University of Ghana http://ugspace.ug.edu.gh 
 
UNIVERSITY OF GHANA 
COLLEGE OF BASIC AND APPLIED SCIENCES 
SCHOOL OF BIOLOGICAL SCIENCES 
 
MICROBIAL DIVERSITY OF ECONOMICALLY IMPORTANT UNPROCESSED 
FRESHWATER FISHES SOLD AT THE MEDINA COURA MARKET IN BAMAKO, 
MALI 
BY: 
AMINATA SISSOKO 
ID: 10591044 
 
A THESIS SUBMITTED TO THE SCHOOL OF GRADUATE STUDIES IN PARTIAL 
FULFILMENT OF THE AWARD OF DEGREE OF DOCTOR OF PHILOSOPHY IN 
FOOD SCIENCE 
DEPARTMENT OF NUTRITION AND FOOD SCIENCE 
OCTOBER 2020 
 
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DECLARATION 
This work was conducted by Aminata Sissoko at the Central Veterinary Laboratory in Bamako 
Mali, and the Department of Nutrition and Food Science, the University of Ghana under the 
supervision of Prof. Kwaku Tano-Debrah, Dr Angela Parry-Hanson Kunadu and Dr Fassé Samaké.  
 
        18th February 2021 
AMINATA SISSOKO       DATE  
(STUDENT)  
     17th February 2021 
PROF KWAKU TANO-DEBRAH     DATE  
(SUPERVISOR)  
 
 
   17th February 2021 
 
DR. ANGELA PARRY-HANSON KUNADU   DATE  
(CO-SUPERVISOR)  
       17th February 2021 
DR. FASSE SAMAKE      DATE  
(CO-SUPERVISOR) 
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ABSTRACT 
Around the world, millions of people depend on fish for its high protein content, supply of 
micronutrients and added health benefits. Fish is extremely perishable; its quality changes very 
quickly after capture unless it is kept cold. Failure to comply with good preservation practices 
favors the risk of deterioration in market quality and safety, which may lead to foodborne illness. 
The purpose of this study was to determine the microbial diversity of fresh water fish and evaluate 
the food safety knowledge and practices of stakeholders of freshwater fish along selected fish value 
chains in Mali. A structured face-to-face questionnaire on food safety knowledge and practices 
was designed and administered to 247 respondents comprising 130 fish sellers and 117 fishermen 
between November 2018 and February 2019. Samples of three fresh water fish species (Lates 
niloticus, Clarias anguillaris and Oreochromis niloticus) were taken during cold and hot seasons 
in four fish production areas and at specific points (capture, landing and selling points) in the 
selected value chains (Niger Central Delta in Mopti, Selingue, Manantali, Markala) and from the 
Central fish market (Medina Coura market) using standard protocols for microbial analysis. Water 
samples at capture areas and swabs of fish containers at each of the landing points were also 
collected for analysis. The following assessments were carried out: enumeration for Aerobic Plate 
Count (APCs), Total Coliform counts (TCs), Fecal Coliform counts (FCs), and Spores of Sulphite 
Reducing Bacteria (SRB), Staphylococcus aureus and prevalence of Salmonella spp. were also 
determined. Bacterial isolates were identified using biochemical tests (catalase oxidase, API 20E 
and 20NE). Parasitic infestations of 120 specimens of three freshwater fish species, comprising 
Lates niloticus (44), Clarias anguillaris (40) and Oreochromis niloticus (36) sold at the Medina 
Coura market in Mali, were also investigated. The results of the questionnaire survey indicated 
that respondents had a good level of food safety knowledge but poor food hygiene practices. Most 
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of the respondents had received no formal education in food safety. It is, therefore, important to 
put in place a good public health management strategy for food sales services, which will give 
stakeholders in the fish value chain the knowledge and skills necessary to provide hygienic and 
safe sales services. Microbial growth was observed in all of the fish species tested. APC ranged 
from 5.08 to 7.64 Log10 CFU.g-1, TC ranged from 4.11 to 7.62 Log10 CFU.g-1, FC ranged from 
3.64 to 7.5 Log10 CFU.g-1 and all had 100% higher counts than the national standard. About 12.7% 
(17/134) of the samples recorded Sulphite Reducing Bacteria, 20.1% (27/134) had Staphylococcus 
aureus, and 93.3 % (125/134) Salmonella spp.. Three species of parasites were detected, namely, 
Salmincola edwardsii (crustacea) at the gills, and Philonema sp. and Raphidascaris sp. 
(nematodes) in the abdominal cavity. An overall prevalence of 10% (12/120) parasitic infestation 
was observed. The study showed that prevalence of parasitic infestation during the cold season 
was 5.2% and the hot season was 14.5%. The highest prevalence of infestation was observed in 
Oreochromis niloticus (16.7%) followed by Lates niloticus (9.1%) and Clarias anguillaris (5.0%). 
A total of 360 isolates (188 in the cold season and 172 in the hot season) were characterized and 
identified as 24 species of bacteria belonging to 15 families. This study is an important contribution 
to the knowledge of the bacterial and parasitological flora of fish along the value chain sold on the 
Medina Coura Market, and contributes, to my knowledge as the first attempt to evaluate the 
microbiological quality of these freshwater fish along the fish value chains. 
  
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DEDICATION 
This work is dedicated to my wonderful late father, Mamadou SISSOKO, for giving me an 
excellent childhood, for always believing in me, and most importantly for teaching me to know 
God, without whom I am nothing.  
May God grant you to Al Jannah. 
  
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ACKNOWLEDGEMENTS 
I would like to express my warmest gratitude and appreciation to the persons below who made this 
research possible and this milestone in my life a reality. My supervisor, Prof. Kwaku Tano-Debrah 
for allowing me to always express myself and for all your guidance and support throughout my 
research period. My co-supervisor, Dr Angela Parry- Hanson Kunadu for inspiring me to believe 
that I could be more and that I could achieve more than I could ever imagine. My co-supervisor, 
Dr Fassé Samaké for his helpful support and guidance during this research. 
Prof. F. K. Saalia for always having the right words to lift me in my lowest moments. Central 
Veterinary Laboratory of Bamako, Food Bacteriology Laboratory and Parasitology Laboratory, 
for allowing me access to their facilities and resources on short notice. Fisheries and Aquaculture 
Department and their Director, Dr Sarro and Dr Bakary Sagara for your technical support, words of 
encouragement, this would not have been possible without your cooperation and support. 
My wonderful Mummy Salimata Faye for her endless encouragement, motivation, support and 
blessings the period of this research, God bless you, Mum. To my sons, Youssouf and Mamadou 
Thiam, I say thank you for believing in me. I love you. 
Finally, I wish to thank BHEARD for providing the funds needed to carry out this research.  
  
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TABLE OF CONTENT 
DECLARATION ............................................................................................................................. i 
ABSTRACT .................................................................................................................................... ii 
DEDICATION ............................................................................................................................... iv 
ACKNOWLEDGEMENTS ............................................................................................................ v 
TABLE OF CONTENT ................................................................................................................. vi 
LIST OF TABLES ........................................................................................................................ xii 
LIST OF FIGURES ..................................................................................................................... xiii 
LIST OF ABBREVIATIONS ...................................................................................................... xiv 
CHAPTER ONE ........................................................................................................................... 16 
1 .0 INTRODUCTION ................................................................................................................. 16 
1.1 Background ......................................................................................................................... 16 
1.2 General objective................................................................................................................. 20 
1.3 Specific objectives............................................................................................................... 20 
CHAPTER TWO .......................................................................................................................... 21 
2 .0 LITERATURE REVIEW ...................................................................................................... 21 
2.1.1 Central Delta of Niger River ........................................................................................ 21 
2.1.2 Selingue Lake ............................................................................................................... 22 
2.1.3 Manantali Lake ............................................................................................................. 22 
2.1.4 Markala Lake ................................................................................................................ 22 
2.2 Fish production in Mali ....................................................................................................... 23 
2.3 The major categories of fishermen in Mali ......................................................................... 25 
2.4 Medina Coura fish market in Bamako ................................................................................ 25 
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2.5 Fisheries value chain in Mali: market organization ............................................................ 26 
2.6 . Artisanal fishing in Mali ................................................................................................... 27 
2.7 Different species of freshwater fish in Mali ........................................................................ 29 
2.8 Nutritional value of fresh fish ............................................................................................. 29 
2.9 Consumption of freshwater fish in Mali ............................................................................. 30 
2.10 Gender distribution in fishing communities in Mali ......................................................... 31 
2.11 Fish in food security .......................................................................................................... 32 
2.12 Post-harvest fish losses...................................................................................................... 32 
2.12.1 Physical losses ............................................................................................................ 33 
2.12.2 Economic losses ......................................................................................................... 33 
2.12.3 Nutritional losses ........................................................................................................ 33 
2.13 Fish Spoilage ..................................................................................................................... 33 
2.14 Microorganisms involved in fish spoilage ........................................................................ 35 
2.15 Microbial pathogens in fish ............................................................................................... 38 
2.16 Parasites ............................................................................................................................. 39 
CHAPTER THREE ...................................................................................................................... 40 
3 .0 METHODOLOGY ................................................................................................................ 40 
3.1 Study design ........................................................................................................................ 40 
3.2 The study areas .................................................................................................................... 40 
3.3 Ethical clearance ................................................................................................................. 41 
3.4 Survey on the knowledge and practices of Stakeholders of the freshwater fish value chains 
to the Medina Coura market ...................................................................................................... 42 
3.5 Physico-chemical and microbiological analysis of samples ............................................... 43 
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3.5.1 Samples and Sampling methods ................................................................................... 43 
3.5.1.1 Water sample at the capture point ................................................................... 43 
3.5.1.2 Swab sample from the storage container at the landing point ......................... 43 
3.5.1.3 Fish sample from fishermen at the capture point: ........................................... 43 
3.5.1.4 Fish sample from wholesalers at the Landing point ........................................ 44 
3.5.1.5 Fish sample from wholesalers at the selling point ........................................... 44 
3.5.2 Analysis of samples ...................................................................................................... 44 
3.5.2.1 Physico-chemical analysis of water samples ................................................... 44 
3.5.2.2 Microbiological analysis of samples ............................................................... 44 
3.5.2.2.1 Sample of fish for analysis ................................................................................. 44 
3.5.2.2.2 Analytical methods ............................................................................................ 49 
3.5.3 Sample preparation ....................................................................................................... 49 
3.5.2 Enumeration of microflora ........................................................................................... 50 
3.5.2.1 Enumeration of the Aerobic mesophilic (Aerobic Plate Counts) ......................... 50 
3.5.2.2 Enumeration of Total Coliforms ........................................................................... 51 
3.5.2.3 Enumeration of fecal or thermo-tolerant coliforms .............................................. 51 
3.5.2.4 Enumeration Sulphite Reducing Bacteria ............................................................. 51 
3.5.2.5 Enumeration of Staphylococcus aureus ................................................................ 52 
3.5.2.6 Detection of Salmonella spp. ................................................................................ 52 
3.5.2.7 Detection of Pseudomonas spp. ............................................................................ 53 
3.5.2.8 Detection of other pathogenic bacteria ................................................................. 53 
3.5.3 Isolation, characterization and identification................................................................ 54 
3.5.4 Parasitic analysis .......................................................................................................... 57 
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3.6 Statistical analysis ............................................................................................................... 57 
CHAPTER FOUR ......................................................................................................................... 59 
4 .0RESULTS AND DISCUSSION ............................................................................................. 59 
4.1 Survey on food safety knowledge and practices of freshwater fish value chain stakeholders
 ................................................................................................................................................... 59 
4.1.1 Demographic characteristics of stakeholders along the fish value chains ................... 59 
4.1.2 Business characteristics ................................................................................................ 61 
4.1.3 Food Safety Knowledge ............................................................................................... 65 
4.1.4 Food Safety practices.................................................................................................... 67 
4.1.5 Relationship among age, education, and fish safety knowledge and practice of the fish 
sellers ..................................................................................................................................... 68 
4.1.6 Relationship among age, duration of service, and food safety knowledge and practice of 
the fishermen ......................................................................................................................... 69 
4.2 Physico-chemical analysis of water and fish in the freshwater fish value chain ................ 70 
4.2.1 Determination of pH of water, and pH of fish species ................................................. 70 
4.3 Microbiological quality of water and fish in the freshwater fish value chain ..................... 72 
4.3.1 Microbial quality of fish containers at landing ............................................................. 74 
4.3.2 Microbial quality of fish samples along the fresh fish value chain .............................. 76 
4.3.3 Prevalence of Salmonella spp. in the various samples ................................................. 84 
4.4 Parasites in Freshwater Fish along the Value Chain of Medina Coura Market .................. 85 
4.4.1 Prevalence of infested fish species ............................................................................... 85 
4.4.2 Variation of parasites per infected organs of the fish and areas of sampling ............... 86 
4.4.3 Seasonal variation of fish parasites per sampling areas ............................................... 88 
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4.4.4 Prevalence of infected fish species at each sampling points ........................................ 88 
4.5 Identification of the spoilage microorganisms associated with fish using phenotypical 
methods ..................................................................................................................................... 89 
4.5.1 Isolation of spoilage microorganisms on fish samples at the various sampling points 89 
4.5.2 Biochemical tests .......................................................................................................... 89 
4.6 Phenotypic identification of pathogenic microorganisms associated with fish .................. 93 
4.6.1 Biochemical test ........................................................................................................... 93 
4.6.2 Isolation of pathogenic microorganisms on fish samples at the various sampling points
 ............................................................................................................................................... 95 
CHAPTER FIVE .......................................................................................................................... 97 
5 .0 CONCLUSION AND RECOMMENDATION ..................................................................... 97 
5.1 Conclusion ........................................................................................................................... 97 
5.2 Recommendations ............................................................................................................... 98 
REFERENCES ........................................................................................................................... 100 
APPENDICES ............................................................................................................................ 113 
Appendix 1A: Fish sellers questionnaire at Medina Coura Market ........................................ 113 
Appendix 1B: Fishermen questionnaire at the four capture point .......................................... 118 
Appendix 2: Chemical composition of the culture media used .............................................. 122 
Appendix 3: Gram Staining..................................................................................................... 125 
Appendix 4: Microbial mean Log10 CFU g_ 1prevalence of Salmonella and pH of fish in 
sampling point in Selingue ...................................................................................................... 126 
Appendix 5: Microbial count, prevalence of Salmonella and pH of fish in sampling point in 
Manantali ................................................................................................................................. 127 
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Appendix 6: Microbial count, Prevalence of Salmonella and pH of fish in sampling point in 
Markala.................................................................................................................................... 127 
Appendix 7: Microbial count, Prevalence of Salmonella and pH of fish in sampling point in 
Mopti ....................................................................................................................................... 128 
Appendix 8: Macroscopy observation for the spoilage microorganisms ................................ 129 
Appendix 9: Microscopy observation and biochemical test for the spoilage microorganisms130 
Appendix 10: Macroscopy observation for the pathogenic microorganisms .......................... 131 
Appendix 11: Microscopy observation and biochemical test for the pathogenic microorganisms
 ................................................................................................................................................. 132 
Appendix 12: API 20NE reading ............................................................................................ 133 
Appendix 13: API 20E reading ............................................................................................... 133 
 
  
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LIST OF TABLES 
Table 1:Nutritional values of some fish species (Dansoko, 2012) ............................................... 30 
Table 2: Demographic characteristics of the study population ..................................................... 61 
Table 3: Frequency of fishing businesses doing by the fish sellers .............................................. 63 
Table 4:Business activities of fishermen in selected fishing areas ............................................... 65 
Table 5: Responses to questions on food safety knowledge by fish sellers .................................. 66 
Table 6:Responses to questions on food safety knowledge by fishermen .................................... 67 
Table 7: Responses to questions on food safety practices by fish sellers ..................................... 67 
Table 8: Responses to questions on food safety practices by a fishermen ................................... 68 
Table 9: Bivariate correlation of age and education with food safety knowledge and food safety 
practice using Spearman’s rho coefficient .................................................................................... 69 
Table 10: Bivariate correlation among age, education and food safety practice and knowledge 
using Spearman’s rho coefficient.................................................................................................. 70 
Table 11: Prevalence of parasites by fish species ......................................................................... 86 
Table 12: Prevalence of parasites per infected organs and areas .................................................. 87 
Table 13: Prevalence of fish infested with parasites per location and season .............................. 88 
Table 14: Prevalence of infected fish species at each sampling point .......................................... 89 
 
 
  
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LIST OF FIGURES 
Figure 2.5.1: Fisheries value chain in Mali (Traore, 2014) .......................................................... 27 
Figure 3.2.1: Map of Mali showing the landing beaches where the study was carried out .......... 41 
Figure 3.5.1: Lates niloticus ......................................................................................................... 45 
Figure 3.5.2: Oreochromis niloticus ............................................................................................. 45 
Figure 3.5.3: Clarias anguillaris .................................................................................................. 46 
Figure 3.5.4: Map showing the different sampling points ............................................................ 46 
Figure 3.5.5: Samples in the cooler with ice for laboratory analysis ............................................ 48 
Figure 4.2.1:Mean value of water pH during the 2 seasons.......................................................... 72 
Figure 4.3.1: Microbial count Log10 CFU/ ml in the water at the capture point ......................... 74 
Figure 4.3.2: Microbial counts in fish containers at various landing points. ................................ 75 
Figure 4.3.3: Fish stored in a broken-down fridge........................................................................ 77 
Figure 4.3.4: Microbial mean Log10 CFU/ g of fish in various sampling point in Selingue ....... 78 
Figure 4.3.5: Microbial mean Log10 CFU / g of fish in in various sampling point in Manantali 79 
Figure 4.3.6: Microbial count Log10 CFU / g of fish in in various sampling point in Markala .. 80 
Figure 4.3.7: Microbial count Log10 CFU / g of fish in various sampling point in Mopti. ......... 81 
Figure4.5.1:The frequency of the different families of spoilage microorganisms during the cold 
and hot seasons ............................................................................................................................. 92 
Figure 4.6.1: Percentage distribution of the different families of pathogenic microorganisms in fish 
during from the cold and hot seasons ........................................................................................... 95 
 
