microbiological investigation of raw goat milk from commercial dairy ...

MICROBIOLOGICAL INVESTIGATION OF RAW GOAT MILK FROM
COMMERCIAL DAIRY GOAT FARMS IN BOGOR, INDONESIA
EPI TAUFIK
MASTER OF VETERINARY PUBLIC HEALTH
CHIANG MAI UNIVERSITY AND FREIE UNIVERSITÄT BERLIN
SEPTEMBER 2007

MICROBIOLOGICAL INVESTIGATION OF RAW GOAT MILK FROM
COMMERCIAL DAIRY GOAT FARMS IN BOGOR, INDONESIA
EPI TAUFIK
A THESIS SUBMITTED TO CHIANG MAI UNIVERSITY AND FREIE
UNIVERSITÄT BERLIN IN PARTIAL FULFILLMENT OF THE
REQUIREMENTS FOR THE DEGREE OF
MASTER OF VETERINARY PUBLIC HEALTH
CHIANG MAI UNIVERSITY AND FREIE UNIVERSITÄT BERLIN
SEPTEMBER 2007

iii
ACKNOWLEDGEMENTS
First, I would like to express my sincere gratitude to my thesis advisory
committee. These are Univ. Prof. Dr. Goetz Hildebrandt and Dr. Josef Nikolaus
Kleer at the Institute of Food Hygiene, Faculty of Veterinary Medicine, Freie
Universität Berlin (FUB), Germany, and also Dr. Tri Indrarini Wirjantoro at the
Department of Food Science and Technology, Faculty of Agro-Industry, and
Assist. Prof. Dr. Khwanchai Kreausukon at Veterinary Public Health Center for Asia
Pacific, Faculty of Veterinary Medicine, Chiang Mai University (CMU), Thailand; as
well as my country advisor, Prof. Dr. Fachriyan H. Pasaribu, at the Department of
Animal Diseases and Veterinary Public Health, Faculty of Veterinary Medicine,
Bogor Agricultural University (BAU), Indonesia. Without their precious advice and
continuous encouragement, this thesis would not have been completed. I wish to
express my real gratitude to them again.
I also wish to express my high appreciation and thanks to the administration of
this program, both from FUB and CMU. I would like to thank Univ. Prof. Dr. Karl
Hans Zessin, Dr. Maximilian Baumann and their staff in Germany, Assoc. Prof. Dr.
Lertrak Srikitjakarn, Assist. Prof. Dr. Khwanchai Kreausukon, Dr. Anucha
Sirimalaisuwan, Assist. Prof. Dr. Pawin Padungtod, and their staff in Thailand.
I would like to thank the German Government via DAAD, EU Asian Link Project and
the Thai Government via VPHCAP for providing me a great financial support.
I am greatly indebted to all the teachers and assistants within this Joint Master
Program in Veterinary Public Health from CMU, FUB and Veterinärmedizinische
Universität Wien (VUW), Austria; for their critical comments, knowledge and
experience-sharing as well as their friendship and cooperation. Special thanks goes to
Prof. Dr. Reinhard Fries, Dr. Moses Kyule, Assist. Prof. Dr. Pawin Padungtod and
Dipl.-Stat. Rose Schmitz for their critical insight, statistical advice and
encouragement. I also would like to extend my gratitude to Assist. Prof. Dr. Peter
Paulsen and his staff at Institute of Meat Hygiene, Meat Technology and Food

iv
Science VUW, Austria, for their guidance in introducing me to the advance laboratory
techniques on food microbiology.
My sincere gratitude also goes to Mrs. Nancy Huber for her great assistance in
editing the english language of my thesis. I am also grateful to all my friends in the
second batch of the MPVH program, we spent a long time together during this study
period. I hope our friendship will last forever.
To the librarian of Faculty of Veterinary Medicine Library, either from CMU
Thailand or FUB, Germany, your cooperation and kindly assistance were highly
appreciated.
It was a great experience for me to have a wonderful stay in Berlin. Therefore
I would like to thank Dr. Norbert Miethe, Mrs. Louise Le Bel, Ms. Juliane Fischer,
my Indonesian friends in Berlin, especially Jamaah Masjid Al Falah Berlin, Pak
Bram and family, Pak Han and family, Pak Ali, Fahmi, Lingga, Nanda, Hasan, Husein
and Firdaus as well as Pak Muis family in Hamburg, for their kind assistance,
experience-sharing and friendship.
I equally enjoyed my staying period in Chiang Mai. To Ms. Jariya Yos-I,
Ms. Supheerutai Buakaew, Ms. Saowaluck Prommin, Ms. Manatchaya U-tairat,
Ms. Nattakarn Awaiwanont, Phi Noy, Phi On, Phi Dang, Phi Tiauw, Phi S, Nuke,
Eddy, Lucas, Poo, Ronny and Ibu Susi, I thank you for all your whole-hearted support
and kindness during my stay in Chiang Mai, Thailand.
To the Rector, Vice Rector for academic affairs and International Program
Office staff as well as the Dean of Faculty, the Head of Department, the Head of
Laboratory, my seniors and colleagues from the Faculty of Animal Science and the
Faculty of Veterinary Medicine, BAU, Indonesia; your continuous support is highly
appreciated. I would also like to thank the farm owners for the cooperation in
allowing their animals to be accessed for sample collection. Thanks to farm workers
for assisting me in sample collection and also to Pak Agus, Pak Raffi, Selyn and
Abenk for laboratory work.

v
This thesis is dedicated to my beloved family; my late father, mom, my
parents-in-law, my elder brother and his wife and their beloved children and also to
my younger brother. Thank you very much for supporting me spiritually, emotionally
and otherwise. Special dedications to my beloved wife, Nurhayati and our daughter
Aisyah Nur Taufik, as well as our next baby, without them I think I would never have
achieved this step. Thank you for the constant support, words of encouragement you
provided and an endless love as well as the patience you showed when I left all of you
towards completion of this endeavor. May The Almighty release a wonderful blessing
to all of us, I love you all.
Lastly, utmost thanks is due to my God, Allah SWT, The Creator of mankind
and universe. Without His willing, blessing and guidance, it would be impossible for
me to face and go through this challenging step in my life.
Epi Taufik

vi
Thesis Title
Author
Degree
Microbiological Investigation of Raw Goat Milk from
Commercial Dairy Goat Farms in Bogor, Indonesia
Mr. Epi Taufik
Master of Veterinary Public Health
Thesis Advisory Committee Prof. Dr. Goetz Hildebrandt Chairperson (FU-Berlin)
Dr. Tri Indrarini Wirjantoro Chairperson (CMU)
Asst. Prof. Khwanchai Kreausukon Member (CMU)
ABSTRACT
Investigation on microbiological quality such as Total Plate Count (TPC),
coliforms and the presence of pathogenic bacteria of goat milk, together with some
risk factors affecting these microorganisms in Indonesia, was very rare. In view of
food hygiene and consumer health as well as animal health protection, however,
evaluation of the microbiological status and presence of pathogenic bacteria in goat
milk, which can cause adverse health effects on the animals as well as pose a high risk
of causing foodborne disease in humans, is of central importance. Therefore this study
was aimed at investigating the microbiological quality of raw goat milk by using
indicator bacteria, and also to evaluate the potential risk factors associated with them.
Information regarding potential risk factors was collected by questionnaire.
The conventional bacteriological method for bacteria isolation and the indirect test
(California Mastitis Test (CMT)) for determining udder inflammation status were
employed. A sample size of 300 udder halves and 30 bulk milk samples from three
commercial dairy goat farms in the Bogor District, West Java Province, Indonesia
were investigated for counts and prevalence of indicator bacteria, which were TPC,
coliforms, Staphylococcus spp., Coagulase Positive Staphylococci (CPS) and
Coagulase Negative Staphylococci (CNS). Ten potential risk factors were also
evaluated in relation to counts and prevalence of indicator bacteria.

vii
The median values of indicator bacterial counts from overall udder-half milk
samples were 3.74, 0.70, 3.00, 1.70 and 2.52 log cfu/ml and from bulk milk samples
were 5.69, 2.98, 3.86, 3.66 and 3.32 log cfu/ml for TPC, coliforms, Staphylococcus
spp., CPS and CNS, respectively.
The indicator bacterial counts from udder-half milk samples were significantly
different (P

viii
ชื่อเรื่องวิทยานิพนธ การสํารวจทางจุลชีววิทยาของน้ํานมแพะดิบจากฟารม
แพะนมในบอกอร อินโดนีเซีย
ผูเขียน นาย เอ ป ทาล ฟค
ปริญญา
สัตวแพทยสาธารณสุขศาสตรมหาบัณฑิต
คณะกรรมการที่ปรึกษาวิทยานิพนธ ศ.ดร.โกส ฮิลเดอร บรานซ ประธานกรรมการ (FU- Berlin)
ดร. ไตรอินดรารินี่ วีจานโตโร ประธานกรรมการ (CMU)
ผศ. ขวัญชาย เครือสุคนธ กรรมการ (CMU)
บทคัดยอ
การสํารวจคุณภาพทางจุลชีววิทยาอยางเชน Total Plate Count (TPC), coliforms
และการพบแบคทีเรียกอโรคของน้ํานมแพะและปจจัยที่เกี่ยวของในอินโดนีเซียมีนอยมาก
ในดานสุขศาสตรอาหารและสุขภาพผูบริโภคนั้น การประเมินสถานะทางจุลชีววิทยาและการพบ
แบคทีเรียกอโรคของน้ํานมแพะที่กอใหเกิดผลตอสุขภาพสัตวและยังกอใหเกิดความเสี่ยงตอการเกิด
โรคในคนจากอาหารเปนเรื่องที่มีความสําคัญอยางมาก ดังนั้นการศึกษาในครั้งนี้มีจุดมุงหมายที่
การสํารวจคุณภาพทางจุลชีววิทยาของนมแพะดิบโดยใชเชื้อแบคทีเรียเปนตัวชี้วัด
และประเมินปจจัยเสี่ยงที่มีผลตอคุณภาพทางจุลชีววิทยา
ขอมูลเกี่ยวกับปจจัยที่มีศักยภาพถูกรวบรวม โดยแบบสอบถามการแยกชนิดของแบคทีเรีย
โดยการตรวจทางหองปฏิบัติการแบคทีเรียและการตรวจการเกิดการอับเสบของเตานมทางออมโดย
น้ํายา ซี.เอ็ม.ที. ตัวอยางน้ํานมแพะที่เก็บจากเตานมจํานวน 300 ตัวอยาง และถังนมรวมจํานวน 30
ตัวอยางจากฟารมแพะนมเอกชน 3 แหง ในเขตบอกอรจังหวัดชวาตะวันตกของอินโดนีเซียถูกนํามา
ตรวจนับจํานวนและหาความชุกของชนิดแบคทีเรียที่ประกอบดวย TPC, coliforms,
Staphylococcus spp., Coagulase Positive Staphylococci (CPS) และ Coagulase
Negative Staphylococci (CNS) ทําการวิเคราะหปจจัยเสี่ยงที่มีศักยภาพ 10
ปจจัยตอจํานวนและความชุกของแบคทีเรีย

ix
มัธยฐานของจํานวนแบคทีเรีย TPC, coliforms, Staphylococcus spp., CPS, และ
CNS ในตัวอยางน้ํานมแพะที่เก็บจากเตานมเทากับ 3.74, 0.70, 3.00, 1.70, และ 2.52 log
cfu/ml ตามลํา ดับและในตัวอยางถังนมรวมเทากับ 5.69, 2.98, 3.86, 3.66, และ 3.33 log
cfu/ml ตามลําดับ
จํานวนเชื้อแบคทีเรียจากตัวอยางน้ํานมแพะที่เก็บจากเตานมมีความแตกตางอยางมีนัยสําคัญ
ทางสถิติ (P

x
TABLE OF CONTENTS
Page
ACKNOWLEGDEMENTS
ABSTRACT IN ENGLISH
ABSTRACT IN THAI
LIST OF TABLES
LIST OF FIGURES
ABBREVIATIONS AND SYMBOLS
iii
vi
viii
xiii
xv
xvi
1. INTRODUCTION AND OBJECTIVES 1
1.1 Introduction 1
1.2 Objectives 3
1.3 Significance and impact of the study 4
2. LITERATURE REVIEW 5
2.1 The goat and its role as a milk producer in the developing
countries
5
2.2 Microbiological characteristics of goat milk 8
2.3 The pathogenic bacteria in dairy goat 11
2.3.1 Prevalence of some pathogenic bacteria 11
2.3.2 Udder infection in dairy goat 13
2.3.3 Relationship between intramammary infections with some
risk factors in dairy goat
15
2.4 Characteristics of Staphylococcus spp 16
2.4.1 Habitat and distribution 17
2.4.2 Growth and requirements 18

xi
Page
2.5 Dairy food safety issues and public health implications 18
3. MATERIALS AND METHODS 21
3.1 Study design 21
3.1.1 Study location 21
3.1.2 Questionnaire 21
3.1.3 Type of sample 21
3.1.4 Bacterial indicators and laboratory investigation standard 22
procedures
3.2 Sample size determination 22
3.3 Sampling strategy 22
3.4 Laboratory procedures 23
3.4.1 Total Plate Count (TPC) isolation and enumeration 23
3.4.2 Total coliforms isolation and enumeration 24
3.4.3 Isolation and identification of coagulase negative and positive
staphylococci (Staphylococcus spp.)
26
3.4.4 California Mastitis Test (CMT) 29
3.5 Information regarding potential risk factors from questionnaire 29
survey
3.6 Data management and statistical analysis 30
4. RESULTS 31
4.1 Results of bacterial isolation and enumeration 31
4.1.1 Results from individual udder-half milk samples 31
4.1.2 Results from bulk milk samples 52
4.2 The comparison of indicator bacterial counts and prevalence 56

xii
Page
between left and right udder milk samples
4.3 The comparison between California mastitis test results and
conventional bacteriological isolation
57
5. DISCUSSION AND CONCLUSIONS 60
5.1 Discussion 60
5.1.1 Quantitative data 60
5.1.1.1 Indicator bacterial counts of udder-half milk
samples among levels of some factors
63
5.1.2 Qualitative data 64
5.1.2.1 The assessment of associations between sample
prevalence of indicator bacteria with potential risk factors
66
5.1.3 California Mastitis Test results 69
5.2 Conclusions 72
REFERENCES 75
APPENDIXES 82
Appendix A 82
Appendix B 91
Appendix C 92
Declaration 95
SIGNED DECLARATION SHEET 95
CURRICULUM VITAE 96

xiii
LIST OF TABLES
Table
1. The twenty highest producing countries of goat milk in the world
according to the rank in 2005
2. List of potential risk factors related to goats, udder and teat
condition
3.
Selected statistical value of indicator bacterial counts from udderhalf
milk samples (n= 100/farm)
4. Indicator bacterial count from udder-half milk samples among
breeds of goat in each farm (n = 100/farm)
5. Total Plate Count from udder-half milk samples among levels of
each factor (n = 300)
6. Coliforms counts from udder-half milk samples among levels of
each factor (n = 300)
7. Staphylococcus spp. count from udder-half milk samples among
levels of each factor (n = 300)
8. Coagulase positive staphylococci (CPS) count from udder- half
milk samples among levels of each factor (n = 300)
9. Coagulase negative staphylococci (CNS) count from udder- half
milk samples among levels of each factor (n = 300)
10. Proportion of positive samples for indicator bacteria from udder –
half milk samples
11. Proportion of positive samples for indicator bacteria from udderhalf
milk samples among breeds of goat in each farm
Page
7
29
32
37
38
39
40
41
42
43
44

xiv
Table
12.
Summary results of the assessment of associations between sample
prevalence of coliforms with potential risk factors (univariate analysis)
Page
45
13. Logistic regression of the risk factor associated with sample
prevalence of coliforms
14. Summary results of the assessment of associations between sample
prevalence of Staphylococcus spp. with potential risk factors
(univariate analysis)
15. Logistic regression of the risk factor associated with sample
prevalence of Staphylococcus spp. (multivariate analysis)
16. Summary results of the assessment of associations between sample
prevalence of CPS with potential risk factors (univariate analysis)
17. Logistic regression of the risk factor associated with sample
prevalence of CPS (multivariate analysis)
18. Summary results of the assessment of associations between
prevalence of CNS with potential risk factors (univariate analysis)
46
47
48
49
50
51
19. Summary of general characteristics of sampling farms 52
20. Selected statistical value of indicator bacterial counts from bulk
milk samples (n=10/farm)
21. Proportion of positive samples of indicator bacteria from bulk milk
samples (n=10/farm)
22. Selected statistical value of indicator bacterial counts from left and
right udder milk samples (n=150/udder half)
23. Proportion of positive samples of indicator bacteria from left and
right udder milk samples
24. The comparison between CMT and conventional bacteriological
isolation results of indicator bacteria from udder-half milk samples
54
55
56
57
58

xv
LIST OF FIGURES
Figure
1. Inoculation, incubation and interpretation steps by using 3M
Petrifilm for coliforms count plate (Petrifilm, 2001)
2. Flow chart for isolation and identification of coagulase positive and
negative staphylococci (ISO 6888-1, 1999)
Page
24
26
3. Scoring of coagulase test reactions 28
4. Box and Whisker plots of TPC in three farms compared to the
maximum limit of available standards ( = SNI, =
EC Directive and “Milchverordnung”). (ο) = outlier values from
data distribution which can be represented either as the maximum or
minimum value
5. Box and Whisker plots of coliforms counts in three farms compared
to the maximum limit of available standards ( = SNI,
33
33
= EC Directive and “Milchverordnung”). (*) values of data
distribution, (ο) = outlier value from data distribution which is
represented as the maximum value
6. Box and Whisker plots of CPS counts in three farms compared to the
maximum limit of S. aureus in available standards ( = SNI,
= EC Dir. & “Milchverordnung”). (ο) = outlier values from
data distribution which can be represented as the maximum value
7. Bar charts of median values of indicator bacterial counts from overall
udder-half milk samples (n=300)
8. Bar charts of median values of indicator bacterial counts from overall
bulk milk samples (n=30)
34
35
55

xvi
ABBREVIATIONS AND SYMBOLS
- Negative
+ Positive
a w
BGBl
BSN
cfu
CI
CMT
CNS
CPS
DGLS
DOM
EC
EFSA
et al.
FAO
IMI
IQR
ISO
Log Logarithm to base 10
ml
Milliliter
MSCC
Milk somatic cell count
o C
OR
P
Water activity
Bundesgesetzblatt (Federal Law Gazette)
Badan Standarisasi Nasional (National Standardization
Body)
Colony forming unit
Confidence interval
California Mastitis Test
Coagulase Negative Staphylococci
Coagulase Positive Staphylococci
Directorate General of Livestock Services
Digestible organic matter
European Council
European Food Safety Authority
et alii
Food and Agricultural Organization
Intramammary infection
Inter quartile range
International Organization for Standardization
Celcius degree
Odd ratio
Probability
S. Staphylococcus
SCC
Somatic cell count

xvii
SEC
SEE
SNI
TPC
US FDA-BAM
Staphylococcal enterotoxin C
Staphylococcal enterotoxin E
Standar Nasional Indonesia (Indonesian National Standard)
Total plate count
United States Food and Drug Administration-Bacteriological
Analytical Manual

