graph, F&V contain only olives and sauerkraut.

4.6.3 PART 3: Correlation analysis

This part will comprise firstly the discussion of the correlations between BA and FAA. Secondly, the

correlations between BA and microbial data will be explained. Notice that for the meat products and

preparations, the relationships between FAA, BA and microbial data have already been debated

under subsections 4.2 and 4.3.

For all correlation analyses, correlation triplots will serve as a means to represent the results of the

RDA. In these figures the explanatory variables (FAA, microbial counts and factors fermented/non-

fermented and animal/plant) will be shown as vectors, while the response variables (BA) are

depicted by red dots. Black circles will represent the individual objects of analysis, in this case the

food products. Also, in a correlation triplot, the correlations between two variables can be judged by

the angle between the corresponding vectors since the cosine of the angle between two vectors

represents the correlation value. As such, the sharper the angle, the stronger the correlation. 90°

angles indicate a non-existent correlations and angles >90° indicate inverse correlations (44; 52; 53).

4.6.3.1 Correlations FAA and BA

In this part, the goal was to investigate whether higher amounts of FAA at day 0 result in higher BA-

concentrations at the end of storage or in greater BA-increases during storage. When studying these

relationships, it is first of all important to know what was expected. As such, in products in which BA

are formed during storage, the FAA measured at day 0 represent the BA-precursors. Hence in these

products a correlation between FAA and BA was expected. However, if no correlation between a BA

and its precursor could be found, this can be explained by a degree of proteolysis still occurring

during storage, generating new FAA not measured on day 0. On the other hand, in products which

are considered microbially stable (chocolate, salami, dried and cured ham,...), the FAA at day 0

represent what FAA are left after BA-formation during fermentation or ripening. As these values do

not represent precursors anymore, the data for food products only analysed at day 0 were

eliminated (cfr. materials and methods).

-0,8

-0,6

-0,4

-0,2

0

0,2

0,4

0,6

0,8

1

1,2

log(

BA

-co

nce

ntr

atio

n +

1)

Fruit and Vegetables

Dairy

Meat

65

The results of the RDA-analysis for this part of the statistics are displayed in figures 30 and 31 in

appendix18 showing the triplots for the B-data and the BA-evolutions respectively. Next to the

triplots, also the results of the MLR are given in table 64 in appendix 19.

When analysing these results, there was a specific search for correlations between the BA and their

precursing FAA. As such, from figure 30 it can be noticed that the strongest positive correlations

were present between histamine and histidine and β-phenylethylamine and tyrosine. For all other

BA-FAA couples, the angels between the BA-point and the FAA-vector were wider, even > 90° for

tryptophane and tryptamine. Nevertheless, the p-values in table 65 show that for each BA, the MLR

extracted their precursor as being a significant explanatory variable, which leads to the conclusion

that BA-concentrations at the end of storage are indeed linearly correlated to the FAA-

concentrations. The correlation between tryptophane and tryptamine were negative though.

Out of figure 31, resulting from the RDA for the BA-evolutions, no conclusions can be formulated

with regard to the correlations between the variables, because the BA are all centred around the

origin. This can be explained by the limited extent of variability in the BA-evolutions. Looking at the

results of the MLR instead shows that for the BA-evolutions, the correlations between BA and FAA

were practically non-existent. Only for tryptamine, the MLR designated its precursor as a significant

explanatory variable.

Finally, looking at the correlations of BA with the factors fermented/non-fermented (F/NF) and

animal/plant, it can be noted that these factors only play a significant role for a limited selection of

BA. When F/NF was designated as correlating significantly with the BA-values, this should be

interpreted as fermentation resulting in a significantly higher amount of that BA (or in a significant

positive evolution). As such, fermentation seems to have played a role for tryptamine, β-

phenylethylamine and cadaverine (both B-data and evolutionary). If F/NF was not extracted by the

MLR, it should simply be concluded that whether or not the product was fermented did not play a

significant role raising the level of that BA.

The factor animal/plant was also extracted several times by the MLR, designating correlations with

some BA. For the tyramine-concentrations at the expiry date, the correlation was positive, while all

other significantly found correlations were negative. Positive correlations meant that animal

products contained a higher level of a certain BA than plant based products, while negative

correlations meant the reverse. Non-significant correlations just meant that the origin of the product

did not seem to play a role for the concentration (or evolution) of that specific BA.

4.6.3.2 Correlations microbial counts and BA

The central question in these analyses was if a higher count of MO on a certain product correlates

with a higher concentration of certain BA, which could be expected in the knowledge that bacteria

are the BA-producers in food and that sterile products remain BA-free (cfr. literature study).

4.6.3.2.1 Fruit and vegetables

For this food group, correlations were sought for total bacterial count (PCA), LAB (MRS), Enterococci

(SB) and Enterobacteriaceae (RE) (see table 7). Pseudomonas-counts were left out because of an

excessive fraction of missing values. Figures 32 and 35 in appendix 18 and table 65 in appendix 19

represent the results of the RDA and MLR executed for the microbial correlations in F&V. First of all,

looking at figure 32, it could be concluded that some significant correlations might be found between

cadaverine and LAB, between putrescine and total bacterial count or between tryptamine and the

66

factor fermented/non-fermented. Indeed, the result of the MLR did show these relationships. On the

other hand, not many explanatory variables were appointed as being significantly related to the end-

of-storage BA-concentrations.

The correlation triplot for the BA-evolutions (figure 35) shows that cadaverine is strongly (and

positively) correlated with Enterococci counts (SB) and with total bacterial count, LAB and

Pseudomonas as well. Also, putrescine seems to have been positively correlated with Pseudomonas,

Enterococci, LAB and total count. Indeed, table 66 confirms these presumptions, although the

significance for Pseudomonas is missing. Out of these results it can now be concluded that for F&V,

the BA-concentrations (both end-of-storage and evolutions) were generally not very strongly

correlated with the microbial counts. Only for the evolution in putrescine and cadaverine

concentration, the MLR detected multiple bacterial groups as significant explanatory variables, while

for the other BA, not many correlations were found.

4.6.3.2.2 Dairy

For this food category, instead of Enterobacteriaceae, the Pseudomonomas counts were included in

the analysis (for the same reason as before), next to total bacterial count, Enterococci and LAB.

Figures 33 and 36 in appendix 18 represent the results of the RDA performed for this food group,

while table 67 in appendix 19 presents the MLR-models generated.

Having a look at the MLR-results first immediately shows that for this food class, even less microbial

factors were appointed as significantly explanatory for the BA-concentrations (or evolutions).

Enterobacteriaceae (RE) were the bacterial group extracted most often in relation to the end-of-

storage BA-contents. The corresponding correlation triplot indeed shows sharp angles between this

explanatory variable and several BA. However, it also shows a close proximity of the other bacterial

groups to the BA, yet MLR did not detect these variables as being significantly explanatory.

4.6.3.2.3 Meat

For this last food group, the microbial variables which were analysed were total bacterial count, LAB,

Enterococci, Staphylococci and Enterobacteriaceae (Pseudomonas was left out again). Again the

results of the RDA's are presented in appendix 18 (figures 34 and 37) and in appendix 19 table 67

shows the models generated by MLR.

A first thing that can be noticed is that the triplot for the B-data in this food group is very similar to

the one for the dairy group, indicating that the correlational pattern in both food groups should be

similar. Looking at table 68, however, shows that MLR mostly did not appoint the same explanatory

variables as being significant. Overall, for the meat category, more microbial variables were

designated as significant explanatory variables by MLR than in dairy or F&V, indicating that the

correlation between the BA-concentrations (both end-of-storage and evolutionary) and the presence

of bacteria is stronger.

4.6.3.2.4 Overall conclusion on microbial correlations

Overall, it can thus be stated that correlations between MO-counts BA-concentrations at the end of

storage (or BA-evolutions) were generally not that strong. Also, comparing the different food groups,

correlations were the strongest in meat-based products. And lastly, a final look at tables 65 to 67

shows that no bacterial agar medium stands out as being extracted more often by the MLR than the

others. Therefore, no type of bacteria could be appointed as showing stronger correlations to the BA

than other MO.

67

5. CONCLUSIONS

The conclusions for this master dissertation can be subdivided in three parts, discussing first the

results of the storage tests. Then the outcomes of the screening tests can be described and finally the

statistical results will be explained.

The results of the storage test on tuna showed that in these samples, histamine was detected as the

most prominent BA. In samples which were misused (non-refrigerated samples) the histamine-

concentrations reached excessive, and undoubtedly toxic concentrations. In marinated pork and

other marinated meat types, tyramine and cadaverine came forward the most dominant BA. It was

also found that from these products, regular people (not taking classical MAOI-drugs) should not

experience any harmful effects. Next, both for tuna and marinated meat, the conclusion was made

that MAP-packaging and refrigeration are effective techniques to suppress BA-formation, which

agrees with literature (1; 8; 10; 54). In tuna, refrigeration even proved to be essential to limit the

formation of toxic levels of histamine. Effects on microbial growth were similar and agreed with the

observations in the BA-profile, knowing that MO are the producers of BA.

Looking at FAA as the precursors for BA and assuming that larger amounts of FAA should result in

higher concentrations of BA, the conclusion for tuna was that the FAA- and the BA-profile matched

nicely. In marinated pork, or the other meat types for that matter, this kind of agreement was not

found. Better agreements were found for the microbial profile, as both in marinated meat and in

tuna the bacteria detected in the highest counts matched the most prominent BA.

A final conclusion drawn from the storage tests concerns the possible camouflage of toxic BA-levels

by preparation of the meat. For this matter, it should be noted that no marinated meat sample was

observed to contain BA-levels toxic to healthy individuals, so a judgement on masking of this health

hazard could not be made. Spoilage by microorganisms, however, which might also bring about some

health risks (foodborne pathogens), was considered to be camouflaged to some extent in all meat

types, certainly in MAP-packaged and refrigerated products.