  
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LIST OF ABBREVIATIONS 
Abs/25g Absence in 25 grams 
AFNOR Association Française de Normalisation 
ANOVA Analysis of Variance 
API Analytical Profile Index  
BPW Buffered Peptone Water  
CFA Communauté Financière Africaine 
CFU/g Colony Formant Unit per gram 
DNAER Direction Nationale de l'Aménagement et de l'Équipement Rural  
DRPD Direction  Régionale de la Pêche du District de Bamako 
EDTA Ethylenediaminetetraacetic acid 
EHEC Enterohemorrhagic E. coli 
EIEC Entero-invasive E. coli 
EISMV Ecole Inter états de Sciences et de Médecine Vétérinaire de Dakar 
EPEC  Enteropathogenic E. coli 
ETEC Enterotoxigenic E. coli 
FAO Organisation des Nations unis pour l’alimentation et l’agriculture 
FC Fecal Coliform 
FST Faculté des Sciences et Techniques de Bamako 
GDP Gross domestic product 
H2S Hydrogen Sulfide 
ICMSF International Commission for Microbiological Specifications for Foods 
IND Indole 
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INRSP National Institute of Research in Public Health 
IRD Institut de Recherche et de Développement  
ISFRA Institut Supérieur de Formation en Recherche Appliquée de Bamako 
PADEPECHE Projet d’Appui au Développement de la Pêche Continentale dans le Delta 
Central du Niger 
PCA Plate Count Agar 
pH potential Hydrogen 
RCM Reinforced Clostridial Agar 
SC:  Selenite Cysteine 
SPSS Statistical Package for the Social Sciences 
SRB Sulfito‐Reductor Bacteria 
S-S Salmonella-Shigella 
TC Total Coliform 
TMA TriMethylAmine 
TMAO TriMethylAmine Oxide 
TSA Trypton Soy Agar 
UICN Union International pour la Conservation de la Nature 
UV Ultra-Violet 
VRBA Violet Red Bile Agar 
WHO World Health Organization 
 
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CHAPTER ONE 
1.0 INTRODUCTION 
1.1 Background 
Around the world, millions of people depend on fish for its high protein content. According to the 
Food and Agriculture Organization (FAO, 2007), fish is an important source of nutrients because 
of its protein, vitamin A and D, phosphorus, sulfur and essential amino acids composition. It is 
also low in cholesterol (Fagbenro et al., 2005; Ayeloja et al., 2013; Aremu et al., 2013; Oladipo 
& Bankole, 2013 ; Khalili Tilami & Sampels, 2017). Fish can play an important role in improving 
nutritional status in Africa's food security; as more than 200 million Africans eat fish regularly 
(Béné & Heck, 2004). Fish, like other agricultural products, is essential for ensuring the food 
security of the poorest in the country. The nutritional profile of the fish is superior to pork, beef 
and chicken, providing an excellent source of highly digestible energy and high-quality animal 
protein (Oladipo & Bankole, 2013). The risk of contracting a cardiovascular disease is rather 
reduced in people who consume more fish because it is rich in omega-3 fatty acids. 
The fishing sub-sector is a key sector of the Malian economy because of its contribution to job 
creation, food security and increased national wealth (Laë et al., 2004). In normal hydrological 
period, fish production is approximately 100,000 metric tons/year (FAO, 2007). Gross value added 
for the entire fishing industry is estimated at more than 90 billion CFA francs ($160,050,637.72), 
which represents 4.2% of the country's total GDP (FAO, 2007). Fishing also contributes to a large 
part of the state’s budget through taxation. This contribution is estimated at around 10% of the 
gross value added in the sector (FAO, 2007). 
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In Mali, fishing activities and practices are common along almost all water bodies in the country. 
It is the largest freshwater fishing country in the world (FAO, 2007). Fishing is practiced in two 
River basins (the basins of Niger and Senegal), lakes, ponds and flood plains. The main fishing 
areas are Central Delta of Niger (about 80% of total freshwater fish production), Selingue Lake, 
Markala Lake and Manantali Lake. Fish from these areas are sold on the Medina Coura market in 
Bamako (Sissoko et al., 2016). In this market, there are nine (9) different fish families: Alestidae, 
Cyprinidae, Osteoglossidae, Gymnarchidae, Centropomidae, Mormyridae, Bagridae, Cichlidae, 
Mochokidae (Sissoko et al., 2016). 
Fish is, however an extremely perishable food product owing to its biological composition; 
deteriorating much faster than most other foods. Indeed, in tropical countries, where ambient 
temperatures range between 25°C and 30 °C, fish are destroyed in less than 12 hours (Degnon et 
al., 2013). After capture and death, fish can normally be stored in chilled brine or crushed ice for 
preservation., Temperature is the most important environmental factor influencing the composition 
of the fish microflora (ICMSF, 2005). 
Cross-contamination with harmful agents through mishandling and unhygienic practices may  
expose consumers to foodborne diseases (Kombat et al., 2013). After capture, dead fish undergoes 
several bacterial and enzymatic alterations. Microbial growth of freshly caught and marketed fish 
may be caused by unhygienic transportation and handling or lack of appropriate chilling during 
storage. Dione (2003), also identified that the causes of this rapid spoilage of fish are mainly due 
to physicochemical and microbiological factors because of poor handling practices, inappropriate 
storage temperatures and poor packaging methods affecting fish quality. In Mali, the artisanal 
fisheries sub-sector suffers from a lack of infrastructure for landing and marketing (FAO, 1996). 
Stakeholders are unaware of the basic hygiene rules and health risks associated with different 
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treatment methods, such as the use of faulty freezers that do not freeze fish. Traditional practices 
such as sun drying, hot smoking and frying, improper storage can lead to fish degradation. Due to 
the high content of unsaturated fatty acids in fish, the oxidation of free radicals is a common 
phenomenon in all fish products (fresh and processed) exposed to the open air (Bourgeois & 
Leveau, 1991).  
Unfortunately, at Medina Coura market, proper fish conservation practices are still not respected. 
Fresh fish are exposed, in unhygienic places, on mats on the ground, under the sun and often 
without ice. This can reduce the marketability of fish by reducing the microbiological quality of 
fresh fish and potentially cause diseases such as gastrointestinal diseases, headaches, diarrhea due 
to Toxic Collective Infections when toxigenic microbes present on fish exceed infectious doses. A 
study by Gram & Huss (1996) suggested that lactic acid bacteria and some psychotropic 
Enterobacteriaceae could cause fish spoilage. In another study, freshwater fish at Medina Coura 
market in Bamako was reported to have prevalence of 51% Enterobacteriaceae family, 23% of 
Aeromonadaceae family, 19% of the family Pseudomonadaceae, 6% for the family Moraxellaceae 
and 1% for the family Vibrionaceae (Sissoko et al., 2016). Aboagye (2016) identified Clostridium 
perfringens, enteropathogenic E. coli, Aeromonas sobria, Staphylococcus aureus, and Listeria 
spp., on fresh and processed fish at different stages of the fish value chain in Ghana. These 
pathogens are among the main microbial cause of foodborne illnesses. Aboagye (2016) also noted 
the presence of putrefactive microorganisms such as Proteus vulgaris, Proteus mirabilis and 
Pseudomonas spp. Microorganisms developing at low temperatures and exhibiting proteolytic 
activity have been presumed to be primarily responsible for the spoilage of fresh fish (Ghaly et al., 
2010). Potential bacterial pathogens that have been found in fish include Streptococcus iniae, 
Vibrio cholera, Staphylococcus aureus, Escherichia coli, Salmonella spp. and Vibrio 
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parahaemolyticus (Kombat et al., 2013). Parasites such as nematodes, cestodes and trematodes are 
found in the aquatic environment. They are associated with freshwater fish and they cause 
morbidity, mortality and economic losses in Africa (Oniye et al., 2004; Ayanda, 2009). 
The body of water which is the source of fish can be the main source of contamination when the 
water becomes polluted through the discharge of sewage and rain run-offs (Kombat et al., 2013). 
The presence of pathogenic and spoilage microorganisms in freshwater fishes has both health and 
economic implications which poses threat to public health. And thus, a threat to public health. 
There is a high rate of fish consumption in Mali amidst poor aquatic environment, unhygienic 
handling and storage at fish markets, however, not much studies have been done to assess or 
characterize the microbiological quality of fish in the fish value chains in the country. This study 
therefore, sought to assess the microbiological safety of the three fish species (Lates niloticus, 
Oreochromis niloticus and Clarias anguillaris) abundant in the Medina Coura market and along 
the value chain to the market. 
The study also aimed to map and document the local fish value chain in southern part of Mali 
(Selingue, Manantali, Markala and Mopti), to identify critical contamination points in the value 
chain to provide information on the food safety knowledge and practices of stakeholders in the 
value chain. This research provides useful information for future diversity studies within Mali and 
even in the sub-region. In addition, to providing information on sociodemographic factors that 
influence fish handling practices along the value chains as well as information on the food safety 
knowledge and practices of stakeholders in the fish value chain. It could also influence future 
policies and interventions aimed at mitigating fish spoilage and addressing food security issues 
related to artisanal freshwater fish. 
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1.2 General objective 
The main objective of this study was to investigate the microbiological quality and microbial 
diversity of fresh fishes sold along the fresh fish value chain in Southern Mali (Selingue, 
Manantali, Markala and Mopti) to Medina Coura market. 
1.3 Specific objectives 
The specific objectives were to: 
- Assess the food safety practices and knowledge of key stakeholders in the identified value 
chain; 
- Determine the effect of seasonal variation on the microbial quality and parasites of 
freshwater fish; 
- Identify the spoilage bacteria associated with freshwater fish using phenotypical methods; 
- Identify the pathogenic bacteria associated with fish using phenotypical methods.  
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CHAPTER TWO 
2.0 LITERATURE REVIEW 
Mali has a Sudano-Sahelian climate; which is characterized by a strong irregularity in 
precipitation, which is observed at all timescales (annual, decennial, centennial and millennial). 
Since the beginning of the 1970s, there have been many periods of drought. During the 
hydrological year 1994-1995, however, very favorable hydro-climatic conditions were observed, 
which had a direct and immediate impact on the fishery industry (FAO, 1996). Fishing is carried 
out on two river basins (Niger river and Senegal river), lakes, ponds and floodplains. Fishing is 
practiced in practically all the water bodies of the national territory. There are, however, three main 
production areas: Delta Central of the Niger river, two-artificial lakes (Manantali and Selingue) 
and Markala dam (FAO, 1996). 
2.1.1 Central Delta of Niger River 
Located downstream from Segou, the Niger Central Delta is fed by two rivers, Niger and Bani 
rivers. Nineteen (19) per cent of the water comes from Côte d’Ivoire and Guinea, and the flood 
occurs from July to August (Laë et al., 2004). The floodplain basins dry up from April to May, but 
the rivers Bani and Niger and some lakes retain water. In hydrological period, there is a lag of 
three months between the beginning of the flood in the North (Dire), in the South (Ke Macina) and 
of the Delta. During the same hydrological cycle, flooded areas can range from 20,000 km2 at 
maximum flood to 3,500 km2 at the end of the low water season (Laë et al., 2004).  
The Central Niger Delta is a vast region of about 30,000 km2 in the centre of Mali. The annual fish 
production varies between 45,000 and 100,000 tons, according to the extent of the floods 
(Quensiere, 1994). In general, the deltaic zone can be considered as fully exploited, irrespective of 
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the level of the flood. Fishermen adjust the number of their annual investments according to the 
extent of the flood (FAO, 1996). 
2.1.2 Selingue Lake 
At about 140 km South of Bamako, Selingue dam was built in 1980. It provides both hydroelectric 
power and irrigation, and its management is done by the Office of Exploitation of Hydraulic 
Resources of the Upper Niger (Laë et al., 2004). The dam is 348 m long and the lake covers 409 
km2 and contains 2.2 billion m3 of water. However, its depth does not exceed 20 m (Paugy & 
Leveque, 2006). Every year, the lake produces about 4000 tons of fish (Miller, 2006). 
2.1.3 Manantali Lake 
Built-in 1987 in the valley of the Bafing river, Manantali Lake provides both irrigation and 
hydroelectric power (Paugy & Leveque, 2006). It is 208m long and with an area of up to 500 km2, 
it contains 11 billion m3 of water, the depths of the medium and maximum dam are respectively 
20 m and 50 m (Paugy & Leveque, 2006). Fish production per year is about 1,500 tons (Miller, 
2006). The hydrology of Manantali Lake is particularly characterized by a significant tidal range 
that reaches more than 8 m between the high-water season and the low water season (Paugy & 
Leveque, 2006). The shores of the lake are also frequently overlooked by high cliffs, allowing no 
landing for fishing. The physicochemical characteristics of the waters are similar to those of the 
Selingue Lake, including waters with satisfactory oxygenation, and enriched with nutrients by the 
progressive degradation of nearly 12,000 ha of submerged forest (FAO, 1996). 
2.1.4 Markala Lake 
The "Office du Niger" is an agricultural zone. The Markala dam allows gravitational irrigation.  
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With 74,000 ha, it is the largest irrigation project in West Africa, was built in 1943, located 250 
km downstream from Bamako in Mali to store water for irrigation (Laë et al., 2004). The "Office 
du Niger" zone, aims to develop agriculture. It allows the production of sugar cane and rice (Laë 
et al., 2004). 
2.2 Fish production in Mali 
In Africa, the total fish supply in 2011 was 9 million tons (Kolding et al. 2016). Production in 
landlocked dryland countries, such as Mali, Burkina Faso and Niger, has grown as a result of 
production from the Senegal and Niger rivers, although the recorded levels of production are much 
less significant than those of coastal countries (Kolding et al. 2016). 
The largest in the Sahel is Mali’s fisheries production and it represents 40% of West Africa’s 
freshwater fish production (FAO, 2007). Depending on rainfall and flooding annually, production 
of fishes varies from an estimated 70,000 to 150,000 tons (FAO, 2007). An estimated 10 to 20% 
of freshwater fish production is exported in the West African sub region (Peterson & Kalende, 
2006). According to FAO (2007) there is very little updated data on the fisheries and aquaculture 
sub-sector, the artisanal type of inland fishing in Mali is carried out on all water bodies: rivers, 
lakes, ponds, reservoirs of hydroelectric dams and agro-pastoral dams, floodplains, etc. 
Mali shares with its neighbors two rivers of major importance: - The Senegal river creates in the 
west a major hydrographic axis 900 km long whose main tributaries are Bafing, Bakoye, Baoulé 
and Falémé; The Niger river, a Sudanian river, is the fourth-longest river in Africa (4,200 km). 
From the mountains of Fouta Djalon in Guinea where it rises, it flows North- East through Mali 
where it forms a seasonal floodplain of 20 000km2 known as the Delta Central. It crosses Nigeria, 
Niger, and the Republic of Benin where the river enters the Gulf of Guinea (Laë et al., 2004). 
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The Niger River plays a vital role in the life of a densely populated and vast region of West Africa 
(FAO, 2007). The drinking water supply of several cities is ensured by the abstraction of the waters 
of this river operated upstream. It is an important waterway both for navigation associated with 
active trade (in Mali from Koulikoro in the bend of Niger and Nigeria on lower Niger) and for 
small canoe traffic throughout its route. Riparian and rural populations benefit from their important 
fisheries resources (Laë et al., 2004). The flood plains and tributaries of the Inner Delta are used 
for rice, cotton and wheat cultivation. Besides, flood plains are vital for nomadic pastoralists who 
use access to water and pastures that are created every year as the water recedes. New 
developments (hydroelectric dams and irrigation dams) are now likely to give the river a 
significant economic role  where 30% of the watershed is in Mali, which crosses the country from 
West to East for 1750 km, drawing the Inner Niger Delta to the North and whose main tributaries 
are Bani and Sankarani (Laë et al., 2004). 
The basins of the Niger River, the Senegal River and the Volta river (along with the Sourou River) 
play a very important role in the conservation of biodiversity owing to the vast plains they flood 
(FAO, 2007). In both lakes, the fish species present are generally the same as those recorded in the 
Central Delta. In the case of the Selingue Lake, it is because at the time of impoundments of the 
lake, the same species settled in the environment. For Manantali Lake, which belongs to the 
Senegal River basin, this could be explained by the proximity of fish population between the waters 
of Senegal and the middle Niger (FAO, 2007). However, the filling of the lakes has modified the 
ecological conditions and provoked significant changes in relative abundance favouring some 
species to the detriment of others (FAO, 1996). In Selingue, the main commercial species belong 
to the family Bagridae (Chrysictis and Auchenoglanis especially), Cyprinodontidae (Labeo) and 
Cichlidae (Tilapias), with respectively 21%, 15% and 13.5% of landings (FAO, 1996). 
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In Manantali, the family Cichlidae and Synodontidae, on the other hand, account for nearly two-
thirds of landings with respectively 48% and 17% (FAO, 1996). In Manantali, the high proportion 
of tilapia during fishing could be explained by the fact that the fishermen concentrate their effort 
on the shallows of the water body (FAO, 1996). 
2.3 The major categories of fishermen in Mali 
Farmers-fishermen (Ethnics groups: Rimaïbé, Bambara, Soninke and Songhai): they devote 
proportionately more time to agricultural work and invest primarily in agriculture, which results 
in the use of small numbers of gear, of poor quality; they are also fundamentally passive since they 
create more time for agriculture. Catches are moreover essentially intended for self-consumption 
at the household level (FAO, 2007).  
The sedentary professional fishermen (Bozo and Somono): they consider fishing as a full-fledged 
economic activity that generates cash income. However, for this second category of fishermen, the 
links with the land are not broken allowing the households concerned to diversify fishing activities 
with agriculture, making them less vulnerable to hydrological hazards (FAO, 2007). 
The migrant professional fishermen (mainly Bozo): fishing is the only way for them to meet the 
needs of households since they generally do not have access to land. Migratory fishermen possess 
a particularly high degree of technicality and minimize the hazards of natural productivity by 
diversifying techniques and fishing grounds frequented during the annual cycle (FAO, 2007). 
2.4 Medina Coura fish market in Bamako 
Medina Coura market, also called Dossolo Traore market, is located in Commune II of the District 
of Bamako. It is limited to the East by Hippodrome, to the West by Modibo Stadium Keita, to the 
North by the hill of Point G and the South Missira. The market monitoring study carried out by 
the DRPD (2010) showed that, refueling of fresh fish is made from the fishing centres of Mopti 
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(34%), Selingue (28%), Senegal (13%), Segou (6%), Mauritania (6%), Manantali (3%), Markala 
(3%), Macina (3%) and Gao (3%). Fish production converges in Bamako the capital; the Medina 
market is the place of transit and of marketing fish. It receives the largest amount of fish from other 
regions. The flow time of fish arriving on the market varies between 2 to 3 days. Fish are exposed 
on the ground with or without ice. Fish that have not been sold on the same day are kept in non-
functional freezers containing ice (Sissoko et al., 2016). The supply for Bamako is made by 
vehicles (truck or public transports) carrying coolers or baskets with fresh fish on ice from 
Selingue, Markala and Manantali (Traore, 2014). 
2.5 Fisheries value chain in Mali: market organization 
The value chain or chain of activities of a product makes it possible to add value to the product. 
Once caught, the fish is brought back to the landing point where it undergoes a first transformation 
(sorting, freezing, etc.). The second transformation is the explain this, it is sent to the wholesaler 
who sends it to the retailer and finally purchased by the consumer (Hempel, 2010). In developing 
countries, value chain analysis is rare and because it results from different interactions it is difficult 
to determine when some stages of the chain are missing (Hempel, 2010). 
Fish marketing channels are generally organized around three types of markets: Wholesale markets 
that centralize production (Mopti in the Central Delta of Niger, Faraba and quarry to Selingue, 
Manantali and Markala); Semi-wholesale markets located in production and consumption centres; 
and retail markets in towns and villages. Wholesale markets can nevertheless be short-circuited 
through direct sales to local consumers (Traore, 2014). 
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Legend 
Transformed or fresh 
Frozen → 
Figure 2.5.1: Fisheries value chain in Mali (Traore, 2014) 
2.6 . Artisanal fishing in Mali 
According to Peterson & Kalende (2006), Malian fishermen use canoes in nailed boards. These 
are rarely motorized given the particular fishing conditions. A fisherman's household has on 
average one to two canoes. In total, taking into account the fishing activities on Malian lakes and 
rivers, one can reasonably estimate about 25000 fishing canoes in Mali. Most fish are caught from 
November to March. Day and night fishing is done with local tools, nets, buckets and canoes. 
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Given seasonal variations in environmental conditions, particularly in the deltaic area, fishermen 
use a wide range of gear and methods of capture adapted to each type of situation. In the Central 
Delta, there is a close relationship between the exploited biotopes (watercourse, flooded plains, 
temporary pools, etc.), the hydrological season (flood, high water, recession, and low water level), 
the species targeted, and the means of fishing used over the last twenty years (Peterson & Kalende 
2006). Production yields per hectare have almost tripled in the Central Delta. On the dam lakes, 
the gear used is less diversified, the fishermen having gradually adopted those which proved to be 
the most adapted to lacustrine fisheries (greater depth, presence of immersed strains, weak 
current). New fishing techniques have also been developed, such as those for gill nets and bell 
nets, while other techniques have been modified (E.g. durankoro nets used as baited traps for deep-
sea fishing).  
The main fishing gear used in Malian fisheries can be grouped into six broad categories: 
- Gear by injury (harpoons) used in ponds in the process of drying up, in floodplains and during 
collective fishing; 
- Deep-filleted nets (triangular nets used in dam fisheries or collective fisheries, two-handed nets 
used in depletion fisheries) or thrown nets (hawks used in collective fishing or on river arms 
in dewatering course); 
- The small seine nets of the xubiseu type (80m x 6m) used by one or two fishermen during low 
water  
-  The large seine nets of the djoba type (400-1000m x 6-10m) handled by 10 to 20 fishermen 
and used in the delta mainly during periods of low water and in dam lakes after deforestation 
of shoreline portions; 
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-  Gill nets used at high water in the plains or the river when the current is not strong, and drifting 
gillnets (130-450m) at a time when the current is strong (flood and start of the recession); 
- The traps of which the most used are Durankoro type or Diene type of larger size;  
- Baited or un-baited longlines. 
2.7 Different species of freshwater fish in Mali 
In Middle Niger, more than 130 species of fish have been identified, which belong to 62 genera 
and 26 families (Laë et al., 2004). These species have been divided into two groups: migratory 
species and opportunistic species. The most important and most commercialized species include 
Lates niloticus, Bagrus bajad, Heterotis niloticus, Alestes dentes, Clarias anguillaris, Brycinus 
leuciscus, Hydrocymus brevis, Oreochromis niloticus and Sarotherodon galilaeus (Laë et al., 
2004). 
2.8 Nutritional value of fresh fish 
The edible part of the meat makes 40 to 80% of the total depending on the nature of the fish and 
the requirements of the consumers. It varies according to the food of the species and the season 
(Ibemenuga & Okeke, 2014). Known for its high nutritional value, fish are relatively low in 
cholesterol and saturated fat, and high in proteins, polyunsaturated fatty acids, and minerals such 
as calcium, potassium, phosphorus, sodium and magnesium (Kumolu-Johnson & Ndimele, 2011; 
Ibemenuga & Okeke, 2014). 
In developing countries, a large portion of the population depends on fish for its protein 
(Ibemenuga & Okeke, 2014) and knowledge of its composition is essential (Ibemenuga & Okeke, 
2014). The amount of protein in fish muscle is usually somewhere between 15 and 20 %, but values 
lower than 15 % or as high as 28 % are occasionally met for some species. Fish also supplies 15 
to 20% nitrogenous substances, 3 to 8% lipids (fat), and 1 to 2% mineral substances. The fish is 
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said to be lean when it contains 3% fat (tilapia) and fatty if its flesh contains 8% fat (Clarias) 
(Ibemenuga & Okeke, 2014). 
Table 1:Nutritional values of some fish species (Dansoko, 2012) 
Fish Proteins Lipids Phosphors Calcium 
Tilapia 26.94% 1.37% 60mg/100g 87mg/100g 
Clarias 21.30% 5.10% 21mg/100g 10mg/100g 
Hydrocynus 24.33% 8.69% 39mg/100g 25mg/100g 
Lates niloticus 25.10% 3.45% 39mg/100g 41mg/100g 
 