1. INTRODUCTION AND OBJECTIVES
1.1 Introduction
Sheep and goats form the most important group of milk producing animals
after dairy cattle in both temperate and tropical agriculture (Devendra and Coop,
1982). The dairy goat industry is rapidly gaining in importance throughout the world
(Boscos et al., 1996).
More than any other mammalian farm animal, the goat is a main supplier of
dairy and meat products for rural people, especially in developing countries. As a
dairy supplier, the goat can accomplish one of the three aspects of the demand for
goat milk: home consumption. This demand is increasing because of the growing
populations of people, and here the old saying of the “goat being the cow of the poor
people” is quite fitting. The second aspect of the demand for goat milk is the special
interest in goat milk products, especially cheeses and yoghurt, in many developed
countries. This demand is growing because of the increasing levels of disposable
incomes. The third aspect of the demand for goat milk derives from the affliction of
people with cow milk allergies and other gastro-intestinal ailments. This demand also
is growing because of a wider awareness of problems with traditional medical
treatments to such afflictions, especially in developed countries. These two latter
aspects of the demand for goat milk are quite different from the “goat being the cow
of the poor people”; here, goat milk is wanted or even needed by people of all income
levels (Haenlein, 2004).
Milk is a nutritious food for human beings, but it also serves as a good
medium for the growth of many microorganisms, especially bacterial pathogens.
Lactococcus, Lactobacillus, Streptococcus, Staphylococcus and Micrococcus spp. are
among the common bacterial flora of fresh milk (Chye et al., 2004). The importance
of various etiological agents in milkborne disease has changed dramatically over time.
However, more than 90% of all reported cases of dairy-related illness continue to be

2
of bacterial origin, with at least 21 milkborne or potentially milkborne diseases
currently being recognized (Bean et al., 1996).
Zweifel et al. (2005) stated that goats and sheep rank third and fourth in
terms of global milk production from different species. But unlike cow milk, which
has stringent hygiene and quality regulations, microbiological standards for the
production and distribution of goat milk and sheep milk are more relaxed (Klinger
and Rosenthal, 1997).
According to FAO (2006), Indonesia was ranked as the 14 th in producing goat
milk globally and ranked as the 1 st in the Southeast Asia region in 2005. It was
estimated to produce around 220,000 metric tons (MT) of goat milk. In 2005, the goat
population in Indonesia was 13,182,000 head in total, out of that West Java province
was ranked the 3 rd in the country with 1,235,973 head of goat (DGLS, 2005). On the
one hand, unlike cow’s milk, hygiene and quality regulations for production and
distribution of small ruminant’s milk, such as goat milk are more relaxed in Indonesia
and are not subject to specific microbiological standards in a legal sense. So far this
product has less attention in terms of quality and safety control from farmer
organizations and/or government institutions than those for cow’s milk and milk
products. On the other hand, most of the consumers prefer to drink raw goat milk due
to their belief in the benefit of raw goat milk as a health promoting agent, or even
disease-relief agent.
Investigation on the microbiological quality such as Total Plate Count (TPC),
coliforms and the presence of pathogenic bacteria of goat milk together with some
risk factors affecting these microorganisms in Indonesia was very rare. In view of
food hygiene and consumer health as well as animal health protection, however,
evaluation of the microbiological status and presence of pathogenic bacteria in goat
milk, which can cause adverse health effects on the animals as well as pose a high risk
of causing foodborne disease in humans, is of central importance.
The presence of microorganisms in milk and milk products has important
ramifications for safety, quality, regulations and public health. TPC is the first and

3
principal tool used by technicians and farmers to evaluate the efficiency of production
processes, cleaning and sanitation practices and to predict the keeping quality and
shelf life of milk (Gonzalo et al., 2006). Jayarao and Wang (1999) stated that milk
from the farm can become contaminated with Gram negative bacteria present on teats,
the teat ends, teat canal, udder surfaces, mastitic udders and contaminated water used
to clean the milking systems and those that are resident in the milking system. Gram
negative organisms associated with milk quality can be placed into two groups,
coliforms and non coliforms. Both groups are responsible in lowering milk quality
and have significant concern on public health importance (Jayarao and Wang, 1999).
Staphylococcus spp. are the main aetiological agents of small ruminant’s
intramammary infections (IMI), the more frequent isolates being Staphylococcus
aureus (coagulase-positive staphylococci [CPS]) in clinical cases and coagulasenegative
staphylococci (CNS) in subclinical IMI (Bergonier et al., 2003).
Staphylococcus spp. can be found widely distributed in animals, and it is a contagious
pathogen that can be transmitted from doe to doe during unhygienic milking
procedures. High prevalence of CPS such as S. aureus, or CNS can be of veterinary
public health concern. Both groups of bacteria are important zoonotic bacterial
pathogens, which can also be transmitted to humans through goats’ raw milk and
cause food poisoning associated with enterotoxin production (Wakwoya et al., 2006).
1.2 Objectives
The objectives of this study were (i) to investigate the microbiological quality
of raw goat milk by using TPC and coliforms as indicators (ii) to investigate the
presence of Staphylococcus spp. (coagulase positive and negative staphylococci) in
raw goat milk, and (iii) to evaluate the potential risk factors associated with them in
dairy goat farms in the Bogor District, West Java Province, Indonesia.

4
1.3 Significance and impact of the study
It was expected that the result of this study would provide a primary scientific
database for the microbiological quality of raw goat milk in Indonesia, and some
potential risk factors associated with it. Moreover, the baseline information from this
research could be used by the related stakeholders in formulating intervention
programs for assisting the farmers to improve their systems in keeping animals and
the quality and safety of their product, as well as in designing further studies aimed in
setting up preventive measures against the introduction of pathogenic agents into the
animal and its product.

2. LITERATURE REVIEW
2.1 The goat and its role as a milk producer in the developing countries
World production of milk is forecast to rise to 665 million tons by 2010,
representing an average annual increase of 1.5 percent, compared to an annual
average growth rate of 1.0 percent during the 1990s. Milk production is projected to
grow in each of the major country groupings (developed, transitional and developing);
however, the largest increment is expected in the developing countries. In these
countries, the output of milk is projected to rise by 71 million tons to reach 293
million tons. As a consequence, the share of developing countries in world milk
production is expected to rise to 44 percent (against 39 percent in the base period and
32 percent at the start of the 1990s). Conversely, while production in the developed
countries and that in transition economies is projected to rise, the relative share of
world milk production is expected to decrease in both groups (FAO, 2002).
FAO (2002) also stated that the strongest growth in demand for milk and milk
products is anticipated to come from the developing countries, where it is projected to
grow at the rate of 2.5 percent per year, broadly comparable with the growth rate
during the 1990s. For the countries in transition, little growth (0.9 percent per year)
over the 1999 benchmark is projected; however, this would be a substantial
improvement over the 1990s, when consumption dropped at an average annual rate of
3.3 percent in this group of countries. In the developed countries, consumption of
milk and milk products is also expected to show only limited growth (0.5 percent per
year - a similar level to that experienced during the 1990s). Amongst the developing
countries, as was the case in the 1990s, consumption of milk and milk products is
expected to grow most strongly in Asia, which is projected to account for almost 52
percent of the growth in world demand. Significant growth in demand, 18 million
tons, or 18 percent of the projected rise in the world total, is also expected in the Latin
America and Caribbean region. Within this region, Brazil and Mexico are anticipated
to see the largest increases in consumption. Africa is expected to register the smallest

6
increase in demand amongst the developing country regions, as was the case in the
1990s, and in many countries in this region this will represent a growth rate slower
than that for the population.
Knights and Garcia (1997) reported that in the ‘developing’ tropics where
there are about 95% of the total world’s goat populations, this increase demand of
milk and milk products could be best made up from goat milk. The goat is well
adapted to the tropics; has short generation intervals, high fertility, prolificacy and
fecundity; has high heritability for milk production (0.5); has superior digestive
efficiency over dairy cattle when fed low quality forages (kg milk yield/100 kg DOM
of 67.1 to 145; 86 to 101.5; 73.6 and 71.1 to 91.1 for goats, dairy cattle, dairy buffalo
and sheep, respectively) and is a more efficient milk producer under tropical
conditions (kg milk yield/kg live weight of 2.8 to 7.1, 2.4 to 3.4, and 4.0 for goats,
dairy cattle and dairy buffalo, respectively). Goat milk, owing to its composition, has
a potentially greater role to play in future human nutrition and medicine than milk
from cattle. Goat farmers would more readily set up or expand goat enterprises
because of the lower capital investments required concurrent with lower risks.
This was also supported by the data from FAO (2006) for the 20 highest
producing countries of goat milk in the world in 2005 (Table 1), which mostly comes
from developing countries and particularly from the tropical area.
According to Galal (2005), developing countries harbour 96% of the world
goat population, but only 60% of the breeds. Europe has the heaviest goat breeds
with the largest litter size and milk production, while Latin America and the
Caribbean scored lowest in all these performance traits. Breed variability was lowest
in Europe and highest in Africa. Many goat breeds are not characterized because most
goats and breeds are in developing countries, and/or under extensive production
systems where characterization becomes more demanding.

7
Table 1: The twenty highest producing countries of goat milk in the world according
to the rank in 2005
Rank
Country
Production
(Metric Tones)
Remark
1. India 2,700,000 *
2. Bangladesh 1,416,000 F
3. Sudan 1,295,000 F
4. Pakistan 660,000
5. France 587,000
6. Greece 495,000 F
7. Spain 465,000 F
8. Iran, Islamic Rep. 365,000 F
9. Ukraine 290,000 *
10. Russian Federation 259,000 *
11. China 256,000 F
12. Turkey 240,000 F
13. Mali 238,590 F
14. Indonesia 220,000 F
15. Algeria 160,000 F
16. Mexico 154,478 F
17. Brazil 135,000 F
18. Italy 115,000 F
19. Mauritania 109,800 F
20. Bulgaria 109,320
Source: (FAO, 2006)
Remark:
* = Unofficial figure
No symbol = Official figure
F = FAO estimate
The European Union (EU) has 1.5% (11,730,164 head in the year 2002) of the
world goat population. Four countries (Italy, Greece, Spain and France) in the
Mediterranean area account for 91% of the EU goat population and 95% of its goat
milk production (Moroni et al., 2005b).

8
2.2 Microbiological characteristics of goat milk
According to compositional differences between the milk from cows, goats
and sheep, the quality standards for the milk from small ruminant animals should be
adjusted and evaluated based on the individual milk source (Morgan et al., 2003;
Zweifel et al., 2005). The European Council (EC) (1992), in European Council
Directive 92/46/EEC, stated that the TPC and S. aureus of small ruminant’s raw milk
used for the manufacture of raw-milk products must not exceed 5.7 and 3.3 log
cfu/ml, respectively. Those maximum limit standards were similar to milk regulation
(Milchverordnung) in Germany which was last amended in 2004 for products ‘made
with raw sheep or goat milk’. There was no specific standard for coliforms count
within this category, but there was a separate category of milk called “Vorzugsmilch”
which was certified for consumption as raw milk. This milk, which was referred to
as “certified Grade A milk,” could be sold commercially as a retail product. The
number of coliforms in “Vorzugsmilch” must not exceed 2 log cfu/ml (BGBl Teil I
Nr. 58 S 2794, 2004). In Indonesia, there was not any specific legal standard for
fresh/raw goat milk but there was a standard from Indonesian National Standard for
fresh milk (SNI 01-3141-1998) designed, based on cow milk. According to the
standard, TPC of fresh milk must not exceed 6.0 log cfu/ml, 1.3 log cfu/ml for
coliforms and 2 log cfu/ml for S. aureus (BSN, 1998).
Difficulties in managing the sanitary quality of sheep and goat milk derive
from a series of factors including the low level of production per head, the milking
system, the difficulty involved in machine milking, the conditions under which the
herds or flocks are raised, adverse climatic conditions and the spread of production
over a wide geographic area (Klinger and Rosenthal, 1997).
The prerequisite to produce hygienic milk and cheese is udder health;
therefore, intramammary infections (IMI) are of great importance to milk hygiene in
dairy goats (Moroni et al., 2005b). Mastitis is one of the most costly diseases in the
dairy industry, and, although much information is available concerning mastitis in
cows, few studies deal with mastitis in goats. Researchers studying subclinical
mastitis in goats agree that IMI caused by coagulase-negative staphylococci (CNS)

9
are the most prevalent. Despite the high prevalence of IMI caused by CNS, CNS were
considered to be minor pathogens. However, IMI caused by CNS was associated with
clinical mastitis, changes in milk composition and reduced milk yield; IMI caused by
CNS was also capable of persisting throughout lactation and the dry period (Contreras
et al., 1997).
Reports regarding factors affecting small ruminant’s milk quality mainly deal
with milk composition as a chemical composition of lipids, phosphatase level,
freezing point, natural bacterial inhibitor levels and especially the parameter Somatic
Cell Count (SCC) (Haenlein, 2002; Sevi et al., 2004). The relationship of SCC to the
microbiological quality of small ruminant’s milk and its expressiveness remains
controversial (Zeng and Escobar, 1995). SCC seems to be always influenced by
various factors such as stage of lactation, oestrus, parity, time of sampling (before,
during or after milking), stress and lambing season (Haenlein, 2002; Sevi et al.,
2004). Several authors did not reveal positive interactions of SCC with the presence
of bacterial infection or target of microbial tested (Foschino et al., 2002; Delgado-
Pertinez et al. 2003, Kyozaire et al., 2005).
Moreover the panel on biological hazards of European Food Safety
Authority (EFSA) (2005) has made an opinion on the usefulness of somatic cell
counts for the safety of milk and milk-derived products from goats. The panel
concluded that due to the high variability of SCC in goat milk, even in healthy
animals, SCC cannot be relied on either as a specific indicator for TSE (Transmissible
Spongiform Encephalopathy) risk, nor as an indicator of udder health. Three main
types of difficulties were noted in the EFSA review:
• The count accuracy is affected by the apocrine nature of milk secretion in
goats. Cytoplasmic particles, which derive from the apical part of secretory
cells, are normal constituents in goat milk. Certain methods used to count
somatic cells cannot distinguish these cytoplasmic particles, similar in size
to somatic cells, from real somatic cells, which may lead to false readings.
Moreover, the reference microscopy method, which is based on staining

10
procedures, does not give satisfactory results in the majority of laboratories,
when used on goat milk.
• Somatic cells that are identified in milk from healthy cows or ewes are
mainly macrophages. Less than 30% are other leukocytes. Higher levels of
the latter are considered to be indicative of inflammation. On the other hand,
leukocytes can reach up to 60% of total cells in normal goat milk. The
somatic cell count is therefore difficult to interpret in terms of udder
inflammation.
• Non-infectious factors greatly influence the somatic cell count in goats.
Physiological normality is dependent on the stage of lactation, age, time of
sampling, the oestrus period, feed, stress, breed and the region. Most experts
in this field therefore consider that a specific somatic cell count-value
derived from one population of goats may describe a normal animal health
status in a second population, and indicate mastitis in a third population.
Most of the reports concerning the microbiological characteristics of goat milk
were dealt only with investigation on the prevalence of target pathogenic organisms,
SCC and microbial quality of the milk (Deinhofer and Pernthaner, 1995; Contreras et
al., 1999; Abou-Eleinin et al., 2000; Ndegwa et al., 2001; McDougall et al., 2002;
Foschino et al., 2002; Contreras et al., 2003; Wakwoya et al., 2006; Leitner et al.,
2007; Hall and Rycroft, 2007).
Whereas reports on the evaluation of different factors concerning farm
management and milking practices as well as other predisposing factors from goat
condition in association with microbial quality and the prevalence of pathogenic
bacteria in goat milk were very limited (Zeng and Escobar, 1995; Zeng and Escobar,
1996; Peris et al., 1999; Sanchez et al., 1999; Ameh and Tari, 2000; Zweifel et al.,
2005; Kyozaire et al., 2005).
Zweifel et al. (2005) reported that from 344 samples of bulk-tank goat milk,
the median for Standard Plate Count (SPC) or Total Bacterial Count (TBC) was 4.69

11
log colony forming units (cfu)/ml. They concluded that farms with a flock size >25
animals, sampled in June, using mechanized milking systems (especially bucket
milking without parlor) as well as farms with milk delivery every second or third day,
showed significantly higher SPC levels, whereas the highest probability of a low SPC
result was observed during July, in farms with a flock size

12
Foschino et al. (2002) reported that E. coli O157:H7 was found in 1.7% of
goat milk samples collected from ten farms in the Bergamo area, Italy. S. aureus was
found in 43% of samples, whereas CNS were found in 90% of samples, including
Staphylococcus caprae as the coagulase negative species that was the most frequently
isolated.
McDougall et al. (2001) also reported that hygienically, goat milk production
conditions in Greece and Portugal, under extensive breeding systems had: total
bacteria of 3.6×10 7 and 4×10 7 cfu/ml; coliforms of 1.8×10 6 and 2.5×10 6 cfu/ml;
staphylococci coagulase positive and negative of 1.7 × 10 5 and 7.6 × 10 4 cfu/ml, for
Greece and Portugal respectively. For France, using intensive breeding systems, the
microbiological quality of the goat milk was: total bacteria 1.08×10 5 cfu/ml; coliforms
1.40×10 2 cfu/ml and staphylococci coagulase positive and negative 2.75 × 10 2 cfu/ml.
Moroni et al. (2005b) reported that among 305 goats with IMI, 52.3% had
unilateral infection, whereas the others had both udder halves infected. Among the
bilateral infections, 87% were caused by CNS versus 5% for Staphylococcus aureus
and environmental bacteria and 3% by Streptococci. The prevalence of IMI in the left
and right half udders were similar with 40.4% and 40.0%, respectively.
Kyozaire et al. (2005) reported that from 270 udder halves, milk samples
collected from dairy goat farms with different production systems were infected with
bacteria in 31.1% of the samples. The lowest IMI was found amongst goats in the
herd under the extensive system (13.3%) compared with 43.3% and 36.7% infection
rates under the intensive and semi-intensive production systems, respectively.
Staphylococcus intermedius (coagulase positive), Staphylococcus epidermidis and
Staphylococcus simulans (both coagulase negative) were the most common cause of
IMI with a prevalence of 85.7% of the infected udder halves. The remaining 14.3% of
the infection was due to Staphylococcus aureus.
In another study conducted by Leitner et al. (2007), they found that of the 754
udder halves from 377 goats tested, 28.8% were infected with various Staphylococcus