The results of the screening tests of the meat products and preparations led to the following

conclusions. First of all, tyramine appears as a constant predominant BA in all types of meat-based

products. Notable appearances of other BA differed greatly between the different types of meat

products and preparations. In fermented sausages, for instance, putrescine was the second most

predominantly occurring BA, next to tyramine. In dried and cured hams and in meat preparations,

also cadaverine and tryptamine came forward. Within fermented sausages, also the difference

between salami and dried sausage, owing to the use (or abscence) of a starter culture became clear

in both the BA- and the microbial profile. Next, in agreement with the storage tests for marinated

meats, agreement between the FAA- and the BA-profile was limited for all categories. In fermented

or cured meat products, this was explained by a process of BA-formation before purchase during

fermentation or ripening, while in more perishable products this non-agreement was attributed to

proteolysis during storage. It was also evidenced, however, that the type of product might be a more

important factor in the FAA-BA relationship. Nevertheless, these indications have important

implications with respect to the development of FSMS. Finally, contrary to the FAA-profile,

agreement between the microbial counts and the BA-concentrations were more obvious and

differences in microbial profiles between the different meat-base products (and by consequence also

the BA-profile) could be explained by differences in production methods.

68

Screening tests conducted on other food groups showed that BA-profiles differed greatly between

all 5 groups and that to some food categories, characteristic BA could be assigned. β-

phenylethylamine, for instance, was the main BA in chocolate. Another important observation was

the large variance in BA-concentrations even within food groups. Toxicologically, it could be

concluded that most classes did not pose a considerable health threat according to currently

available toxicological data. Only in cheese, 4 (out of 86) samples were found to contain toxic levels

of histamine. Combining this with the results of the storage test for tuna, it can be stated that the

observations match literature stating that fish and cheese are the most important food groups

causing histamine intoxication.

Next, the results of the independent t-tests, investigating the effects of fermentation and the origin

of the food product (animal or plant-based), showed that significant differences in BA-concentration

were detected between animal and plant-based products for half of the BA. The increase in BA-

concentrations during storage was significantly higher in animal products than in their plant-based

counterparts, a feature which can mainly be explained, though, by the larger fraction of stable

products in the plant-based group. Comparison of fermented versus non-fermented food products

showed that fermentation leads to significant differences in BA-content compared to non-fermented

products at the moment of purchase, but that due to microbial growth, causing BA-production in

non-fermented products, some of these significant differences disappeared after storage. Also

remarkable was that when splitting the data in animal and plant-based products, the earlier detected

significant differences between fermented and non-fermented products did not occur anymore.

The mean comparisons of the different food groups showed (as observed before) that the BA-profile

is clearly different in different types of food, and some BA can be considered characteristic for

certain food groups, like for instance tryptamine and β-phenylethylamine in chocolate. Other BA are

less characteristic and occur in statistically equal amounts in practically all food groups analysed,

such as cadaverine and tyramine. An important note here, however, is that the extent of variability in

BA-concentrations in each food group was that large that the conclusions sketched here for the

mean BA-concentrations might not be valid for individual or smaller groups of samples.

And finally, during the correlation analysis for FAA, significant correlations were found for all BA

between the BA-concentrations detected at the expiry date and the FAA measured at day 0. Using

the evolutions in BA during storage, however, the resulting correlations were less strong. Thus it is

only with caution that the statement can be made that higher levels of BA at day 0 might result in

higher levels of BA at the end of storage. Future investigations should confirm this message. Next,

the correlation analyses for microbial data showed that only limited correlations could be found

between several groups of bacteria and BA-concentrations or -evolutions and that the correlations

appeared stronger in the group of meat-based products, than in dairy of F&V. Lastly, no bacterial

groups came forward as being more correlated with the BA than the others.

69

6. FUTURE INVESTIGATIONS

Following the completion of this master dissertation, the database gathered before and during this

thesis on the occurrence of BA in different food groups and products should be used to perform an

exposure assessment (and subsequently a risk assessment) following the steps proposed under 2.7

exposure and risk assessment. The data gathered during the Belgian food consumption survey of

2014 (55) might function as consumption data for this exposure calculation. Next, after calculation of

exposures to the detected BA, performing a risk assessment would require sufficient toxicological

data, which is where still a major gap lies. Currently available data carries insufficient information on

the toxic level (NOAEL) of the different BA, the associated toxic concentrations in several food

groups/products (in mg/kg), the potentiating effect of putrescine and cadaverine, the effect of

process and environmental parameters on BA-formation, etc. Data which do exist usually originate

from long outdated studies. As such, before any meaningful risk assessment can be made, new and

detailed research projects investigating these topics should be elaborated.

Another task yet to be performed is the characterisation of the microbial flora detected on the

screened food products. For this purpose, agar plates of MRS, SB and PA were preserved in the fridge

for samples containing sufficient amounts of BA (values >100 mg/kg1 for any BA) and they will be

sent to a specialized research unit. This will result in a more in depth view on the species present on

the screened food products, information which can then, in consultancy with literature, be linked to

their BA-content.

Also, although the BA-contents in fish are already well characterized by literature, it would be

interesting to finish the screening tests for the food group of fish and fish products as well, as they

were originally a part of the sampling plan. Those data will be more representative for the Belgian

food market and will thus yield a more representative risk assessment for the Belgian population.

Moreover, literature proves that histamine from fish forms an important health risk, frequently

causing food intoxications, which is an additional reason to characterize this risk for the Belgian food

market as precisely as possible.

Some other useful additions to the results of the storage and screening tests could also be made. For

instance, the influence of the packaging atmosphere (O2 and CO2 -concentrations) and the pH of the

samples on the BA-profile could be investigated for instance by finding correlations between the data

recorded during this project. Results of such investigations would be very useful in the optimalisation

of MAP-packaging techniques. The influence of different preparations methods within a certain type

of food product - think about the different marinades on the meat used during the second storage

test or the different production methods of cooked hams - should be investigated as well.

A final suggestion for future investigation concerns the correlation between FAA and BA. The RDA

and MLR performed during the statistical analysis appointed a possible correlation between these

two parameters, yet the correlations were only determined on a wider scale and no distinction was

made between the different food groups. Therefore, additional correlation analyses should be

executed, during which the database should be split up into different food groups. These studies

might then confirm the significant correlations found during this thesis. Or they might reject them,

which would be an equally interesting outcome.

1 The treshold of 100 mg/kg was based on the legal limit of 100 mg/kg, set by Europe for certain fish products (see literature

study). This value is evidently not ideal, because it cannot be representative for other BA than histamine or other food groups than fish, but is was used nevertheless because it was the only guideline available.

70

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74

8. APPENDICES

Appendix 1: Design of the 9-day storage test for marinated pork.

Day 0 Day 3 Day 5 Day 8 Day 9

Number of plates

Analyses Number of plates

Analyses Number of plates

Analyses Number of plates

Analyses Number of plates

Analyses

7 °C Pictures,

atmosphere, pH, BA, FAA, MO,

Sensorial

Pictures,

atmosphere, pH, BA, MO,

Sensorial

Pictures,

atmosphere, pH, BA, MO,

Sensorial

Pictures,

atmosphere, pH, BA, MO,

Sensorial

MAP / 2

2 2

AIR 2 2

2 2

22°C + 7°C Pictures,

atmosphere, pH, BA, MO,

Sensorial

Pictures,

atmosphere, pH, BA, MO,

Sensorial

Pictures,

atmosphere, pH, BA, MO,

Sensorial

MAP

2

2 2

AIR 2

2 2

22°C Pictures,

atmosphere, pH, BA, MO,

Sensorial

Pictures,

atmosphere, pH, BA, MO,

Sensorial

MAP

2 2

AIR 2 2

Total samples 2

12

4

8

8

Appendix 2: Design of the 9-day storage test for 3 types of marinated meat, stored at 7°C and MAP-packaged (70/30 O2/CO2).

Day 0 Day 3 Day 8 Day 9

Number of samples

Analyses Number of

samples Analyses

Number of samples

Analyses Number of

samples Analyses

2 chicken 2 beef 2 lamb

Pictures, atmosphere, pH, BA, FAA, MO,

sensorial

2 chicken 2 beef 2 lamb

Pictures, atmosphere, pH, BA, MO, Sensorial

2 chicken 2 beef 2 lamb

Pictures, atmosphere, pH, BA, MO, Sensorial

2 chicken 2 beef 2 lamb

Pictures, atmosphere, pH, BA, MO, Sensorial

75

Appendix 3: Reagents used during the chemical analyses.

Table 39:Reagents for the FAA-protocol

Reagent R-number Producer Code

TCA R170 Acros Organics 152130025 HCl (25%) R106 Chem-lab CL00.0368.2500 NaOH R92 Chem-lab CL00.1404.5000 H3BO3 R88 Chem-lab CL00.0216.1000 ACN (HPLC-grade) R1872 Fisher Scientific UK A/0627/17 MeOH (HPLC-grade) R1536 Sigma-Aldrich 34860-2.5L-R NaH2PO4.H2O R99 Chem-lab CL00.1465.1000 NaN3 R348 Sigma Aldrich 101338117 o-phtalaldehyde R904 Sigma P1378-5G 3-mercaptopropionic R1960 Acros-Organics 125531000 9-fluorenylmethylformate R1973 Fluka 1286226 22707178

Norvaline Fluka 74670 Sarcosine Fluka 84529 Alanine R217 Fluka 05150 Arginine HCL R216 Sigma A-5131 Asparagine H2O R214 Acros 175272500 Aspartic acid R215 Merck 126 Glutamine R337 Fluka 49419 Glutamic acid R232 Sigma G1626 Glycine R208 Sigma 50046-50G Histidine R233 Fluka 53330 Isoleucine R229 Fluka 58879 Leucine R228 Fluka 61840 Lysine HCl R231 Sigma L6001-25G Methionine R227 M9500-100G Ornithine R432 Sigma O2375-25G Phenylalanine R224 Sigma P-2126 Proline R223 Acros 157620250 Serine R221 Janssen Chimica 13.265.73 Threonine R219 Merck 8410 Tryptophane R218 Fluka 93659 Tyrosine R222 CA Biochem 6570 Valine R220 Fluka 94640

Table 40:Reagents for the BA-protocol.

Reagent R-number Producer Code

TCA R170 Acros Organics 152130025 ACN (HPLC-grade) R1872 Fisher Scientific UK A/0627/17

Dichloromethane R189 Acros Organics 326760025

1,7- diaminoheptane R2075 Sigma-Aldrich 101438602

Na2CO3 R97 Emsure (VWR) 1063921000 Dansyl chloride R1266 Sigma-Aldrich 101563354 MeOH (HPLC-grade) R1536 Sigma-Aldrich 34860-2.5L-R

76

Appendix 4: Materials and Machines used for the chemical analyses.