Tilapia is the richest fish in terms of nutritional value; Lates comes in second, and Hydrocynus 
and Clarias in terms of protein, fat, phosphorus and calcium. 
The flesh of the fish contains vitamins; A, B12, D; and minerals essential to man: calcium (bone); 
phosphorus (brain); iodine (growth) etc. The amount of vitamin in fish varies by species; there are 
fat soluble vitamins such as vitamins a, d, e and k, and water-soluble groups, such as vitamins b 
and c. (FAO, 2007). 
2.9 Consumption of freshwater fish in Mali 
Per capita, fish consumption is estimated at 10.5 kg/year (compared to meat consumption of 7.8 
kg/year), although fish consumption among fishing families is probably much higher (Laë et al., 
2004; Peterson & Kalende, 2006). In Africa, fish is widely consumed as a remarkable source of 
animal protein (Ibemenuga & Okeke, 2014). 
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2.10 Gender distribution in fishing communities in Mali 
Throughout the world, the fishing sector is very important, providing livelihoods for millions of 
individuals. Fish is an important source of income for many families in developing countries. It 
has been estimated that the fishing industry supports more than 120 million people around the 
world (Oladipo & Bankole, 2013; Nwabeze et al., 2013). In terms of employment, fishing activities 
directly affect nearly 71,000 fishermen, grouped in 32,800 households. Fishing activity is, 
therefore, a vital resource for about 256, 400 people (Peterson & Kalende, 2006). Applying that 
figure to Malian rural population, which has about 7.2 million people, it is estimated that fishing 
activities directly affect nearly 3.6% of the rural population (PADEPECHE, 2004). This average 
figure, however, masks large disparities encountered at the regional level. Fishing is carried out 
on almost all the rivers of the Malian territory. There are three main fish production areas, 
including Lake Selingue, the Central Delta of Niger and Lake Manantali. Thus, in the region of 
Central Delta of Niger, the largest producing region of the country with almost 80% of the total 
catch, more than a third of the population is directly affected by fisheries (FAO, 2007).  
Taking into account the jobs generated upstream and downstream of the fishing activity, the 
number of jobs provided by the entire sector can be estimated at 284,000 persons, representing 
approximately 7.2% of the Malian workforce. The fishing industry could, therefore, employ a total 
of nearly 8% of the active population (FAO, 2007).   
According to FAO (2007), in the fishing sector, men and women complement each other. In most 
communities, large boats used for fishing, have male crews, while women manage smaller boats 
and canoes. Land-based activities such as catch processing and marketing and the manufacture 
and repair of fishing nets are the responsibilities given to women in most communities. In most 
developing countries, various studies reveal that women in fishing communities work long hours 
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of daily work in household chores, fishing, fish processing, packaging, storage, fish marketing and 
other non-revenue generating activities (Nwabeze et al., 2013).Women play an important role in 
fish processing (drying or smoking fish) and marketing (Laë et al., 2004). 
2.11 Fish in food security 
The role and importance of fish in securing food and nutrition for humans, particularly in 
developing countries, has frequently been overlooked. There is a growing demand for fisheries 
resources due to population growth, so it is important to improve fishing techniques. This 
population growth has an impact on poverty and food security (Limburg et al., 2011). Certain 
factors such as the uncontrolled practice of fishing as well as the pollution and the degeneration of 
the fishing environment allow the reduction of aquatic resources. In Africa, severe cyclical drought 
causes increased desertification, decreases in surface water, huge losses in agriculture and 
decreases in fish catches (Miller, 2006). These are the difficulties facing Sahelian countries. 
Alongside these problems are population growth and the people’s urgent need for food (Miller, 
2006).  
2.12 Post-harvest fish losses 
‘'Food security is when all people have economic and physical access to the basic food that they 
need at all times’’ (FAO, 1984). Reducing post-harvest losses and increasing the amount of fish 
used improves food security by making better use of the fish produced. According to Kumolu-
Johnson & Ndimele (2011), the losses caused by the alteration of fish after harvest are of various 
forms. The method of fishing, lack of regulations governing inadequate handling facilities and 
time delays between capture, collection and distribution, the quality and standards of fish for sale 
for human consumption, lack of regular surveillance on the side Government and poor extension 
services are seen as the main reasons for fish losses (Gebretsadik, 2016). 
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2.12.1 Physical losses 
Physical losses of material are due to poor conservation or handling and the rejection of incidental 
losses. Physical loss can be caused by insects or others fish (animal predation) eating the fish, by 
theft, or by bird (Alemu et al., 2021). Mechanical damage (e.g. small cut through the sharp edge 
of the ice and net damage) can help and provide the right conditions for enzyme activities 
(Sivakumar et al., 2018).  
2.12.2 Economic losses 
Economic losses are caused by the denaturation of the wet fish which causes the loss of the value 
of the fish; also, the nutritional value of the product is reduced. The exact figures of the total 
economic losses due to food spoilage is not known, however, the physical damage of fish, 
obviously leads to the reduction in the price of the fish (Sivakumar et al., 2018; Alemu et al., 
2021). 
2.12.3 Nutritional losses 
As fish spoils, it loses its nutritional value. The main mechanism of spoilage is protein hydrolysis, 
which is intended to be the main human food. This is not generally a major factor; as bacterial 
action generates nitrogenous substances with objectionable smells. The fish will lose its 
appearance when there is too much nutritional damage (Ghaly et al., 2010). 
2.13 Fish Spoilage 
Food spoilage encompasses any undesirable changes by food spoilage microorganisms and their 
microbial metabolites that cause repugnant tastes and odors (Veld, 1996). The food becomes both 
unpleasant smell and sometimes harmful. Food spoilage is mainly due to chemical, enzymatic or 
microbial activities (Sevindik & Uysal, 2021). A quarter of the world's food supply and 30% of 
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the fish landed are lost due to microbial activity (Ghaly et al., 2010). With population growth, it is 
necessary to store and transport food from one place to another. Good food preservation becomes 
a necessity to increase shelf life to maintain its nutritional value, flavor and texture (Ghaly et al., 
2010). 
Microbial spoilage is rapid and evident in proteinaceous foods such as meat, poultry, shellfish, 
fish, milk and some dairy products as changes in flavor, texture and taste. These foods are highly 
nutritious, possess a neutral or slightly acid pH and a high moisture content and therefore permit 
the growth of a wide range of microorganisms(Veld, 1996). At temperatures near to 37 °C, most 
human pathogens grow best whereas most foods are usually stored at temperatures well below the 
normal body temperature.  
The major pathogens associated with post-harvest fish spoilage which can produce toxins and 
cause food poisoning are Staphylococcus aureus, Escherichia coli, Klebsiella spp. Salmonella 
spp., and Pseudomonas spp. etc. (Awe & Adejo, 2018). Poor handling and washing of the fish in 
polluted water can result in food poisoning caused by pathogenic bacterial contamination of fresh 
fish. Fish are extremely perishable (Abiodun, 2020). This is due to the phenomena of post-mortem 
damage caused by autolytic reactions due to muscular and digestive enzymes and bacteriological 
changes due to proliferation and microbial invasion. The loss of the fish quality starts as soon as it 
dies or is caught in the tropics, where the ambient temperature is very high (25 to 30 °C), the fish 
is altered after 12 to 20 hours depending on the species (Dione, 2003). The cells then initiate new 
processes characterized by the degradation of glycogen (glycolysis) and energy-rich products. The 
first autolytic processes occur in the muscle of the fish. The body of healthy fish, alive or freshly 
caught, carries a very variable microbial load, of the order of 102 to 105 germs / cm2 of the skin, 
103 to 107 germs / g of gills and 103 to 108 germs / g of intestines (Bourgeois & Leveau, 1991). 
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This great variability reflects the condition of the environment. At death or after capture, when the 
fish is exposed to a temperature above 8 °C, the bacteria invade the fish flesh through collagen 
fibers to cause physical and biochemical changes. The softening of the flesh, the weakening of the 
abdomen and the detachment of the peritoneum is partly due to bacterial activity (Bourgeois & 
Leveau, 1991; Gram & Huss, 1996). 
2.14 Microorganisms involved in fish spoilage 
According to Huss (1995), it is important to know that many microorganisms do not propagate on 
spoilage. The spoilage is the result of fermentative Gram-negative bacteria (such as Vibrionaceae), 
while psychro-tolerant Gram-negative bacteria (such as Pseudomonas spp. and Shewanella spp.) 
tend to spoil chilled fish. 
Universally, to determine the microbial spoilage of fish by using their trimethylamine level 
(TMA). Fish use trimethylamine oxide (TMAO) for osmoregulation to avoid dehydration in 
marine environments and engorgement of tissues in freshwater (Gram & Dalgaard, 2002). 
Bacteria such as Aeromonas spp., Shewanella putrifaciens, Photobacterium phosphoreum, 
Enterobacteriaceae psychrotolerant, and Vibrio spp. can obtain energy by transforming TMAO 
into TMA, as well as agents similar to ammonia (Gram & Dalgaard, 2002). Bacteria alteration of 
the genera Pseudomonas such as Ps. putrifaciens, Ps. fluorescens and others propagate quickly 
during the first stages of deterioration and produce proteolytic and hydrolytic enzymes (Ghaly et 
al., 2010). These bacteria are responsible for the sweet and fruity odors of spoilage while 
Shewanella putrefaciens is responsible for the production of H2S. 
The composition of the microbial flora of fish products is generally quite similar to that of their 
natural environment (Austin, 2006). The primary factors associated with food spoilage are 
associated with intrinsic food properties and contamination during harvesting, slaughter and 
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processing in combination with temperature abuse (Veld, 1996). The species found in the gut of 
fish are essentially the same as those isolated from the water in which the fish is caught. The 
detection of microorganisms in fishery products can have two main origins namely microbial 
contaminants native to natural freshwater habitats (where fish is sourced) and those associated 
with water pollution (Bourgeois & Leveau, 1991; Gram & Huss, 1996; Novoslavskij et al., 2015). 
Contamination of the waters of the fishing zones: At this level, the pollution is quite important. 
The pathogens brought by this route are generally organisms with associated faecal transmission 
(Salmonella, viruses, parasites). The search for faecal indicators will be very useful in this case. In 
fish, contamination germs are found in the gills in the gut and on the skin. A muscle is free of 
germs on live fish (Ghaly et al., 2010). 
Post-capture contamination: A product that is not originally contaminated may have been 
contaminated during the various stages preceding its placing on the market. The contamination 
can already take place on a boat, by contact with dirty material (crate, the ice of bad bacteriological 
quality). Ice can ensure long conservation of fishing products while preserving their freshness. 
However, to be fully effective and cost-effective, the hygienic and technological principles of a 
cold application must be respected. Washing with contaminated water can sometimes introduce 
pathogens onto the fish. 
According to Bourgeois & Leveau (1991), microorganisms isolated from the gills, the intestines 
and the skin belong mainly to the following genera: 
Pseudomonas, Acinebacter, (60%), 
Corynebacterium, Flavobacterium, Micrococcus (20%), 
Bacillus, Proteus, Serratia and others (20%). 
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According to Fane (2011), aquatic environments are generally rich in microorganisms due to 
favorable environmental conditions for microbial growth. The presence and the number of these 
microorganisms are largely influenced by several abiotic factors such as temperature, dissolved 
oxygen, pH, and the presence of dissolved or suspended mineral substances and the availability of 
organic matter. 
Microbial species vary according to the quality and type of water. However, the same species are 
not found in cold waters, warm waters and polluted waters. Aquatic environments are easily 
polluted by both wastes from homes, farmlands or industries. This endangers the life of aquatic 
biota such as fish since fish takes in a large number of bacteria into their alimentary tract from 
water and food (Ibemenuga & Okeke, 2014). The bacterial flora of living fish reflects the flora of 
its aquatic ecosystem, but there is a specific flora related to the type of fish. According to Shewan 
in Fane (2011), microorganisms occur on the entire outer surface of live or freshly caught fish. 
The microbial load is of the order of 102 to 107 germs / cm² of skin and 103 to 109 germs / g of gills 
or intestine. 
Thus, the bacterial flora of freshly caught fish depends more on the environment in which it was 
caught, than the species of fish itself. Fish caught in clean, very cold waters have a lower bacterial 
load than fish caught in warm waters (FAO, 2007). This bacterial load is 107 CFU / cm2 on fish 
from polluted water (FAO, 2007). Several species of bacteria are found in fish, psychrotrophs can 
develop at 0 °C. The microflora of temperate fish, dominated by gram-negative psychrotrophic 
rod-shaped bacteria, belong to the genera Pseudomonas, Acinetobacter, Moraxella, Shewanella 
and Flavobacterium. 
Pseudomonas belongs to the family Pseudomonadaceae. This genus includes the species 
Pseudomonas aeroginosa which can secrete pigments such as pyocyanin (blue-green), pyoverdine 
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yellow-green fluorescent (Abdulhussien, 2018). Also, the genus Aeromonas, belonging to the 
family of Aeromonadaceae are associated with fresh water fish. They are straight bacilli with 
rounded ends, Gram-negative, catalase-positive, motile and facultative anaerobic. They are 
ubiquitous in water and many foods. They are psychrotrophic organisms. Aeromonas species are 
human pathogens associated mainly with diarrhea1 symptoms (Hanninen et al., 1997). The optimal 
growth temperature is 28°C and with a wide growth range and variability in the optimum 
temperature have been observed. Many strains can grow at 5°C, making Aeromonas particularly 
significant in refrigerated foods (Isonhood & Drake, 2002). This microorganism is an opportunistic 
pathogen of both aquatic and terrestrial animals (Hanninen et al., 1997; Isonhood & Drake, 2002). 
2.15 Microbial pathogens in fish 
Some harmful microorganisms in food can invade the human body (Salmonella spp., Escherichia 
coli, Listeria monocytogenes, etc.) and other generators of toxins ingested with a portion of food 
such as Staphylococcus aureus, Bacillus cereus and Clostridium botulinum). Food spoilage is not 
necessarily due to the growth of pathogenic microorganisms in food. However, pathogenic bacteria 
such as Salmonella spp., Shigella spp., Escherichia coli and Staphylococcus aureus are responsible 
for many foodborne disease outbreaks (Gram & Huss, 1996). The aquatic environment may also 
contain pathogens such as Aeromonas spp., which is a pathogen of both fish and humans 
(Mhongole, 2009). Enterobacteriaceae is one of the most important families of ubiquitous 
bacteria. These are Gram-negative bacilli of medium size (coccobacillus, often polymorphic), and 
negative oxidase. The presence of Enterobacteriaceae is often used as an indication of poor 
hygiene, inadequate processing or post-process contamination (Veld, 1996). Moreover, the 
presence of Escherichia coli which is an indicator of fecal contamination suggests the probability 
of contamination of food produced with wastewater of human or animal origin. On the other hand, 
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certain strains of E.coli (Enteropathogenic EPEC; Entero-invasive EECI; Enterotoxigenic ETEC; 
and Enterohemorrhagic EHEC) are pathogenic and cause serious human disease transmitted by 
water and food (Mhongole, 2009). Vibrionaceae family is gram-negative bacilli with a positive 
mobile oxidase reaction through a polar ciliate. These include particularly V. cholera, V. 
parahaemolyticus and V. vulnificus, which are generally recognized as the leading cause of human 
gastroenteritis associated with seafood consumption globally (Bonnin-Jusserand et al., 2017). 
Consumption of raw or undercooked seafood contaminated especially with V. parahaemolyticus 
may lead to the development of acute gastroenteritis characterized by diarrhea, vomiting, 
headache, nausea, abdominal cramps and low fever (Aboagye, 2016). The source of contamination 
of cholera is the transmission of the microorganism through water and food and the pollution of 
the aquatic environment by the excrement of infected people (Mhongole, 2009). 
2.16 Parasites 
Some major public health problems can be caused by helminth parasites transmitted by fish and 
shellfish products. Globally, the number of people at risk including those in developed countries 
is more than half a billion (Rim et al., 1994). The consumption of raw, undercooked fish or 
inadequately preserved fish infected by the parasites may cause human infection due to their 
pathogenicity (Rim et al., 1994; Lima dos Santos & Howgate, 2011). 
The main cause of diseases is the consumption of raw or undercooked fish in which parasites 
present are not killed. Approximately 50 helminthic parasites from fish may cause disease in man. 
The fish borne parasites come from three groups of parasites; namely nematodes (roundworms), 
trematodes (flukes), and cestodes (tapeworms) (ICMSF, 2005; Lima dos Santos & Howgate, 
2011). In addition, a study by Dorny et al. (2009) explained that various types of parasites could 
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infect fish and cause zoonotic infections in humans when consumed raw or not properly cooked. 
Most of the species have lifecycles involving several hosts.  
CHAPTER THREE 
3.0 METHODOLOGY 
3.1 Study design 
The study was in three parts: 
A cross-sectional survey to assess the food safety knowledge and practices of key players or 
stakeholders within the identified value chain through questionnaire surveys.  
A microbiological survey was also conducted along three value chains for the following fish: Lates 
niloticus, Oreochromis niloticus and Clarias anguillaris to assess quality and bacterial diversity 
through various stages of the respective value chains. These fishes were selected based on their 
availability, their economic importance, popularity and high commercial value in Medina Coura 
market. 
Fish samples were taken during two seasons (cold and hot), three different samples (fishes, water 
and Storage container) were taken at four areas (Selingue, Manantali, Markala and Mopti) at three 
sampling points (Capture, landing and selling). Water samples at the Capture points and swabs of 
storage containers were also taken for microbiological analyses.  
3.2 The study areas 
The study was carried out at the Medina Coura market and four (4) landing areas (Selingue, 
Manantali, Markala, and Mopti) from where fish is supplied to the market, between December 
2018 -February 2019 (cold season) and April-June 2019 (hot season). Medina Coura market, also 
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called Dossolo TRAORE market is located in Commune II of the District of Bamako. The study 
areas are depicted in figure 3.2.1. 
 