13
species i.e. S. aureus, 9.6%; S. chromogenes, 3.3%; S. epidermidis, 5.9%; S. simulans,
5.5% and S. caprae, 3.3% or Corynebacteria spp., 1.5%.
Whereas Hall and Rycroft (2007) reported that an IMI was found in 53
(33%) of the goat’s udder halves; the prevalence was 26 per cent on farm A, 39% on
farm C and 42% on farm B. CNS were the most common group of organisms,
affecting 47 per cent of the infected halves. The number of bacteria in the milk ranged
from 1 x 10 3 to 1.2 x 10 5 cfu/ml. S. aureus was found in seven of the samples (13 per
cent), most of which yielded between 1 x 10 4 and 3 x 10 4 cfu/ml; the highest yielded
(maximum value) was 1.8 x 10 5 cfu/ml. Corynebacterium species were present in 16
(31%) of the positive samples and α-haemolytic streptococci were present in three
(6%) of them.
2.3.2 Udder infection in dairy goats
Mastitis in sheep and goats is predominantly subclinical (Contreras et al.,
1999). CNS are the most prevalent pathogens causing subclinical mastitis in dairy
ruminants. Although less pathogenic than S. aureus, CNS can also produce persistent
subclinical mastitis, significant increase in milk somatic cell count (MSCC), cause
clinical mastitis (Deinhofer and Pernthaner, 1995; Ariznabarreta et al., 2002), as well
as produce thermostable enterotoxins (Meyrand et al., 1999). Nevertheless, despite
the accepted role of these bacteria as major IMI-causing pathogens in small
ruminants, the pathogenicity of the different CNS species varies widely (Contreras et
al., 2007). The most commonly isolated CNS species in persistent subclinical IMI in
goats and sheep are Staphylococcus epidermidis, Staphylococcus caprae,
Staphylococcus simulans, Staphylococcus chromogenes and Staphylococcus xylosus
(Contreras et al., 2003; Bergonier et al., 2003).
CNS are the most prevalent organisms detectable on udder skin, inside the
streak canal and in mammary glands of dairy goats and sheep. Various CNS species
are commonly detected in goat milk and these microorganisms can frequently cause
subclinical infections persisting for several months, even through the dry period
(Moroni et al., 2005a). In caprine intramammary infection, the CNS are the most

14
prevalent microorganisms (ranging from 25 to 93% of IMI, depending on the study),
and are isolated mainly from chronic and subclinical infections (Bergonier et al.,
2003).
CNS are contagious pathogens found on the skin of goats and human hands
and can easily be transmitted during unhygienic milking procedures (Kalogridou-
Vassiliadou, 1991). Among the CNS, Staphylococcus caprae is the most prevalent
species, followed by S. epidermidis, S. xylosus, S. chromogenes, and S. simulans
(Contreras et al., 1999). Although many of the coagulase negative species noted adapt
primarily to non-human hosts, their entry into human foods is not precluded. Once in
susceptible foods, their growth may be expected to lead to the production of
enterotoxin which can cause staphylococcal food poisoning or food intoxication (Jay
et al., 2005).
S. epidermidis and S. caprae are among the most prevalent causal
microorganisms in goats and S. epidermidis and S. simulans are in ewes. The presence
of different CNS species could be attributable to certain practices for controlling
mastitis, such as the protocol and type of disinfectant used for teat dipping or dry-off
treatments (Contreras et al., 2003). Because novobiocin-sensitive CNS seem to be the
most pathogenic, we should consider including this antibiotic in the dry-off treatment
procedure (Deinhofer and Pernthaner, 1995), although maximum residue limits for
sheep and goat milk have not yet been defined for this antibiotic (Contreras et al.,
2007).
Microbiological quality of goat’s milk obtained under different production
systems in South Africa was investigated by Kyozaire et al. (2005). They reported
that Staphylococcus intermedius (coagulase positive), S. epidermidis and S. simulans
(both coagulase negatives) were the most common cause of IMI with a prevalence of
85.7% of the infected udder halves, the remaining 14.3% of the infection was due to
S. aureus. Wakwoya et al. (2006) reported that the main bacterial pathogens isolated
from goat milk samples were S. aureus (12.8%), Bacillus spp. (13.8%),
Corynebacterium (10.9%) and CNS (9.6%). Other bacteria that were also detected
included Streptococcus agalactiae, Streptococcus dysagalactiae, Klebsiella

15
pneumoniae, Enterobacter aerogenes, Escherichia coli, Pasteurella (Mannheimia)
haemolytica and Micrococcus spp.
S. aureus is the most important mastitic pathogen in most herds. Symptoms
vary from acute clinical to subclinical mastitis. In particularly severe cases the
infection may progress to gangrene. It is characterized by the presence of a watery,
dark red secretion which may be accompanied by gas bubbles resulting from
secondary infection with gas forming organisms (particularly Clostridium spp). Death
may be immediate or occur after several days. Some animals will recover and
eventually slough away the necrotic tissue (Shearer and Harris, 2003).
2.3.3 Relationship between intramammary infections with some risk factors in dairy
goats
Studies have been conducted to investigate the relationship between IMI and
some risk factors associated with it in dairy goats to find out the effective way in
preventing mastitis at the farm level. Zeng and Escobar (1996) evaluated the effect of
breeds and milking methods on SCC, standard plate count and goat milk composition,
whereas Boscos et al. (1996) studied the prevalence of subclinical mastitis and the
influence of breed, parity, stage of lactation and mammary bacteriological status with
the California Mastitis Test (CMT), Coulter Colony Count (CCC), in dairy goats. The
relationship between CMT and SCC in dairy goats was investigated by Perrin et al.
(1997). Winter and Baumgartner (1999) stated, based on their study results, that
CMT can be used as an additional diagnostic tool concerning goat mastitis.
McDougall et al. (2001) have studied the relationship among SCC, CMT,
impedance and the bacteriological status of milk with lactation stages in goats and
sheep. Shearer and Harris (2003) also stated that the CMT score can be used as a tool
for indicating the mastitis status in dairy goats. The CMT reagent reacts with genetic
material of somatic cells present in milk to form a gel. In general milk samples from
non-infected glands will yield a negative (0), trace, or +1 reaction, score of +2 or +3
are indicative of mastitis.

16
2.4 Characteristics of Staphylococcus spp.
The staphylococci were first described by the Scottish surgeon, Sir Alexander
Ogston as the cause of a number of pyogenic (pus forming) infections in humans. In
1882, he gave them the name Staphylococcus (Greek: staphyle, bunch of grapes;
coccus, a grain or berry), after their appearance under the microscope (Adams and
Moss, 2000).
The genus Staphylococcus includes over 30 species and those of real and
potential interest in foods are about 18 species, out of them only 6 species are
coagulase positive (S. aureus, S. aureus subsp. anaerobius, S. intermedius, S. hyicus,
S. delphini and S. schleiferi subsp. coagulans). These coagulase positive
staphylococci group bacteria generally produce thermostable nuclease (TNase).
Among the coagulase positive species, S. intermedius is well known as an enterotoxin
producer. Ten of the coagulase negative species have been shown to produce
enterotoxins, but they do not produce nuclease, or those that do produce a
thermolabile form. The coagulase negative enterotoxigenic strains are not consistent
in their production of hemolysins or their fermentation of mannitol (Jay et al., 2005).
Valle et al. (1990) reported that 22% of the 272 CNS isolates originated from
healthy goats were enterotoxin positive, and staphylococcal enterotoxin C (SEC) was
the most frequently found enterotoxin among the goat isolates. Seven species of the
goat isolates produced more than one enterotoxin (S. caprae, S. epidermidis, S.
haemolyticus, S. saprophyticus, S. sciuri, S. warneri and S. xylosus) and two species
produced only one, SEC by S. chromogens and staphylococcal enterotoxin E (SEE)
by S. lentus (Valle et al.,1990).
Contreras et al. (2007) stated that rather than be a risk for human health that
could be caused by some mastitis-causing bacteria, milk is generally heat-treated to
minimize this effect. However, in regions where cheese is made from raw milk,
controlling clinical and subclinical mastitis becomes a priority. Even when using
pasteurized milk, the ability of some bacteria, such as Staphylococcus aureus, to
produce thermostable toxins, enhances the zoonotic role of these pathogens. Under

17
European legislation, the control of S. aureus is mandatory, such that the marketing of
sheep, goat and cow milk containing S. aureus is highly restricted (Directive
92/46ECC Council, 1992).
2.4.1 Habitat and distribution
According to Jay et al. (2005), the staphylococcal species are host-adapted
with about one-half of the known species inhabiting humans solely (e.g.,
Staphylococcus cohnii subsp. cohnii) or humans and other animals (e.g., S. aureus).
The largest numbers tend to be found near openings to the body surface such as the
anterior nares, axillae, and the inguinal and perineal areas where in moist habitats,
numbers per square centimeter may reach 10 3 – 10 6 , and in dry habitats, 10 - 10 3 . The
two most important sources to foods are nasal carriers and individuals whose hands
and arms are inflicted with boils and carbuncles, who are permitted to handle food.
Most domesticated animals harbor S. aureus. Staphylococcal mastitis is not
unknown among dairy herds, and if milk from infected cows is consumed or used for
cheese making, the chances of contracting food intoxication are excellent. There is
little doubt that many strains of this organism that cause bovine mastitis are of human
origin. However, some are designated as “animal strains” such as S. lentus and S.
caprae which are associated with goats, especially goat milk (Jay et al., 2005).
Staphylococcus aureus is highly vulnerable to destruction by heat treatment
and to nearly all sanitizing agents. Thus, the presence of this bacterium or its
enterotoxins in processed foods or on food processing equipment is generally an
indication of poor sanitation. The presence of a large number of S. aureus organisms
in a food product may indicate poor handling or sanitation; however, it is not
sufficient evidence to incriminate the food products as the cause of food poisoning.
The isolated S. aureus must be shown to produce enterotoxins. Conversely, small
staphylococcal populations at the time of testing may be remnants of large
populations that produced enterotoxins in sufficient quantity to cause food poisoning.
Therefore, the analyst should consider all possibilities when analyzing a food sample
for S. aureus (FDA, 2001).

18
2.4.2 Growth requirements
Staphylococci are typical of other Gram-positive bacteria in having a
requirement for certain organic compounds in their nutrition. Amino acids are
required as nitrogen sources, and thiamine and nicotinic acid are required among B
vitamins. When grown anaerobically, they appear to require uracil. In one minimal
medium for aerobic growth and enterotoxin production, monosodium glutamate
serves as C, N and energy source. In general, growth occurs over the range 7 –
47.8 o C and enterotoxins are produced between 10 o C and 46 o C, with the optimum
between 40 o C and 45 o C (Jay et al., 2005).
Growth occurs optimally at pH values of 6-7, with minimum and maximum
limits of 4.0 and 9.8 – 10.0, respectively. The pH range over which enterotoxin
production occurs is narrower with little toxin production below pH 6.0 but, as with
growth, precise values will vary with the exact nature of the medium (Adams and
Moss, 2000).
Jay et al. (2005) also stated that with respect to a w , the staphylococci are
unique in being able to grow at values lower than any other non-halophilic bacteria.
Growth has been demonstrated as low as 0.83 under otherwise ideal conditions,
although 0.86 is the generally recognized as a minimum a w .
2.5 Dairy food safety issues and public health implications
Consumers are increasingly concerned about the safety of their food and
uncertain food production practices. Potential threats to human health related to dairy
products and dairy farming include errors in pasteurization, consumption of raw milk
products, contamination of milk products by emerging heat-resistant pathogens,
emergence of antimicrobial resistance in zoonotic pathogens, chemical adulteration of
milk, transmission of zoonotic pathogens to humans through animal contact and
foodborne diseases related to dairy animals (Ruegg, 2003).
Ruegg (2003) also reported that the safety of dairy products can be enhanced
by adoption of a number of management practices. Sources of microbial

19
contamination of milk must be minimized by adoption of hygienic standards that can
be easily evaluated. There is evidence that microbial contamination of milk can be
controlled by the use of standardized best management practices. Mastitis control
programs focusing on the hygienic harvest of milk have been widely adopted for at
least 50 years. Worldwide, farmers have achieved tremendous success in reducing the
incidence of contagious mastitis by adopting the five basic principles of mastitis
control: post-milking teat disinfection, universal dry cow antibiotic therapy,
appropriate treatment of clinical cases, culling of chronically infected cows and
regular milking machine maintenance. Contagious bacteria, such as S. aureus and
Streptococcus agalactiae, are now responsible for less than one-third of all mastitis
cases compared with >75% of all cases 20 years ago (Hillerton et al., 1995).
Although numerous studies have documented that foodborne pathogens of
public health significance have been isolated from bulk tank milk and are capable of
causing disease in humans, people continue to consume raw milk. Many farm families
consume raw milk simply because it is a traditional practice and it is less expensive to
take milk from the bulk tank than buying pasteurized retail milk, some of them
believe that raw milk has a higher nutritional value than pasteurized milk (Oliver et
al., 2005).
Oliver et al. (2005) also stated that in addition to direct consumption of
contaminated raw milk, introduction of raw milk contaminated with foodborne
pathogens into dairy processing plants represents an important risk for the
contamination of milk products that could lead to consumers’ exposure to pathogenic
bacteria. Although milk pasteurization is regarded as an effective method to eliminate
foodborne pathogens, some dairy products do not undergo pasteurization (i.e,
specialty cheeses). Furthermore, pathogens such as Listeria monocytogenes survive
and thrive in post-pasteurization processing environments, thus leading to the
recontamination of dairy products. These two significant exposure pathways pose a
risk to the consumer from direct exposure to foodborne pathogens in unpasteurized
dairy products as well as dairy products which are re-contaminated in the postpasteurization
processing environment. The increasing number of incidences in which

20
foodborne pathogens are detected in fluid milk and ready-to-eat dairy products clearly
indicates that pasteurization is not the ultimate tool to control milkborne pathogens. It
is likely that fecal and foodborne pathogen contamination occurs during the
harvesting of raw milk (i.e., milking, collection and storage), and the farm
environment likely plays a major role in the presence of foodborne pathogens in bulk
tank milk. Reducing the potential for contamination during milk harvesting should
result in the reduction of foodborne pathogens in raw milk.
The dairy industry should be concerned about food safety because: (1) bulk
tank milk contains several foodborne pathogens that cause human disease, (2)
outbreaks of disease in humans have been traced to the consumption of raw
unpasteurized milk and have also been traced back to pasteurized milk, (3) raw
unpasteurized milk is consumed directly by dairy producers and their families, farm
employees and their families, neighbors, etc., (4) raw unpasteurized milk is consumed
directly by a much larger segment of the population via consumption of several types
of cheeses including ethnic cheeses manufactured from unpasteurized raw milk, (5)
entry of foodborne pathogens via contaminated raw milk into dairy food processing
plants can lead to a persistence of these pathogens in biofilms and subsequent
contamination of processed food products, (6) pasteurization may not destroy all
foodborne pathogens in milk and (7) faulty pasteurization will not destroy all
foodborne pathogens (Oliver et al., 2005).
Not only must research be conducted to solve complex food safety problems,
results of that research must be communicated effectively to producers and
consumers. Research and educational efforts identifying potential on-farm risk factors
will better enable dairy producers to reduce/prevent foodborne pathogen
contamination of dairy products leaving the farm. Identification of on-farm reservoirs
could be aided with the implementation of farm-specific pathogen reduction
programs. Foodborne pathogens, mastitis, milk quality and dairy food safety are
indeed all interrelated (Oliver et al., 2005).

3. MATERIALS AND METHODS
3.1 Study design
This study was a cross sectional survey to investigate the microbiological
quality and the association of possible risk factors with the microbiological status of
raw goat milk.
3.1.1 Study location
Three dairy goat farms with herd sizes of 600, 400 and 200, respectively, in
the Bogor District, West Java Province, Indonesia were conveniently selected as
sampling sites.
3.1.2 Questionnaire
Questionnaires were administered for collecting information regarding
possible risk factors, which reflected udder, teat and the goat’s general condition.
Additional information regarding general farm management and milking practices
was also collected (Appendix A). The questionnaires were completed by the
investigator during the farm visits.
3.1.3 Type of sample
The main milk sample that was used in this study was individual udder half
(left and right udder) milk of lactating goats, which was collected at the time of
sampling visits. Two parallel bulk milk samples were taken from each farm at every
visiting time as an additional sample. Ten milliliters of milk was collected for each
sample, either from udder-half or bulk milk.