Material Producer Product Code / Model

Plastic falcon tubes (50 ml and 15 ml)

Test tubes with screw caps

Racks for falcon tubes and test tubes

Measuring cups

Erlenmeyers

Duran Schott-bottles Novolab lab bottles boroglas 1L+scrc.GL45 blauw PP.

Flasks + caps (2000, 1000, 500, 25 and 10ml)

Funnels

Glass pipets

Plastic pipets

Nitrile blue examination gloves VWR Cat No 112-2373

HPLC-vials 854165) SUPELCO 854165

Sterile microfilter (0.45 µm) Thermo Scientific Nalgene Rapid-Flow filters Cat.No.290-4545

Paper filters novolab A26464 130 mm

3 ml syringes Romes Holland 3 part-syringes 3SYR-3ML

Sterile needles Braun 100 Sterican 0,8 x 120 mm 21 G x4 ¾

HPLC-filters Millipore PN SLCR013NR

pH-strips EMD Millipore® 1.09531.0001 MColorpHast® pH Test Strips, 0-6 (Box of 100)

Micropipets (1000 µl + 200 µl) Sigma Aldrich BRAND® Transferpette S

Tips for micropipets Greiner Bio-one Ref 740290

Machines

Analytical balance Sartorius CP6201 + BP301S + CPA324S

Refrigerator chamber (4°C)

Refrigerator (7°C)

Mixer Braun 4165 en 4191

Ultraturrax IKA T25 digital

pH-meter Mettler Toledo SevenCompact pH/Ion s220 (liquid foods); Seveneasy pH (solid food products)

Headspace analyser PBI Dansensor CheckMate 3

HPLC–apparatus Agilent 1100 Series

UPLC-apparatus Dionex Ultimate 3000

Hot water bath (40°C) memmert WNB 29

Centrifuge Sartorius Sigma 4K15

Vortex VWR international P/N VWRI444-1372

Ultrasonic water bath Elma Ultrasonic cleaner Elmasonic SH025EL

77

Appendix 5: Tables required during the calculation of the BA-concentrations.

Table 41: Matrices assigned to each group of food product.

Matrix Food Products

Fresh white cabbage Fresh vegetables, sauerkraut and olives Mixture of coconut fat, syrup and emulsifier Chocolate Wort Beer Very young cheese Non-aqueous diary Milk Aqueous diary Minced meat Meat, meat products and fish

Table 42: Recovery percentages for each food matrix (FWC = fresh white cabbage; MFSE = Mixture of coconut fat, syrup

and emulsifier; VYC = Very young cheese; MM = Minced meat).

Product Tryptamine B-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

FWC 83 +/- 2 92 +/- 7 100 +/- 6 93 +/- 4 89 +/- 6 84 +/- 8

MFSE 62 +/- 10 84 +/- 2 81 +/- 5 89 +/- 3 89 +/- 2 103 +/- 7

Wort 86 +/- 8 95 +/- 3 106 +/- 15 94 +/- 2 95 +/- 2 103 +/- 5

VYC 52 +/- 3 63 +/- 9 92 +/- 8 111 +/- 11 110 +/- 14 83 +/- 10

Milk 93 +/- 14 106 +/- 6 94 +/- 7 98 +/- 2 99 +/- 4 96 +/- 8

MM 53 +/- 5 75 +/- 5 104 +/- 6 101 +/- 2 108 +/- 6 102 +/- 4

Table 43: LOD, LOQ, slopes and intercepts calculated for the lower concentration range calibration curve.

Tryptamine B-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

LOD (ppm) 1,17 1,00 0,11 0,48 3,36 1,88 LOQ (ppm) 4,26 4,31 1,91 2,16 9,94 5,90 a 5,52 8,57 5,87 5,81 7,06 4,24 b -0,06 -0,10 -0,13 -0,06 0,02 -0,02

78

Appendix 6: Materials used during the microbial analyses.

Media and PPS Producer Product Code / Model

PCA Oxoid CM 0325

MRS Oxoid CM 0361

RE Bio-Rad 356-4004

SB Oxoid CM 0377

KAA Oxoid CM XXX

PA Oxoid CM 0559

MSA Oxoid CM 0085

RCA Oxoid CM XXX

Neutralized bacteriological peptone Oxoid LP 0034

Salt Fluka Analytical 71383 -5KG

Pseudomonas supplement Oxoid C-F-C Supplement SR0103E

KAA supplement Oxoid SR 0092E

Preparation of media and PPS

Schott bottles + caps

Erlenmeyer (2L)

Graduated cylinder

Test tubes

Spoon

Heat-proof gloves

Analytical balance Sartorius CP 6201 and TE 4101

Bunsen flame + lab tripod + heating tile

Water boilers Tefal Justine: Type 4054 Series 1

Tefal Gold: Type 2125 Series 1

Phillips Type 4646

Autoclave Presto pbi Field Koch 39160

Autoclaving tape Novolab A00006

Demineralized water

HCl Chem-lab CL00.0368.2500

50/50 ethanol/ water Ethanol:Chem-lab CL00.1807.2500

Timer

Lucifers

Paper

Plating

Vortex Mixer Stuart SA8,

Hot water bath Memmert WNB 29

Analytical balance Sartorius CP 6201 and TE 4101

Metal rack for stomacher bag

Test tubes with 9 ml PPS

Racks for test tubes

Stomacher bags Novolab A11048

Stomacher Stomacher Lab- Blender 400

Microwave Proline SM 107

79

Petri plates Gosselin SB93-101

Pipette (1.0, 10 and 50 ml) Novolab A13671 (1ml), A13684 (10ml)

Greiner bio one 768180 (50ml)

Micropipette Finnpipette

Fridges Liebherr profi line UKS2600/UKS1800/FKU2610

Incubators Termaks KB 8400/B8133

Cup filled with 100% ethanol

Anaerogen bags Oxoid AN0010C

Spoon

Scalpel

Pincet

Drigalski spatula’s Novolab A10538

Waste bag

80

Appendix 7: Pictures of tuna samples during 6-day storage test.

DAY 3

MAP – 7°C MAP – 22°C (3h) + 7°C MAP – 22°C

Air – 7°C Air – 22°C (3h) + 7°C Air – 22°C

DAY 5

MAP – 7°C MAP – 22°C (3h) + 7°C MAP – 22°C

Air – 7°C Air – 22°C (3h) + 7°C Air – 22°C

Day 6

MAP – 7°C MAP – 22°C (3h) + 7°C MAP – 22°C

81

Air – 7°C Air – 22°C (3h) + 7°C Air – 22°C

82

Appendix 8: BA-concentrations on the last day of analysis of the storage test for marinated pork:.

Mean values of the two samples on the last day of analysis for each condition and each BA are

plotted.

0

50

100

150

200

250

300

350

400

7°C - MAP 22°C - MAP 22°C/7°C - MAP

7°C - Air 22°C - Air 22°C/7°C - Air

BA

- c

on

cen

trat

ion

(p

pm

)

Tryptamine

B-Phenylethylamine

Putrescine

Cadaverine

Histamine

Tyramine

83

Appendix 9: Pictures of marinated pork during the 9-day storage test.

DAY 3

MAP -7°C MAP -22°C MAP – 22°C (3h) + 7°C

Air – 7°C Air – 22°C Air - 22°C (3h) + 7°C

DAY 5

MAP -7°C MAP -22°C MAP – 22°C (3h) + 7°C

Air – 7°C Air – 22°C Air - 22°C (3h) + 7°C

/

/

DAY 8

MAP -7°C MAP -22°C MAP – 22°C (3h) + 7°C

/

84

Air – 7°C Air – 22°C Air - 22°C (3h) + 7°C

/

DAY 9

MAP -7°C MAP -22°C MAP – 22°C (3h) + 7°C

/

Air – 7°C Air – 22°C Air - 22°C (3h) + 7°C

/

85

Appendix 10: Results of the screening tests on salami’s and dried sausages.

Table 44: BA-concentrations (mg/kg) in dried sausages and salami’s collected during screening tests. For the calculation of means and other characteristics, B-values were filled out when unavailable by copying the A-concentrations (see materials and methods).

Tryptamine B-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

DRIED SAUSAGES

262 A 9 4 14 39 2 124

263 A <LOD 4 9 1 <LOD 18

264 A 33 12 84 65 3 205

265 A 23 6 8 2 <LOD 71

266 A <LOD 9 156 10 <LOD 134

267 A 6 <LOD <LOD 1 <LOD <LOD

268 A <LOD 1 <LOD 2 <LOD 15

268 B <LOD <LOD 12 1 <LOD 12

269 A 9 <LOD 0 0 <LOD 3

272 A 33 <LOD 307 63 3 226

272 B <LOD <LOD <LOD 3 <LOD 35

273 A <LOD <LOD <LOD <LOD <LOD 8

273 B <LOD 7 6 <LOD 5 12

277 A <LOD <LOD <LOD 13 <LOD 93

308 A <LOD <LOD <LOD <LOD <LOD <LOD

308 B <LOD <LOD 7 1 <LOD <LOD

309 A <LOD <LOD <LOD 7 <LOD 30

309 B <LOD <LOD 7 8 2 41

310 A <LOD <LOD <LOD <LOD <LOD 139

310 B <LOD 14 9 <LOD <LOD 182

311 A 2 4 3 2 <LOD <LOD

311 B 5 <LOD 9 10 <LOD 64

312 A 10 24 137 <LOD 54 163

313 A 32 8 55 158 22 115

Mean A 9 4 45 21 5 79

B 7 6 30 18 5 75

Stdev A 13 6 84 41 14 77

B 11 7 49 40 14 68

Min A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

P50 A 2 1 3 2 <LOD 71

B <LOD 4 9 2 <LOD 64

P90 A 32 10 145 64 11 180

B 27 13 105 50 12 171

Max A 33 24 307 158 54 226

B 33 24 156 158 54 205

SALAMI’S

270 A <LOD 1 <LOD 7 <LOD 24

270 B <LOD 4 4 7 <LOD 30

271 A <LOD <LOD 57 2 2 97

271 B 2 <LOD <LOD 57 1 8

274 A <LOD 12 8 3 <LOD 53

274 B <LOD 10 4 1 <LOD 26

275 A <LOD 4 141 2 3 153

275 B <LOD 1 136 4 3 134

276 A <LOD 2 <LOD 3 <LOD 73

86

276 B <LOD 2 8 3 <LOD 64

305 A 31 10 63 2 13 121

306 A <LOD <LOD <LOD 2 <LOD <LOD

306 B <LOD <LOD <LOD 1 <LOD <LOD

307 A <LOD <LOD <LOD <LOD <LOD <LOD

307 B <LOD <LOD 8 <LOD <LOD <LOD

Mean A 4 4 34 3 2 65

B 4 3 28 9 2 48

Stdev A 11 5 51 2 4 56

B 11 4 49 19 4 53

Min A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

P50 A <LOD 1 4 2 <LOD 63

B <LOD 2 6 3 <LOD 28

P90 A 9 11 87 4 6 130

B 11 10 85 22 6 125

Max A 31 12 141 7 13 153

B 31 10 136 57 13 134

Table 45: FAA-concentrations (mg/kg) for salami's/dried sausages, measured on day 0.