Figure 3.2.1: Map of Mali showing the landing beaches where the study was carried out 
3.3 Ethical clearance 
Ethical approval was obtained from the Ethics Committee of the National Institute of Research in 
Public Health (INRSP), Mali. The provisions relating to ethics were observed and respected 
according to the provisions of Law No. 2013-015 of 21 May 2013 on the Protection of Personal 
Data in the Republic of Mali and the Declaration of 'Helsinki 5 version 2013 to establish fact sheet, 
a free and informed consent form. Participation in the survey was on a voluntary basis. 
The inclusion criteria: Fishermen and wholesalers in the study areas above 18 years and who 
consented to participate in this study. 
 
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3.4 Survey on the knowledge and practices of Stakeholders of the freshwater fish value 
chains to the Medina Coura market 
The survey was targeted at fishermen and fish sellers. A total of 247 stakeholders (117 fishermen 
at the landing site and 130 vendors at the selling point) were interviewed in the value chain. The 
questionnaire comprised four sections: demographic characteristics, business characterization, 
food safety knowledge and personal hygiene practices (Appendix 1A, 1B). The declarations on the 
questionnaire were obtained from previous studies (Kunadu et al., 2016; Aboagye, 2016) and 
modified to correspond to the objective of the study. 
Fishermen were the first point of contact. They were asked about their activities, what types of 
fishing gear and canoes they used for their activities, what the three species frequently caught were, 
the period of successful fishing, how much fish they caught per day, how often they went fishing, 
who provided the resources necessary for their expeditions, to which groups of people they sold 
their catch and, finally what problems are encountered in their fishing activities (Appendix 1B). 
The value chain was then followed to identify the next group of participants. These are wholesalers 
or retailers operating at the Medina market (Appendix 1A). Questions related to the origin of the 
fish, the means of transport, the quantity of fish traded, how they detected spoiled fish and what 
they did with them, and difficulties they encountered during their work. 
All questionnaires were administered in the local language to the fishermen (Selingue, Manantali, 
Markala and Mopti) and to the sellers at the market; to determine the different fish handling and 
storage practices. Data were collected through face-to-face interviews. The interviewer entered 
responses given. The average completion time for one questionnaire was between 10-15 minutes. 
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3.5 Physico-chemical and microbiological analysis of samples 
3.5.1 Samples and Sampling methods 
3.5.1.1 Water sample at the capture point 
During this study, it was not possible to collect water samples from the exact location of the capture 
point in the river in the Selingue, Manantali and Markala areas as women are not allowed to go 
there. Three samples of river water were collected using a sterile 100 ml bottle (Falcon) at 3 
different locations on the surface of the water. Duplicate samples of water were taken at the river’s 
edge for Selingue, Manantali, Markala, and where the fish was taken for Mopti. Immediately, the 
bottle containing the water sample was properly closed and stored in a cooler with ice and 
transported to the laboratory. 
3.5.1.2 Swab sample from the storage container at the landing point 
Four swab samples were taken at each landing site from the basket used to transport fish to the 
selling sites in Bamako. Samples were taken by rubbing sterilized cotton swab over the inner-
surface of the storage container. The swab was inoculated into 9ml of sterile Peptone Buffered 
Water PBW. The tube was closed and stored in a cooler with ice for transport to the laboratory. 
The sampling was done before the basket was filled with fish.  
3.5.1.3 Fish sample from fishermen at the capture point: 
The sampling was done by convenience. Fish samples were purchased at the edge of the river from 
fishermen coming directly from the fishing point (Selingue, Manantali, Markala and Mopti). Four 
fish samples of each specimen were collected. The sampled fish were transferred to sterile plastic 
bags. The bags were sealed and put in the thermos cooler containing ice and transported to the 
laboratory for analyses. 
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3.5.1.4 Fish sample from wholesalers at the Landing point 
At each landing point, fresh fish samples were purchased from wholesalers before being 
transported to the Medina Coura market. Sampling of each fish type was done in duplicates and 
transported as earlier described. The fish samples were transported the same day to the laboratory 
at Bamako.  
3.5.1.5 Fish sample from wholesalers at the selling point 
Samples of fresh fish were purchased from wholesalers or retailers at the Medina Coura fish 
market. In the Medina Coura market, the fish were sampled from retailers who were recipients of 
the fish coming from the different landing points in each area. 
3.5.2 Analysis of samples 
3.5.2.1 Physico-chemical analysis of water samples 
The sample were collected for the determination of pH, recorded immediately after sample 
collection using a multi-parametric probe (mobile pH-meter, 604 Metrohm AG, Herisau, 
Switzerland). 
3.5.2.2 Microbiological analysis of samples 
The freshwater fish species were sampled from four (4) landing points (Selingue, Manantali, 
Markala, and Mopti) and the commercial hub, Medina Coura market, where the fish from the four 
landing points are retailed.  
3.5.2.2.1 Sample of fish for analysis 
Four (4) specimens of three (3) species of fish were sampled at each sampling point. The fish 
species were: 
- Nile perch: Lates niloticus, vernacular name in Bambara (Saalen); 
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- Tilapia: Oreochromis niloticus, vernacular name in Bambara (N'teben fin); 
- Catfish: Clarias anguillaris, vernacular name in Bambara (Maanogo Blen). 
 
Figure 3.5.1: Lates niloticus 
 
 
Figure 3.5.2: Oreochromis niloticus 
 
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Figure 3.5.3: Clarias anguillaris 
 
 
Figure 3.5.4: Map showing the different sampling points 
 
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Fish samples were purchased from various points of sampling by convenience sampling then 
placed in sampling bags. Water samples from the four (4) landing points (Selingue, Manantali, 
Markala, and Mopti) and swab samples of fish storage container surfaces, were collected as earlier 
described. A total of 300 samples were taken, 134 fish samples for bacteria and fungi analysis, 120 
fish samples for parasite analysis, 24 water samples and 22 swab samples of the fish storage 
containers (Table 3.5.1). 
Table 3.5.1: Number of samples collected during the study 
Sampling Sampling Number of fish species examined Number of Number 
areas  point L. niloticus C. anguillaris O. niloticus Water sample container 
examined sample 
examined 
CS HS CS HS CS HS CS HS CS HS 
Selingue Capture 5 4 5 4 5 4 3 3 N/A N/A 
(64) Landing 5 4 3 4 5 4 N/A  N/A 4 2 
Selling N/A 4 N/A 4 N/A 4 N/A N/A N/A N/A 
Manantali Capture 4 4 4 4 4 4 3 3 N/A N/A 
(64) Landing 4 4 4 4 4 4 N/A N/A 2 3 
Selling 4 4 2 4 2 N/A N/A N/A N/A N/A 
Markala Capture 4 4 2 4 2 4 3 3 N/A N/A 
(56) Landing 4 4 4 4 4 4 N/A N/A 3 2 
Selling 4 N/A 4 N/A 4 N/A N/A N/A N/A N/A 
Mopti  Capture 4 4 4 4 4 2 3 3 N/A N/A 
(70) Landing 4 4 4 4 4 4 N/A N/A 3 3 
Selling 4 4 4 4 4 4 N/A N/A N/A N/A 
Total 46 44 40 44 42 38 12 12 12 10 
Total 254 24 22 
N/A: Not Applicable (No sample were taken at this area) CS: cold Season, HS: Hot Season 
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The samples were transported in an isolated container with ice chest, to the laboratory for analysis. 
Bacteria and parasite were determined at the Central Veterinary Laboratory of Bamako. 
 
 
Figure 3.5.5: Samples in the cooler with ice for laboratory analysis 
 
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3.5.2.2.2 Analytical methods 
Samples were analyzed for bacteria and parasites. Bacteria characterization was done on spoilage 
and pathogenic microorganisms associated with fish using phenotypic methods. Prevalence and 
seasonal distribution of parasites in the sampled fish species were determined. 
To analyze the samples, suspensions and decimal dilutions were performed according to standard 
AFNOR (2004) i.e French Standardization Association. In the samples, the Aerobic Plate Count 
(APC), Total Coliforms (TC), Thermo-tolerant Coliforms or Fecal Coliforms (FC), spores of 
Sulphite Reducing Bacteria, presumptive Staphylococcus aureus were enumerated, presence of 
Salmonella spp. was also determined.  
According to the manufacturer’s instructions, all microbiological media were prepared and 
sterilized (Appendix 2). The overnight incubation was done for each media and diluents for 
sterility check at their respective temperatures for the required time prior to use for microbiological 
assessments. 
3.5.3 Sample preparation 
Samples of the fish were collected. An amount of ten grams of each sample was taken from the 
skin, flesh, intestines and gills of each fish sample with sterilized scissors and knife and added to 
a 90 ml of 0.1% Buffered Peptone Water (BPW) to prepare an initial dilution. The samples were 
transferred to the stomacher model 400 and blended for 1 to 2 min. 
One (1) ml of this suspension was transferred aseptically into each tube in dilutions of 10-1 to 10-5 
in sterile Petri dishes. The serial dilutions were carried out for the various microbial counts 
described above and according to the methods applied by the International Commission for 
Microbiological Specifications for Foods (ICMSF, 2005). 
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Figure 3.5.6:10 g of the sample in 90 ml of Buffered peptone water 
3.5.2 Enumeration of microflora 
3.5.2.1 Enumeration of the Aerobic mesophilic (Aerobic Plate Counts) 
Plate Count Agar PCA (Sigma- Aldrich) was used for enumeration. One (1) mL inoculum from 
appropriate serial dilutions were transferred into sterile petri dishes. The sterilized molten PCA 
was cooled in a water bath to 50°C and poured onto the inoculum using the pour plate technique. 
Then, rotary movements were done to homogenize the mixture. After solidification, the second 
layer of 5 to 7 ml of PCA was added to limit the contamination. The inoculated plates were 
incubated at 30°C for 72 hours. All colonies that grew between the two layers were counted using 
a colony counter with a magnifying glass. Plates containing 30 to 300 colonies were counted and 
recorded. All counts were reported as the logarithm to base 10 of colony-forming units per gram 
(Log10 CFU/g). 
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3.5.2.2 Enumeration of Total Coliforms 
The culture was carried out on Violet Red Bile Agar (VRBA, Sigma- Aldrich) by the double-layer 
method. The sterilized molten VRBA was cooled in a water bath to 50°C. Appropriate serial 
dilutions were enumerated by pour plate overlay method as described in 3.6.1.  
The incubation was carried out at 30°C for 24 hours. Only very red colonies with a diameter greater 
than 0.5 mm were enumerated. 
3.5.2.3 Enumeration of fecal or thermo-tolerant coliforms 
The culture was carried out on VRBA (Sigma- Aldrich) as before by the double-layer method. The 
medium was cooled in a water bath to 50°C. The enumeration was made at the dilution 1/10; 1 ml 
of dilution is introduced into a Petri dish to which the VRBA has been added. After solidification, 
a second layer was poured on the surface as before. The incubation was carried out at 44°C for 48 
hours. Only very red colonies with a diameter greater than 0.5 mm and having grown deep were 
counted. 
3.5.2.4 Enumeration Sulphite Reducing Bacteria 
Reinforced Clostridial Agar RCM (Becton Dickinson) was used for the enumeration of Sulphite 
Reducing Bacteria. A quantity of the suspension was boiled at 80°C for 15 minutes to eliminate 
the vegetative forms. The enumeration was made at the dilution 1/10; 1 ml of dilution from a boiled 
suspension is introduced into a Petri dish to which the RCM agar has been added. After 
solidification, a second layer was poured on the surface as before. The incubation was carried out 
at 37°C for 48 hours in anaerobic jars. The large black colonies were selected and counted. 
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3.5.2.5 Enumeration of Staphylococcus aureus 
The cooled, melted Mannitol Salt Agar (Scharlau) was poured into a Petri dish. After solidification, 
0.1 ml of the 1/10 solution was spread over the entire surface of the plate and incubated at 37°C 
for 24 hours. Mannitol salt agar was used to presumptively identify Staphylococcus aureus which 
appear as golden yellow colonies. Colonies were selected and counted. The colony on Mannitol 
Salt Agar was added to 0.5 ml of reconstituted rabbit plasma (Bactident Coagulase EDTA, Merck 
KGaA and Darmstadt, Germany). After mixing by gentle rotation, the tubes were incubated at 
37°C. Clotting was evaluated at 30 min intervals for the first 4 h of the test and then after 24 h 
incubation. The reaction was considered positive, if any degree of clotting was visible within the 
tube when tilted. 
3.5.2.6 Detection of Salmonella spp. 
Twenty-five grams of fish samples were homogenized in 225ml of Peptone Buffered Water (Difco, 
BBL/USA) 
- The pre-enrichment: was carried out by incubating the suspension for 24 hours at 37°C. 
- Enrichment: 1 ml of the pre-enrichment medium was seeded in a tube containing 10 ml 
of Selenite Cysteine Broth (Difco) and incubated at 37°C for 24 hours. 
- Isolation: a drop of Selenite Cysteine Broth was streaked on dried plates of Salmonella-
Shigella Agar (Conda pronadisa) previously poured and solidified. 
The inoculated plate was incubated at 37°C for 24 hours. Colorless colonies with a black center 
are considered presumptive Salmonella spp. Presumptive Salmonella were purified on nutrient 
agar. The isolates were further identified biochemically. 
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3.5.2.7 Detection of Pseudomonas spp. 
Pseudomonas was detected on King A and King B medium. For this, two petri dishes containing 
King A and two petri dishes King B agars were inoculated with the first dilution and incubated at 
37°C for 24 hours. The first plate was used to determine fluorescence of bacterial colonies under 
Ultraviolet light, and the other for purification and biochemical characterization.  
The presence of diffusible pigments results in the appearance of a color, which can diffuse 
throughout the plate: 
- The blue color on King A medium (presence of pyocyanin), 
- Fluorescent yellow-green color on King B medium (presence of pyoverdin). 
3.5.2.8 Detection of other pathogenic bacteria 
Suspect Salmonella colonies were isolated and purified on Trypton Soy Agar TSA (Liofilchen) 
for biochemical testing. 
Table 3.55.2: Summary of microbiological media and culture conditions for detection and 
enumeration of bacteria 
Germs Media References Incubation Temperatures 
Aerobic Plate Count (APC)  Plate Count Agar (PCA) NF V08-051 30°C for 72H 
Total Coliforms Violet Red Bile Agar (VRBA) NF ISO 4831 30°C for 24H 
Thermo-Tolerant Coliforms Violet Red Bile Agar (VRBA) NF ISO 4831 44°C for 24H 
(Fecals) 
Sulphite Reducing Bacteria Reinforced Clostridial Agar (RCM) NF V 08-061 37°C for 24H 
Presumed pathogenic Chapman NF EN ISO 6888-1 37°C for 24H 
staphylococci 
Salmonella Peptone water NF V 08-052 37°C for 18H 
Selenite cysteine Broth 42°C for 24H 
Salmonella- Shigella Agar 37°C for 24H 
Spoilage microorganisms King A, B NFV04-505-1988 37°C for 24H 
 