22
3.1.4 Bacterial indicators and laboratory investigation standard procedures
General rules for the preparation of the initial suspension and decimal
dilutions were based on ISO 6887-1 (1999). US FDA-BAM (United States Food and
Drug Administration – Bacteriological Analytical Manual) online for analysis of
Aerobic Plate Count (FDA, 2001) was followed for conventional culture of total plate
count (TPC), whereas for the total coliforms count, the 3M Petrifilm
interpretation guide for the total coliforms count (Petrifilm, 2001) was followed. To
investigate the presence and enumeration of Coagulase Positive and Negative
Staphylococci (Staphylococcus spp.) in the sample, the ISO 6888-1 (1999) standard
technique by using Baird Parker agar medium was used. The California Mastitis Test
(CMT) was done according to Shearer and Harris (2003).
3.2 Sample size determination
Win Episcope 2.0 software program was used to determine sample size based
on estimate prevalence. As the most prevalent IMI causing agent according to many
scientific reports, the prevalence of CNS in goat milk was used as the expected
prevalence. Since no report was found from Indonesia regarding CNS prevalence in
goat milk, the prevalence of 25% of CNS reported by Bergonier et al. (2003) was
used. At a 95% level of confidence and 5% accepted error, the sample size of 288 was
obtained and then it was rounded up to 300 samples. If the prevalence turns out to be
the expected value, the true prevalence will be between 20.78 and 29.22% (given the
diagnostics were perfect).
3.3 Sampling strategy
Three dairy goat farms in the Bogor District, West Java Province, Indonesia
with herd sizes of 600, 400 and 200 were included in the study. The sampling period
was done in the rainy season, starting from early December 2006 until the end of
March 2007. The sample size was distributed to all farms equally, therefore from
each farm 100 udder-half milk samples (from 50 different individual lactating goats)
were collected. The equal distribution of sample size to each sampling farm was due

23
to the fact that the object of this study was only the lactating goat. The number of
lactating goat varied among farms during sampling time, it was depends on the
stocking and reproduction management and also herd size composition (number of
buck, doe and kid) of each farm. The apparently healthy lactating goats were selected
conveniently in a studied farm during a visiting time. Each lactating goat was marked
after milk sampling to avoid redundancy in the sample collection. Observation of the
general condition of the selected dairy herd, including examination of variation in teat
and udder conformation, udder cleanliness and any abnormalities of the individual
goat was recorded (Appendix A). Approximately 10 ml of pre-milking milk samples
were collected into sterile bottles from each udder half (left and right). Milk samples
were directly kept at ≤4 o C and transported in an icebox to the laboratory for
microbiological analysis within 3 hours. The milking process was done by the
farmer/milker, teat disinfection was carried out prior to the milk sampling using
alcohol and fore-stripping was done before the main sample collection.
3.4 Laboratory procedures
To make 1:10 dilution, the primary dilution (initial suspension) was made by
mixing one ml of milk sample with nine ml of sterile maximum recovery diluent
(MRD) in the test tube, and then continued by further decimal dilution (ISO 6887-
1:1999).
3.4.1 Total Plate Count (TPC) isolation and enumeration
The procedure for TPC isolation and enumeration according to FDA-BAM
(2001) was as follows: 1 ml of each dilution is transferred into separate, duplicate,
appropriately marked petri dishes by using sterile pipettes. Re-shake dilution bottle 25
times in 30 cm arc within 7 seconds if it stands more than 3 minutes before it was
pipetted into petri dish. Add 12-15 ml plate count agar (PCA) (cooled to 45 ± 1°C) to
each plate within 15 min of original dilution. For milk samples, pour an agar control,
pour a dilution water control and pipette water for a pipette control. Add agar to the
latter two for each series of samples. Pour agar and dilution water control plates for
each series of samples. Sample dilutions and agar medium are immediately mixed

24
thoroughly and uniformly by alternate rotation and back-and-forth motion of plates on
flat level surface. After the agar in the petri dishes has solidified, the dishes are
inverted and incubated promptly for 48 ± 2 h at 35°C. The calculation and reporting
are based on standard plate count method recommended by ISO 4833 (2003). Detail
explanation of calculation is presented in Appendix C.
3.4.2. Total coliforms isolation and enumeration
Inoculation, incubation and interpretation steps by using Petrifilm
coliforms count are depicted in Figure 1.
1. Petrifilm plate was placed on a flat
surface. Top film was lifted.
2. With pipette perpendicular to Petrifilm
plate, 1 ml of sample was placed for
coliforms test onto the centre of
bottom film. Each sample was
inoculated in two Petrifilm plates.
3. Top film was carefully rolled down to
avoid trapping air bubbles. Do not let
top film drop.

25
4. With ridge side down, spreader was
placed on top film over inoculum.
5. Sample was distributed with a gentle
pressure on the handle of the
spreader. Do not twist or slide the
spreader. The spreader was then
lifted and left about one minute for
gel to solidify.
6. Petrifilm plates were incubated with
the clear side up in stacks up to 20 or
less. Incubation time and temperature
of 35°C ±1°C for 24 ± 2 h was used
as recommended by ISO 4832 (1991)
standard on general guidance for the
enumeration of coliforms.
7. Petrifilm plates were read and the
colonies were counted with reference
to interpretation guide (Petrifilm,
2001).
Figure 1: Inoculation, incubation and interpretation steps by using 3M Petrifilm
for coliforms count plate (Petrifilm, 2001)

26
3.4.3 Isolation and identification of coagulase positive and negative staphylococci
(Staphylococcus spp.)
Similar to those samples for TPC and coliforms isolation, milk samples for
coagulase positive or negative staphylococci isolation were diluted by 1:10 dilution.
One ml of milk sample was mixed with nine ml of sterile MRD in the test tube to
make initial suspension, and then further decimal dilution was done (ISO 6887-
1:1999).
The flow chart for isolation and identification of coagulase positive and
negative staphylococci (ISO 6888-1, 1999) is depicted in Figure 2.
Initial suspension of milk sample in MRD (1:10) series of
decimal dilutions
0.1 ml of test sample transferred aseptically from initial
suspension into two Baird Parker Agar (BPA) plates,
repeat the procedure for further decimal dilution
Plates were inverted and incubated for 24 ± 2 h
at 37 o C in an incubator
After incubation, the positions of typical colonies were marked on the
bottom of the plates. Plates were re-incubated for further 24 ± 2 h at the
same temperature, new typical colonies and atypical colonies were
marked
Typical and atypical colonies definition were based on
ISO 6887-1:1999 standard*

27
The plates containing a maximum of 300 colonies with 150 typical and/or atypical
colonies at two successive dilutions were taken for enumeration. One of the plates
should contain at least 15 colonies. Within this step Staphylococcus spp. were
enumerated
The inoculum was spread by using sterile spreader as quickly as
possible, dried with the lids on
For confirmation test a given number of colonies were selected (in general 5
typical colonies if there are only typical colonies or 5 atypical colonies if there
are only atypical colonies or 5 typical colonies and 5 atypical colonies if both
types present in each plate)
Confirmation (Coagulase test)
An inoculum was removed with a sterile wire from the surface of each
selected colony, transferred into a tube of Brain Heart Infusion broth (BHI)
and then incubated for 24 ± 2 h at 37 o C
Aseptically 0.1 ml of each culture was added to 0.3 ml of the rabbit
plasma in sterile haemolysis tubes or bottles and incubated at 37 o C
By tilting the tube, clotting of the plasma was examined after
4 h to 6 h of incubation time and if the test was negative,
reexamination was carried out at 24 h of incubation
The coagulase was considered to be positive if volume of clot occupied
more than half of original volume of liquid or at least at score +3.
Enumeration of CPS and CNS according to ISO 6887-1:1999 standard
(Appendix C)
Figure 2: Flow chart for isolation and identification of coagulase positive and
negative staphylococci (ISO 6888-1, 1999)

28
Remarks: (*) Typical colonies are black or grey, shining and convex (about 1.5 to 2.5
mm in diameter after incubation of 48 h) and surrounded by a clear zone
with immediate contact of opalescent ring. Atypical colonies may be
present as shining black colonies with or without a narrow white edge, the
clear zone is absent or barely visible; or grey colonies free of clear zones.
The coagulase test was considered to be positive if the volume of clot occupies
more than half of the original volume of the liquid or if the culture yielded at least 3+
coagulase reaction according to the scoring guidance in Figure 3.
Legend:
I
II
III
IV
V
: negative, no evidence of fibrin formation
: +1 positive, small unorganized clot
: +2 positive, small organized clot
: +3 positive, large organized clot
: +4 positive, entire content of tube coagulase and is not displaced
when tube was inverted
Figure 3: Scoring of coagulase test reactions (source: http://www.hc-sc.gc.ca/Tfnan/........../volume1/mfo22_e.html)
As the negative control for each batch of plasma, 0.1 ml of sterile brain heart
infusion (BHI) broth was added into 0.3 ml of rabbit plasma and incubated without
inoculation. For the best to be valid, the control plasma should show no signs of
clotting.

29
3.4.4 California Mastitis Test (CMT)
CMT was done by mixing 3 ml of milk sample with 3 ml of CMT reagent
(provided by Faculty of Veterinary Medicine, CMU) in the CMT paddle. By gently
rocking the CMT plate, the sample and reagent were carefully mixed and the result
was observed within around 20 seconds. The CMT scores were 0, trace, +1, +2 and
+3 (Shearer and Harris, 2003).
For determining the status of udder inflammation, the score of CMT was
further classified into two categories: negative and positive. The negative score was
represented by CMT scores of 0 and “trace” and the positive score (indicator of
subclinical mastitis/intramammary infection) by CMT scores of +1, +2 and +3
(Wakwoya et al., 2006).
3.5 Information regarding potential risk factors from questionnaire survey
Information regarding potential risk factors related to goats and udders, as well
as teat condition, was collected by using the questionnaire. The investigator collected
all information during farm visits. There were 10 potential risk factors obtained in this
study and listed in Table 2. Some of the risk factors were subjectively scored by the
investigator based on an adoption of the available scoring standard for dairy cow. The
complete description about the level of each factor and/or scoring system can be
found in the Appendix A.
Table 2: List of potential risk factors related to goats, udder and teat condition
No. Factors Description
1. Breed Breed of animal
2. Parity Parity number
3. Lactation stage Stage of lactation
4. Udder symmetry Symmetry of udder
5. Udder hygiene Score of udder hygiene
6. Teat end condition Score of teat end condition

30
No. Factors Description
7. Teat skin condition Score of teat skin condition
8. Teat shape Teat shape condition
9. Udder inflammation status Inflammatory status of the udder (based
on CMT test result)
10. Milk appearance Normality of milk appearance
General farm, milking and management practice information was also
collected by the investigator during farm visits. The detailed information about this
matter can be seen in Appendix A.
3.6 Data management and statistical analysis
Laboratory and questionnaire data were managed by using Microsoft Office
Excel 2003. Databases were prepared for each type of data and later merged into one.
Descriptive statistics were used to describe enumeration and prevalence data. The
prevalence estimates were determined by using the standard formula (i.e. the number
of positive samples divided by the number of total samples examined). Chi-square
univariate analysis was performed to evaluate the impact of each potential risk factor
(derived from the questionnaire responses) to the pathogenic outcomes (present or not
present) in samples. McNemar Chi-square test was used to compare the true
proportion of positive results among two testing methods, whilst Cohen’s kappa
coefficient was used to evaluate the agreement between two test results. The logistic
regression model for multivariate analysis was carried out to evaluate the impacts of
particular risk factors without interaction from the other factors. Mann-Whitney U test
or Kruskall-Wallis one way ANOVA (depending on the number of data groups) were
used to evaluate statistical significance in bacteria population among farms and within
the evaluated potential risk factors (Petrie and Watson, 1999; Dawson and Trapp,
2004).

4. RESULTS
4.1 Results of bacterial isolation and enumeration
4.1.1 Results from individual udder-half milk samples
Table 3 shows the compilation of some selected statistical values of indicator
bacterial count data from udder-half milk samples. The median values of overall
samples (n=300) for TPC, coliforms, Staphylococcus spp., CPS and CNS were 3.74,
0.70, 3.00, 1.70 and 2.52 log cfu/ml, respectively.
It should be noted that for the enumeration purpose, the samples yielded no
growth of bacteria (negative results) were registered with half of the detection limit of
bacterial isolation method (10:2 = 5 colonies = log 0.70 for coliforms; 100:2 = 50
colonies = log 1.70 for Staphylococcus spp., CPS and CNS).
Within the farm level (n=100/farm), the highest median value of TPC,
coliforms, Staphylococcus spp. and CNS were 3.92 log cfu/ml (Farm 2), 2.39 log
cfu/ml (Farm 3), 3.34 log cfu/ml (Farm 2) and 2.85 log cfu/ml (Farm 2), respectively,
whereas the median values of CPS from every farm were the same. Statistically
significant differences (P

32
Table 3: Selected statistical value of indicator bacterial counts from udder half milk
samples (n= 100/farm)
No.
Selected Overall Farm Farm Farm
Indicator
Statistical [n=300] 1 2 3
Bacteria
Value
log cfu/ml
1. Total Plate Median 3.74 3.03 3.92 3.77
Count (TPC) Maximum 6.96 6.01 6.40 6.96
Minimum 0.70 1.00 1.30 0.70
IQR* 1.68 2.10 1.06 1.79
2. Coliforms Median 0.70 0.70 1.00 2.39
Maximum 5.99 5.99 4.24 4.66
Minimum 0.70 0.70 0.70 0.70
IQR* 1.41 0.00 1.20 2.12
3. Staphylococcus Median 3.00 2.59 3.34 2.83
spp.
Maximum 6.51 6.10 6.51 5.70
Minimum 1.70 1.70 1.70 1.70
IQR* 2.10 2.48 1.70 2.00
4. Coagulase Median 1.70 1.70 1.70 1.70
Positive Maximum 6.18 6.02 6.18 5.51
Staphylococci Minimum 1.70 1.70 1.70 1.70
(CPS) IQR* 1.30 1.25 1.75 0.99
5. Coagulase Median 2.52 2.00 2.85 2.60
Negative Maximum 6.41 6.09 6.41 5.49
Staphylococci Minimum 1.70 1.70 1.70 1.70
(CNS) IQR* 2.01 1.67 2.11 2.21
* IQR = Inter Quartile Range
P-value
(among
farms)
0.002
0.000
0.029
0.298
0.003

33
7.00
6.00
5.00
TPC (log cfu/ml)
4.00
3.00
2.00
1.00
0.00
1
2
Farm ID
3
Figure 4: Box and Whisker plots of TPC in three farms compared to the maximum
limit of available standards ( = SNI, = EC Directive and “Milchverordnung”).
(ο) = outlier values from data distribution which can be represented either
as the maximum or minimum value
6.00
5.00
Coliforms (log cfu/ml)
4.00
3.00
2.00
1.00
0.00
1
2
Farm ID
3
Figure 5: Box and Whisker plots of coliforms counts in three farms compared to the
maximum limit of available standards ( = SNI, = EC Directive and
“Milchverordnung”). (*) values of data distribution, (ο) = outlier value from data
distribution which is represented as the maximum value

34
Box and Whisker plots in Figure 5 show the descriptive statistics of coliforms
counts in each sampling farm. Only the median value of the coliforms count from
farm 3 [2.39 log cfu/ml] (Table 3), exceeded the maximum limit of available
standards, i.e. 1.3 log cfu/ml from SNI (SNI 01-3141) (BSN, 1998) and 2 log cfu/ml
in EC Directive 92/46/EEC (1992) and German “Milchverordnung” for
“Vorzugsmilch” (BGBl Teil I Nr. 58 S 2794, 2004). However all the farms had
maximum coliforms values (Table 3) exceeding the maximum limits of those
standards.
8.00
6.00
CPS (log cfu/ml)
4.00
2.00
0.00
1
2
Farm ID
3
Figure 6: Box and Whisker plots of CPS counts in three farms compared to the
maximum limit of S. aureus in available standards ( = SNI, = EC Directive
and “Milchverordnung”). (ο) = outlier values from data distribution which can
be represented as the maximum value
Figure 6 shows the descriptive statistics of CPS counts in each sampling farm.
CPS was compared with the S. aureus maximum limit standard, because S. aureus is
the major species within CPS. ISO 6888-1 standard (1999), which was used as the
standard procedure for CPS isolation, stated that the standard was mainly concerned
about S. aureus, but it was possible that other minor CPS species existed, especially

35
when the coagulase test results showed weak reaction. None of the median values of
CPS counts from every farm (Table 3) exceeded the maximum limit of S. aureus
(2 log cfu/ml) from SNI (SNI 01-3141) (BSN, 1998) and 3.3 log cfu/ml in EC
Directive 92/46/EEC (1992) and German “Milchverordnung” (BGBl Teil I Nr. 58 S
2794, 2004). All farms had maximum values of CPS counts exceeding the maximum
limits of those standards.
CNS
2.52
I ndic ato r ba cter ia
CPS
Staphylococcus spp.
Coliforms
TPC
0.70
1.70
3.00
3.74
0 0.5 1 1.5 2 2.5 3 3.5 4
Median Value (log cfu/ml)
Figure 7: Bar charts of median values of indicator bacterial counts from overall
udder-half milk samples (n=300)
Median values of TPC, coliforms and CPS from overall udder-half milk
samples (Figure 7) did not exceed the maximum limit of each bacterium standard both
from SNI [TPC = 6 log cfu/ml; coliforms = 1.3 log cfu/ml; S. aureus = 2 log cfu/ml]
(SNI 01-3141) (BSN, 1998) and from the European (EC, 1992) and German
“Milchverordnung” (BGBl, 2004) [TPC = 5.7 log cfu/ml; coliforms = 2 log cfu/ml; S.
aureus = 3.3 log cfu/ml]. However, TPC, coliforms and CPS counts of the overall
udder-half milk samples had maximum values which exceeded the maximum limit for
each bacterium in all three available standards. The maximum values of each
indicator bacteria were 6.96, 5.99 and 6.18 log cfu/ml for TPC, coliforms and CPS
respectively (Table 3).

36
Table 4 shows indicator bacterial count from udder-half milk samples among
breeds of goat in each farm. Statistically significant differences (P

37
Table 4: Indicator bacterial count from udder-half milk samples among breeds of
goat in each farm (n = 100/farm)
Indicator Bacteria Farm Breed* n Median (log
cfu/ml)
P-value
(among
breeds)
TPC
1
1 72 3.69
2 20 2.34 0.012
3 8 2.88
2
1 72 3.99
2 14 3.92 0.120
3 14 3.20
3
1 32 2.83
2 68 4.31 0.000
3 - -
Coliforms
1
1 72 0.70
2 20 0.70 0.293
3 8 0.70
2
1 72 1.00
2 14 0.70 0.185
3 14 1.15
3
1 32 0.70
2 68 2.75 0.000
3 - -
Staphylococcus spp. 1
1 72 2.91
2 20 2.15 0.076
3 8 1.70
2
1 72 3.75
2 14 3.34 0.433
3 14 2.98
3
1 32 3.22
2 68 2.63 0.121
3 - -
CPS
1
1 72 1.70
2 20 1.70 0.634
3 8 1.70
2
1 72 1.70
2 14 1.70 0.265
3 14 2.30
3
1 32 1.70
2 68 1.70 0.507
3 - -
CNS
1
1 72 2.15
2 20 1.70 0.222
3 8 1.70
2
1 72 3.04
2 14 3.17
0.164
3 14 2.29
3
1 32 3.00
2 68 2.46 0.034
3 - -
* Breed of goat: 1. Ettawa crossbreed, 2. Saanen crossbreed, 3. Jawarandu

38
Table 5: Total Plate Count from udder-half milk samples among levels of each factor
(n = 300)
Factors/Level* n Median
(log cfu/ml)
Breed
- Ettawa Crossbreed (EC)
- Saanen Crossbreed
- Jawarandu (Local crossbreed)
Parity
- First
- Second
- Third
- Fourth
- Fifth
Lactation stage
- First
- Second
- Third
Udder symmetry
- Yes
- No
Udder hygiene
- Free of dirt
- Slightly dirty
Teat end condition
- No ring
- Smooth rough ring
Teat skin condition
- Free from scales/smooth
- Shows some scaling
Teat shape
- Normal
- Dilatated
- General dilatated
Udder inflammation status
- Yes
- No
Milk appearance
- Normal
- Abnormal
176
102
22
66
114
80
32
8
183
66
51
176
124
296
4
225
75
295
5
166
117
17
186
114
3.76
3.87
3.06
3.25
3.91
3.67
3.95
4.18
3.72
3.64
3.99
3.57
3.97
3.74
4.60
3.53
4.12
3.74
4.00
3.26
4.13
4.28
4.15
2.84
P-value
0.035
0.010
0.392
0.180
0.271
0.001
0.892
0.000
0.000
293 3.73
0.028
7 4.57
*Detail explanation of each factor level is presented in Appendix A