Histidine Arginine Tyrosine Tryptophane Phenylalanine Ornithine Lysine

DRIED SAUSAGE

262 64 102 60 12 82 19 163

263 92 11 <LOD 12 177 75 264

264 99 9 13 <LOD 319 111 397

265 70 54 21 <LOD 97 38 187

266 112 11 <LOD 29 187 <LOD 329

267 18 22 30 18 35 <LOD 85

268 178 32 158 34 291 266 584

269 132 346 139 49 165 <LOD 570

272 220 9 <LOD 31 379 25 688

273 115 18 137 32 198 184 363

277 169 126 71 55 232 20 683

308 93 38 130 39 242 178 323

309 84 34 57 23 105 80 305

310 104 216 54 40 255 65 386

311 65 11 86 20 108 101 282

312 44 84 139 11 246 56 405

313 198 405 272 1 85 10 125

Mean 109 90 80 24 189 72 361

Stdev 55 121 74 17 95 76 182

Min 18 9 <LOD <LOD 35 <LOD 85

P50 99 34 60 23 187 56 329

P90 186 268 147 43 302 180 624

Max 220 405 272 55 379 266 688

SALAMI

270 121 5 90 21 150 150 326

271 137 11 96 28 212 173 392

274 131 6 98 37 192 173 343

275 108 11 38 32 222 52 553

276 128 6 58 34 179 174 363

87

305 53 14 2 <LOD 97 39 211

306 55 10 79 19 109 89 151

307 57 73 44 12 104 53 133

Mean 99 17 63 23 158 113 309

Stdev 37 23 34 13 50 60 139

Min 53 5 2 <LOD 97 39 133

P50 114 10 69 24 165 119 335

P90 133 31 97 35 215 173 440

Max 137 73 98 37 222 174 553

Table 46: Log-values of microbial counts (CFU/g) of different groups of bacteria on salami/dried sausages. An upper bound scenario was used in the calculations of means and other characteristics.

Total count LAB Staphylococci Enterobactericeae Enterococci

DRIED SAUSAGE

262 8,61 7,63 7,40 <1 <3

263 7,68 7,31 <4 <1 7,36

264 8,39 8,58 3,60 <3 <3

265 8,53 8,52 8,00 <3 <3

266 4,56 8,43 <4 <3 3,95

267 8,00 8,00 7,18 <3 <3

268 8,59 8,51 6,00 <3 <3

272 7,01 6,76 5,43 <3 5,66

273 8,20 8,40 6,53 <3 <3

277 7,33 7,51 5,70 <3 <3

308 8,47 8,54 5,93 <3 5,48

309 8,18 8,16 5,85 <3 <3

310 8,22 7,09 <3 <3 6,00

311 6,92 7,22 5,37 <3 <3

312 8,35 8,25 5,25 <3 <3

313 9,17 8,65 8,94 5,02 5,43

Mean 7,89 7,97 6,24 0,30 3,99 Stdev 1,08 0,62 1,37 1,22 1,47 Min 4,56 6,76 3,60 <1 <3 P50 8,21 8,20 5,77 3,00 3,00 P90 8,60 8,56 7,70 3,00 5,83 Max 9,17 8,65 8,94 5,02 7,36

SALAMI

270 8,87 8,42 8,42 <3 4,90

271 7,76 7,33 6,51 <3 5,19

274 8,57 8,51 7,10 <3 3,00

275 8,57 8,50 5,66 <3 <3

276 8,43 8,39 6,82 <3 3,00

306 7,34 7,53 5,60 <3 <3

307 8,68 8,24 5,30 <3 <3

Mean 8,32 8,13 6,49 <3 3,58 Stdev 0,55 0,49 1,09 <3 1,00 Min 7,34 7,33 5,30 <3 3,00 P50 8,57 8,39 6,51 <3 3,00 P90 8,76 8,50 7,63 <3 5,02 Max 8,87 8,51 8,42 <3 5,19

Appendix 11: Results of the screening tests on cooked hams.

88

Table 47: BA-concentrations (mg/kg) in cooked hams. For the calculation of means and other characteristics, B-values were filled out when unavailable by copying the A-concentrations (see materials and methods).

Tryptamine B-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

317 A 2 3 47 2 2 86

B <LOD <LOD <LOD 56 1 11

321 A 6 <LOD <LOD 2 <LOD 2

B <LOD <LOD <LOD 2 <LOD 3

326 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD 33

327 A 2 <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD 30

328 A 2 <LOD <LOD <LOD <LOD <LOD

B 2 <LOD <LOD <LOD <LOD 36

332 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD 17

335 A <LOD <LOD <LOD <LOD <LOD <LOD

B 4 <LOD <LOD 3 <LOD 15

341 A <LOD <LOD <LOD <LOD <LOD <LOD

B 2 <LOD <LOD 9 <LOD 24

342 A <LOD <LOD <LOD <LOD <LOD 4

B <LOD <LOD <LOD 1 <LOD 25

343 A <LOD <LOD <LOD <LOD <LOD 8

B <LOD <LOD <LOD <LOD 2 61

344 A <LOD <LOD <LOD 5 <LOD 2

B <LOD <LOD <LOD 3 <LOD <LOD

345 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD 3 8 2 70

347 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD 26

351 A <LOD <LOD <LOD <LOD <LOD 2

B 3 <LOD <LOD <LOD <LOD <LOD

352 A <LOD <LOD <LOD <LOD <LOD 49

B <LOD <LOD <LOD 3 <LOD 59

353 A <LOD <LOD <LOD <LOD <LOD <LOD

B 2 <LOD <LOD <LOD <LOD <LOD

Mean A 1 <LOD 3 1 <LOD 10

B 1 <LOD <LOD 5 <LOD 26

Stdev A 2 1 12 1 1 24

B 1 <LOD 1 14 1 22

Min A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

P50 A 0 0 0 0 0 0

B 0 0 0 0 0 25

P90 A 2 0 0 2 0 28

B 3 0 0 9 2 60

Max A 6 3 47 5 2 86

B 4 <LOD 3 56 2 70

89

Table 48: FAA-concentrations (mg/kg) in cooked hams.

Sample nr. Histidine Arginine Tyrosine Tryptophane Phenylalanine Ornithine Lysine

317 38 100 95 23 89 <LOD 160

321 <LOD 152 106 30 138 <LOD 217

326 48 230 63 17 91 <LOD 147

327 29 66 57 23 66 <LOD 71

328 36 54 36 23 37 <LOD 60

332 45 93 68 25 61 <LOD 96

335 40 77 49 22 44 <LOD 84

341 30 67 50 20 55 <LOD 62

342 31 70 50 22 58 <LOD 70

343 73 87 56 49 109 <LOD 150

344 45 78 62 48 69 <LOD 115

345 89 114 90 51 129 <LOD 175

347 94 118 85 55 117 <LOD 193

351 47 71 66 54 78 <LOD 150

352 79 49 25 56 110 91 164

353 76 163 107 57 113 65 170

Mean 50 99 67 36 85 10 130 Stdev 25 48 24 16 31 27 51

Min <LOD 49 25 17 37 <LOD 60

P50 45 82 62 27 84 0 148 P90 84 157 100 56 123 32 184 Max 94 230 107 57 138 91 217

Table 49: Log-values of microbial counts (CFU/g) of different groups of bacteria in cooked hams.

Sample nr. Total count LAB Staphylococci Enterobacteriaceae Enterococci

317 8,37 8,44 <3 <3 <3

321 7,09 6,62 <3 <3 <3

326 8,75 8,71 <3 <3 <3

327 8,68 8,81 <3 <3 <3

328 7,26 7,34 <3 <3 3,48

332 8,64 8,68 <3 <3 <3

335 5,92 <3 3,30 <3 <3

341 9,00 9,03 <3 <3 <3

342 8,87 8,54 <3 <3 <3

343 8,86 8,42 <3 <3 <3

344 8,25 8,31 <3 <3 <3

345 8,56 8,57 <3 <3 <3

347 8,90 8,81 <3 <3 3,30

351 6,10 6,05 <3 <3 <3

352 8,84 8,75 <3 <3 <3

353 7,08 7,00 6,85 <3 <3

Mean 8,07 8,14 0,63 <3 0,42

Stdev 1,03 0,92 1,85 <3 1,16

Min 5,92 6,05 <3 <3 <3

P50 8,60 8,49 3,00 <3 3,00

P90 8,89 8,81 3,15 <3 3,15

Max 9,00 9,03 6,85 <3 3,48

90

Appendix 12: Results of the screening tests on raw dried and cured hams and beef products.

Table 50: BA-concentrations (mg/kg) in raw hams. For the calculation of means and other characteristics, B-values were filled out when unavailable by copying the A-concentrations (see materials and methods).