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The results of the bacteriological analyses were interpreted according to the 2-class plan regarding 
the microbiological criteria for fresh animal products (French legislative and regulatory guide, N° 
8155 of 12 December 2000). 
3.5.3 Isolation, characterization and identification 
Representative colonies on the King A and King B Agar for detection of the spoilage 
microorganisms and Salmonella- Shigella Agar for Pathogenic microorganisms were isolated and 
characterized. Two suspect colonies were taken from each plate. These colonies were purified 
using a buttoned Pasteur pipette on Trypton Soy Agar TSA (Liofilchen). The incubation was 
carried out at 37 ° C for 24 hours, and the isolated colonies were repetitively sub-cultured until 
pure cultures were obtained.  
3.5.3.1 Macroscopic characterization 
After 24 hours of incubation of the cultures, the colonies were observed. The size, appearance of 
the surface, the shape of the outline, the color, the consistency and the elevation of the colonies 
were observed. 
3.5.3.2 Microscopic observation 
The microscopic examination was used to determine the form of the microbial cells, their gram 
stain and initial grouping of the isolates (Appendix 3). From a pure culture, the smear produced on 
a slide was fixed and stained with gentian violet for 1 minute, and then the slide was rinsed with 
demineralized water. A few drops of Lugol iodin were placed on the slide to strengthen the 
adhesion of the dye for 20 seconds. The slide was discolored using alcohol for (5-10 seconds). 
Rinsed under a trickle of demineralized water, it was recolored by adding fuchsin for 1 minute. 
Finally, the slide was rinsed gently with deionized water and dried. The slide thus prepared was 
observed at 100X objective (G 1000X) in a drop of immersion oil. 
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3.5.3.3 Biochemical characterization of isolates 
The characterization of the isolates was done using the catalase and oxidase tests as well as API 
20NE for the colonies on King A and King B Agar and API 20E for the colonies on S-S Agar. 
This gallery included 20 micro tubes containing dehydrated substrates. 
- Catalase test 
The catalase test was based on the decomposition of hydrogen peroxide (H2O2) into H2O and O2, 
which is released according to the reaction stated below: 
2 H2O2 → 2 H2O + O2 
A few drops of hydrogen peroxide were placed on a slide. Using a sterile buttoned Pasteur pipette, 
a portion of the colony to be identified was removed and placed in the H2O2 solution. The 
formation of bubbles (release of oxygen resulting from the decomposition of the peroxide) 
signified a positive reaction (catalase +). 
- Oxidase test 
Oxidase testing involved looking for the presence of a cytochrome (presumably cyt C) present in 
the respiratory chain. This presence was revealed by the ability of the bacteria to oxidize the 
reduced colorless form of N-methylated derivatives of paraphenylenediamine. Oxidation leads to 
the purplish-pink semi-quinone form. For this test the soluble reagent was used. The colony 
identified was deposited using a buttoned pipette on the blotting paper previously impregnated 
with the reagent. Oxidation of the reagent was manifested by the appearance of purple coloration. 
- Coagulase test  
Coagulase test was used to differentiate between the non-coagulase producing Staphylococcus 
from the coagulase producing staphylococci. Mannitol salt agar was used to presumptively identify 
Staphylococcus aureus which appeared as golden yellow colonies. Plates were incubated 
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aerobically at 37°C for 24 h. Colonies were selected and counted. The colony on Mannitol Salt 
Agar was added to 0.5 ml of reconstituted rabbit plasma (Bactident Coagulase EDTA, Merck 
KGaA, and Darmstadt, Germany). After mixing by gentle rotation, the tubes were incubated at 
37°C. Clotting was evaluated at 30 min intervals for the first 4 h of the test and then after 24 h 
incubation. The reaction was considered positive, if any degree of clotting was visible within the 
tube when tilted. 
- Biochemical identification on API 20NE system 
API 20NE is a standardized system for the identification of non-fastidious, non-enteric Gram-
negative rods. A pipette was used to pick up 1-4 colonies of identical morphology from the agar 
plate. NaCl 0.85 % Medium, 2 ml (Ref. 20 070) was used to make the suspension. Suspension 
touches were prepared with a turbidity equivalent to 0.5 McFarland Standard (Ref. 70 900). 
Inoculate test NO3 to PNPG was done by distributing saline suspension into the tubes using the 
same pipette. 
The tubes and cupules of test GLU and PAC with the suspension. Mineral oil was added to the 
cupules of the 3 underlined tests (GLU, ADH, URE). The incubation box was closed and incubated 
at 30° C for 24 hours. The reagents: JAMES (Ref. 70 542) NIT 1 + NIT 2 (Ref. 70 442), Zn (Ref. 
70 380) were added. The strip was read by referring to identification software V 7.0. 
- Biochemical identification on API 20E system 
API 20E system is an identification system for Enterobacteriaceae and other non-fastidious Gram-
negative rods. It has 20 microtubes containing API M Medium (Ref. 50 120) which are dehydrated 
substrates. Colony of the bacterial strains (isolated colonies) of the 24 hours’ cultures was added 
to the saline solutions of 5.0 ml of 0.85% NaCl (Ref. 20 070) and vortexed to form a bacterial 
suspension. A bacterial suspension of about 0.5 McFarland Standard (Ref. 70 900) was used for 
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inoculation. Each of the microtubes in the test was filled with the bacterial suspension using a 
sterile Pasteur pipette. Mineral oil (Ref. 70 100) was used to create anaerobiosis: Interpretation of 
the test results was made by dropping a media: TDA (Ref. 70 402), JAMES (Ref. 70 542) and VP 
1 + VP 2 (Ref. 70 422) - API 20 E identification software (consult bioMérieux) bioMérieux® was 
used to do the reading. 
3.5.4 Parasitic analysis  
Two (2) specimen of each of the three (3) species of fish were purchased at the Capture point, at 
the landing point where the fishes are packed for the market and at Medina Coura market (selling 
point). The samples were transported directly to the helminthology laboratory of the Central 
Veterinary Laboratory of Bamako in a cooler, where they were subjected to parasite analyses. 
Dissection was performed on each fish sample; Skin, flesh, gills and abdominal cavity were 
observed macroscopically. The macroscopic observation was made by observing the general state 
of each sample; the level of skin damage, observation of the flesh to see if there was a presence or 
absence of cyst or larva, state of the gills (pink color, sharp and no attack) the presence of 
crustacean, observation in the abdominal cavity of a parasite, larva, and cyst, and finally the 
coprological result was determined. The fish were also examined under the Olympus BO61 
binocular magnifier for the presence of cysts.  
3.6 Statistical analysis 
The results of the analysis were synthesized and processed using the Microsoft Excel 2016 spread 
sheet. Descriptive statistics such as means, standard deviations and frequencies were used to 
analyze microbial counts. Analysis of variance (one-way ANOVA) was used to test the multi 
interaction effect of the two seasons, various areas, different sampling points (capture, landing and 
selling) and fish species. pH was tested for statistical significance (p=0.05). 
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The means were data from three independent experiments for microbial counts of fresh and 
processed fish. Frequency calculation, averaging and variance analysis (ANOVA) were performed 
with SPSS v 23.0 software. Tukey HSD post-hoc analysis was performed to further identify 
significant differences within sample groups and within value chains. 
For the parasitic analysis, the results were analyzed for the following parameters Margolis et 
al.(1982).  
Prevalence (%) = number of infected hosts × 100 / total number of hosts examined. 
The one-way analysis of variance (ANOVA) was applied to determine the significance of 
variations in the prevalence of infection between the two seasons of the study period. The 
percentages of infestation were compared by the chi-square test. The SPSS 23.0 program was used 
for all statistical tests and the security level chosen was 95%. 
  
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CHAPTER FOUR 
4.0RESULTS AND DISCUSSION 
4.1 Survey on food safety knowledge and practices of freshwater fish value chain 
stakeholders 
4.1.1 Demographic characteristics of stakeholders along the fish value chains 
In all 247 respondents participated in this study. 130 respondents worked in the market of Medina 
Coura as fish sellers and 117 were in the capture point as fishermen in various areas of sampling 
(Table 4.1.1). Among the respondents in the market, the sale of fresh fish was dominated by 
women (84.6%), except for fishing areas where the fishermen were all men. Similar studies have 
also reported a higher proportion of women than men in sales, where both men and women have 
distinct roles in fish value chains (FAO, 2013; Kunadu et al., 2016; Iwu et al., 2017; Aboagye, 
2016; Mgqibandaba et al., 2020). According to FAO (2013), women are dominant in the secondary 
sector, which is handling, conservation and processing of fishery products, especially in activities, 
which are generally considered appropriate activities for women given their home tasks and 
responsibilities related to family care. The predominance of women in the sales sector could be 
attributed to their traditional responsibilities of housework and childcare. Through these income 
generating activities, women are able to contribute to the household income and therefore play a 
key role in poverty mitigation and food security (Omemu & Aderoju, 2008; FAO, 2013).  
The majority of respondents that participated in the study were over 40 years of age. This could 
be explained by the fact that the choice of respondents was made according to the duration and 
stability in the field. These were also similar to the results of Mgqibandaba et al. (2020) whose 
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survey revealed that 40% of their respondents were between 31 and 40 years old and that of 
Kunadu et al. (2016) of which 31% were between 36-50 years old. 
The majority of fishermen (78.6%) had no formal education, and sellers had an incomplete basic 
school education (53.1% middle school and 40.0% primary school); this is in agreement with other 
studies carried out by Zanin et al. (2015) where 51.8% had an incomplete basic school education 
and that of Aboagye (2016) in Ghana that 32% of fishermen had no formal education. This could 
be an impact on the safe delivery of fish and result in a change in food handling behavior. Majority 
of the sellers were Bambara (48.5%) and the fishermen were Bozo (64.1%). This is because in 
Bamako, Bambara is the main ethnic group and fishing belongs to the Bozo or the sedentary 
professional fishermen for whom fishing represents a full-time economic activity (Konare, 1977). 
For the seller study population, 65.4% were wholesaler while 33.8% retailer in Mali. In Mali, the 
marketing circuit for fresh fish shows that the wholesaler at the same time serves as the retailer or 
the consumer from which he is most favored. The retailer is the least favored because the fish from 
this outlet is more expensive (Traore, 2014). 
For the fishermen, the level of experience in fishing activities ranged from 0-40 years with a 
majority (85.5%) having between 31-40 years. According to FAO (2013), family communities that 
practically monopolize the fishery sector operate in the sector. 
  
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Table 2: Demographic characteristics of the study population 
Variable     % Stakeholder (n)  
      Sellers (n=130) Fishermen (n=117) 
Gender  Male   15.4 (20)  100(117) 
   Female  84.6 (110)  0 
Age   18-24 yrs  0   9.4(11) 
   25-29yrs  1.5(2)   5.1(6) 
   30-39yrs  20(26)   24.8(29) 
   > 40yrs  78.5(102)  60.7(71) 
Ethnic Group  Bozo   29.2(38)  64.1(75) 
   Bambara  48.5(63)  18.8(22) 
   Malinke  6.2(8)   10.3(12) 
   Songhai  2.3(3)   0.9(1) 
   Soninke  3.1(4)   2.6(3) 
   Fulani   10.8(14)  3.4(4) 
Educational Level Middle School 53.1(69)  0 
   Secondary  3.1(4)   0.9(1) 
   Primary  40(52)    20.5(24) 
   No formal education 3.8(5)   78.6(92) 
Stakeholders  
   Wholesaler  65.4(85)   100(117) 
   Wholesale-Retailer 33.8(44)   0 
   Retailer  0.8(1)    0 
Number of years 1 – 10   5.4(7)    4.3(5) 
 in fishing activity 11-20    24.6(32)   10.3(12) 
   21-30   25.4(33)   0 
   31-40   44.6(58)   85.5(100) 
n: frequency 
4.1.2 Business characteristics 
Table 4.1.2 shows how business takes place in the fresh fish sales process. In Medina Coura 
market, fish come from different areas; 8.5% are sourced from Mopti and Markala, 52.3% from 
Mopti-Segou-Manantali, 25.4% Mopti-Selingue-Gao- Manantali and 13.8% from Mopti-Selingue. 
These data are in agreement with those obtained by FAO (2007), which assert that the major 
capture sites are, in order of importance, the Central Delta of Niger at Mopti (80,000 to 90,000 
tons of fresh fish), Lake Selingue (4,000 tons of fresh fish) and Lake Manantali (3,000 tons of 
fresh fish). 
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The means of transportation of fish to the retail market was mainly by public transport (Car) 99.2%. 
However, the process of transporting fish to Bamako is trouble laden. The problems include among 
others, the socio-political crises or uncontrolled or sometimes restrictive administrative and 
customs procedures, and especially the instability in the northern part of the country, causing the 
majority of fishermen to abandon their activities. Poor transport could lead to a decrease in the 
shelf life of the fish, and the degradation of the fish leading to a drop in the price of the product 
(Diei-Ouadi & Mgawe, 2011). The time taken to sell 80% of fish stock on the market is 2-3 days. 
Fifty percent of sellers believe that the quantity of spoiled fish is low. Post-harvest losses during 
fishing activities is a major concern since it is equivalent to the loss of animal protein for 
consumers and a loss of income for fishermen, processors and traders (FAO, 2007). In Medina 
Coura market the sellers receive their fish in basket but they sell by kilo.  
  
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Table 3: Frequency of fishing businesses doing by the fish sellers 
Variable  Categories    % Sellers (n=130) 
 
Origin   Mopti-Markala    8.5 (11) 
   Mopti-Segou-Manantali   52.3 (68) 
   Mopti-Selingue-Gao-Manantali  25.4 (33) 
   Mopti-Selingue    13.8(18) (5) 
Means of transport  
   Car (public transport)   99.2 (130) 
   Refrigerated truck   0.8(1) 
Flow time of fish 2-3 days    46.9 (61) 
   7 days     0.8(1) 
   1 day     46.2(60) 
   3-4 days    4.6(6)      
With what measure do you sell your fish in the market?  
   In weight (Kg)    100(130) 
   Per basket     0 (0%) 
How many kg of fish can one basket contain?     
   300kg      65.4(85) 
   600kg     34.6(45) 
How many baskets do you take from various areas?   
4-6 Baskets    64.6(84) 
   1-3 Baskets    33.1(43) 
   1-7 tons    0.8(1) 
   1 ton     1.5(2) 
What is the frequency of reception of fish per week?  
2 -3 days    1.5(2) 
   4-5 days    15.4(20) 
   6-7 days    83.1(108) 
    
How long does it take before the fish gets to the market? 
   >24hrs     33.1(43) 
   11-15 hrs    63.8(83)  
   6-10hrs     3.1(4) 
Can you estimate the average amount of spoiled fish per batch? 
   1-5 fish     53.8(70) 
   6-10 fish    14.6(19) 
   11-20 fish    31.5(41) 
Have you encountered sick fish in the lot you selling?  
   Yes     100(130) 
How do you display the fish for sale?  
   On floor mat    93.8(122) 
   On the table    6.2(8) 
How do you store fish during the sales period?  
   In a broken fridge with ice  100(130) 
n: frequency 
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The fishing gears used by fishermen vary depending on the area (Table 4.1.3). Malian fishermen 
use a wide range of gear and catching techniques, adapted to changing conditions, to the 
environment depending on the season (Kodio & Keita, 1999; FAO, 2007). Exposure of fishing 
gear-containing fish for long periods could lead to spoilage of the fish, especially at elevated 
temperatures. In some areas, either the number of canoe owners is low or some fishermen do not 
have the financial means to have motorized canoes. 
According to the fishermen respondents, there is no difficulty in selling freshly caught fish. Once 
they land in, the women come to take them as wholesalers to sell them locally or send them to 
Bamako for sale. 
Fishermen face a lot of difficulties resulting in a huge loss in their activities. The survey showed 
that these difficulties include the mining in the area of Selingue, depletion of fish in the river, theft 
of fishing gear and also insecurity in the Northern part of the country. According to Olagunju 
(2015), over the past two decades, drought and demographic factors (increase in the fishing 
population) have contributed to reducing fishermen's income as well as economic returns, 
technical and economic factors (diversification of fishing gear and increased fishing effort) and 
commercial factors such as poor valuation of products, reduction in the quantity of marketable 
fish. 
  