39
Table 6: Coliforms counts from udder-half milk samples among levels of each factor
(n = 300)
Factors/Level n Median
(log cfu/ml)
Breed
- Ettawa Crossbreed (EC)
- Saanen Crossbreed
- Jawarandu (Local crossbreed)
Parity
- First
- Second
- Third
- Fourth
- Fifth
Lactation stage
- First
- Second
- Third
Udder symmetry
- Yes
- No
Udder hygiene
- Free of dirt
- Slightly dirty
Teat end condition
- No ring
- Smooth rough ring
Teat skin condition
- Free from scales/smooth
- Shows some scaling
Teat shape
- Normal
- Dilated
- General dilated
Udder inflammation status
- Yes
- No
Milk appearance
- Normal
- Abnormal
176
102
22
66
114
80
32
8
183
66
51
176
124
296
4
225
75
295
5
166
117
17
186
114
293
7
0.70
2.11
0.70
0.70
0.98
0.70
0.70
1.00
0.70
0.70
0.96
0.70
0.70
0.70
2.63
0.70
0.70
0.70
0.70
0.70
1.00
0.70
0.70
0.70
0.70
1.30
P-value
0.000
0.065
0.629
0.833
0.104
0.459
0.181
0.111
0.415
0.152

40
Table 7: Staphylococcus spp. count from udder-half milk samples among levels of
each factor (n = 300)
Factors/Level n Median
(log cfu/ml)
Breed
- Ettawa Crossbreed (EC)
- Saanen Crossbreed
- Jawarandu (Local crossbreed)
Parity
- First
- Second
- Third
- Fourth
- Fifth
Lactation stage
- First
- Second
- Third
Udder symmetry
- Yes
- No
Udder hygiene
- Free of dirt
- Slightly dirty
Teat end condition
- No ring
- Smooth rough ring
Teat skin condition
- Free from scales/smooth
- Shows some scaling
Teat shape
- Normal
- Dilated
- General dilated
Udder inflammation status
- Yes
- No
Milk appearance
- Normal
- Abnormal
176
102
22
66
114
80
32
8
183
66
51
176
124
296
4
225
75
295
5
166
117
17
186
114
293
7
3.30
2.68
2.77
2.48
2.82
3.70
3.15
4.01
3.10
2.48
3.30
3.09
2.90
3.02
2.09
2.80
3.75
3.00
3.92
2.79
3.34
3.42
3.56
2.48
3.00
3.53
P-value
0.014
0.000
0.004
0.774
0.257
0.003
0.406
0.052
0.000
0.738

41
Table 8: Coagulase positive staphylococci (CPS) count from udder-half milk
samples among levels of each factor (n = 300)
Factors/Level n Median
(log cfu/ml)
Breed
- Ettawa Crossbreed (EC)
- Saanen Crossbreed
- Jawarandu (Local crossbreed)
Parity
- First
- Second
- Third
- Fourth
- Fifth
Lactation stage
- First
- Second
- Third
Udder symmetry
- Yes
- No
Udder hygiene
- Free of dirt
- Slightly dirty
Teat end condition
- No ring
- Smooth rough ring
Teat skin condition
- Free from scales/smooth
- Shows some scaling
Teat shape
- Normal
- Dilated
- General dilated
Udder inflammation status
- Yes
- No
Milk appearance
- Normal
- Abnormal
176
102
22
66
114
80
32
8
183
66
51
176
124
296
4
225
75
295
5
166
117
17
186
114
293
7
1.70
1.70
2.00
1.70
1.70
1.70
2.00
3.87
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.70
3.70
1.70
1.70
1.70
1.70
1.70
1.70
2.30
P-value
0.282
0.000
0.010
0.774
0.132
0.003
0.085
0.588
0.000
0.738

42
Table 9: Coagulase negative staphylococci (CNS) count from udder-half milk
samples among levels of each factor (n = 300)
Factors/Level n Median
(log cfu/ml)
Breed
- Ettawa Crossbreed (EC)
- Saanen Crossbreed
- Jawarandu (Local crossbreed)
Parity
- First
- Second
- Third
- Fourth
- Fifth
Lactation stage
- First
- Second
- Third
Udder symmetry
- Yes
- No
Udder hygiene
- Free of dirt
- Slightly dirty
Teat end condition
- No ring
- Smooth rough ring
Teat skin condition
- Free from scales/smooth
- Shows some scaling
Teat shape
- Normal
- Dilated
- General dilated
Udder inflammation status
- Yes
- No
Milk appearance
- Normal
- Abnormal
176
102
22
66
114
80
32
8
183
66
51
176
124
296
4
225
75
295
5
166
117
17
186
114
293
7
2.76
2.37
1.85
2.13
2.30
2.90
2.67
3.59
2.74
2.15
2.30
2.60
2.48
2.58
2.09
2.48
3.13
2.48
2.85
2.48
2.66
2.00
2.74
2.00
2.48
2.66
P-value
0.028
0.023
0.035
0.317
0.551
0.003
0.625
0.134
0.000
0.738

43
Table 10 shows overall and farm level prevalence of indicator bacteria from
udder-half milk samples. Overall prevalence of coliforms, Staphylococcus spp., CPS
and CNS were 46.3, 78.7, 37.7 and 66.0%, respectively.
Within the farm level, the highest prevalence for each indicator bacteria were
77% for coliforms (Farm 3), 86% for Staphylococcus spp. (Farm 2), 43% for CPS
(Farm 2) and 75% for CNS (Farm 2). Statistically significant difference was observed
only for the prevalence of coliforms and CNS among farms.
Table 10: Proportion of positive samples for indicator bacteria from udder-half milk
samples
Indicator
Bacteria
Factor/level
n
No. of
positive/contaminated
samples
Prevalence
(%)
Coliforms Overall 300 139 46.3
By Farm
- Farm 1
- Farm 2
- Farm 3
100
100
100
6
56
77
6
56
77
Staphylococcus
spp.
Overall 300 236 78.7
By Farm
- Farm 1
- Farm 2
- Farm 3
100
100
100
72
86
78
72
86
78
CPS Overall 300 113 37.7
By Farm
- Farm 1
- Farm 2
- Farm 3
100
100
100
35
43
35
35
43
35
CNS Overall 300 198 66.0
By Farm
- Farm 1
- Farm 2
- Farm 3
100
100
100
53
75
70
53
75
70
P-value
0.000
0.053
0.403
0.003

44
Table 11: Proportion of positive samples for indicator bacteria from udder-half milk
samples among breeds of goat in each farm
Indicator
Bacteria
Farm Breed* n No. of
positive
samples
1
Prevalence
(%)
P-value
(among
breeds)
Coliforms
1 72 6 8.30
2 20 0 0.00 0.463
3 8 0 0.00
2
1 72 42 58.3
2 14 5 35.7 0.250
3 14 9 64.3
3
1 32 13 40.6
2 68 64 94.1 0.000
3 - - -
Staphylococcus 1
1 72 56 77.7
spp.
2 20 13 65.0 0.036
3 8 3 37.5
2
1 72 63 87.5
2 14 12 85.7 0.657
3 14 11 78.6
3
1 32 25 78.1
2 68 53 77.9 1.000
3 - - -
CPS
1
1 72 26 36.1
2 20 7 35.0 0.939
3 8 2 25.0
2
1 72 29 40.3
2 14 4 28.6 0.050
3 14 10 71.4
3
1 32 12 37.5
2 68 23 33.8 0.893
3 - - -
CNS 1
1 72 42 58.3
2 20 8 40.0 0.234
3 8 3 37.5
2
1 72 56 77.8
2 14 11 78.6 0.324
3 14 8 57.1
3
1 32 24 75.0
2 68 45 66.2 0.510
3 - - -
* Breed of goat: 1. Ettawa crossbreed, 2. Saanen crossbreed, 3. Jawarandu

45
Table 11 shows the prevalence of indicator bacteria from udder-half milk
samples among breeds of goat in each farm. Statistically significant difference
(P

46
Data in Table 12 show number of coliforms positive samples from overall
udder-half milk samples in each level of potential risk factors. Only one out of 10
potential risk factors (breed of goat) was significantly (P

47
Table 14: Summary results of the assessment of associations between sample
prevalence of Staphylococcus spp. with potential risk factors (univariate analysis)
Factors/Level n n (+) n (-) % (+) P-value
Breed
- Ettawa Crossbreed (EC)
- Saanen Crossbreed
- Jawarandu (Local crossbreed)
Parity
- First
- Second
- Third
- Fourth
- Fifth
Lactation stage
- First
- Second
- Third
Udder symmetry
- Yes
- No
Udder hygiene
- Free of dirt
- Slightly dirty
Teat end condition
- No ring
- Smooth rough ring
Teat skin condition
- Free from scales/smooth
- Shows some scaling
Teat shape
- Normal
- Dilated
- General dilated
Udder inflammation status
- Yes
- No
Milk appearance
- Normal
- Abnormal
176
102
22
66
114
80
32
8
183
66
51
176
124
296
4
225
75
295
5
166
117
17
186
114
293
7
144
78
14
47
86
67
28
8
152
44
40
138
98
234
2
171
65
231
5
124
100
12
157
79
230
6
32
24
8
19
28
13
4
0
31
22
11
38
26
62
2
54
10
64
0
42
17
5
29
35
63
1
81.8
76.5
63.6
71.2
75.4
83.8
87.5
100
83.1
66.7
78.4
78.4
79.0
79.1
50.0
76.0
86.7
78.3
100.0
74.7
85.5
70.6
84.4
69.3
78.5
85.7
0.117
0.100
0.021
1.000
0.427
0.073
0.533
0.066
0.003
1.000
The results of logistic regression of two risk factors which were significantly
associated with sample prevalence of Staphylococcus spp in univariate analysis are
shown in Table 15. The second stage of lactation had significantly lower

48
Staphylococcus spp. contamination in the samples than the first lactation stage
(OR=0.392, P=0.005). The odd ratio (OR) of udder inflammation status factor was
greater than one, meaning that factor was positively associated with the presence of
Staphylococcus spp. in the samples. Therefore the udder with inflammation had
significantly higher results of Staphylococcus spp. positive samples than udder
without inflammation (OR= 2.490, P=0.002). It can also be said that the risk of
having Staphylococcus spp. positive milk samples was 2.49 times more likely if the
udder had inflammation than if it had not.
Table 15: Logistic regression of the risk factor associated with sample prevalence of
Staphylococcus spp. (multivariate analysis)
Lactation stage
- First
- Second
- Third
Factors/Level OR P-value 95% Confidence
Interval
Udder inflammation status
- Yes
- No
1
0.392
0.662
2.490
1
-
0.005
0.305
0.002
-
0
[0.203, 0.755]
[0.301, 1.456]
[1.403. 4.418]
0
Table 16 shows number of CPS positive samples in each level of potential risk
factors. Only three out of 10 potential risk factors were significantly (P

49
Table 16: Summary results of the assessment of associations between sample
prevalence of CPS with potential risk factors (univariate analysis)
Factors/Level n n (+) n (-) % (+) P-value
Breed
- Ettawa Crossbreed (EC)
- Saanen Crossbreed
- Jawarandu (Local crossbreed)
Parity
- First
- Second
- Third
- Fourth
- Fifth
Lactation stage
- First
- Second
- Third
Udder symmetry
- Yes
- No
Udder hygiene
- Free of dirt
- Slightly dirty
Teat end condition
- No ring
- Smooth rough ring
Teat skin condition
- Free from scales/smooth
- Shows some scaling
Teat shape
- Normal
- Dilated
- General dilated
Udder inflammation status
- Yes
- No
Milk appearance
- Normal
- Abnormal
176
102
22
66
114
80
32
8
183
66
51
176
124
296
4
225
75
295
5
166
117
17
186
114
293
7
67
34
12
20
34
35
18
6
75
16
22
70
43
113
0
80
33
109
4
62
43
8
82
31
108
5
109
68
10
46
80
45
14
2
108
50
29
106
81
183
4
145
42
186
1
104
74
9
104
83
185
2
38.1
33.3
54.5
30.0
29.8
43.8
56.3
75.0
41.0
24.2
43.1
39.8
34.7
38.2
0.00
35.6
44.0
36.9
80.0
37.3
36.8
47.1
44.1
27.2
36.9
71.4
0.174
0.004
0.037
0.438
0.296
0.242
0.132
0.709
0.005
0.141

50
Table 17: Logistic regression of the risk factor associated with sample prevalence of
CPS (multivariate analysis)
Parity
- First
- Second
- Third
- Fourth
- Fifth
Lactation stage
- First
- Second
- Third
Factors/Level OR P-value 95% Confidence
Interval
Udder inflammation status
- Yes
- No
1.000
0.900
1.853
1.764
6.033
1.000
0.814
1.449
2.622
1.000
-
0.778
0.118
0.253
0.050
-
0.577
0.333
0.001
-
0
[0.431, 1.876]
[0.856, 4.013]
[0.666, 4.672]
[0.999, 36.455]
0
[0.395, 1.679]
[0.684, 3.070]
[1.487, 4.623]
0
None of the potential risk factors was significantly (P

51
Table 18: Summary results of the assessment of associations between prevalence of
CNS with potential risk factors (univariate analysis)
Factors/Level n n (+) n (-) % (+) P-value
Breed
- Ettawa Crossbreed (EC)
- Saanen Crossbreed
- Jawarandu (Local crossbreed)
Parity
- First
- Second
- Third
- Fourth
- Fifth
Lactation stage
- First
- Second
- Third
Udder symmetry
- Yes
- No
Udder hygiene
- Free of dirt
- Slightly dirty
Teat end condition
- No ring
- Smooth rough ring
Teat skin condition
- Free from scales/smooth
- Shows some scaling
Teat shape
- Normal
- Dilated
- General dilated
Udder inflammation status
- Yes
- No
Milk appearance
- Normal
- Abnormal
176
102
22
66
114
80
32
8
183
66
51
176
124
296
4
225
75
295
5
166
117
17
186
114
293
7
122
64
11
40
72
56
22
7
129
38
30
115
82
195
2
142
55
193
4
105
83
9
130
67
192
5
54
38
11
26
42
24
10
1
54
28
21
61
42
101
2
83
20
102
1
61
34
8
56
47
101
2
69.3
62.7
50.0
60.6
63.2
70.0
68.8
87.5
70.5
57.6
58.8
65.3
66.1
65.9
50.0
63.1
73.3
65.4
80.0
63.3
70.9
52.9
69.9
58.8
65.5
71.4
0.148
0.469
0.088
0.986
0.893
0.140
0.837
0.213
0.065
1.000

52
4.1.2 Results from bulk milk samples
Two parallel bulk milk samples were taken from each farm in the time of
sampling visits. Totally, ten bulk milk samples were collected from each farm (five
samples, double), therefore there were 30 bulk milk samples as a total. General farm,
milking and management practices information was also collected by the investigator
during farm visits. General characteristics of farms are summarized in Table 19.
Based on data in Table 19, it could be summarized that generally all sampling
farms had qualitatively similar characteristics in farm management and milking
practices. This was supported also by the data regarding counts and prevalence of
indicator bacteria of bulk milk samples among farms (Table 20 and 21).
Table 19: Summary of general characteristics of sampling farms
No. Factors Level Farm
1
1. Farm location from Close
√
residence area Medium
Far
Farms
Farm
2
√
Farm
3
2. Herd size Heads 200 400 600
3. Stocking density Low (≥2)
(m 2 /animal) Medium (1.5) √ √ √
High (1)
4. Number of workers Person 5 6 8
5. Animal housing On the ground
Elevated √ √ √
6. Type of house Loose housing
Pen √ √ √
7. House for lactating Yes
√ √ √
goat
No
8. Ventilation Poor
Good √ √ √
9. House surface Bamboo
Wood √ √ √
10. Surface condition Clean
Medium
Dirty
11. Hygiene status Poor
Good √ √
√
√
√
√
√

53
Farms
No. Factors Level Farm
1
Farm
2
Farm
3
12. Special worker for
milking
Yes
No
√ √ √
13. Hand washing
before milking
Yes
No
√ √ √
14. Worker hygiene Poor
√ √ √
status
Good
15. Water source Tap
Well √ √ √
16. Water/chlorinate Yes
No √ √ √
17. Water/storage Close
√ √ √
Open
18. Animal/milking Hand
√ √ √
technique
Machine
19. Animal/special
place for milking
Yes
No
√
√
√
20. Animal/frequency
of milking (per day)
Once
Twice
√ √ √
More
21. Pre-milking Yes
√ √ √
washing of udder No
22. Pre-milking drying
of udder
Yes
No √ √ √
23. Pre-dipping of teat Yes
No √ √ √
24. Fore-stripping Yes
√ √ √
No
25. Post-dipping of
udder
Yes
No √ √ √
26. Other animal Yes
√ √ √
species in the farm No
Note: For a detailed description of every factor and level, please refer to Appendix A

54
Table 20: Selected statistical value of indicator bacterial counts from bulk milk
samples (n=10/farm)
No.
Indicator
Bacteria
1. Total Plate
Count (TPC)
2. Coliforms
3. Staphylococcus
spp.
4. Coagulase
Positive
Staphylococci
Selected
Statistical
Value
Overall
[n=30]
Farm
1
log cfu/ml
Farm
2
Farm
3
Median 5.69 5.48 6.91 5.51
Maximum 7.50 7.00 7.50 6.98
Minimum 3.74 4.34 3.95 3.74
IQR 1.85 1.82 1.35 0.96
Median 2.98 3.49 3.34 2.24
Maximum 4.45 4.45 3.54 3.02
Minimum 0.70 0.70 0.70 0.70
IQR 1.48 1.85 0.97 0.76
Median 3.86 4.10 4.09 3.55
Maximum 5.65 4.92 5.65 4.48
Minimum 1.70 3.13 1.70 3.00
IQR 1.08 1.15 1.00 0.65
Median 3.66 4.05 3.76 3.41
Maximum 5.65 4.83 5.65 3.86
Minimum 1.70 1.70 1.70 1.70
(CPS) IQR 2.10 1.58 2.84 1.13
Median 3.32 3.30 3.60 3.17
Maximum 5.54 4.23 5.54 4.52
Minimum 1.70 1.70 1.70 1.70
5. Coagulase
Negative
Staphylococci
(CNS) IQR 0.79 0.60 1.00 1.22
P-value
(among
farms)
0.059
0.040
0.068
0.275
0.638
Table 20 shows some selected statistical values for indicator bacterial counts
from bulk milk samples. Coliforms counts differed significantly (P