Tryptamine B-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

RAW HAMS

314 A <LOD <LOD 1 1 <LOD <LOD

B <LOD <LOD 2 1 <LOD <LOD

315 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD 5 <LOD <LOD

316 A <LOD <LOD <LOD 5 <LOD 5

B <LOD <LOD <LOD 7 <LOD 10

318 A <LOD <LOD 2 1 <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

319 A <LOD <LOD 1 <LOD <LOD <LOD

B <LOD <LOD 1 <LOD <LOD <LOD

320 A <LOD <LOD 1 3 <LOD 4

B <LOD <LOD 2 2 <LOD 3

322 A <LOD <LOD <LOD <LOD <LOD <LOD

323 A <LOD <LOD 7 77 <LOD <LOD

B <LOD <LOD <LOD 2 7 <LOD

324 A <LOD <LOD <LOD <LOD <LOD <LOD

B 17 6 183 18 22 178

325 A <LOD <LOD 7 3 2 <LOD

B <LOD <LOD 5 2 <LOD <LOD

330 A <LOD <LOD 1 1 <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

331 A 20 2 32 <LOD 2 107

B 112 8 114 2 <LOD 365

333 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD 1 1 <LOD <LOD

334 A 2 <LOD <LOD <LOD <LOD 59

B 7 3 41 <LOD <LOD 90

336 A <LOD <LOD <LOD 3 <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

337 A <LOD <LOD 3 1 <LOD 10

338 A 10 <LOD <LOD 5 <LOD 65

B 33 12 28 12 <LOD 140

339 A 8 <LOD <LOD <LOD <LOD 35

B 38 8 14 <LOD <LOD 111

346 A <LOD <LOD 1 15 <LOD 7

B <LOD <LOD 1 13 <LOD 10

349 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD 2 <LOD <LOD

350 A <LOD <LOD 1 1 2 <LOD

B <LOD <LOD 3 1 <LOD 7

356 A <LOD <LOD 3 <LOD <LOD 3

B <LOD 1 <LOD <LOD <LOD <LOD

357 A <LOD <LOD 4 1 <LOD 9

B <LOD <LOD <LOD 1 <LOD 24

Mean A 2 <LOD 3 5 <LOD 13

B 9 2 17 3 1 41

Stdev A 5 1 7 16 1 28

91

B 25 3 44 5 5 87

Min A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

P50 A 0 0 1 1 0 0

B 0 0 1 1 0 0

P90 A 7 0 6 5 1 54

B 30 7 38 11 0 134

Max A 20 2 32 77 2 107

B 112 12 183 18 22 365

RAW DRIED BEEF PRODUCTS

329 A <LOD <LOD 1 31 4 5

B <LOD 2 23 3 7 57

340 A <LOD <LOD 1 <LOD <LOD 10

B 9 <LOD 3 <LOD <LOD 107

348 A 59 5 1 <LOD 3 238

B 52 <LOD <LOD <LOD 3 227

354 A <LOD <LOD 1 <LOD 2 28

B 109 4 21 177 <LOD 265

355* A 10 <LOD 3 44 <LOD 62

B <LOD <LOD 1 <LOD 2 97

Mean A 14 1 1 15 2 69

B 34 1 10 36 2 151

Stdev A 25 2 1 21 2 97

B 47 2 11 79 3 90

Min A <LOD <LOD 1 <LOD <LOD 5

B <LOD <LOD <LOD <LOD <LOD 57

P50 A <LOD <LOD 1 <LOD 2 28

B 9 <LOD 3 <LOD 2 107

P90 A 39 3 2 39 3 168

B 86 3 22 107 5 250

Max A 59 5 3 44 4 238

B 109 4 23 177 7 265

*Horsemeat

Table 51: FAA-concentrations (mg/kg) in raw ham (pork) and raw dried beef products.

Histidine Arginine Tyrosine Tryptophane Phenylalanine Ornithine Lysine

RAW HAM

314 777 1647 934 200 1133 100 2750

315 488 1115 575 107 741 42 1836

316 734 1408 720 167 973 137 2612

318 613 1290 677 149 819 94 2057

319 1117 2150 1158 280 1530 236 3787

320 1388 2687 1422 381 1992 205 4488

322 1345 2615 1463 326 1914 220 4308

323 <LOD 3105 1341 445 2188 143 4829

324 56 41 89 19 111 <LOD 176

325 576 963 630 120 720 348 2008

330 665 1464 822 178 964 67 2469

331 318 192 365 104 656 232 957

333 655 1458 889 176 873 71 2391

334 54 87 23 28 98 34 141

336 960 2107 1003 284 1542 59 3437

92

337 734 1610 883 221 1166 47 2676

338 71 195 57 30 123 24 <LOD

339 67 137 77 28 130 17 253

346 892 1739 1191 263 1212 107 2937

349 248 604 371 88 416 62 918

350 1533 3234 1940 516 2370 210 5167

356 242 36 279 87 324 313 671

357 561 1122 650 186 739 <LOD 1675

Mean 613 1348 763 191 988 120 2284

Stdev 450 990 509 135 677 101 1561

Min <LOD 36 23 19 98 <LOD <LOD

P50 613 1408 720 176 873 94 2391

P90 1299 2673 1405 370 1977 235 4452

Max 1533 3234 1940 516 2370 348 5167

RAW DRIED BEEF

329 479 763 611 137 679 72 1577

340 66 121 114 36 175 20 138

348 701 114 471 157 1001 527 2226

354 69 127 96 62 164 <LOD 171

355* 373 629 27 87 797 172 634

Mean 338 351 264 96 563 158 949

Stdev 274 319 260 51 378 217 920

Min 66 114 27 36 164 <LOD 138

P50 373 127 114 87 679 72 634

P90 612 709 555 149 920 385 1967

Max 701 763 611 157 1001 527 2226

*Horsemeat

Table 52: Log-values of microbial counts(CFU/g) in raw hams (pork) and raw dried beef products.

Total count LAB Staphylococci Entero-

bacteriaceae Enterococci Pseudomonas

RAW HAM

314 9,81 <3 3,85 <3 <3

315 4,89 4,41 3,30 <3 <3 <3

316 <3 <3 <3 <3 <3

318 4,58 <3 4,28 <3 <3

319

<3 <3 <3 <3 <3

320 5,64 3,60 <4 <3 3,00 <3

322 4,08 4,48 <3 <3 <3 <3

323 5,26 5,45 4,32 <3 <3 3,30

324 8,47 8,37 <4 <3 6,48 <3

325 3,48 <3 <4 <3 <3 <3

330 3,00 <3 3,30 <3 <3

331 7,94 7,83 <4 <3 <3 <3

333 3,48 <3 3,78 <3 <4 <3

334 8,32 8,40 <3 <3 <3

336 4,46 4,08 4,59 <3 <3 <3

337 4,64 4,28 4,46 <3 <3 <3

338 8,29 7,84 <3 <3 <3

339 8,47 8,39 <3 <3 <3

346 4,76 3,30 4,38 <3 <3

349 6,64 6,74 <3

9,30 <3

350 3,48 3,48 <2 <2 <3 <3

93

356 8,23 8,10 6,20 <3 <3

357 7,53 7,50 6,36 <3 <3

Mean 5,84 5,10 3,64 2,95 3,47 3,02

Stdev 2,17 2,20 1,32 0,21 1,47 0,08

Min <3 <3 <2 <3 <3 <3

P50 5,07 4,28 3,85 3,00 3,00 3,00

P90 8,45 8,31 4,57 3,00 3,80 3,00

Max 9,81 8,40 6,36 <3 9,30 3,30

RAW DRIED BEEF

329 6,95 6,28 6,78 <2 <3 <3

340 8,31 8,13 <3 <3 <3

348 6,75 3,60 6,58 <3 <3 <3

354 8,12 8,02 3,48 <3 <3

355* 8,34 8,24 <3 <3 <3

Mean 7,70 6,86 4,57 2,80 3,00 3,00

Stdev 0,78 1,99 1,94 0,45 0,00 0,00

Min 6,75 3,60 3,00 <2 <3 <3

P50 8,12 8,02 3,48 3,00 3,00 3,00

P90 8,33 8,20 6,70 3,00 3,00 3,00

Max 8,34 8,24 6,78 <3 <3 <3

*Horsemeat

Appendix 13: Results of the screening tests on meat preparations.

Table 53: BA-concentrations (mg/kg) in several meat preparations. For the calculation of means and other characteristics, B-values were filled out when unavailable by copying the A-concentrations (see materials and methods).

Tryptamine B-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

372 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD 30 50 3 64

373 A <LOD 1 1 <LOD 2 <LOD B <LOD <LOD <LOD <LOD 1 3

374 A <LOD <LOD <LOD <LOD 2 <LOD B 13 <LOD <LOD <LOD 2 39

375 A <LOD <LOD 1 <LOD 1 10 B <LOD 1 <LOD <LOD <LOD 139

376 A <LOD <LOD 2 1 <LOD <LOD B <LOD <LOD <LOD 47 <LOD 2

377 A <LOD 4 2 9 <LOD 27 B <LOD 3 2 9 <LOD 25

378 A <LOD <LOD <LOD 2 <LOD <LOD B <LOD <LOD <LOD 2 <LOD <LOD

379 A <LOD <LOD <LOD 8 <LOD 8 B 11 1 <LOD 78 <LOD 41

380 A <LOD <LOD <LOD <LOD <LOD 2 B 40 <LOD 2 1 11 95

381 A <LOD <LOD 1 7 <LOD 8 B <LOD <LOD <LOD 15 <LOD 3

382 A <LOD <LOD 3 <LOD <LOD <LOD B <LOD <LOD 1 <LOD <LOD 9

383 A <LOD <LOD <LOD <LOD <LOD <LOD B 2 <LOD <LOD 1 <LOD 11

384 A <LOD <LOD 2 <LOD <LOD <LOD

B <LOD <LOD 3 5 <LOD <LOD

385 A <LOD <LOD <LOD <LOD <LOD <LOD

B 8 <LOD 1 1 4 <LOD

386 A <LOD <LOD <LOD 1 <LOD 3 B <LOD <LOD 1 2 <LOD 11

94

387 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

388 A <LOD <LOD 1 6 <LOD <LOD

B 5 <LOD 1 11 <LOD 39

389 A <LOD <LOD <LOD 2 <LOD 13 B <LOD 2 <LOD 1 <LOD 121

390 A <LOD <LOD <LOD 1 <LOD 33 B 44 3 9 2 <LOD 104

391 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD 5

392 A <LOD <LOD 1 <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

393 A <LOD <LOD 1 1 <LOD <LOD

B <LOD <LOD 1 2 <LOD <LOD

394 A <LOD <LOD 1 <LOD <LOD <LOD

B <LOD <LOD 1 <LOD <LOD <LOD

395 A <LOD <LOD 1 <LOD <LOD 3 B 21 <LOD <LOD 73 8 63

396 A <LOD <LOD <LOD <LOD <LOD <LOD

B 83 3 163 269 29 195

462 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD 3 <LOD 5

463 A <LOD <LOD 1 1 <LOD <LOD

B <LOD <LOD <LOD 10 <LOD <LOD

464 A <LOD <LOD <LOD 0 <LOD <LOD

B <LOD <LOD <LOD 1 <LOD 22

465 A <LOD <LOD 2 3 1 11

B <LOD <LOD 6 2 <LOD <LOD

466 A <LOD <LOD 157 18 3 102 B <LOD <LOD 4 13 <LOD 19

467 A <LOD <LOD 1 <LOD <LOD <LOD

B <LOD <LOD 1 <LOD <LOD <LOD

468 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

469 A <LOD <LOD <LOD 2 <LOD <LOD

B <LOD <LOD <LOD 3 <LOD <LOD

470 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD 1 <LOD <LOD <LOD

471 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD 1 9 3 31

472 A <LOD <LOD <LOD <LOD <LOD <LOD B <LOD <LOD <LOD <LOD <LOD 5

473 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

474 A <LOD <LOD 1 <LOD <LOD <LOD

B <LOD <LOD 5 8 2 52

475 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD 1 <LOD <LOD <LOD

476 A <LOD <LOD <LOD <LOD 3 <LOD

B 15 2 1 <LOD 7 38

Mean A <LOD <LOD 4 2 <LOD 6 B 6 <LOD 6 15 2 29

Stdev A <LOD 1 25 4 1 17 B 16 1 26 45 5 45

Min A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD <LOD <LOD <LOD <LOD

P50 A <LOD <LOD <LOD <LOD <LOD <LOD

B <LOD <LOD 1 1 <LOD 5

P90 A <LOD <LOD 2 6 1 12 B 16 2 5 47 4 96

95

Max A <LOD 4 157 18 3 102 B 83 3 163 269 29 195

Table 54: FAA-concentrations (mg/kg) in meat preparations.