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Table 4:Business activities of fishermen in selected fishing areas 
Variables Categories   Areas % (n) 
      Selingue (31) Manantali (25) Markala (31)    Mopti (30) 
What fishing gear do you use for fishing?  
Gill net    80.6(25)  40(10)  100(31)  60(18) 
  Cast net    6.5(2)  -  -  7(11)  
  Fishing net   12.9(4)  4(1)  -  - 
  Seine net   -  56(14)  -  3.3(1)  
What types of fishing canoes do you use?  
%Canoes non-motorized  -  -  100(31)  16.7(5)  
%Canoes motorized  100(31)  100(25)    83.3(25) 
How do you do your fishing activities?  
The nets are left at 4 p.m. and collected overnight  
100(31)  28(7)  96.8(30)  73.3(22) 
Spend 4 to 5 days in the lake -  8(2)  -  - 
Spend 5 to 7 days in the lake -  64(16)  -  - 
Spend less than 2 hours in the river -  -  3.2(1)  26.6(8) 
Which period of the year is fishing most beneficial to you?  
February - September  100(31)   -  -  - 
  June - August   -  100(25)  -  - 
  November - January  -  -  100(31)  100(30) 
What is a average quantity of fish you harvest by shipment?  
1-20Kg    96.8(30)  16(4)  74.2(23)  40(12) 
  21-40Kg   3.2(1)  8(2)  16.1(5)  13.3(4) 
  41-60Kg   -  16(4)  3.2(1)  26.7(8) 
  61-80Kg   -  8(2)  -  3.3(1) 
  >100Kg    -  52(13)  6.5(2)  16.7(5) 
How often do you go fishing?  
4-5 Days/week   3.2(1)  16(4)  -  6.7(2) 
  6-7 Days/week   96.8(30)  81(21)  100(31)  93.3(28) 
In average, how much time do you spent on each shipment?  
> 2hrs    -  -  -  46.7(14) 
  2-6hrs    96.8(30)  100(25)  96.8(30)  36.7(11) 
  7-12hrs    3.2(1)  -  3.2(1)  16.7(5) 
What are the problems you are having?  
The use of pesticides in water by miners (cyanide, Mercury)  
87.1(27)  -  -  - 
  Lack of fish in a water  3.2(1)  44(11)  51.6(16)  30(9) 
  Lack of ice and storage material 9.7(3)  56(14)  9.7(3)  40(12) 
  Theft of fishing gear  -  -  9.7(3)  3.3(1) 
  Insecurity in a North of the country -  -  9.7(3)  26.7(8) 
n: Frequency 
4.1.3 Food Safety Knowledge 
From this study, it is shown that the respondents had a good knowledge of food safety (Table 
4.1.4). A similar study done by Grema et al. (2018), indicated the importance of food safety 
knowledge of food handlers. It reported that good knowledge mostly translates into positive 
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behaviour and practices leading to safe food production and handling. All personnel involved in 
food handling must maintain good hygiene, and a high degree of cleanliness to ensure food safety 
in food preparation, and to avoid contamination of the diet with pathogenic microorganisms 
(Howes et al., 1996). 
The study revealed that the level of knowledge could be significantly associated with the food 
hygiene practices. This was consistent with the study by Iwu et al.(2017) in Nigeria, where 
knowledge, attitude and training were significantly associated with the practice. On the contrary, 
a study in Nigeria by OTU (2014), suggested that knowledge was not linked to practice and that 
this was attributed to the existing socio-cultural context that probably had a greater influence on 
safe eating practices. 
Table 5: Responses to questions on food safety knowledge by fish sellers 
Variable       Categories %Fish sellers (n) 
 
Do you know spoilt fish?      Yes   100(130) 
Do you know what causes fish spoilage?    Lack of ice   64.6(84) 
        Broken down car  34.6(45) 
Insanitary condition of sale 0.8(1) 
Do you think the way the fish is handled contributes to its spoilage? Yes   100(130) 
Have you encountered sick fish in the lot you are selling?  Yes   100(130) 
If yes, please describe the state of the spoiled fish   Texture change  47(61) 
        Change in eye color 15.4(20) 
        Discoloration  10(13) 
         Fish swelling  27.2(36) 
Do you think the infected fish could cause illness?   No   74.6(97) 
        Yes   25.4(33) 
If yes, which kind of disease?      Abdominal pain  15.4(20) 
        Diarrhea   84.6(110) 
What measures could be taken to ensure that the fish in our local markets are healthy and safe for human consumption?
    Need a refrigerated truck for transport, and a cold room 83.1(108) 
    Financial aid      0.8(1) 
    Vehicle stop by customs for a long time   9.2(12) 
    Unsanitary conditions, lack of evacuation system  6.9(9) 
n: frequency 
  
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Table 6:Responses to questions on food safety knowledge by fishermen 
Variable   Categories %Areas (n=117) 
      Selingue Manantali Markala Mopti 
Are you able to identify fish which is going bad or spoilt? 
    Yes  100(31)  100(25)  100(31)  100(30) 
    No  -  -  -  - 
Do you think the way the fish are handled could contribute to their spoilage?  
Yes  100(31)  100(25)  100(31)  20(6) 
    No  -  -  -  80(24) 
n: frequency 
4.1.4 Food Safety practices 
Table 4.1.6 shows that all fish sellers received the fish from different areas in baskets with ice. At 
Medina Coura market, unsanitary conditions of the sales outlets were observed. Fish was stored in 
broken-down freezers with ice and the fish was displayed on a mat on the floor for sale, sometimes 
without ice. The breaking of the cold chain following the use of broken-down freezers with their 
walls covered with rust, in which worn bags were placed to prevent their contact with the products 
and the escape of cold produced by ice are improper techniques. According to the FAO & WHO, 
(2012) fish sale areas must be in good condition, durable and easy to maintain and disinfect. 
Appropriate and adequate facilities must be provided for the storage and / or production of ice. 
Table 7: Responses to questions on food safety practices by fish sellers 
Variables      Categories  % Sellers (n=130) 
How do you store fish during the sales period?  In broken fridge with ice 100(130) 
Cold-store refrigeration  0(0) 
In which condition does the fish arrive on the market? Basket with ice  100(130) 
Basket with wet sand 0(0) 
Basket with wet cloth 0(0) 
How do you display the fish for sale?   On floor mat  93.8(122) 
       On table   6.2(8) 
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n: frequency 
In all the areas, the majority of the respondents lose their fish after capture due to spoilage (Table 
4.1.7). The loss of fresh fish could be due to the inadequate use of ice from capture to sale, in the 
market the use of freezers without insulation, the practice of exposing fish on the ground at room 
temperature is often high. During transport, the delay is often due to vehicle breakdown, or 
stopping of the vehicle by customs officers. At the landing point, the fish are not washed in potable 
water, contrary to stipulations by the FAO & WHO (2012) that water for cleaning fish must be 
potable to avoid cross-contamination. 
Table 8: Responses to questions on food safety practices by a fishermen 
Variable   Categories % Areas (n=117) 
      Selingue Manantali Markala Mopti 
Do you sometimes lose fish? Yes   100(31)  100(31)  87.1(27)  66.7(20) 
    No  -  -  12.9(4)  20(6) 
    Rarely  -  -  -  13.3(4) 
If not, please describe how you handle your catch to avoid spoilage?  
Bringing the ice 93.5(29)  100(25)  -  70(21) 
 Go fishing very early in the morning 3.2(1)  -  -  - 
    Speed  3.2(1)  -  6.5(2)  3.3(1) 
    Nothing  -  -  93.5(29)  26.7(8) 
What have you done with the spoilt fish?  
Sell it to retailers at low cost  100(31)  4(1)  -  13.3(4) 
 Sell it to wholesalers at low cost  -  96.0(24)  100(31)  3.3(1) 
   Self-processing  -  -  -  46.7(11) 
   Retailer   -  -  -  36.7(11) 
 
n: frequency 
4.1.5 Relationship among age, education, and fish safety knowledge and practice of the fish 
sellers 
Table 4.1.8 presents the results of the relationship between age, duration of service, fish safety 
practice and knowledge. The analysis of the table reveals that fish safety knowledge of the vendors 
has a significant positive impact on their safety practices. This result implies that the more educated 
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the vendors are the more knowledge they have and the more their fish handling behavior will be 
positively influenced. This means regular training and workshops will greatly improve their fish 
safety knowledge and practice. Additionally, the age and educational status of the vendors also 
have a positive influence on their knowledge; implying that, the older they are and the more 
educated they are, the better their handling practices of fish along the value chain. The results 
differ from the findings of Grema et al.(2018) in Kaduna State, Nigeria, that indicated that most 
fish sellers had good knowledge of food hygiene practices such as hand washing; however, 
knowledge about hygienic handling of fish could not be translated into practice. This study 
supports the findings of a study done by Amuna (2014) which also reported that food handlers 
tend to overestimate the frequency with which they carry out safe food handling practices 
Table 9: Bivariate correlation of age and education with food safety knowledge and food 
safety practice using Spearman’s rho coefficient 
Predictors    Correlation Coefficient             P-Value  
Food safety knowledge VRS Food safety practice        0.249**  0.007 
Age VRS Food safety knowledge                               0.262**  0.004 
Education VRS Food safety knowledge  0.384**                0.000 
**. Correlation is significant at the 0.01 level (2-tailed). 
4.1.6 Relationship among age, duration of service, and food safety knowledge and practice 
of the fishermen 
Bivariate Spearman’s rho correlation coefficient was used to investigate whether or not knowledge 
has any influence on fishermen’s fish safety practice, and also to find out if age and duration of 
service have any influence on their knowledge. The results displayed in Table 4.1.9 reveal that 
food safety knowledge significantly influence the food safety practices of the fishermen (P < 0.05); 
however, age and duration of service have no effects on food safety knowledge of the fishermen 
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(P > 0.05). This means that the more food safety training and workshops are organized for the 
fishermen to improve their knowledge, the more it will enhance their food safety practices. Besides 
the food safety knowledge of the fishermen is not influenced by length of service in the fishing 
business nor their age. This finding is similar to findings of Grema et al.,(2018) which found a 
positive correlation recorded between knowledge and practices (rs = 0.2, P = 0.23) but negative 
correlation (n) between practices with years of business experience (rs = -0.03, P = 0.830). 
Table 10: Bivariate correlation among age, education and food safety practice and 
knowledge using Spearman’s rho coefficient 
Predictors     Correlation Coefficient    P-Value 
Food safety knowledge VRS Food safety practice  -0.231*    0.012 
Age VRS Food safety knowledge    0.053    0.573 
Duration of Service VRS Food safety knowledge  -0.043    0.643 
**. Correlation is significant at the 0.01 level (2-tailed). 
4.2 Physico-chemical analysis of water and fish in the freshwater fish value chain 
4.2.1 Determination of pH of water, and pH of fish species 
The pH values of the surface water recorded ranged from 5.05 to 5.6 during the cold season and 
5.1 to 5.9 during the hot season (Figure 4.2.1). According to AMANORM (2011) (Malian Agency 
for Standardization and Promotion of Quality, pH standard of water must be between 5.5 and 9. 
The average pH value of the water remained slightly acidic, i.e., between 5.05 and 5.9 throughout 
the study periods and it was found slightly higher during the hot season. This may be due to a 
higher water temperature during this period, which could cause the conversion of CO2 to organic 
carbon by the process of photosynthesis.  A similar study done by Merhabi (2020) in Libya, also 
found the pH of the water to be slightly acidic. The pH of the water can have a significant influence 
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on the toxic action on fish due to the presence of hydrogen sulfide, ammonia, cyanides and also of 
heavy (Pedrosa‐Menabrito & Regenstein, 2007). 
The pH values of the fish samples are listed in Table 4.2.1. The values vary from 6.1 ± 0.3 to 6.9 
± 0.6 during the cold season and 6.2 ± 0.2 to 6.9 ± 0.6 during the hot season. The values for the 
various seasons are not, statistically, significantly different (p≤0.05). In the cold season, samples 
of Oreochromis niloticus in Mopti had higher pH at the capture point while samples of Clarias 
anguillaris in Markala had lower pH at the landing point. In the hot season, samples of Lates 
niloticus in Manantali had higher pH at the selling point and lower pH at landing point. 
The values of pH recorded were close to that of well-preserved harvested fish (pH of 6.2- 6.9). 
The pH measurements in this study were carried out 4 to 9 hours after the death of the fish, 
depending on the place of sampling. The low pH encountered a few hours after harvest may also 
indicate that the fish was not harvested under the right conditions and that they must have been 
stressed. The glycogen in fish muscle had been metabolized to lactic acid, causing a drop from the 
typical pH of ≈ 7.0 of live fish muscle. The pH is one of the important parameters for determining 
the quality of fish flesh during storage (Abbas et al., 2008). According to Degnon et al.( 2013), 
after the death of the fish, the initial pH varies from 5.4 to 7.2.Acid pH leads to gill damage while 
alkaline pH leads to super oxygenation (Ikeogu et al., 2010). 
 
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6 5,9
5,8 5,7
5,6
5,6 5,5
5,4
5,4 5,3
5,2 5,1
5,05
5
4,8
4,6
Cold season Hot Season Seson
pH of Water
Selingue Manantali Markala Mopti
 
Figure 4.2.1:Mean value of water pH during the 2 seasons 
Table 4.2.1: Mean values of pH of fish species sampled in different seasons 
Sampling Selingue Manantali Markala Mopti 
Fish species 
point Cold Hot Cold Hot Cold Hot Cold Hot 
L. niloticus 6.3 6.5 6.4 6.6 6.8 6.6 6.5 6.6 
Capture C. anguillaris 6.6 6.8 6.5 6.7 6.6 6.3 6.4 6.6 
O. niloticus 6.5 6.3 6.3 6.3 6.2 NA 6.9 6.5 
L. niloticus 6.6 6.5 6.7 6.7 6.7 6.2 6.5 6.5 
Landing C. anguillaris 6.8 6.5 6.4 6.7 6.1 6.5 6.7 6.5 
O. niloticus 6.2 6.5 6.4 6.7 6.4 6.6 6.6 6.5 
L. niloticus NA 6.6 6.4 6.5 6.3 NA 6.4 6.9 
Selling C. anguillaris NA 6.6 6.6 6.5 6.4 NA 6.4 6.4 
O. niloticus NA 6.4 6.5 NA 6.3 NA 6.5 6.3 
Overall P value 0.06 0.73 0.17 0.33 0.28 0.41 0.63 0.09 
NA: Not applicable 
 
4.3 Microbiological quality of water and fish in the freshwater fish value chain 
Microbiological analysis of freshwater fish species was carried out. Fishes were examined for 
microbial quality. Fishes were examined for microbial quality. The purpose of these tests was to 
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detect pathogenic and spoilage microorganisms on freshwater fishes. Microbial quality of water 
sample at the capture point. 
The mean microbial counts in water samples in Selingue, Manantali, Markala and Mopti at capture 
in the two seasons are presented as Figure 4.3.1. There were significant differences between Total 
Coliforms, Fecal Coliforms and Sulphite Reducing Bacteria counts for the four sampling areas. 
The values were higher than microbiological criteria in international standards (AFNOR, 2004). 
Aerobic Plate Counts of the fresh fish species investigated ranged from 5±0.69 to 6.6±0.9 Log10 
CFU/ml for samples in Markala in the hot season and Selingue in the cold season, respectively. 
Total coliforms, ranged from, 3.98±0.33 to 5.77±0.17 Log10 CFU /ml in hot season at Manantali 
and Selingue. Faecal coliforms of the water samples ranged from 2 to 5.6±0.13Log10 CFU/ml in 
hot season at Markala and Selingue. For the Sulphite Reducing Bacteria spores in the water 
samples, Mopti in the cold season had a higher concentration, 1.13±0.0513 Log10 CFU/ml than 
the standard. The microbiological data obtained from this study clearly showed a high number of 
Aerobic Plate Counts, Total and Fecal Coliforms and Sulphite Reducing Bacteria. The relatively 
high counts of total and fecal coliforms may be due to additional contamination from bathing, 
washing, and swimming activities carried out by the occupants near this point. The contamination 
levels of water samples analyzed were of relatively within acceptable levels as regards 
Staphylococcus aureus. These results are in agreement with that of Simplice et al. (2018) who 
found a low rate of water contamination by Staphylococcus aureus. 
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Cell concentration (Log10 CFU/g)
7
a
6 a a a
b
5 b a a aa a
4
b
3
2
a b
1 b a
a aa a
0
Selingue Manantali Markala Mopti
APC TC FC SRB Staph. aureus
  
Figure 4.3.1: Microbial count Log10 CFU/ ml in the water at the capture point 
Aerobic Plate Counts (P=0.36); Total coliforms count (P=0.39); Fecal coliforms count (P=0.25); Sulphite Reducing 
Bacteriacount (P=0.18); Staphylococcus aureus (P=0.53) across sampling areas. For each microorganism, mean 
counts (bars) with different alphabets across sampling locations showed statistically significant differences (P < 0.05). 
Error bars refer to standard error of the mean. 
 
4.3.1 Microbial quality of fish containers at landing 
The mean microbial counts and prevalence of Salmonella on container surfaces in Selingue, 
Manantali, Markala and Mopti areas at the landing point in the hot and cold seasons are presented 
in Figure 4.3.2. There were no significant differences in the Aerobic Plate Counts (P = 0.15), Total 
coliforms (P = 0.46), Fecal coliforms (P = 0.37), Sulphite reducing bacteria (P = 0.23) and 
Staphylococcus aureus (P = 0.21) on containers surfaces. Aerobic Plate Counts ranged from 
6.46±0.1 to 8.71±0.3 Log10 CFU /cm2 in Manantali in the cold season and Selingue in the hot 
season, respectively. In different areas, the results showed Total Coliforms, ranged from, 
3.98±0.33 to 5.77±0.17 Log10 CFU /cm2 at Manantali in the cold season and Selingue in the hot 
season. Fecal Coliforms ranged from 4.3±0.42 to 8.29±0.2 Log10 CFU /cm2 in hot season at 
Markala and Selingue, respectively. The analysis of Sulphite Reducing Bacteria from the container 
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swap samples taken was higher (5.02±0.04 Log10 CFU /cm2) in the cold season in Markala. 
Prevalence of Staphylococcus aureus was higher in Manantali in the cold season (3.49±0.27 Log10 
CFU /cm2). 
86. 4 % representing of the container samples had Salmonella spp. The concentration of 
microorganisms in the container samples might be due to how the fish are off-loaded from the 
canoes, washed in water at the landing site and thrown into a container.  
The hygiene and cleanliness of these containers are important in the contamination of fish. The 
duration of the transport of the fish from the original landing site to the next landing, which is the 
Medina Coura market can take from 3 to 9 hours depending on the distance from the different 
areas in Bamako, the engine speed and also the customs stop time. These different conditions of 
transportation of the fish are likely to affect its quality. 
Cell concentration (Log10 CFU/cm
2)
8 a a b
a a a
7 b a bb b
6 a
5
4
3 b
a
2 b
a
1 b b a a
0
Selingue Manantali Markala Mopti
APC TC FC SRB Staph. aureus
Figure 4.3.2: Microbial counts in fish containers at various landing points. 
Aerobic Plate Count (APC) (P=0.15); TC: Total coliforms count (P=0.46); FC: Fecal coliforms count (P=0.37); SRB: 
Sulphite Reducing Bacteria count (P=0.23); STAPH: Staphylococcus aureus (P=0.21) 
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Error bars refer to standard error of the mean. 
1: Selingue, 2: Manantali, 3: Markala, 4: Mopti. 
4.3.2 Microbial quality of fish samples along the fresh fish value chain 
The value chain of the fishing sector in Mali from capture to sale is generally characterized by the 
off-loading of unrefrigerated fish at the landing sites and an unhygienic transfer of fish into the 
loading container intended to be sold at Medina Coura market of Bamako. These different practices 
affect and reduce the quality of the fish, thus accelerating spoilage and promoting a reduction in 
the shelf life of the fish. Fish are typically harvested and stored with ice in the transport vehicles 
to the final destination. Depending on the collection areas, some stakeholders send their fish on 
the same day to Bamako (Selingue); the other areas (Manantali, Markala and Mopti) store fish for 
a minimum of 2 days in the broken-down fridge with ice until transportation to the point of sale at 
Medina Coura market. As soon as it arrives in Bamako, the fish is sold immediately. The rest of 
the fish not sold the same day is kept in the melting ice and stored in a broken-down fridge until 
they are completely sold (Figure 4.3.3). 
 