55
S. aureus in the European standard (EC, 1992) and German “Milchverordnung”
(BGBl, 2004).
Indicator bacteria
CNS
CPS
Staphylococcus spp.
Coliforms
TPC
3.32
3.66
3.86
2.98
5.69
0 1 2 3 4 5 6
Median Value (log cfu/ml)
Figure 8: Bar charts of median values of indicator bacterial counts from overall bulk
milk samples (n=30)
Table 21 shows the proportion of positive samples of indicator bacteria from
bulk milk samples. The overall prevalence of coliforms, Staphylococcus spp., CPS
and CNS were 86.7, 96.7, 76.7, and 86.7%, respectively. No statistically significant
difference was observed among prevalence of each indicator bacteria within the farm
level.
Table 21: Proportion of positive samples of indicator bacteria from bulk milk
samples (n=10/farm)
Indicator
Bacteria
Factor/level
n
No. of
positive/contaminated
samples
Percent of
positive
samples
Coliform Overall 30 26 86.7
By Farm
- Farm 1
- Farm 2
- Farm 3
10
10
10
9
8
9
90
80
90
Staphylococcus
spp.
Overall 30 29 96.7
P-value
0.749

56
Indicator
Bacteria
Factor/level
By Farm
- Farm 1
- Farm 2
- Farm 3
n
10
10
10
No. of
positive/contaminated
samples
10
9
10
Percent of
positive
samples
100
90
100
CPS Overall 30 23 76.7
By Farm
- Farm 1
- Farm 2
- Farm 3
10
10
10
8
7
8
80
70
80
CNS Overall 30 26 86.7
By Farm
- Farm 1
- Farm 2
- Farm 3
10
10
10
9
8
9
90
80
90
P-value
0.355
0.830
0.749
4.2 The comparison of indicator bacterial counts and prevalence between left
and right udder milk samples
Data for the indicator bacterial counts and prevalence in each udder half (left
and right) milk samples are presented in Table 22 and Table 23, respectively. No
statistically significant difference was observed either for indicator bacterial counts or
prevalence between left and right udder milk samples.
Table 22: Selected statistical value of indicator bacterial counts from left and right
udder milk samples (n=150/udder half)
No.
Indicator Bacteria
1. Total Plate Count
(TPC)
2. Coliforms
Selected
Statistical
Value
Left
Udder
Right
Udder
Log cfu/ml
Median 3.86 3.59
Maximum 6.96 6.85
Minimum 1.00 0.70
IQR 1.77 1.60
Median 0.70 0.70
Maximum 5.99 4.41
Minimum 0.70 0.70
IQR 1.56 1.30
P-value
0.267
0.217

57
No.
Indicator Bacteria
3. Staphylococcus
spp.
4. Coagulase Positive
Staphylococci
(CPS)
5. Coagulase Negative
Staphylococci
(CNS)
Selected
Statistical
Value
Left
Udder
Right
Udder
Log cfu/ml
Median 2.98 3.02
Maximum 6.10 6.51
Minimum 1.70 1.70
IQR 2.03 2.11
Median 1.70 1.70
Maximum 6.02 6.18
Minimum 1.70 1.70
IQR 1.52 1.25
Median 2.54 2.52
Maximum 5.39 6.41
Minimum 1.70 1.70
IQR 1.87 2.16
P-value
0.740
0.483
0.499
Table 23: Proportion of positive samples of indicator bacteria from left and right
udder milk samples
Indicator Bacteria Udder n
Coliform
Staphylococcus
spp.
CPS
CNS
- Left
- Right
- Left
- Right
- Left
- Right
- Left
- Right
150
150
150
150
150
150
150
150
No. of
positive/contaminated
samples
73
66
119
117
59
54
98
99
Prevalence
(%)
48.7
44.0
79.3
78.0
39.3
36.0
65.3
66.0
P-value
0.487
0.888
0.634
1.000
4.3 The comparison between California mastitis test results and conventional
bacteriological isolation
Table 24 shows the comparison between CMT results (positive and negative)
and conventional bacteriological isolation results by using McNemar’s test.
McNemar’s Chi-square test was used to test the null hypothesis that the true

58
proportions of successes (positive results) using the two methods in the same sample
were equal (Petrie and Watson, 1999). The isolation of indicator bacteria by using
conventional bacteriological methods was considered a gold standard. Further
epidemiological and statistical analyses were done by calculating sensitivity,
specificity for CMT as well as calculating Cohen’s kappa coefficient (κ) for
measuring agreement between results of the two diagnostic tests/methods.
Statistically significant differences (P

59
Cohen’s kappa coefficient interpretation of agreement between two tests (Petrie and
Watson, 1999):
• “Poor” if κ ≤ 0.20;
• “Fair” if 0.21 ≤ κ ≤ 0.40;
• “Moderate” if 0.41 ≤ κ ≤ 0.60;
• “Substantial” if 0.61 ≤ κ ≤ 0.80;
• “Good” if κ exceeds 0.80

5. DISCUSSION AND CONCLUSIONS
5.1 Discussion
The objective of this study was to determine out the microbiological status
(quantitatively and qualitatively) of raw goat milk and some potential risk factors
associated with it, from commercial dairy goat farms in Indonesia. Despite of a
limited sampling location, which include only three commercial dairy goat farms
located in the Bogor District, West Java Province, it was likely that the results of this
study would be useful to show some real data about the present situation of the
microbiological status of goat milk in Indonesia. This was due to the fact that in
Indonesia, dairy goat farms were concentrated in the West and Central Java Provinces
and some other farms located in other provinces located on Java Island. Therefore the
majority of the commercial dairy goat farms had approximately similar general
characteristics of the management and milking practices.
It should be noted also that the milk produced from all sampling farms within
this study, as well as from other dairy goat farms, was sold and consumed in raw
condition by the consumers. Moreover, in Indonesia, the consumers preferred to
consume the goat milk as fresh as possible, since they consider the milk to be fresher
when they can consume it as soon as the milk is secreted from the goat udder.
Here, data on the counts and prevalence of indicator bacteria for the
microbiological status of raw goat milk and also some potential risk factors associated
with were obtained.
5.1.1 Quantitative data
There were 300 udder-half milk samples as the main sample and 30 bulk milk
samples as a supporting sample collected from three commercial dairy goat farms
with intensive breeding systems in the Bogor District, West Java Province, Indonesia.
The samples were examined for the counts and presence of indicator bacteria, which

61
were TPC, coliforms, Staphylococcus spp., CPS and CNS. The information regarding
some potential risk factors, which was predicted to have association with the indicator
bacteria, was also assessed.
In this study the median values of indicator bacterial counts from overall
udder-half milk samples were 3.74, 0.70, 3.00, 1.70 and 2.52 log cfu/ml for TPC,
coliforms, Staphylococcus spp., CPS and CNS, respectively. Median values of
indicator bacterial counts from overall bulk milk samples were 5.69, 2.98, 3.86, 3.66
and 3.32 log cfu/ml for for TPC, coliforms, Staphylococcus spp., CPS and CNS,
respectively.
Study or investigation reports regarding counts of bacteria in goat milk were
very limited as compared to cow milk, and mostly concerned about proportion or
prevalence of these bacteria. There was also no study/investigation report found in
Indonesia regarding counts and prevalence of indicator bacteria in raw goat milk and
potential risk factors associated with it.
This was due to the fact that commercial dairy goat farms in Indonesia just
emerged about 10 – 15 years ago. In the past, goat milk was produced from backyard
farming systems with a small number of animals. Today, the commercial dairy goat
farms have from100 to a thousand animals per farm.
The median of the TPC of overall udder-half milk samples in this study (3.74
log cfu/ml) was lower compared to the findings reported by Delgado-Pertinez et al.
(2003) and Kyozaire et al. (2005). Delgado-Pertinez et al. (2003) reported that they
collected udder-half goat milk samples from 28 farms in Spain and the mean value of
TPC from those samples was 4.81 log cfu/ml. Whereas the mean values of TPC of
270 udder halves milk samples collected from 3 commercial dairy goat farms which
were using bucket milking machine, pipeline milking machine and hand milking
machine in South Africa were 4.21, 4.56 and 4.68 log cfu/ml, respectively (Kyozaire
et al., 2005).

62
Other studies conducted in Switzerland and the USA reported lower TPC of
bulk milk samples than here (5.69 log cfu/ml): the median of TPC of 344 bulk milk
samples from three commercial dairy goat farms in Switzerland was 4.68 log cfu/ml
(Muehlherr et al., 2003; Zweifel et al., 2005), whereas the mean of TPC of bulk milk
samples from three commercial dairy goat farms located in Arkansas and Oklahoma
USA was 2.95 log cfu/ml (Zeng and Escobar, 1996).
The results of this study for the bulk milk samples were relatively higher as
compared to the following findings: Morgan et al. (2003) collected bulk milk samples
from intensive breeding systems of small and medium scale dairy goat farms in
France. The mean values of goat milk from those farms in France were 5.03, 2.15 and
2.44 log cfu/ml for TPC, coliforms and Staphylococcus spp. (CPS and CNS),
respectively. Another finding was reported by Foschino et al. (2002), who collected
60 bulk milk samples from 10 dairy goat farms during a six month period in Italy.
The mean values of TPC, coliforms, S. aureus and CNS of Italian raw goat milk
samples were 4.70, 2.96, 3.07 and 3.11 log cfu/ml, respectively.
However, these study results were relatively lower compared to the finding
which was also reported by Morgan et al. (2003) from small and medium scale dairy
goat farms under extensive breeding systems in Greece and Portugal. They reported
that mean values of indicator bacteria in goat bulk milk in Greece and Portugal were
TPC = 7.5 and 7.6 log cfu/ml; coliforms = 6.25 and 6.39 log cfu/ml; Staphylococcus
spp. = 5.23 and 4.28 log cfu/ml, respectively. The results of CNS counts here were
also comparable to the finding of CNS counts in three commercial milking goat herds
in the UK by Hall and Rycroft (2007), which ranged from 3.00 to 5.08 log cfu/ml.
This study result of coliform counts was comparable to the finding reported by
Little and de Luvois (1999), who did a pilot study to determine microbiological
quality of unpasteurized milk from goat and sheep taken along the food chain in
England and Wales, UK. They found that 11 out of 100 unpasteurized goat milk
samples had coliform counts of more than 2 log cfu/ml, whereas 38 samples contained
coliform counts less than 2 log cfu/ml and no coliforms were detected in the rest of
the samples.

63
Little and de Luvois (1999) also found that 15 out of 100 unpasteurized goat
milk samples were S. aureus positive and 6 out of 15 samples had S. aureus counts of
more than 2 log cfu/ml.
The indicator bacterial counts from udder-half milk samples were significantly
different (P

64
(2005) in Switzerland, which found that the median of TPC was not significantly
different among breeds of goats.
In the parity factor, the indicator bacteria counts, except for coliforms, were
significantly different among parity levels. TPC, Staphylococcus spp., CPS and CNS
counts tended to increase as the does got older. Only for Staphylococcus spp. group
bacterial counts, the statistically significant differences were observed among
lactation stages.
Counts of indicator bacteria, except for coliforms, based on the teat end
condition were observed to have statistically significant differences, in which normal
teat ends had significantly lower counts of bacteria compared to teat ends with a
smooth rough ring form. A similar pattern was found for the teat shape condition and
udder inflammation status. In the teat shape condition, only the TPC showed a
statistically significant difference. The TPC was significantly increased as the teat
shape condition was more dilated, whereas in the normal udder, the counts of
indicator bacteria except for coliforms had significantly lower counts compared to the
udder with inflammation.
In the factor of milk appearance, indicator bacterial counts were not
significantly different between the normal and abnormal milk appearance, except for
TPC. TPC was significantly higher in the abnormal milk appearance than the normal
one.
5.1.2 Qualitative data
Overall prevalence of coliforms, Staphylococcus spp., CPS and CNS from
udder-half milk samples were 46.3, 78.7, 37.7 and 66.0%, respectively and from bulk
milk samples were 86.7, 96.7, 76.7, and 86.7%, respectively.
In the udder-half milk samples, statistically significant difference was
observed only for prevalence of coliforms and CNS among farms, whereas in bulk
milk samples no statistically significant difference was observed among prevalence of
indicator bacteria within farm level.

65
The prevalence of coliforms in these study results, either from udder-half or
bulk milk samples, were higher compared to a study result of coliform prevalence in
unpasteurized goat milk in England and Wales, UK by Little and de Luvois (1999).
They reported that the prevalence of coliforms was 12%. However within the farm
level, farm 1 had a lower prevalence of Coliforms with only 6% in the udder-half milk
samples.
Prevalence of Staphylococcus spp. both from udder-half and bulk milk
samples from this study were higher to the prevalence of these bacteria reported in the
previous reports from other countries by Kalogridou-Vassiliadou (1991); Contreras et
al. (1995); White and Hinckley (1999); Sanchez et al. (1999); Ndegwa et al. (2001);
Leitner et al. (2004); Moroni et al. (2005b) and Leitner et al. (2007), which were 3.1
(Greece), 4.1 (Italy), 38.2 (USA), 70.0 (Spain), 60.3 (Kenya), 32.9 (Israel), 1.6 (Italy)
and 28.8% (Israel), respectively.
However the prevalence of Staphylococcus spp. in the bulk milk samples
found here was comparable to the study results reported by Contreras et al. (1999).
They examined bulk tank milk from commercial dairy goats in Maryland, USA and it
was found that most of the pathogen isolated was Staphylococcus spp. with 95.7% of
prevalence.
As reported by many others studies, this study also recorded CNS as the most
prevalent pathogens within Staphylococcus spp. Staphylococcus spp. is the most
prevalent pathogen responsible for IMI in small ruminants and CNS is the most
prevalent one within this group of bacteria (Contreras et al., 2007). Although less
pathogenic than S. aureus, CNS can also produce persistent subclinical mastitis,
significantly increase MSCC and cause clinical mastitis (Deinhofer and Pernthaner,
1995; Contreras et al., 1997).
Most studies on the IMI estimated the prevalence by halves and not by
animals because the half is an anatomically independent unit (Sanchez et al., 1999).

66
In this study 64.7% (97/150) of goats had infections in both of their udders
(positive bacteriological isolation of Staphylococcus spp.) and it was found also that
the counts and prevalence of indicator bacteria were not observed to have statistically
significant differences between samples from left and right udders (Table 20 and 21).
The results of this study showed that the CNS prevalence was higher
compared to CPS. The CNS and CPS prevalence from udder-half milk samples were
66 and 37.7%, respectively.
Following studies reported to have lower CNS and CPS prevalence of udderhalf
goat milk samples than here: 44.5 and 17.2%, respectively in Greece
(Kalogridou-Vassiliadou, 1991); 61.1 and 18.5%, respectively in Greece (Boscos et
al., 1996), 9.6% in Ethiopia (Wakwoya et al., 2006); 17.9 % in Israel (Leitner et al.,
2007) and 47% in UK (Hall and Rycroft, 2007) (the last three data only for CNS).
Whereas these following studies reported higher CNS prevalence compared to
these study results: 76.1% in Austria (Deinhofer and Pernthaner, 1995); 71.4% in
Spain (Contreras et al., 1997); 68.1% in USA (White and Hinckley, 1999).
Comparable results were found from the study in dairy goat farms in Vermont, USA
which reported 66.7% prevalence of CNS from udder-half milk samples taken in 40
days after parturition (McDougall et al., 2002).
5.1.2.1 The assessment of associations between sample prevalence of indicator
bacteria and potential risk factors
The evaluation of several potential risk factors in its association with the
presence of indicator bacteria in the samples was shown in Tables 10 – 16. All
potential risk factors were analyzed for the prevalence of each indicator bacteria both
by univariate (Chi-square test) and by multivariate analysis of the logistic regression
test. Multivariable analysis permits estimation of the real impact of a particular factor
without interaction from other factors. The results show that some of those potential
risk factors could be considered to be risk factors, which increased the risk of
presence of each indicator bacteria.

67
Breed of goats: these study results show that the breed of goats was only
significantly associated with the presence of coliforms in the samples, and the Saanen
crossbreed had a significantly higher chance of coliform contamination (P

68
evaluation by logistic regression showed that the lactation stage was not a risk factor
for those bacteria (Table 13 and 15). Bergonier et al. (2003) stated that the incidence
of clinical IMI did not vary with the lactation stage in the same way as in dairy cattle,
on the contrary, higher rates were observed during the first third of lactation. This
statement was in agreement with the results presented in Tables 13 and 15. Bergonier
et al. (2003) also stated that the variations of subclinical IMI incidence according to
the stage of lactation should be assessed by systematic, monthly milk culturing of
large numbers of healthy udders, and this kind of a study was very rare. However a
finding reported by Moroni et al. (2005b) was contrary to this study result. They
concluded that later stages of lactation had more infection than earlier lactation stages.
Udder inflammation status: another potential risk factor, which was found to
have a positive association with indicator bacteria, was the udder inflammation status.
The status of udder inflammation was based on a CMT score by following the method
suggested by Wakwoya et al. (2006). Udder inflammation status was found to have a
significant association with the presence of Staphylococcus spp. and CPS. Moreover
results of logistic regression confirmed that the udder inflammation status was a risk
factor for the presence of both bacteria in the milk samples. The udders with
inflammation had a strong and significant association with and higher prevalence of
Staphylococcus spp. [OR= 2.490, P= 0.002, 95%CI= 1.403, 4.418] and CPS [OR=
2.622, P= 0.001, 95%CI= 1.487, 4.623] compared to the udders without
inflammation.
None of the potential risk factors was significantly associated with the
presence of CNS in the samples, but as a member of Staphylococcus spp. and despite
of statistical insignificancy, numerical prevalence of CNS in the udder with
inflammation was higher than in the normal udder (Table 16). Therefore the udder
inflammation status could be used as an indicator of the presence of CNS in the milk
samples.
Other potential risk factors (udder symmetry, udder hygiene status, teat end
condition, teat skin condition, teat shape and milk appearance) were found to have no
statistically significant association with the presence of indicator bacteria in the

69
samples either in univariate or multivariate analysis. Those potential risk factors were
unrelated to indicator bacteria detection rates.
5.1.3 California Mastitis Test results
CMT was conducted on 300 udder-half milk samples for determining the
udder inflammation status as well as for an indicator of the presence of subclinical
mastitis or IMI. Regarding the CMT score, 62.7% (188/300) of the samples were
CMT positive and 37.3% (112/300) of the samples were CMT negative. This result
was different compared to the study result reported by Wakwoya et al. (2006) in
Ethiopia, that showed from 680 udder-half goat milk samples, 278 (40.9%) milk
samples were CMT positive, while 402 (59.1%) samples were CMT negative. On the
other hand, 28 (10.1%) of the 278 CMT positive milk samples yielded no bacterial
growth while the remaining 250 (89.9%) samples were also culture positive in which
diverse bacterial pathogens were identified. They did not present a further proportion
of the bacteria growth in CMT positive-negative samples for each identified bacteria.
In the isolation of indicator bacteria using conventional bacteriological
isolation method, it was found that for coliforms 47.3% (89/188) of CMT positive
samples yielded coliform growth, while the remaining 52.7% (99/188) of CMT
positive samples yielded no coliform growth. On the other hand, 44.6% (50/112) of
the CMT negative samples yielded coliform growth and 55.4% (62/112) of the CMT
negative samples yielded no bacterial growth.
For the Staphylococcus spp., 84.0% (158/188) of CMT positive samples
yielded bacterial growth and the rest [16.0% (30/188) of CMT positive samples]
yielded no bacterial growth. Whereas 69.6% (78/112) of CMT negative samples
yielded bacterial growth and the rest [30.4% (34/112)] yielded no growth.
In CPS, 44.1% (83/188) of CMT positive samples yielded bacterial growth
and the remaining 55.9% (105/188) yielded no bacterial growth. In CMT negative
samples, 26.8% (30/112) yielded bacterial growth and for the rest of the samples
(73.2% (82/112)) yielded no growth of bacteria.