Sample nr. Histidine Arginine Tyrosine Tryptophane Phenylalanine Ornithine Lysine

372 160 421 214 88 178 <LOD 423 373 25 68 32 14 25 <LOD 66 374 25 68 32 14 25 <LOD 66 375 25 68 32 14 25 <LOD 66 376 25 68 32 14 25 <LOD 66 377 79 55 51 56 117 57 188 378 59 99 63 65 51 <LOD 121 379 55 15 35 <LOD 46 <LOD 76 380 67 136 90 48 101 <LOD 270 381 127 124 129 65 164 78 326 382 168 403 193 82 154 <LOD 343 383 47 86 38 <LOD 41 <LOD 79 384 51 88 64 53 65 <LOD 122 385 61 94 63 <LOD 70 <LOD 104 386 61 131 79 49 93 <LOD 124 387 76 169 121 27 90 <LOD 203 388 37 50 53 21 80 19 112 389 62 150 73 23 175 32 184 390 77 122 58 23 141 12 254 391 44 163 54 21 91 <LOD 112 392 41 90 69 27 71 <LOD 113 393 42 77 54 25 43 <LOD 106 394 67 143 112 28 85 <LOD 165 395 138 294 205 54 155 <LOD 316 396 27 42 37 <LOD 29 <LOD 57 462 16 145 25 13 39 <LOD 44 463 87 53 94 19 181 80 289 464 44 0 85 31 67 0 175 465 25 223 29 20 30 41 77 466 106 45 95 24 195 106 349 467 67 143 84 28 78 33 146 468 18 59 22 14 31 17 46 469 26 89 27 11 38 13 63 470 14 159 17 18 25 0 43 471 53 278 96 21 79 15 248 472 20 50 33 15 46 13 63 473 17 69 25 12 38 12 48 474 44 0 86 34 69 <LOD 145 475 47 139 85 27 90 18 151 476 18 98 22 13 27 24 45

Mean 56 119 61 23 74 19 126 Stdev 38 93 49 22 52 25 102 Min 14 <LOD 17 <LOD 25 <LOD 43 P50 47 92 61 22 69 <LOD 117 P90 108 228 122 57 165 43 317 Max 168 421 214 88 195 106 423

96

Table 55: Log-values of the microbial counts (CFU/g) in meat preparations at the end of storage.

Sample nr. Total count LAB Staphylococci

Entero- bacteriaceae

Enterococci Pseudomonas

372 8,60 8,40 5,02 6,86 3,85

373 8,79 8,83 4,66 4,08 <3

374 8,64 8,66 4,32 4,98 3,00

375 8,79 8,83 3,78 <3 3,00

376 8,55 8,68 3,90 <3 4,20

377 4,81 <3 <3 <3 <3

378 <3 <3 <3 <3 <3

379 7,73 7,81 <3 <3 4,00

380 7,91 8,02 3,60 <3 <3

381 <3 <3 <3 <3 <3

382 8,14 8,09 <3 <3 <3

383 8,31 8,51 <3 4,99 <3

384 8,68 7,82 4,23 6,08 <3

385 7,92 7,92 <3 <3 <3

386 7,98 8,00 3,00 <3 <3

387 6,38 6,32 4,94 <3 <3

388 8,85 8,57 4,18 <3 <3

389 8,85 8,68 3,00 <3 <3

390 8,74 8,68 3,95 <3 <3

391 8,89 8,73 3,70 <3 <3

392 4,66 4,54 <3 <3 <3

393 <3 <3 <3 <3 <3

394 4,32 5,30 3,70 <3 <3

395 9,11 8,58 3,30 7,10 4,00

396 7,87 8,21 <3 <3 <3

462 8,19 7,95 <4 7,63 <3 7,72

463 7,93 7,05 4,00 <3 <3 4,79

464 8,33 8,28 <4 4,98 5,43 5,63

465 8,76 6,63 4,85 4,68 <3 8,84

466 6,32 6,15 <4 <3 <3 7,36

467 <3 <3 <3 <3 4,08 <3

468 9,18 3,78 0,00 0,00 <3 4,49

469 <3 <3 <3 <3 <3 <3

470 <3 <3 <3 <3 <3 3,60

471 8,58 7,91 4,60 5,52

7,06

472 4,79 7,41 3,60 4,11 <3 4,18

473 6,88 6,78 <4 <3

<3

474 8,93 8,99 <3 5,68 4,08 5,27

475 5,87 5,81 <3 <3 <3 <3

476 8,16 8,72 <4 <3 <3 3,48

Mean 7,06 6,84 3,53 3,69 3,23 4,96 Stdev 2,16 2,15 0,86 1,46 0,54 1,96 Min <3 <3 <3 <3 <3 <3

97

P50 8,06 7,92 3,60 3,00 3,00 4,49 P90 8,86 8,72 4,61 5,72 4,03 7,57 Max 9,18 8,99 5,02 7,63 5,43 8,84

Appendix 14: Preparation methods of cooked and raw dried and cured ham samples as designated

on the package.

COOKED

Sample nr. Smoked Grilled Roasted

317 321 326 327 328 332 335 341 342 343 344 345 347 351 352 353 RAW

Sample nr. Dried Smoked Specification

314 12 months 315

316 318 319 320 min 24 months

322 18 months 323

324

Ferments added

325 12- 14 months 329

Beef

330 331

Beef

333 9 months 334

336 337 11 months

338 339

98

340

Beef

346 7 months

348

Beef, Ferments added

349 350 354

Beef

355

Horse

356 357

99

Appendix 15: Overview of the BA-concentrations in different food groups and their subgroups.

Table 56: Overview of BA-distribution in F&V and it's subgroups. Mean, median, P50, P90 and max are given in mg/kg. Timepoint A = day of purchace = day 0; Timepoint B = after expiry date.

Subgroup N Timepoint

Tryptamine B-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

Overall 103 A mean 3 0 50 9 10 16

P50 0 0 7 0 0 0

P90 14 1 172 33 31 75

max 30 13 419 74 64 100

N <LOD 69 86 26 67 54 70

B mean 4 5 67 13 12 21

P50 0 0 6 0 0 0

P90 10 2 167 37 44 74

max 41 322 419 82 133 99

N <LOD 77 82 33 60 54 73

Fresh products 34 A mean 0 1 9 0 11 1

P50 0 0 9 0 0 0

P90 0 2 16 0 27 3

max 2 13 26 0 39 5

N <LOD 32 26 1 31 17 26

Olives 41 A mean 4 0 2 0 0 0

P50 0 0 0 0 0 0

P90 17 0 4 1 2 0

max 30 0 15 12 5 0

N <LOD 29 41 24 34 34 41

B mean 2 0 1 0 0 0

P50 0 0 0 0 0 0

P90 2 0 2 1 2 0

max 41 0 7 1 4 0

N <LOD 35 41 31 35 35 41

Sauerkraut 28 A mean 7 1 173 33 23 57

P50 4 0 145 32 19 61

P90 11 1 185 36 31 76

max 21 2 419 74 64 100

N <LOD 8 18 0 1 1 1

100

B mean 7 12 173 33 30 55

P50 4 0 152 31 21 55

P90 17 2 297 62 57 88

max 21 322 419 82 133 99

N <LOD 9 19 0 1 1 2

Table 57: Overview of BA-distribution in chocolate and it's subgroups. Mean, median, P50, P90 and max are given in mg/kg. Timepoint A = day of purchace = day 0; Timepoint B = after expiry date.

Subgroup N Timepoint

Tryptamine B-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

Chocolate 43 A mean 4 2 3 3 1 8

P50 4 2 1 1 0 7

P90 8 5 7 9 4 16

max 15 8 16 17 18 29

N <LOD 15 12 13 19 29 11

Dark 33 A mean 5 3 3 4 2 10

P50 5 3 3 1 0 8

P90 9 5 9 9 4 17

max 15 8 16 17 18 29

N <LOD 5 3 4 10 20 2

White 10 A mean 0 0 1 1 0 1

P50 0 0 0 0 0 0

P90 0 0 1 1 0 1

max 0 4 7 9 2 14

N <LOD 10 9 9 9 9 9

Table 58: Overview of BA-distribution in beer and it's subgroups. Mean, median, P50, P90 and max are given in mg/kg. Timepoint A = day of purchace = day 0; Timepoint B = after expiry date.