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Figure 4.3.3: Fish stored in a broken-down fridge 
 
The microbiological analysis of the freshwater fish species was carried out to assess the quality of 
the fish during the cold and hot seasons along the value chain. In this study there was no significant 
seasonal fluctuation in the quality of fish in the 4 areas.  
In Selingue, there was no significant difference between the same group of microorganisms in the 
cold and hot seasons. In cold season: Aerobic Plate Counts (P=0.28); Total coliforms (P=0.26); 
Fecal coliforms (P=0.40); Sulphite Reducing Bacteria (P=0.24); Staphylococcus aureus (P=0.29). 
In hot season: Aerobic Plate Counts (P=0.28); Total coliforms (P=0.39); Fecal coliforms (P=0.43); 
Sulphite Reducing Bacteria (P=0.36); Staphylococcus aureus (P=0.18) (Figure 4.3.4) 
 
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Cell concentration (Log10 CFU/g)
8 a a a
a a a a
7 a a
a
6 a a a
5 a a
4
3 b
a aa
2
a a
1 a a
a 0
0
Cold Hot Cold Hot Hot
Capture Landing Selling
APC TC FC SRB S. aureus
 
Figure 4.3.4: Microbial mean Log10 CFU/ g of fish in various sampling point in Selingue 
In cold season: Aerobic Plate Counts (P=0.28); Total coliforms (P=0.26); Fecal coliforms 
(P=0.40); Sulphite Reducing Bacteria (P=0.24); Staphylococcus spp. (P=0.29). In hot season: 
Aerobic Plate Counts (P=0.28); Total coliforms (P=0.39); Fecal coliforms (P=0.43); Sulphite 
Reducing Bacteria (P=0.36); Staphylococcus aureus (P=0.18). For each microorganism, mean 
counts (bars) with different alphabets showed statistically significant differences (P < 0.05). Error 
bars refer to the standard error of the mean. 
 
Figure 4.3.5 shows that in Manantali there were no significant differences between the same 
microorganism between the two seasons. In cold season: Aerobic Plate Counts (P=0.23); Total 
coliforms (P=0.42); Fecal coliforms (P=0.66); Sulphite Reducing Bacteria (P=0.15); 
Staphylococcus aureus. (P=0.74). In hot season: Aerobic Plate Counts (P=0.23); Total coliforms 
(P=0.20); Fecal coliforms (P=0.29); Sulphite Reducing Bacteria (P=0.18); Staphylococcus aureus 
(P=0.21). 
 
 
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Cell concentration (Log10 CFU/g)
8
a a
a
a a b
7 a b
a a a a a
6 a a
a
5 a
a
4
a
3 a a
a
2
a
1 a a
a a a a
0
Cold Hot Cold Hot Cold Hot
Capture Landing Selling
APC TC FC SRB Staph. aureus
 
Figure 4.3.5: Microbial mean Log10 CFU / g of fish in in various sampling point in Manantali 
In cold season: Aerobic Plate Counts (P=0.23); Total coliforms (P=0.42); Fecal coliforms 
(P=0.66); Sulphite Reducing Bacteria (P=0.15); Staphylococcus spp. (P=0.74). In hot season: 
Aerobic Plate Counts (P=0.23); Total coliforms (P=0.20); Fecal coliforms (P=0.29); Sulphite 
Reducing Bacteria (P=0.18); Staphylococcus aureus (P=0.21). For each microorganism, mean 
counts (bars) with different alphabets showed statistically significant differences (P < 0.05). Error 
bars refer to standard error of the mean. 
 
Figure 4.3.6 shows that in Markala the microbial counts were not significantly different same 
between a same group of microorganisms in the cold and hot seasons. 
 
 
 
 
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Cell concentration (Log10 CFU/g)
8 a
a
a a
7 a
a a a
6 aa a a a
a
5 a
4
3 a
2 b
a a
a
1 a a
a 0 a
0
Cold Hot Cold Hot Cold
Capture Landing Selling
APC TC FC SRB Staph. aureus
 
Figure 4.3.6: Microbial count Log10 CFU / g of fish in in various sampling point in 
Markala 
In cold season: Aerobic Plate Counts (P=0.57); Total coliforms (P=0.57); Fecal coliforms 
(P=0.44); Sulphite Reducing Bacteria (P=0.349); Staphylococcus aureus (P=0.17). In hot season: 
Aerobic Plate Counts (P=0.14); Total coliforms (P=0.18); Fecal coliforms (P=0.33); Sulphite 
Reducing Bacteria (P=0.15); Staphylococcus aureus (P=0.079). For each microorganism, mean 
counts (bars) with different alphabets showed statistically significant differences (P < 0.05). Error 
bars refer to standard error of the mean. 
 
In Mopti, the counts of the various microorganisms were also not statistically significantly 
different as shown in (Figure 4.3.7). 
 
 
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Cell concentration (Log10 CFU/g)
8 a a a a a
a a a a a a7 a
a a a a
6 aa
5
4
3 a
a a
2 a
a a1 b a
a a a 0
0
Cold Hot Cold Hot Cold Hot
Capture Landing Selling
APC TC FC SRB Staph. aureus
 
Figure 4.3.7: Microbial count Log10 CFU / g of fish in various sampling point in Mopti. 
In cold season: Aerobic Plate Count (P=0.46); Total coliforms (P=0.37); Fecal coliforms (P=0.46); 
Sulphite Reducing Bacteria (P=0.23); Staphylococcus spp.  (P=0.69). In hot season: Aerobic Plate 
Counts (P=0.39); Total coliforms (P=0.51); Fecal coliforms (P=0.39); Sulphite Reducing Bacteria 
(P=0.11); Staphylococcus spp.  (P=0.35). For each group of microorganisms, mean counts (bars) 
with different alphabets showed statistically significant differences (P < 0.05). Error bars refer to 
standard error of the mean. 
 
Among the different fish species investigated, mean Aerobic Plate Counts ranged from 5.23 to 
7.83 Log10 CFU g_ 1. O. niloticus at the landing point in Mopti recorded the highest mean counts 
(Appendix 7), while Nile perch at the capture point in Markala had the lowest. (Appendix 7).  All 
the fish samples tested had mean contamination levels of ≥5.0 Log10 CFU g_ 1. The high Aerobic 
Plate Counts recorded for freshwater fishes in this study could be due to a lack of integrity of the 
cold chain from dispatch, transportation, storage, and cross-contamination from handling by 
stakeholders. It could also be due to the use of broken refrigerators as containers in the landing 
area and on the market in the Medina Coura (Sissoko et al., 2016). APC indicates the state of 
decomposition of the product and therefore constitutes an index of the quality of fish (Kunadu et 
al., 2018). According to International Standards AFNOR (2004) related to fresh fish, 100% or the 
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entire sample of the fish are non-compliant. The fish in the value chain are likely to have shorter 
shelf-life.  
Among different fish species investigated Total Coliforms (TC), ranged from, 4.11 to 7.49 Log10 
CFU g-1. The highest TC count was recorded in O. niloticus at the landing point in Manantali 
(Appendix 5), and the lowest in O. niloticus at the selling point in Selingue. Total Coliform counts 
of the freshwater fish were above the International Commission on Microbiological Specifications 
for Foods (ICMSF) criteria of ≤ 1 Log10 CFU g_ 1. Coliforms are not among the normal bacterial 
flora of fish and their presence demonstrates the level of pollution of their environment (Sichewo 
et al., 2014). 
Among the different fish species investigated, Fecal Coliforms ranged from 3.64 to 7.5 Log10 
CFU g-1. The highest number of Fecal Coliforms was recorded in C. anguillaris at the selling point 
at Markala (Appendix 6), and the lowest in O. niloticus at the selling point in Selingue (Appendix 
5). Fecal coliform bacteria or thermotolerant coliforms are abundant in the aquatic environment, 
in the soil and on vegetation, also in warm-blooded animal species. These are indicator organisms 
whose presence in food in large quantities may indicate the presence of pathogenic bacteria. 
Terentjeva et al. (2015) had a similar results in a study in Latvia, where many Enterobacteriaceae 
in gills ranged from 0.7 up to 5.78 Log10 CFU g_ 1, with the highest Enterobacteriaceae count in 
European perch. Degnon et al. (2013) also recorded high rate of thermotolerant coliforms in all 
samples analyzed in a study; which was explained to be due to the lack of good hygienic practice 
and the break in cold chain Bornert (2000), indicated that thermotolerant coliforms constitute 
germs of faecal contamination and are therefore indicators of poor hygienic conditions when 
handling foodstuffs. Sulphite Reducing Bacteria spores were detected in 11% (4/36) of samples at 
Selingue, 5.9% (2/34) of samples at Manantali 25% (7/28) of samples at Markala and 11.1% (4/36) 
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of samples at Mopti. Nile perch had a concentration of Sulphite Reducing Bacteria above the 
standard 1.05±1.48 Log10 CFU g_ 1in both seasons at the landing point. From the results, in Mopti, 
Nile perch had a higher concentration of Sulphite Reducing Bacteria at a selling point 6.05 Log10 
CFU g_ 1 (Appendix 7) Nile perch had a concentration of Sulphite Reducing Bacteria above the 
standard of 1.05±1.48 Log10 CFU g_ 1in both seasons at the landing point. There were no statistical 
differences between microbial counts at the sampling points in Selingue, Manantali and Markala 
(p≤5%) for all samples of fish taken. However, at Mopti, there was significant difference between 
the samples at the capture point between a same group of microorganisms in the cold and hot 
seasons. 
According to Degnon et al.(2013) in Benin, Sulphite Reducing Bacteria spores is one of the major 
causes of food poisoning in humans. The bacterium has been found in many fish. Contamination 
with sewage is usually the main source of this organism in fishery products.  
Prevalence of Staphylococcus aureus was 22.2% (8/36) at Selingue, at 29, 4% (10/34) Manantali, 
21, 4% (6/28) at Markala and 8.3% (3/36) at Mopti. In Manantali, Nile perch fish samples had 
higher concentration of Staphylococcus aureus, 5.01Log10 CFU g-1, at a selling point (Appendix 
6). About 20% (27/134) of the samples recorded Staphylococcus aureus above international 
standard. Degnon et al. (2013) reported the absence of Staphylococcus aureus in 100% of the 
samples, Staphylococcus aureus are ubiquitous pathogens, widely distributed in nature; but the 
main source of contamination is humans. Staphylococcus aureus can cause severe food poisoning. 
The presence of this bacteria indicates unhygienic conditions because the product contamination 
could be the result of a combination of improper handling, improper storage and cross 
contamination. The ice used for transport may be contaminated with Staphylococcus aureus. 
According to Bujjamma & Padmavathi (2015), the cumulative effect of these practices coupled 
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with unhygienic handling during transportation can lead to high level of Staphylococcus aureus in 
food fish. The use of contaminated water for cleaning and processing fish in the fish market is 
probably the cause of the secondary contamination. A heavy infestation of flies in this market also 
promotes tertiary contamination to a large extent due to the lack of adequate drainage of the 
facilities. 
4.3.3 Prevalence of Salmonella spp. in the various samples 
Fifty percent (50%) of water samples are positive for Salmonella spp. These results are not in 
agreement with that of Simplice et al. (2018) who found a complete absence of Salmonella spp. . 
In this study, Salmonella spp. were prevalent at 100% of samples from Manantali in a cold season, 
Markala and Mopti in the hot season. Surface waters are vital and vulnerable freshwater systems 
that are critical for the sustenance of all life. 
The prevalence of Salmonella spp. in the fish samples was 8.9% at Selingue (32/36), 91.2% (31/34) 
at Manantali, 100% (28/28) at Markala and 94.4% (34/36) at Mopti. Salmonella spp. was not 
detected in any of the samples taken in the hot season; which were Nile tilapia at the capture point, 
Nile perch, and African catfish at the landing point and Nile tilapia at the selling point. Salmonella 
spp. was detected in 50% of samples from Manantali in in the cold season, which were African 
catfish and Nile tilapia at capture point. Nile perch had a higher concentration at the landing point 
Salmonella spp. was also detected in all samples (100%) from Markala (both seasons). The 
prevalence of Salmonella spp in fish samples in Mopti at selling point, 50% for both African catfish 
and Nile tilapia in the cold season. The results indicate that 93.3% (125/134) of samples had 
Staphylococcus spp. above the international microbiological criteria. The results of the present 
study showed higher prevalence of Salmonella compared to those obtained by Sissoko et al. (2016) 
which is 25% Salmonella spp. According to Dione (2003), this pathogen is common to animal 
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species and can contaminate fishery products through contaminated instruments, sick workers or 
healthy carriers, insects and other animals, and water polluted by waste water, and poor hygiene 
control (Gamane Kaffine et al., 2018). Salmonella spp. can tolerate NaCl concentrations of 2 to 
8% depending on the pH of the medium and the temperature, but they are destroyed by normal 
cooking of food. This pathogen is responsible for the deterioration of the sanitary and food safety 
status of the product and can cause gastroenteritis, septicemia and typhoid fever when a fish 
product is not adequately cooked prior to consumption. 
4.4 Parasites in Freshwater Fish along the Value Chain of Medina Coura Market 
4.4.1 Prevalence of infested fish species 
About 120 fish samples were analyzed for parasite infestation, parasites were present in fishes at 
the capture points, the landing point at Selingue, Manantali, Markala, and Mopti and at the selling 
point Medina Coura market. Parasite infestation varied from one species to another. A low 
infestation rate was generally observed (10%) in the fish samples. The highest parasite infestation 
was observed in Nile tilapia with an infestation rate of 16.7% followed by Nile perch, 9.1% and 
African catfish, 5.0%, during both seasons (Table 4.4.1). No significant difference in prevalence 
among infestation rates of the fish species examined was observed (χ2= 0.87). The study revealed 
an overall rate of parasite infestation of 10% in Nile perch, African catfish, Nile tilapia species. 
The preliminary investigation of the parasitofauna of fish in Okhuo River in Benin City, Nigeria 
by Edema et al. (2008) indicated 6.94% infestation rate. These were rather very low as compared 
to other similar studies, such as (Amare et al., 2014) who reported 47.8% prevalence of parasites, 
in Lake Lugo (Hayke), Northeast Ethiopia and Olofintoye (2006) who observed 62.6% in some 
freshwater fish species in Ekiti States, Nigeria. These suggest that the distribution of parasites can 
vary from one habitat to the other due to host parasite relationship and abiotic factors like dissolved 
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oxygen, temperature and pH; and also, the nature of the water, which reflects human use, and the 
endemicity of infection in the area. The prevalence of parasites was higher in Nile tilapia 16.7% 
followed by Lates niloticus 9.1% and Clarias anguillaris 5%. These are lower than rates reported 
by Amare et al. (2014) of the species in Lake Lugo (Hayke), Northeast Ethiopia, which was 
50.22%. 
Table 11: Prevalence of parasites by fish species 
Fish species Number examined Number infected Prevalence (%) 
Lates niloticus 44 4 9,1 
Clarias anguillaris 40 2 5 
Oreochromis niloticus 36 6 16,66 
Total 120 12 10 
 
4.4.2 Variation of parasites per infected organs of the fish and areas of sampling 
The skin, flesh, gills and abdominal cavity were observed macroscopically. The most affected 
internal organs of the fish were the gills with the presence of Salmincola edwardsii (crustaceans) 
and the abdominal cavity with the presence of nematodes Rhaphidascaris spp. and Philonema spp. 
These parasites belonging to different taxonomic groups were recovered from 12 positive sampled 
fish. The frequency distribution of parasites among per infected organs per sampling areas is 
presented in Table 4.4.2. Philonema spp. (12.5%) were the most frequently detected parasite in 
Markala, followed by Raphidascaris spp. which were recovered from the abdominal cavity in 10% 
and 8.82% respectively, of fishes sampled in Selingue and Mopti. Salmincola edwardsii was found 
in the gills of 4.16% of the fish sampled at Markala.  There was no significant difference between 
parasite variation and prevalence at the sampling areas (χ2 = 0.821). 
The study showed that, the prevalence of nematodes was higher than crustacea. The higher rate of 
nematode infestation may be due to the low host specificity of the adult stage of these parasites, 
or the ability of different genera and species of nematodes to infect the fish species studied, and 
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the availability of the different host required for the completion of the life cycle of these parasites 
(Yamaguti, 1963). 
The prevalence of Salmincola edwardsii was 4.16%; and was observed only in Manantali on 
Oreochromis niloticus in the gills. Salmincola edwardsii belongs to the Arthropoda Phylum, 
subphylum Crustacea, family Lernaeopodidae, and are commonly called "gill lice" or "gill fly" 
(Alteen, 2009). Boucenna et al. (2015) also detected the presence of this parasite in the gills. They 
reported that this parasite can cause swelling around the site of attachment of the bubble, with 
heavy parasite loads. The presence of this crustacean reduces the feeding activity of the host fish 
by weakening the host fish and negatively affecting its weight gain, reproduction, and therefore 
growth. According to Gamane Kaffine et al. (2018) the frequency of gill infestation by these 
parasites may be because gills have a close relationship with the aquatic environment where fish 
lives. It was observed that Oreochromis niloticus collected at the point of sale in the Mopti area 
during the hot season has a much higher prevalence (50%) than other species. These parasites are 
capable of absorbing nutrients, vitamins, micro and macronutrients in the digestive tract of fish. 
According to Bichi & Dawaki (2010) these parasites develop metabolic wastes that have a negative 
impact on the physiology and reproduction of fish. 
Table 12: Prevalence of parasites per infected organs and areas 
Parasites Infected Selingue Manantali Markala Mopti 
organs Number Prevalence Number Prevalence Number Prevalence Number Prevalence 
of  (%)  of (%)  of (%)  of (%)  
positive        positive positive positive 
 