70
For CNS, 69.68% (131/188) of CMT positive samples yielded bacteria growth
and the remaining 30.32% (57/188) of the samples yielded no growth of bacteria. In
CMT negative samples, 59.82% (67/112) yielded bacterial growth, whereas 40.18%
(45/112) of the remaining samples yielded no growth of bacteria.
The study results showed that except in coliforms and CPS, the proportion of
CMT positive samples which yielded bacterial growth was higher compared to CMT
positive samples with no bacterial growth. Wakwoya et al. (2006) explained that the
CMT positive and culture negative samples (those which yielded no bacterial growth)
could be partly explained in that the udder could be injured and was recovering from
infection or the infection could be not due to a bacterial pathogen. It could also be
due to an organism such as mycoplasma, which requires special media and cannot be
detected using routine bacterial isolation techniques.
The proportion of CMT negative samples that yielded bacterial growth in each
indicator bacteria, except for CPS, in this study was relatively higher than a report
from Wakwoya et al. (2006). They found that from a total of 402 milk samples taken
as CMT negative, 124 (30.8%) yielded bacterial growth on cultures. This study result
was also higher compared to the study results in Kenya by Ndegwa et al. (2000), who
reported that 22.5% of 568 CMT negative samples yielded bacterial growth. They
suggested that bacterial organisms isolated from the CMT negative samples were
either a latent cause of infections or did not stimulate any significant increase in
somatic cell counts.
McNemar Chi-square test results showed that statistically significant
differences (P

71
The results were comparable with findings by Ndegwa et al. (2000), who
reported no significant direct relationship between bacterial isolation and CMT in
goat milk from dairy goat farms in Kenya; Winter and Baumgartner (1999) reported
from their study results in Austria regarding the evaluation of CMT reaction in goat
milk, that CMT was not specific for infected udder halves, but can be used as an
additional diagnostic tool concerning goat mastitis without overestimation, due to the
influence of different factors in cell counts.
Another previous report was comparable to the result here, Schaeren and
Maurer (2006) had evaluated the relationship of subclinical udder infection and
individual SCC as well as CMT in three dairy goat herds in Bern, Switzerland. They
concluded that the relation between CMT reactions and udder infections was not very
close. More than 20% of mammary halves infected with CNS showed negative CMT
reactions. On the other hand, 25% of the samples from mammary halves without a
proven infection reacted positively.
However, these study results showed that despite of statistical significance,
numerically the proportion of CMT positive samples which yielded bacterial growth
was higher compared to CMT negative samples which yielded bacterial growth in all
indicator bacteria.
McDougall et al. (2001) stated that definite detection of infected animals relies
on the positive culture of pathogens from aseptically collected milk samples. However
bacteriology has limitations due to the requirements for laboratory support, the time
delays for culture to occur and the costs associated with the bacteriology assessment.
Contreras et al. (1996), Perrin et al. (1997) and McDougall et al. (2001) stated that
CMT is a subjective screening test based on scoring the degree of gel formation of a
milk and bromocresol reagent mixture. The CMT score has been shown to be
positively associated with SCC and with the probability of bacterial infection.
McDougall et al. (2001) also stated that of the “animal side test” CMT was
superior to other indirect test such as impedance. They concluded from their study
that wide variation in the test characteristics of SCC, CMT and impedance were

72
reported in sheep and goat. This was at least partly due to differences in the
prevalence of infection within the population studied. Their study result showed the
effect of changing prevalence on the test performances. Perrin et al. (1997) also
suggested that CMT had to be used carefully for low milk-yield goats or for late
lactations.
Furthermore Gonzalez-Rodriguez and Carmenes (1996) reported their study
results about the accuracy of CMT that was higher when compared with SCC, but an
increase of false-positive samples was observed toward the end of lactation, which
also implied a decrease in the predictive value of positive results. They also concluded
that samples taken in the last month prior to the dry therapy would have a high error
rate in predicting infected glands. They suggested taking the samples in the second
and third months after parturition. Constant CMT positive reactions should be
submitted for bacteriological analysis.
Based on these study results and the above mentioned previous reports, it
could be stated that CMT can be used as an effective, reliable, cheap and “farm and
farmer friendly test” for screen testing of IMI or subclinical mastitis in dairy goats.
5.2 Conclusions
Three hundred udder halves and thirty bulk milk samples from three
commercial dairy goat farms, in the Bogor District, West Java Province, Indonesia
were investigated for counts and prevalence indicator bacteria, which were TPC,
coliforms, Staphylococcus spp., CPS and CNS. Ten potential risk factors were also
evaluated in relation to the counts and prevalence of indicator bacteria.
The median values of the indicator bacterial counts from overall udder-half
milk samples were 3.74, 0.70, 3.00, 1.70 and 2.52 log cfu/ml and from the bulk milk
samples 5.69, 2.98, 3.86, 3.65 and 3.32 log cfu/ml for TPC, coliforms, Staphylococcus
spp., CPS and CNS, respectively.

73
The indicator bacterial counts from udder-half milk samples were significantly
different (P

74
and higher risk of having CPS in the samples, and udders with inflammation, that had
a strong significant association and a higher chance of having contaminated samples
by Staphylococcus spp. or CPS, compared to udders without inflammation.
No statistically significant difference was observed either for counts or
prevalence of indicator bacteria between left and right udder milk samples.
A statistically insignificant difference (P>0.05) between the CMT result and
the bacterial isolation was only observed for CNS, but the agreement between the two
test results was poor (κ = 0.100) and the CMT had moderate sensitivity (66%) and a
relatively low specificity (44%). However, numerically, the proportion of CMT
positive samples that yielded bacterial growth was higher compared to the CMT
negative samples that yielded bacterial growth in all indicator bacteria. It was also
supported by the fact that udder with inflammation, which was determined based on
the CMT result, had been proved to have statistically significant higher results of
Staphylococcus spp. and CPS positive samples than udder without inflammation.
Therefore CMT could be used as an effective, reliable, cheap and “farm and farmer
friendly test” for screen testing of IMI or subclinical mastitis in dairy goats.

REFERENCES
Abou-Eleinin, A.A., Ryser, E.T., Donelly, C.W. (2000): Incidence and seasonal
variation of Listeria species in bulk milk tank goat’s milk. J. Food Prot. 63
(9), 1208-13.
Adams, M.R., Moss, M.O. (2000): Food Microbiology. 2 nd Ed. The Royal Society of
Chemistry. Cambridge.
Ameh, J.A., Tari, I.S. (2000): Observations on the prevalence of caprine mastitis in
relation to predisposing factors in Maiduguri. Small Rumin. Res. 35, 1-5.
Ariznabarreta, A., Gonzalo, C., San Primitivo, F. (2002): Microbiological quality and
somatic cell count of ewe milk with special reference to staphylococci. J.
Dairy Sci. 85, 1370–1375.
Bean, N.H., Goulding, J.S., Lao, C., Angulo, F.J. (1996): Surveillance of foodborne
disease outbreaks-United States, 1988-1992. Morbidity and Mortality Weekly
Rep. 45 (SS-5), 1.
Bergonier, D., De Cremoux, R., Rupp, R., Lagriffoul, G., Berthelot, X. (2003):
Mastitis of dairy small ruminants. Vet. Res. 34, 689-716.
BGBl (Bundesgesetzblatt). (2004): Milchverordnung - Verordnung über Hygieneund
Qualitätsanforderungen an Milch und Erzeugnisse auf Milchbasis.
Neugefasst durch Bek. v. 20. 7.2000 I 1178; zuletzt geändert durch Art. 5 V
v. 9.11.2004 I 2791. Bundesministerium der Justiz, Bundesrepublik
Deutschland.
Boscos, C., Stefanakis, A., Alexopoulos, C., Samartzi, O. (1996): Prevalence of
subclinical mastitis and influence of breed, parity stage of lactation and
mammary bacteriological status on coulter counts and California mastitis test
in milk of Saanen and autochthonous goats. Small Rumin. Res. 21, 139-147.
BSN (Badan Standardisasi Nasional) (1998): Susu Segar. SNI 01-3141-1998. Jakarta.
Chye, F.K., Abdullah, A., Ayob, M.K. (2004): Bacteriological quality and safety of
raw milk in Malaysia. Food Microbiol. 21, 535-541.
Contreras, A., Corrales, J.C., Sierra, D., Marco, J. (1995): Prevalence and aetiology of
nonclinical intramammary infection in Murciano–Granadina goats. Small
Rumin. Res. 17, 71–78.

76
Contreras, A., Sierra, D., Corrales, J.C., Sanchez, A., Marco, J. (1996): Physiological
threshold of somatic cell count and California mastitis test for diagnosis of
caprine subclinical mastitis. Small Rumin. Res. 21, 259-264.
Contreras, A., Corrales, J.C., Sanchez, A., Sierra, D. (1997): Persistence of
subclinical intramammary pathogens in goats throughout lactation. J. Dairy
Sci 80, 2815–2819.
Contreras, A., Paape, M.J., Miller, R.H. (1999): Prevalence of subclinical
intramammary infection caused by Staphylococcus epidermidis in a
commercial dairy goat herd. Small Rumin. Res. 31, 203-208.
Contreras, A., Sierra, D., Sanchez, A., Corrales, J.C., Marcoc, J.C., Paape, M.J.,
Gonzalo, C. (2007): Mastitis in small ruminants. Small Rumin. Res. 68, 145–
153.
Dawson, B., Trapp, R.G. (2004): Basic and Clinical Biostatistics. 4 th ed. Mc Graw
Hill. International Edition.
Deinhofer, M., Pernthaner, A. (1995): Staphylococcus spp. as mastitis-related
pathogens in goat milk. Veterinary Microbiology 43, 161-166.
Delgado-Pertinez, M., Alcalde, M.J.,Guzman-Guerrero, J.L., Castel, J.M., Mena, Y.,
Caravaca, F. (2003): Effect of hygiene-sanitary management on goat milk
quality in semi-extensive systems in Spain. Small Rumin. Res. 47, 51–61.
Devendra, C., Coop, I.E. (1982): Ecology and Distribution. In: I.E. Coop (Editor):
World Animal Science C 1 Production System Approach: Sheep and Goat
Production. Amsterdam: Elsevier. pp. 1-14.
DGLS (Directorate General of Livestock) (2005): Livestock statistics of Indonesia.
DGLS-Ministry of Agriculture, Republic of Indonesia.
EFSA (European Food Safety Authority) (2005): Opinion on the usefulness of
somatic cell counts for safety of milk and milk derived products from goats.
EFSA Journal 305, 1-19.
EC (European Council) (1992): EC Directive 92/46/EEC of 16 June 1992 laying
down the health rules for the production and placing on the market of raw
milk, heat-treated milk and milk-based products. Luxembourg.
FAO (Food and Agricultural Organization) (2002): Medium term projections for meat
and dairy products to 2010. Committee on commodity problems.
Intergovernmental group on meat and dairy products. 19 th session. Rome.
[cited 2006 Aug 31]. Available from: http://www.fao.org/DOCREP/
MEETING /004/Y7022E /y7022e00.htm.

77
FAO (Food and Agricultural Organization) (2006): Major food and agricultural
commodities and producers. Country by commodity. [cited 2006 Aug 25].
Available from: http://www.fao.org/es/ess/top/commodity.html?lang=en&
item=1020&year=2005.
FDA (Food and Drug Administration) (2001): Aerobic Plate Count. Bacteriological
Analytical Manual Online. US FDA CFSAN. [cited 2006 Aug 20].
Available from: http://www.cfsan.fda.gov/~ebam/bam-3.html.
Foschino, R., Invernizzi, A., Barucco, R., Stradiotto, K., (2002): Microbial
composition, including the incidence of pathogens, of goat milk from the
Bergamo region of Italy during a lactation year. J. Dairy Res. 69, 213–225.
Galal, S. (2005): Biodiversity in goats. Small Rumin. Res. 60, 75–81.
Goldberg, J. J., Murdough, P.A., Howard, A.B., Drechsler, P.A., Pankey,J.W.,
Ledbetter, G.A., Day, L.L., Day, J.D. (1994): Winter evaluation of a
postmilking powdered teat dip. J. Dairy Sci. 77: 748-758.
Gonzalez-Rodriguez, M.C., Carmenes, P. (1996): Evaluation of the California
mastitis test as a discriminant method to detect subclinical mastitis in ewes.
Small Rumin. Res. 21, 245-250.
Gonzalo, C., Carriedo, J.A., Beneitez, E., Juarez, M.T., De La Fuente, L.F., San
Primitivo, F. (2006): Short communication: Bulk tank total bacterial count
in dairy sheep: Factor of variation and relationship with somatic cell count.
J. Dairy Sci. 89, 549-552.
Haenlein, G.F.W. (2002): Relationship of somatic cell counts in goat milk to mastitis
and productivity. Small Rumin. Res. 45, 163–178.
Haenlein, G.F.W. (2004): Goat milk in human nutrition. Small Rumin. Res. 51, 155-
163.
Hall, S.M., Rycroft, A.N. (2007): Causative organisms and somatic cell counts in
subclinical intramammary infections in milking goats in the UK. Vet. Rec.
160, 19-22.
Hillerton, J. E., Bramley, A. J., Staker, R. T., McKinnon, C. H. (1995): Patterns of
intramammary infection and clinical mastitis over a 5-year period in a closely
monitored herd applying mastitis control measures. J. Dairy Res. 62, 39–50.
ISO (International Organization for Standardization) 4832 (1991): International
Standard: Microbiology – General guidance for the enumeration of coliforms
– colony count technique. Geneve.

78
ISO (International Organization for Standardization) 6887-1 (1999): International
Standard: Microbiology of food and animal feeding stuffs – Preparation of
test samples, initial suspension and decimal dilutions for microbiological
examination - Part 1: General rules for the preparation of the initial
suspension and decimal dilutions. Geneve.
ISO (International Organization for Standardization) 6888-1 (1999): International
Standard: Microbiology of food and animal feeding stuffs – horizontal
method for the enumeration of coagulase-positive staphylococci
(Staphylococcus aureus and other species). Part 2: Technique using Baird
Parker agar medium. Geneve.
ISO (International Organization for Standardization) 4833 (2003): International
Standard: Microbiology of food and animal feeding stuffs – horizontal
method for the enumeration of microorganisms – colony count technique at
30 o C. Geneve.
Jay, J.M., Loessner, M.J., Golden, D.A. (2005): Modern Food Microbiology. 7 th ed.
New York: Springer.
Jayarao, B.M., Wang, L. (1999): A study on the prevalence of Gram negative
bacteria in bulk milk tank. J. Dairy Sci. 82, 2620-2624.
Kalogridou-Vassiliadou, D. (1991): Mastitis-related pathogens in goat milk. Small
Rumin. Res. 4, 203–212.
Klinger, I., Rosenthal, I. (1997): Public health and the safety of milk and milk
products from sheep and goats. Rev.sci.tech.Off.int Epiz.16 (2), 482-488.
Knights, M., Garcia, G.W. (1997): The status and characteristics of the goat (Capra
hircus) and its potential role as a significant milk producer in the tropics: A
Review. Small Rumin. Res. 26, 203-215.
Kyozaire, J.K., Veary, C.M., Petzer, I.M., Donkin, E.F. (2005): Microbiological
quality of goat’s milk obtained under different production systems. J. S. Afr.
Vet. Assoc. 76 (2), 69-73.
Leitner, G., Merin, U., Silanikove, N. (2004): Changes in milk composition as
affected by subclinical mastitis in goats. J. Dairy Sci. 87, 1719–1726.
Leitner, G., Merin, U., Lavi, Y., Egber, A., Silanikove, N. (2007): Aetiology of
intramammary infection and its effect on milk composition in goat flocks.
Journal of Dairy Research 74, 186–193.
Little, C.L., de Louvois, J. (1999): Health risks associated with unpasteurized goats'
and ewes' milk on retail sale in England and Wales. A PHLS Dairy Products
Working Group Study. Epidemiol. Infect. 122, 403-408.

79
McDougall, S., Murdough, P., Pankey, W., Delaney, C., Barlow, J., Scruton, D.
(2001): Relationship among somatic cell count, California mastitis test,
impedance and bacteriological status of milk in goats and sheep in early
lactation. Small Rumin. Res. 40, 245-254.
McDougall, S., Pankey, W., Delaney, C., Barlow, J., Murdough, P.A., Scruton, D.
(2002): Prevalence and incidence of subclinical mastitis in goats and dairy
ewes in Vermont, USA. Small Rumin. Res. 46, 115–121.
Mein, G. A., Neijenhuis, F., Morgan, W. F., Reinemann, D. J., Hillerton, J. E., Baines,
J. R., Ohnstad, I., Rasmussen, M. D., Timms, L., Britt, J. S., Farnsworth, R.,
Cook, N., Hemling, T. (2001): Evaluation of bovine teat condition in
commercial dairy herds: 1. Non-infectious factors. Pages 347–351 in Proc.
2nd Int. Symp. on Mastitis and Milk Quality, Vancouver, BC, Canada.
Meyrand, A., Montet, M.P., Bavai, C., Ray-Gueniot, S., Mazuy, C., Gaspard, C.E.,
Jaubert, G., Perrin, G., Vernozy-Rozand, C. (1999): Risk linked to an
enterotoxigenic strain of Staphylococcus lentus during the manufacture and
ripening of raw goats’ milk Camembert-type cheeses. Rev. Med. Vet. 150 (8–
9), 703–708.
Morgan, F., Massouras, T., Barbosa, M., Roseiro, L., Ravasco, F., Kandarakis, I.,
Bonnin, V., Fistakoris, M., Anifantakis, E., Jaubert, G., Raynal-Ljutovac, D.
(2003): Characteristics of goat milk collected from small and medium
enterprises in Greece, Portugal and France. Small Rumin. Res. 47, 39–49.
Moroni, P., Pisoni, G., Antonini, M., Ruffo, G., Carli, S., Varisco, G., Boettcher, P. J.
(2005a): Subclinical mastitis and antimicrobial susceptibility of
Staphylococcus caprae and Staphylococcus epidermidis isolated from two
Italian goat herds. J. Dairy Sci. 88, 1694-1704.
Moroni, P., Pisoni, G., Ruffo, G., Boettcher, P.J. (2005b): Risk factors for
intramammary infections and relationship with somatic-cell counts in Italian
dairy goats. Prev. Vet. Med. 69, 163–173.
Muehlherr, J.E., Zweifel, C., Corti, S., Blanco, J.E., Stephan, R. (2003):
Microbiological quality of raw goat’s and ewe’s bulk-tank milk in
Switzerland. J. Dairy Sci. 86, 3849–3856.
Ndegwa, E.N., Mulei, C.M., Mynyua, S.J. (2000): The prevalence of subclinical
mastitis in dairy goats in Kenya. J. S. Afr. Vet. Assoc. 71 (1), 25-27.
Ndegwa, E.N., Mulei, C.M., Mynyua, S.J. (2001): Prevalence of microorganism
associated with udder infections in dairy goats on small-scale farms in Kenya.
J. S. Afr. Vet. Assoc. 72 (2), 97-98.