Category N Timepoint

Tryptamine B-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

Beer 70 A mean 0 0 5 4 4 10

P50 0 0 3 0 0 0

P90 0 2 8 10 16 33

max 7 6 36 52 29 67

N <LOD 65 56 0 44 51 46

101

Amber 7 A mean 0 0 4 0 3 1

P50 0 0 3 0 0 0

P90 0 0 7 0 8 4

max 0 0 11 0 20 9

N <LOD 7 7 0 7 6 6

Light/Lager 22 A mean 0 0 5 1 2 8

P50 0 0 3 0 0 0

P90 0 1 4 2 0 40

max 0 1 36 13 20 67

N <LOD 22 18 0 16 20 18

Dark 13 A mean 2 0 4 0 0 1

P50 0 0 3 0 0 0

P90 6 0 4 0 0 0

max 7 0 5 1 0 11

N <LOD 8 13 0 12 13 12

Home-brewed 7 A mean 0 0 3 0 0 0

P50 0 0 3 0 0 0

P90 0 0 4 0 0 0

max 0 0 5 0 0 0

N <LOD 7 7 0 4 7 7

Fruit beer 21 A mean 0 1 6 10 11 25

P50 0 0 5 4 11 26

P90 0 2 12 33 23 39

max 0 6 19 52 29 64

N <LOD 21 11 0 5 5 3

Table 59:Overview of BA-distribution in dairy products and it's subgroups. Mean, median, P50, P90 and max are given in mg/kg. Timepoint A = day of purchace = day 0; Timepoint B = after expiry date.

Category N Timepoint

Tryptamine B-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

Dairy 104 A mean 2 4 17 30 25 86

P50 0 0 0 1 0 0

P90 0 16 48 77 56 300

max 110 73 269 406 1025 1111

N <LOD 92 75 61 39 62 53

102

B mean 3 8 17 39 30 104

P50 0 0 0 1 0 4

P90 0 18 56 100 67 390

max 110 219 255 904 1025 1306

N <LOD 92 75 53 37 64 50

Yoghurt 18 A mean 0 0 0 0 0 0

P50 0 0 0 0 0 0

P90 0 0 0 1 0 0

max 0 0 3 2 0 6

N <LOD 16 16 15 9 16 15

B mean 0 0 0 1 0 0

P50 0 0 0 0 0 0

P90 0 0 0 1 0 0

max 0 0 3 2 0 6

N <LOD 16 16 15 8 16 15

Soft cheese 26 A mean 0 3 23 40 13 21

P50 0,0 0,0 0,0 0,0 0,0 0,0

P90 0,0 12,8 61,2 112,1 48,9 41,2

max 3 20 253 399 110 245

N <LOD 25 20 14 14 17 20

B mean 1 3 26 75 18 33

P50 0,0 0,0 1,3 0,9 0,0 0,0

P90 0,0 12,5 102,5 141,0 65,2 77,0

max 15 19 252 904 176 393

N <LOD 24 19 12 11 18 18

Half Hard cheese 19 A mean 1 7 12 28 22 54

P50 0 0 0 2 0 14

P90 4 17 51 28 71 209

max 12 73 98 406 207 227

N <LOD 16 13 11 5 11 9

B mean 4 28 13 29 35 135

P50 0 0 2 3 0 17

P90 6 93 59 35 71 326

max 69 219 98 406 444 1029

N <LOD 16 12 7 5 11 6

103

Hard cheese 23 A mean 8 7 22 58 77 133

P50 0 0 0 4 11 19

P90 8 21 29 250 125 437

max 110 44 269 281 1025 561

N <LOD 18 13 17 5 5 4

B mean 8 7 21 58 81 135

P50 0 0 0 5 15 16

P90 8 21 29 250 130 441

max 110 33 255 281 1025 561

N <LOD 18 14 16 6 6 5

Blue cheese 16 A mean 0 3 24 6 2 256

P50 0 0 2 1 0 85

P90 0 10 52 21 6 819

max 3 30 258 25 14 1111

N <LOD 15 12 2 6 13 5

B mean 0 3 18 7 2 249

P50 0 0 4 1 0 34

P90 0 8 55 22 6 774

max 0 37 139 48 13 1306

N <LOD 16 13 1 7 13 6

Melted cheese 2 A mean 0 2 0 26 5 18

P50 0 2 0 26 5 18

P90 0 3 0 45 7 28

max 0 4 0 50 7 30

N <LOD 3 3 3 3 3 3

Table 60: Overview of BA-distribution in meat products and preparations and it's subgroups. Mean, median, P50, P90 and max are given in mg/kg. Timepoint A = day of purchace = day 0; Timepoint B = after expiry date.

Category N Timepoint

Tryptamine B-Phenylethylamine Putrescine Cadaverine Histamine Tyramine

Meat 109 A mean 3 1 12 6 1 26

P50 0 0 0 0 0 0

P90 9 4 17 9 2 103

max 59 24 307 158 54 238

104

N <LOD 89 90 55 57 88 56

B mean 7 2 13 12 2 45

P50 0 0 1 1 0 15

P90 25 7 28 22 4 134

max 112 24 183 269 54 365

N <LOD 76 79 48 36 82 34

Salami 8 A mean 4 4 34 3 2 65

P50 0 1 4 2 0 63

P90 9 11 87 4 6 130

max 31 12 141 57 13 153

N <LOD 3 3 4 1 5 2

B mean 4 3 28 9 2 48

P50 0 2 6 3 0 28

P90 11 10 85 22 6 125

max 31 10 136 57 13 134

N <LOD 2 2 2 2 2 2

Dried sausage 17 A mean 9 4 45 21 5 79

P50 2 1 3 2 0 71

P90 32 10 145 64 11 180

max 33 24 307 158 54 226

N <LOD 8 8 7 5 12 3

B mean 7 6 30 18 5 75

P50 0 4 9 2 0 64

P90 27 13 105 50 12 171

max 33 24 156 158 54 205

N <LOD 9 7 4 4 11 2

Cooked ham 16 A mean 1 0 3 1 0 10

P50 0 0 0 0 0 0

P90 2 0 0 2 0 28

105

max 6 3 47 5 2 86

N <LOD 12 15 15 13 15 9

B mean 1 0 0 5 0 26

P50 0 0 0 0 0 25

P90 3 0 0 9 2 60

max 4 0 3 56 2 70

N <LOD 11 16 14 8 13 3

Raw ham 23 A mean 2 0 3 5 0 13

P50 0 0 1 1 0 0

P90 7 0 6 5 1 54

max 20 2 32 77 2 107

N <LOD 19 22 9 10 20 13

B mean 9 2 17 3 1 41

P50 0 0 1 1 0 0

P90 30 7 38 11 0 134

max 112 12 183 18 22 365

N <LOD 18 17 8 7 21 12

Raw dried beef 5 A mean 14 1 1 15 2 69

P50 0 0 1 0 2 28

P90 39 3 2 39 3 168

max 59 5 3 44 4 238

N <LOD 3 4 0 3 2 0

B mean 34 1 10 36 2 151

P50 9 0 3 0 2 107

P90 86 3 22 107 5 250

max 109 4 23 177 7 265

N <LOD 2 3 1 3 2 0

Meat preparations 40 A mean 0 0 4 2 0 6

P50 0 0 0 0 0 0

106

P90 0 0 2 6 1 12

max 0 4 157 18 3 102

N <LOD 40 38 20 25 34 29

B mean 6 0 6 15 2 29

P50 0 0 1 1 0 5

P90 16 2 5 47 4 96

max 83 3 163 269 29 195

N <LOD 30 33 19 13 30 15

107

Appendix 16: Box-plots of BA-concentrations belonging to Part 1 of the statistical analysis.

Figure 21: BA-concentrations at day 0 for animal versus plant-based food products.

Figure 22: BA-concentrations at the expiry date for animal versus plant-based food products.

108

Figure 23: Evolution in BA-concentrations during storage for animal versus plant-based food products.

Figure 24: BA-concentrations at day 0 for fermented versus non-fermented food products.

109

Figure 25: BA-concentrations at the expiry date for fermented versus non-fermented food products.

Figure 26: Evolution in BA-concentrations during storage for fermented versus non-fermented food products.

110

Figure 27: BA-concentrations at day 0 for fermented versus non-fermented within animal and plant-based products.

Figure 28: BA-concentrations at the expiry date for fermented versus non-fermented within animal and plant-based products. Note: non-fermented plant-based products were eliminated from the database, due to invalid B-values.

111

Figure 29: Evolution in BA-concentrations during storage for fermented versus non-fermented within animal and plant-based products. Note: non-fermented plant-based samples were eliminated from the database, due to invalid B-values.

112

Appendix 17: Tables representing the p-values resulting from the mean comparisons (ANOVA) of

the BA-concentrations in the different food groups.

Table 61: p-values for the independent one-way ANOVA tests comparing the BA-concentrations in the different food groups at day 0 (significance level of 5%). Significant p-values are presented in bold.

Tryptamine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0,041 0 0,006 0,358

Chocolate

1 0 0 0

Beer

1 0,776 0,043

Dairy

1 0,485

Meat

1

β-phenylethylamine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0 0,994 0,001 0,483

Chocolate

1 0 0,179 0

Beer

1 0,004 1

Dairy

1 0,068

Meat

1

Putrescine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0 0,007 0 0

Chocolate

1 0,001 1 0,951

Beer

1 0,003 0

Dairy

1 0,967

Meat

1

Cadaverine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0,969 0,360 0,394 0,863

Chocolate

1 0,775 0,128 0,999

Beer

1 0,004 0,829

Dairy

1 0,035

Meat

1

Histamine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0 0,054 0,943 0

Chocolate

1 0,679 0,017 0,540

Beer

1 0,384 0,044

Dairy

1 0

Meat

1

Tyramine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0,123 1 0,038 0,481

Chocolate

1 0,121 0,914 0,951

Beer

1 0,037 0,454

Dairy

1 0,600

Meat

1

113

Table 62: p-values for the independent one-way ANOVA tests comparing the BA-concentrations between the different food groups at the expiry date (significance level of 5%). Significant p-values are presented in bold.

Tryptamine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0,166 0 0,024 1

Chocolate 1 0 0 0,198

Beer 1 0,601 0

Dairy 1 0,008

Meat 1

β-phenylethylamine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0 1 0,006 0,102

Chocolate 1 0 0,489 0,001

Beer 1 0,002 0,028

Dairy 1 0,479

Meat 1

Putrescine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0,003 0,310 0,016 0,013

Chocolate 1 0,001 0,960 0,960

Beer 1 0,042 0,018

Dairy 1 1

Meat 1

Cadaverine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0,196 0,013 0,983 0,955

Chocolate 1 0,775 0,032 0,325

Beer 1 0,001 0,010

Dairy 1 0,626

Meat 1

Histamine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0,004 0,132 0,995 0,001

Chocolate 1 0,679 0,010 0,994

Beer 1 0,271 0,366

Dairy 1 0,001

Meat 1

Tyramine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0,918 0,735 0,368 0,014

Chocolate 1 0,121 0,726 0,041

Beer 1 0,013 0

Dairy 1 0,765

Meat 1

114

Table 63: p-values for the independent one-way ANOVA tests comparing the evolutions in BA-concentrations between the different food groups (significance level of 5%). Significant p-values are presented in bold.

Tryptamine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0,120 0,120 0,078 0,001

Chocolate

1 0 0,879 0,011

Beer

1 0,879 0,011

Dairy

1 0,053

Meat

1

β-phenylethylamine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0,965 0,965 1 0,799

Chocolate

1 1 0,866 0,064

Beer

1 1 0,064

Dairy

1 0,854

Meat

1

Putrescine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0,065 0,065 0,003 0,039

Chocolate

1 1 0,087 0,363

Beer

1 0,087 0,363

Dairy

1 0,926

Meat

1

Cadaverine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0,858 0,858 0,110 0,007

Chocolate

1 1 0,171 0,012

Beer

1 0,171 0,012

Dairy

1 0,314

Meat

1

Histamine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0,845 0,845 0,999 0,769

Chocolate

1 1 0,646 0,244

Beer

1 0,646 0,244

Dairy

1 0,863

Meat

1

Tyramine

Fruit and Vegetables Chocolate Beer Dairy Meat

Fruit and Vegetables 1 0,698 0,698 0,599 0

Chocolate

1 1 0,827 0

Beer

1 0,827 0

Dairy

1 0,001

Meat

1

115

Appendix 18: Correlation triplots resulting from redundancy analyses (RDA) executed to analyze

the correlations between BA, FAA and microbial concentrations.

Figure 30: Triplot for the RDA with FAA and factors fermented/non-fermented and animal/plant as explanatory variables (blue arrows) and BA-concentrations at the expiry date as response variables (red dots and names). The black circles represent the individual samples.

116

Figure 31: Triplot for the RDA with FAA and factors fermented/non-fermented and animal/plant as explanatory variables (blue arrows) and BA-evolutions as response variables (red dots and names). The black circles represent the individual samples.

117

Figure 32: Triplot for the RDA with microbial data and factors fermented/non-fermented and animal/plant as explanatory variables (blue arrows) and BA-concentrations at the expiry date (F&V) as response variables (red dots and names). The black circles represent the individual samples.

118

Figure 33: Triplot for the RDA with microbial data and factors fermented/non-fermented and animal/plant as explanatory variables (blue arrows) and BA-concentrations at the expiry date (dairy products) as response variables (red dots and names). The black circles represent the individual samples.

119

Figure 34: Triplot for the RDA with microbial data and factors fermented/non-fermented and animal/plant as explanatory variables (blue arrows) and BA-concentrations at the expiry date (meat) as response variables (red dots and names). The black circles represent the individual samples.

120

Figure 35: Triplot for the RDA with microbial data and factors fermented/non-fermented and animal/plant as explanatory variables (blue arrows) and BA-evolutions (F&V) as response variables (red dots and names). The black circles represent the individual samples.

121

Figure 36: Triplot for the RDA with microbial data and factors fermented/non-fermented and animal/plant as explanatory variables (blue arrows) and BA-evolutions (dairy products) as response variables (red dots and names). The black circles represent the individual samples.

122

Figure 37: Triplot for the RDA with microbial data and factors fermented/non-fermented and animal/plant as explanatory variables (blue arrows) and BA-evolutions (meat) as response variables (red dots and names). The black circles represent the individual samples.

123

Appendix 19: Results of the multiple linear regressions (MLR) executed during the analysis of the correlations between FAA, BA and microbial counts.

Table 64: Result of the MLR with BA as responsible variables and FAA and factors F/NF and A/P as explanatory variables. Precursing FAA are expressed in bold, as well as significant p-values. (F/NF = fermented/non-fermented; A/P = animal/plant)

END OF STORAGE

Tryptamine β-phenylethylamine Putrescine

Model p-value Coefficient Model p-value Coefficient Model p-value Coefficient

F/NF 0,012 0.152 F/NF 0,010 -0.135 A/P 0 0.489

Tyrosine 0,024 -0.115 Tyrosine 0,086 -0.076 Histidine 0,009 0.194

Tryptophane 0 -0.242 Tryptophane 0,053 -0.082 Tyrosine 0 -0.429

Phenylalanine 0 0.405 Phenylalanine 0 0.329 Phenylalanine 0 0.384

Lysine 0,004 0 Lysine 0,096 0 Ornithine 0,003 0.132

Lysine 0,001 0

Cadaverine Histamine Tyramine

Model p-value Coefficient Model p-value Coefficient Model p-value Coefficient

F/NF 0,069 0.163 Histidine 0 -0.401 A/P 0,011 -0.247

Arginine 0,002 -0.164 Arginine 0,020 -0.101 Arginine 0,096 -0.098

Tyrosine 0,003 -0.219 Tyrosine 0,003 -0.193 Tyrosine 0 -0.490

Tryptophane 0,072 -0.120 Tryptophane 0,160 -0.077 Tryptophane 0,068 -0.143

Phenylalanine 0 0.604 Phenylalanine 0 0.647 Phenylalanine 0 1.039

Ornithine 0,018 0.115 Ornithine 0,039 0.090 Lysine 0,061 0 Lysine 0,009 0 Lysine 0,058 0

EVOLUTION

Tryptamine β-phenylethylamine Putrescine

Model p-value Coefficient Model p-value Coefficient Model p-value Coefficient

F/NF 0 0.1888 A/P 0,019 -0.100 A/P 0,019 -0.135

A/P 0,010 -0.113 Arginine 0,014 0.050 Arginine 0,086 0.053

Tyrosine 0,012 0.080 Phenylalanine 0,150 0.067 Tyrosine 0,127 0.062

Tryptophane 0,005 -0.083 Lysine 0,063 -0.080 Lysine 0,028 -0.092

Lysine 0,039 -0.063

124

Cadaverine Histamine Tyramine

Model p-value Coefficient Model p-value Coefficient Model p-value Coefficient

F/NF 0 0.206 A/P 0,042 -0.056 F/NF 0 0.330

Histidine 0,002 0.133 Phenylalanine 0,100 0.034 A/P 0,002 -0.211

Arginine 0,046 -0.064 Ornithine 0,014 -0.040 Arginine 0,127 -0.063

Ornithine 0,001 -0.091 Phenylalanine 0,131 0.083

Ornithine 0,005 -0.108

Table 65: Result of the MLR with BA as responsible variables and microbial counts (F&V) and factors F/NF and A/P as explanatory variables. Significant p-values are expressed in bold. (F/NF = fermented/non-fermented; A/P = animal/plant, PCA: total bacterial count; MRS: Lactic acid bacteria; SB: Enterococci; RE: Enterobacteriaceae)

END OF STORAGE

Tryptamine β-phenylethylamine Putrescine

Model p-value Coefficient Model p-value Coefficient Model p-value Coefficient

F/NF 0,004 -0.322 SB 0,026 0.111 F/NF 0,07 0.389

Cadaverine Histamine Tyramine

Model p-value Coefficient Model p-value Coefficient Model p-value Coefficient

F/NF 0,026 0.414 1 / / F/NF 0,013 -0.451

SB 0,002

EVOLUTION

Tryptamine β-phenylethylamine Putrescine

Model p-value Coefficient Model p-value Coefficient Model p-value Coefficient

F/NF 0,159 0.113 1 / / F/NF 0,003 0.323

PCA 0,001 -0.101

MRS 0,011 0.070

SB 0,013 0.123

Model p-value Coefficient Model p-value Coefficient Model p-value Coefficient

PCA 0,004 -0.108 1 / / MRS 0,061 0.026

MRS 0 0.129 PA 0,037 -0.017

125

SB 0 0.336

PA 0,007 0.061

Table 66: Result of the MLR with BA as responsible variables and microbial counts (dairy products) and factors F/NF and A/P as explanatory variables. Significant p-values are expressed in bold. (F/NF = fermented/non-fermented; A/P = animal/plant, PCA: total bacterial count; MRS: Lactic acid bacteria; SB: Enterococci; RE: Enterobacteriaceae)

END OF STORAGE

Tryptamine β-phenylethylamine Putrescine

Model p-value Coefficient Model p-value Coefficient Model p-value Coefficient

1 / / SB 0,001 0.115 SB 0,093 0.071

RE 0 0.209

Cadaverine Histamine Tyramine

Model p-value Coefficient Model p-value Coefficient Model p-value Coefficient

SB 0,031 0.111 MRS 0,024 0.094 MRS 0,047 0.096

RE 0,001 0.171 RE 0,152 0.076 RE 0 0.252

EVOLUTION

Tryptamine β-phenylethylamine Putrescine

Model p-value Coefficient Model p-value Coefficient Model p-value Coefficient

1 / / 1 / / 1 / /

Cadaverine Histamine Tyramine

Model p-value Coefficient Model p-value Coefficient Model p-value Coefficient

SB 0,099 0.031 MRS 0,082 0.016 1 / /

Table 67: Result of the MLR with BA as responsible variables and microbial counts (meat) and factors F/NF and A/P as explanatory variables. Significant p-values are expressed in bold. (F/NF = fermented/non-fermented; A/P = animal/plant, PCA: total bacterial count; MRS: Lactic acid bacteria; SB: Enterococci; RE: Enterobacteriaceae)

Tryptamine

β-phenylethylamine

Putrescine

Model p-value Model p-value Model p-value

PCA 0,003 0.088 F/NF 0 -0.335 F/NF 0 -0.557

MRS 0,014 0.042 MRS 0,095 0.049

126

RE 0,082 -0.062

Cadaverine Histamine Tyramine

Model p-value Model p-value Model p-value

SB 0,038 0.148 MRS 0,029 0.039 MRS 0 0.212

RE 0,102 0.100 MSA 0,123 0.039

Tryptamine β-phenylethylamine Putrescine

Model p-value Model p-value Model p-value

F/NF 0,004 0.363 F/NF 0,132 0.128 PCA 0,059 0.065

MRS 0,007 0.069 MRS 0,015 0.040

SB 0,064 0.074

RE 0,080 -0.060

Cadaverine Histamine Tyramine

Model p-value Model p-value Model p-value

PCA 0,038 0.064 MRS 0,047 0.031 F/NF 0,005 0.566

RE 0,005 0.169 MRS 0 0.168

MSA 0,023 -0.091 MSA 0,134 -0.082