80
Oliver, S.P., Jayarao, B.M., Almeida, R.A. (2005): Foodborne pathogens, mastitis,
milk quality and dairy food safety. Papers presented at a National Mastitis
Council Annual Meeting. USA.
Peris, S., Caja, G., Such, X. (1999): Relationships between udder and milking traits
in Murciano-Granadina dairy goats. Small Rumin. Res. 33, 171-179.
Perrin, G.G., Mallereau, M.P., Lenfant, D., Baudry, C. (1997): Relationships between
California mastitis test (CMT) and somatic cell counts in dairy goats. Small
Rumin. Res. 26, 167-170.
Petrie, A., Watson, P. (1999): Statistics for Veterinary and Animal Science.
Blackwell Science Ltd. London.
Petrifilm. (2001): Coliform count plates interpretation guide. Microbiology
Products. 3M Health Care Ltd. USA.
Ruegg, P.L. (2002): Managing the dry period for milk quality. University of
Wisconsin, Madison. USA.
Ruegg, P.L. (2003): Practical food safety interventions for dairy production. J. Dairy
Sci. 86 (E. Suppl.), E1-E9.
Sanchez, A., Contreras, A., Corrales, J.C. (1999): Parity as a risk factor for caprine
subclinical intramammary infection. Small Rumin. Res. 31, 197-201.
Schaeren W, Maurer J. (2006): Prevalence of subclinical udder infections and
individual somatic cell counts in three dairy goat herds during a full lactation.
[Article in German]. Schweiz Arch Tierheilkd. 148 (12), 641-648.
Sevi, A., Albenzio, M., Marino, R., Santillo, A., Muscio, A. (2004): Effects of
lambing season and stage of lactation on ewe milk quality. Small Rumin. Res.
51, 251–259.
Shearer, J.K., Harris Jr., B. (2003): Mastitis in dairy goats. IFAS Extension.
University of Florida. USA.
Valle, J., Gomez-Lucia, E., Piriz, S., Goyache, J., Orden, J.A., Vadillo, S. (1990):
Enterotoxin production by staphylococci isolated from healthy goats. Appl.
Environ. Microbiol. 56, 1323-1326.
Wakwoya, A., Molla, B., Belihu, K., Kleer, J., Hildebrandt, G. (2006): A cross
sectional study on the prevalence, antimicrobial susceptibility patterns and
associated bacterial pathogens of goat mastitis. Intern. J. Appl. Res. Vet.
Med. 4 (2), 169-176.

81
White, E.C., Hinckley, L.S. (1999): Prevalence of mastitis pathogens in goat milk.
Small Rumin. Res. 33, 117-121.
Winter, P., Baumgartner, W. (1999): Evaluation of the California mastitis test
reaction in goat milk and its interpretation. [Article in German]. Dtsch.
Tierarztl. Wochenschr. 106 (1), 30-4.
Zeng, S.S., Escobar, E.N. (1995): Effect of parity and milk production on somatic cell
count, standard plate count and composition of goat milk. Small Rumin. Res.
17, 269–274.
Zeng, S.S., Escobar, E.N. (1996): Effect of breed and milking method on somatic cell
count, standard plate count and composition of goat milk. Small Rumin. Res.
19, 169–175.
Zweifel, C., Muehlherr, J.E., Ring, M., Stephan, R. (2005): Influence of different
factors in milk production on standard plate count of raw small ruminant’s
bulk-tank milk in Switzerland. Small Rumin. Res. 58, 63-70.

APPENDIX
Appendix A:
A. GENERAL INFORMATION
1. Farm owner
QUESTIONNAIRE
(Principal investigator: Epi Taufik)
Name:
2. a. Address
Street
Telephone/MP
Village
Sub district
FARM ID
b. Farm characteristics
Location in the residence
area
No. of animals
No. of workers
3. Educational level
1. None
2. Elementary school
3. Secondary school
4. University
Male
Age
Female
Age
B. GENERAL FARM CONDITION AND MANAGEMENT PRACTICES
4. Herd size
1 200 heads

83
5. Animal housing
1 Elevated
2 On the ground
6. Type of house
1 Pen
2 Loose housing barn
7. Ventilation
1 Good
2 Poor
8. House for lactating goats
1 Yes
2 No
9. House surface material
1 Bamboo
2 Wood
10. Surface condition
1 Good
2 Poor
11. General hygiene status of the farm
1 Good
2 Poor
12. Special worker for milking?
1 Yes
2 No
13. Hygiene status of workers?
1 Good
2 Poor

84
14. Source of water?
1 Tap
2 Well
15. Water storage?
1 Closed
2 Open
16. Is water chlorinated?
1 Yes
2 No
17. Stocking density?
1 Low
2 Medium
3 High
18. Presence of other animal species in the farm?
1 Yes
2 No
C. MILKING PRACTICES
20. How do you milk the goat?
1 Machine milking
2 Hand milking
21. Is there a special place for milking the animal?
1 Yes
2 No
22. How many times is the goat milked?
1 Once a day
2 Twice a day

85
23. Is pre-milking washing done?
1 Yes
2 No
24. Is pre-milking drying done?
1 Yes
2 No
25. Is pre-dipping done?
1 Yes
2 No
26. Is fore-stripping done?
1 Yes
2 No
27. Is post-dipping done?
1 Yes
2 No
D. GOAT CONDITION
28. Breed of goat?
1
2
3
29. Animal parity?
1 Primiparous
2 Multiparous
If multiparous in
which parity?
30. Animal lactation stage?
1 First
2 Second
3 Third

86
31. Udder halves symmetric?
1 Yes
2 No
32. Teat end condition scoring*
1 No ring
2 Slightly or smooth
rough ring
33. Teat skin condition scoring**
Score
0
1
2
3
4
5
34. Teat shape?***
1 Normal
2 Dilated
3 Generally dilated
35. Udder hygiene scoring****
Score
0
1
2
3
4
36. Udder inflammation? (from CMT result)*****
1 Normal
2 Inflammation
37. Appearance of milk?
1 Normal
2 Abnormal

87
38. If no. 37 is abnormal, please check below!
1 Discoloration
2 Clotting
3 Watery
4 Blood
5 Off odor
Remarks regarding the above-mentioned scoring are as follows:

88
(*) Teat end scoring
Since no rough ring and very rough ring teat ends were found, the scoring was made
only for no ring and smooth or slightly rough ring (Mein et al., 2001)

89
(**) Subjective Teat Skin and Teat End Evaluation System, University of Vermont,
USA (cited from: Goldberg et al., 1994)
TEAT SKIN CONDITION SCORING
0 = Teat skin has been subjected to physical injury (e.g. stepped on or frostbitten) not
related to the treatment, or the quarter is nonlactating.
1 = Teat skin is smooth and free from scales. cracks, or chapping.
2 = Teat skin shows some evidence of scaling
3 = Teat skin is chapped. Some small warts may be present.
4 = Teat skin is chapped and cracked, Redness, indicating inflammation, is present.
Numerous warts may be present.
5 = Teat skin is severely damaged and ulcerative with scabs or open lesions. Large or
numerous warts are present that interfere with teat end function
- Since no score of 0, 3, 4 and 5 were found, the scoring was only for 1 and 2
(***) Example for teat shape scoring
Normal
Dilated
Generally dilated

90
(****) udder hygiene scoring was adopted from scoring for cow’s udder
(Ruegg, 2002)
- No scores of 3 and 4 were found, so the scores were only for 1 and 2
(*****) CMT result:
- 0 or Trace = Normal (negative)
- +1, +2, +3 = Inflammation (positive)
(Wakwoya et al., 2006)
Example of +3 CMT reaction of milk
sample (gel like form) indicated that the
udder had inflammation

91
Appendix B: Lists of materials and equipments
1 . Equipment and materials
- Eppendorf tubes
- Autoclave
- Balance with a 2000 g-weights capacity and a sensitivity of 0.1 g
- Bunsen burner
- Culture tubes, 16*150 and 20*150 m
- Incubator
- Ose/loop
- Laboratory refrigerator, - 20 o C and -1 to 4 o C
- Sterile Petri dishes, 15*100 mm
- Sterile Hockey stick
- Petrifilm plates for Coliform isolation (3M Petrifilm, USA)
- Sterile pipettes
- Micropipette
- Micropipette tip
- Sterile culture tubes
- Test or culture tube racks
- Vortex mixer
- Ice box, 24 liters
- Beakers, and containers
- Sterile 500, 1000 and 2000 ml Erlenmeyer flasks, sterile 250 and 500 ml
- Sterile Schott Duran bottles 50, 250 ml
- Marker pen
2 . Media, reagents and chemicals
- Maximum Recovery Diluent (MRD) (Merck, Germany)
- Brain Heart Infusion Broth (BHI) (Merck, Germany)
- Plate Count Agar (PCA) (Merck, Germany)
- Baird Parker Agar (BPA) (Merck, Germany)

92
- Sterile aquadestila (Faculty of Veterinary Medicine, Bogor Agricultural University)
- Egg yolk tellurite (Faculty of Veterinary Medicine, Bogor Agricultural University)
- Rabbit plasma (Faculty of Veterinary Medicine, Bogor Agricultural University)
- CMT reagents (Faculty of Veterinary Medicine, Chiang Mai University)
- Alcohol/Ethanol 95% (PT Kimia Farma, Indonesia)
Appendix C: Calculation of total aerobic mesophilic bacteria/total plate count and
Staphylococcus spp. (coagulase positive and negative)
1. Calculation of total aerobic mesophilic bacteria/total plate count
1.1 General case (for the dishes containing 15 – 300 colonies)
N =
∑ C
[(n1) + (n2 + 0.1)] x (d)
N
∑ C
n1
n2
d
= Number of colonies per ml of product
= Sum of all colonies on all plates counted
= Number of plates selected at the first dilution
= Number of plates selected at the second dilution
= Dilution rate corresponding to the first dilution selected
1.2. Estimation of low numbers
1.2.1 If the two dishes contained less than 15 colonies, the formula was simplified
and only the arithmetical mean was used for calculation
N = y/d
y
d
= Arithmetical mean of the colonies counted on two dishes
= The dilution factor of the initial suspension

93
1.2.2 If the two dishes did not contain any colonies, the results are to be expressed as
follows:
- Less than 1/d per ml, where d is the dilution factor of the initial suspension
2. Calculation of Staphylococcus spp. (coagulase positive and negative)
2.1 Calculation of the number a of either coagulase positive or negative staphylococci
identified for each plate selected
a = (b c /A c x c c ) + (b nc /A nc x c nc )
A c
A nc
b c
b nc
c c
c nc
= Number of typical colonies submitted to the coagulase test
= Number of atypical colonies submitted to the coagulase test
= Number of typical colonies which have been shown to be coagulase
positive/negative
= Number of atypical colonies which have been shown to be coagulase
positive/negative
= Total number of typical colonies seen on the plate
= Total number of atypical colonies seen on the plate
2.2 Calculation of the number N of identified coagulase positive or negative staphylococci
in the test portion
N =
∑ a
V x [(n1) + (n2 + 0.1)] x (d)
N
∑ a
= Number of colonies per ml of product
= Sum of the coagulase positive or negative staphylococcal colonies
identified on all the dishes selected

94
V = Volume of inoculum on each dish, in mililitres (in this study 0.1 ml =
spreading method)
n1 = Number of plates selected at the first dilution
n2 = Number of plates selected at the second dilution
d = Dilution rate corresponding to the first dilution selected
2.3 Estimation of low numbers
2.3.1 If the two dishes, corresponding to the test sample or the initial suspension each
contain less than 15 identified colonies, the calculation is as follows:
N =
∑ a
V x 2 x d
∑ a = Sum of the coagulase positive or negative staphylococcal colonies
identified on all the dishes selected
V = Volume of inoculum on each dish, in mililitres (in this study 0.1 ml =
spreading method)
d = Dilution rate corresponding to the first dilution selected
2.3.2 If the two dishes, corresponding to the test sample or the initial suspension do
not contain any colonies, the results are to be expressed as follows:
- Less than 10/d per ml, where d is the dilution factor of the initial suspension

96
CURRICULUM VITAE
Name : Epi Taufik
Place/date of birth : Ciamis, Indonesia December 2 1975
Sex : Male
Religion : Islam
Marital Status/children : Married/one daughter
Present status : Lecturer/academic staff of lab. of animal product
technology, Faculty of Animal Science, Bogor
Agricultural University (IPB) Indonesia.
http://www.ipb.ac.id
Home Address : Perumahan IPB Alamsinarsari Jl. Dahlia D64
Darmaga, Bogor, Indonesia Post code 16680
email: etaufik@yahoo.com
Office Address : Laboratory of Animal Product Technology,
Department of Animal Science and Technology,
Faculty of Animal Science, Bogor Agricultural
University. Jl. Agatis Kampus IPB Darmaga,
Bogor, West Java, INDONESIA 16680. Phone and
Fax. 62-251-629104
email: fapetipb@indo.net.id
EDUCATION:
Level of
Education
University
(undergraduate)
School Name
Study Program Animal
Product Technology,
Department of Animal
Production, Faculty of
Animal Science, Bogor
Agricultural University,
Indonesia
Year
Diploma and date
of issued
1994 - 1999 Diploma No.
1006990025
Graduate Status:
With Honor
February 27 1999

97
Master degree
Study Program of
Veterinary Public Health,
Graduate School of Bogor
Agricultural University,
Indonesia
2004 - present - (postponed, will be
continued January
2008 for final thesis
research)
TRAININGS: (Last 5 years)
No. Training Organizer Year
1. Research Proposal Making IPB in cooperation with
Directorate General of Higher
Education
2. Community Empowerment
Program
3. National Training on
Microbiology in Animal
Science and Veterinary Public
Health
INDONESIA
IPB in cooperation with
Directorate General of Higher
Education
INDONESIA
Ministry of National
Education in cooperation
with Department of
Veterinary Public Health,
Faculty of Veterinary
Medicine IPB
INDONESIA
2004
2004
2004

98
PROFESSIONAL ORGANIZATIONS:
1. INDONESIAN SOCIETY FOR MICROBIOLOGY/PERHIMPUNAN
MIKROBIOLOGI INDONESIA / PERMI Member Registration No. 002 – BGR
298
RESEARCH EXPERIENCES:
1. Physical, chemical and microbiological characteristics of dadih (Indonesian
traditional fermented milk food) made from cow’s milk fermented with different
starter probiotic bacteria combinations stored at different temperatures. 2003
2. Antimicrobial activity of dadih (Indonesian traditional fermented milk food) made
from cow’s milk fermented with different starter probiotic bacteria combinations.
2004
3. Antimicrobial activity of different fermented goat milk products from different
breeds of goats. 2005
4. Microbiological Investigation of Raw Goat Milk from Commercial Dairy Goat
Farms, in Bogor Indonesia. 2006-2007.
5. Survival of Pathogenic Bacteria in Yoghurt and Kefir during Fermentation and
Cold Storage. 2007
RESEARCH GRANTS:
1. Young Academic Staff Research Grant from Bogor Agricultural University
(IPB), 2003
2. Young Academic Staff Research Grant Bogor Agricultural University (IPB),
2004
3. Research Grant under A2 Competition Grant Program, Directorate General of
Higher Education, Ministry of National Education, Indonesia, 2005
4. Research Grant under A2 Competition Grant Program, Directorate General of
Higher Education, Ministry of National Education, Indonesia, 2007
PROFESSIONAL EXPERIENCES:
1. Internship at PT Sierad Produce, Poultry Processing Plant, 1998

99
2. Assistant specialist in the agricultural sector for project benefit evaluation of
projects funded by the JAPAN BANK FOR INTERNATIONAL
COOPERATION (JBIC) Loan INP 22 dan 23, 2002-2003
SCIENTIFIC PUBLICATIONS:
1. Production Technology and Product Quality Control at PT Sierad Produce Tbk.
Poultry Processing Plant, Parung, Bogor. Internship report 1998
2. Shelf life of duck carcasses chlorinated with different concentration levels. Jurnal
Peternakan dan Lingkungan, Vol. 08. No. 2 (Juni 2002) ISSN: 0852-4092
(Indonesia National Scientific Journal)
3. Quality of dadih (Indonesian traditional fermented milk food) fermented with
probiotic starter bacteria and stored at low temperature: I. chemical characteristic.
Media Peternakan. Vol. 27 No. 3: 88-100, December 2004 (Indonesia National
Scientific Journal)
4. Quality of dadih (Indonesian traditional fermented milk food) fermented with
probiotic starter bacteria and stored at low temperature: II. physical,
organoleptical and microbiological characteristics. Media Peternakan. Volume 28
No. 1 : 13- 20 April 2005 (Indonesia National Scientific Journal)
5. Physical, Chemical and Microbiological Characteristics of Dadih (Indonesian
Traditional Fermented Milk Food) Made from Cow’s Milk Fermented with
Different Starter Probiotic Bacteria Combination and Stored at Different
Temperatures. Research Report, Research Institute of IPB, 2003
6. Antimicrobial Activity of Dadih Fermented with Probiotic Starter Bacteria.
Research Report, Research Institute of IPB, 2004
SCHOLARSHIP AWARDS
1. McDonald Indonesia Family Restaurant Co. Ltd. for Undergraduate Study, 1994 –
1999
2. Scholarship for Postgraduate Study, Ministry of National Education of
The Republic of Indonesia, 2004 – 2006 (for Master study at Bogor Agricultural
University)

100
3. Deutscher Akademischer Austauschdienst (DAAD)/German Academic Exchange
Service for Postgraduate Study in Master of Veterinary Public Health in the Joint
Master Program between the Freie Universitaet Berlin, Germany and Chiang Mai
University, Thailand, 2005 - 2007