Raphidascaris Abdominal 3 10 1 3.57 0 0 3 8.82 
spp. cavity 
Philonema sp. Abdominal 0 0 0 0 3 12.5 2 5.88 
cavity 
Salmincola Gill 0 0 1 4.16 0 0 0 0 
edwardsii 
 
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4.4.3 Seasonal variation of fish parasites per sampling areas 
To assess the seasonal prevalence of parasites in the cold and hot season, 58 and 62 samples were 
examined for hot and cold seasons respectively of which 3 (5.17%) and 9 (14.52%) were infested 
respectively (Table 4.4.3). 
The parasite frequency distribution per season and per location shows that the highest parasite 
infestation was observed during the hot season in Selingue with 25% prevalence; followed by 
Mopti, 20%, Manantali, 16.66% and Medina Coura, 1.7%. In the cold season fish sampled from 
the selling points had parasite infestation rate of 10% in Selingue, followed by Manantali and 
Markala with 8.33% at the landing site. There was no significant difference (χ2= 0.363, p> 0.05) 
of infestation rates during the different seasons. 
Table 13: Prevalence of fish infested with parasites per location and season 
Seasons Areas of sampling Number examined Number infected Prevalence (%) 
Cold Selingue 12 0 0 
season Manantali 12 1 8.33 
Markala 12 1 8.33 
Mopti 12 0 0 
Medina Coura Market 10 1 10 
Total 58 3 5.17 
Hot Selingue 12 3 25 
season Manantali 12 2 16.7 
Markala 12 0 0 
Mopti 10 2 20 
Medina Coura Market 16 1 1.60 
Total 62 9 14.52 
TOTAL 120 12 10 
 
4.4.4 Prevalence of infected fish species at each sampling points 
Table 4.4.4 shows the prevalence of each species of fish in each location of sampling. Parasite 
prevalence varied from one fish species to another. The highest prevalence of the parasite in 
Oreochromis niloticus was observed at Mopti at the selling point, 50%; followed by Lates 
niloticus, 25%. The other species of fish had a prevalence of 0% at the same point of sale. 
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Table 14: Prevalence of infected fish species at each sampling point 
Areas of Fish species Capture point Landing point Selling point 
sampling 
Number Number Prevalence Number Number Prevalence Number Number Prevalence 
examine infected %P examined infected %P examined infected %P 
d 
Selingue L. niloticus 4 0 0 4 1 25 2 0 0 
C. anguillaris 4 0 0 4 0 0 2 0 0 
O. niloticus 4 1 25 4 1 25 2 0 0 
Manantali L. niloticus 4 0 0 4 0 0 4 0 0 
C. anguillaris 4 0 0 4 0 0 2 0 0 
O. niloticus 4 0 0 4 1 25 0 0 0 
Markala L. niloticus 4 0 0 4 0 0 2 0 0 
C. anguillaris 4 1 25 4 1 25 0 0 0 
O. niloticus 4 1 25 4 0 0 0 0 0 
Mopti L. niloticus 4 1 25 4 1 25 4 1 25 
C. anguillaris 4 0 0 4 0 0 4 0 0 
O. niloticus 2 0 0 4 0 0 4 2 50 
Total  42 4 9.52 44 5 11.36 26 3 11.54 
 
4.5 Identification of the spoilage microorganisms associated with fish using phenotypical 
methods 
4.5.1 Isolation of spoilage microorganisms on fish samples at the various sampling points 
The parameters used for macroscopic observations of colonies on King A and King B media were 
the relief, the colour, and the diameter (Appendix 8). The study showed that the bacterial flora of 
the samples collected was very dense and very diverse. For microscopic observation (Appendix 
9), the bacteria which grew on King medium were all Gram-negative. Two bacterial types were 
observed for all of the isolates, including 264 rods; 92 cocci. The grouping method was able to 
show groupings in pairs or diplococcus (146 isolates), in a chains (25 isolates) and in clusters (166 
isolates). 
4.5.2 Biochemical tests 
The Biochemical test showed that 100% of the bacteria were catalase-positive and oxidase-positive 
(Appendix 9). 
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A total of 360 isolates (188 in a cold season and 172 in a hot season) were identified and were 
distributed among 24 species of bacteria. These 24 species of bacteria belonged to 20 genera (Table 
4.5.1).  
Table 4.5.1: Erreur ! Il n'y a pas de texte répondant à ce style dans ce document. 
Family Bacteria species Cold season Hot season 
Capture Landing Selling Capture Landing Selling 
Enterobacteriaceae Proteus vulgaris 0 0 0 0 0 1 
Citrobacter freundii 0 0 0 0 0 1 
Enterobacter cloacae 0 0 0 0 0 1 
Providencia rettgeri 0 0 0 0 0 1 
Vibrionaceae Vibrio alginolyticus 1 1 0 0 0 0 
Vibrio parahaemolyticus 2 4 0 0 0 0 
Photobacterium damsellae 1 0 1 1 0 0 
Plesiomonas shigelloides 1 3 1 0 0 1 
Moraxellaceae Psychrob. Phynyl pyrivicus 8 1 2 3 3 0 
Brucellaceae Ochrobactrum anthropi 1 1 2 5 5 7 
Pseudomonadaceae Ps. Fluorescens 1 0 0 3 1 0 
Ps. aeroginosa 7 13 2 3 0 1 
Ps. luteola 2 0 3 1 5 1 
Ps. putida 0 0 0 0 0 2 
Aeromonadaceae Aeromonas hydrophilae/ caviae 26 13 15 38 23 25 
Aeromonas salmonica spp 1 7 0 0 0 0 
salmonicoda 
Aeromonas sobria 1 3 0 0 0 0 
Flavobacteriaceae Chryseobacterium indologenes 1 2 0 0 0 1 
Chryseobacterium 0 0 1 0 0 1 
meningosepticum 
Rhizobiaceae Agrobacterium radiobacter 1 1 1 2 4 2 
Burkholderiaceae Burkholderia cepacia 10 11 3 2 0 0 
Comamonadaceae Comamonas testosteroni 4 1 1 1 0 0 
Methylobacteriaceae Methylobacterium mesophilicum 3 9 0 2 5 2 
Sphingobacteriaceae Sphingobacterium multivorum 1 4 1 0 0 0 
Caulobacteraceae Brevundimonas vesicularis 3 5 1 2 4 4 
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Alcaligenaceae Oligella ureolytica 0 0 0 0 0 1 
Neisseriaceae Chromo. Violaceum 0 0 0 3 0 2 
TOTAL 75 69 34 66 51 55 
 
These bacteria also belong to 15 families as shown in Figure 4.5.1. In the cold season samples, 
35.1% were Aeromonadaceae, 14.9% Pseudomonadaceae; 12.8% Burkholderiaceae; 7.9% 
Vibrionaceae; 6.4% Methylobacteriaceae; 5.8% Moraxellaceae, 4.9% Caulobacteraceae; 3.2% 
Sphingobacteriaceae; 3.2% Comamonadaceae; 2.1% Brucellaceae; 2.1% Flavobacteriaceae and 
1.6% Rhizobiaceae. Sissoko (2014) reported only 5 families (Pseudomonadaceae, 
Aeromonadaceae, Enterobacteriaceae, Vibrionaceae and Moraxellaceae) in fish samples from 
Medina Coura market. The present results show a large diversity of families, which may be 
explained by the native flora of the freshly caught fish and the flora of contaminants added along 
the value chain (capture, landing and sale). This difference could be explained by length of the 
time between the capture of the fish and the sampling of the fish at the sale point in the market and 
also by the number of samples taken i.e 134 fresh fish samples in this study as against 20 samples 
in the study by Sissoko et al. (2016) sold on the Medina Coura market. The samples collected 
during the hot season recorded 50% prevalence of Aeromonadaceae as the highest, followed by 
Brucellaceae (10.5%) Pseudomonadaceae (9.9%) families with Comamonadaceae (0.6%) as the 
least prevalent family (Figure 4.5.2). Fane (2011) worked on “Diversity of the microbial flora of 
fish and waters of southern rivers in Mali)” recorded three bacterial families: Pseudomonadaceae, 
Enterobacteriaceae and Bacillaceae from 43 samples of 8 species of fish (Brycinus nurse, 
Sarotherodon galilaeus, Synodontis membranaceus, Clarias anguillaris, zillii Tilapia, 
Oreochromis aureus, Oreochromis niloticus and  Heterotis niloticus) from rivers in Mali southern. 
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A study done by Kluga et al.(2017) in Nigeria on identification of microflora of freshwater fish 
caught in the Driksna river and pond in Latvia reported that the majority belonged to bacteria with 
Pseudomonas spp. (55%). In that study, Pseudomonas spp. were isolated from the River and the 
pond. Pseudomonadaceae families are well-known fish specific spoilage microorganisms and 
their abundance in fish may led to rapid fish spoilage processes that causes changes in fish meat 
quality and makes fish unfit for human consumption. The presence of the spoilage microorganisms 
potentially may cause consumer health concerns. 
 
40
35
30
25
20
15
10
5
0
Capture Landing Selling Capture Landing Selling
Cold season Hot season
Enterobacteriaceae Vibrionaceae Moraxellaceae Brucellaceae Pseudomonadaceae
Aeromonadaceae Flavobacteriaceae Rhizobiaceae Burkholderiaceae Comamonadaceae
Methylobacteriaceae Sphingobacteriaceae Caulobacteraceae Alcaligenaceae Neisseriaceae
 
Figure4.5.1:The frequency of the different families of spoilage microorganisms during the 
cold and hot seasons 
 
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4.6 Phenotypic identification of pathogenic microorganisms associated with fish 
4.6.1 Biochemical test 
All the bacteria isolates were catalase-positive and oxidase-positive. A total of 117 (59 in a cold 
season and 58 in a hot season) isolates were identified (Table 4.61). 
Table 4.6 1:Frequency of isolation of pathogenic microorganisms on fish on various 
sampling point 
Family Bacteria species Cold season Hot season 
Capture Landing Selling Capture Landing Selling 
Enterobacteriaceae Proteus vulgaris 3 1 4 2 3 2 
Proteus mirabilis 0 0 3 3 3 0 
Salm. Choler. Arizonae 0 0 0 0 0 0 
Salmonella. Spp 2 1 4 1 2 1 
Citrobacter youngae 0 1 0 1 1 0 
Citrobacter koseri/ amalonaticus 0 0 0 0 2 0 
Citrobacter freundii 1 1 1 1 2 0 
Enterobacter cloacae 1 0 1 0 1 0 
Enterobacter sakazaki 1 0 0 0 0 0 
Ser. marcescens 1 0 0 0 0 0 
E. coli 0 0 0 0 1 0 
Klebsiella ocytoca 1 0 0 1 0 0 
Edwardsiella tarda 0 0 0 1 0 0 
Providencia stuartii 6 0 0 1 0 0 
Providencia alcalifaciens 0 0 0 0 1 0 
Providencia rettgeri 0 0 0 1 0 0 
Vibrionaceae Grimonthia hollisae 1 1 0 1 0 1 
Vibrio alginolyticus 0 2 0 0 1 0 
Photobacterium damsellae 0 0 0 2 5 0 
Morganellaceae Morganella morganii 2 1 2 2 0 0 
Moraxellaceae Moraxella spp. 0 2 0 0 0 0 
Brucellaceae Pasteurella multocida 0 0 0 1 0 0 
Ochrobactrum anthropi 4 4 0 0 0 0 
Pseudomonadaceae Ps. Fluorescens 3 0 0 0 0 0 
Ps. aeroginosa 0 0 0 2 1 0 
Shewarnellaceae Shewarnella putrefaciens 0 3 0 1 1 0 
Aeromonadaceae Aeromonas hydrophilae/ caviae 0 0 0 3 1 0 
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Flavobacteriaceae Chryseobacterium indologenes 0 0 0 1 1 0 
Burkholderiaceae Burkholderia cepacia 0 0 0 1 0 0 
Alcaligenaceae Bordetella/Alca/M. spp. 0 1 0 0 0 0 
Neisseriaceae Chromo. Violaceum 0 0 0 0 0 1 
Total 26 18 15 25 27 5 
 
They were made up of 31 species and belonged to 23 genera and 12 families (Figure 4.6.1).  In the 
cold season, Enterobacteriaceae was most prevalent (54.4%), followed by Brucellaceae (13.5 %, 
Alcaligenaceae and least of all (1.7%). In the hot season, Enterobacteriaceae was most prevalent 
(55.9%) followed by Vibrionaceae (17.5%) and then Pseudomonadaceae (5.3%) and Brucellaceae 
the least (1.7 %). The genus Enterobacteriaceae is an important indicator of the hygienic state of 
the environment and products, and it suggests the contamination of the environment (Terentjeva 
et al., 2015). After capture, the microflora of fish surfaces and skin is continuously affected by the 
aquatic environment, including bacteria present in water, sediments and contamination by polluted 
wastewater (Terentjeva et al., 2015). 
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18
16
14
12
10
8
6
4
2
0
Capture Landing Selling Capture Landing Selling
Cold season Hot season
Enterobacteriaceae Vibrionaceae Morganellaceae Moraxellaceae
Brucellaceae Pseudomonadaceae Shewarnellaceae Aeromonadaceae
Flavobacteriaceae Burkholderiaceae Alcaligenaceae Neisseriaceae
 
Figure 4.6.1: Percentage distribution of the different families of pathogenic 
microorganisms in fish during from the cold and hot seasons 
4.6.2 Isolation of pathogenic microorganisms on fish samples at the various sampling points 
Salmonella- Shigella agar medium was used to isolate the pathogenic microorganism from the 
samples collected for the study and the results are recorded in Appendix 13. 
Macroscopic and microscopic characteristics of the microbial flora of fish species. 
The parameters used for macroscopic observations were the color, and the diameter (Appendix 
10). The study showed that the bacterial flora of the samples collected was very dense and very 
diverse. 
For microscopic observation in Appendix 11, the bacteria which grew on S-S medium were all 
Gram-negative. Two bacterial types were identified, including 117 rods; 8 cocci. 
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CHAPTER FIVE 
5.0 CONCLUSION AND RECOMMENDATION 
5.1 Conclusion 
This study found that although respondents have a certain level of knowledge that does not 
translate into food safety practices in the artisanal fish value chain. Poor handling practices by 
workers, in particular, non-compliance with hygiene rules and storage at an inappropriate 
temperature could be associated with the fish losses. Insufficient knowledge and practices of 
respondents in food safety lead to poor microbial quality of fish and self-reported fish losses by 
respondents. 
The bacteriological analysis has shown that fresh freshwater fish sold along the value chain in the 
Medina Coura market has high counts of Aerobic Plate Counts, Total coliform, Fecal coliform, 
Sulphite Reducing Bacteria spores, Staphylococcus aureus. and Salmonella spp. However, the 
prevalence of parasites was low. Microorganisms isolated from fish samples analyzed were diverse 
and were made up of 24 species of bacteria (spoilage and pathogenic flora) belonging to15 families 
for a spoilage bacteria and 31 species of bacteria belonging to 23 genera for the pathogenic 
bacteria. These bacteria are divided into 12 families. An overall prevalence of 10% (12/120) 
parasitic infestation was observed. Prevalence was lower during the cold season, (5.2% of the fish) 
than in the hot season (14.5%). The highest prevalence of infestation was observed in Oreochromis 
niloticus (Tilapia) at 16.7% followed by Lates niloticus (Nile Perch) (9.1%) and Clarias 
anguillaris (Catfish) (5.0%). Research finding showed that infection prevalence and diversity of 
parasites were relatively low. 
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Overall, the study is an important contribution to the knowledge of the bacterial and parasitological 
flora of fish along the value chain of fish sold on the Medina Coura Market, It is the first study to 
elucidate the microbiological quality of these freshwater fish along studied value chain. 
5.2 Recommendations 
Given the importance of fish in human food and the rapid increase the consumers it is necessary 
to strengthen vigilance and control of the practices of the actors of the application of regulations, 
good hygiene practices and food security control. Fish marketing systems should be clean with 
improvements in handling and processing to minimize the prevalence of pathogenic bacteria. 
Measures must be taken by local authorities, who are empowered to exercise their functions 
without constraints, to prevent and control the potential risk and spread of the disease. In the 
interest of public health, the government and the regulatory bodies, good management of the 
fishing sector must be implemented, starting with formal training in hygienic practices and regular 
controls of the personal and environmental hygiene of all actors in the artisanal fish value chain. 
The landing site must be constructed and well equipped with cold storage facilities, which would 
allow stricter regulations by the appropriate bodies to ensure proper sanitation and safety of the 
fish. Parasites should not be detected in fish because they reduce the market value of fish and may 
cause human infections when live cysts or matured parasites are ingested. This study shows that 
microbial contaminants in fish samples sold along the value chain are high but further investigation 
is needed to determine the levels and extent of microbial contamination. Further studies on 
identification driven by molecular biology could involve a quantitative evaluation of samples of 
fish contaminated with these pathogens, as this would provide a clear indication of the levels of 
contamination of fish sold in the Medina Coura market. Follow up studies could be carried out to 
determine the economic, public health and social implications of high contamination levels on the 
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fishes studied and the efficacy of targeted interventions to improve microbiological quality and 
safety of fish. 
  
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Rim, H.-J., Farag, H., Sornmani, S., & Cross, J. (1994). Food-borne trematodes: Ignored or 
emerging? Parasitology Today, 10, 207–209. 
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Sevindik, M., & Uysal, İ. (2021). Food spoilage and Microorganisms. Turkish Journal of 
Agriculture - Food Science and Technology, 9(10), 1921–1924. 
https://doi.org/10.24925/turjaf.v9i10.1921-1924.4658 
Sichewo, P. R., Gono, R. K., Muzondiwa, J., & Mungwadzi, W. (2014). Isolation and identificatio 
of pathogenic bacteria in edible fish: A case study of rural aquaculture projects feeding 
livestock manure to fish in Zimbabwe. International Journal of Current Microbiology and 
Applied Science, 3, 897–904. 
Simplice, M., Womeni, H., Hervé, N., Tonfack Djikeng, F., Justin, D., Francois, T., & Kuiate, J.-
R. (2018). Chemical composition and antibacterial activity of oils from Chrysicthys 
nigrodigitatus and Hepsetus odoe, two freshwater fishes from Yabassi, Cameroon. Lipids 
in Health and Disease, 17. https://doi.org/10.1186/s12944-018-0690-z 
Sissoko, A., Samaké, F., Diabaté, D., Sidibe, S., Sanogo, Y., & Babana, A. H. (2016). Qualité 
microbiologique et diversité de la flore bactérienne des espèces de poisson frais d’eau 
douce du Mali vendues au Marché de Médina Coura. 103–108. 
Sivakumar, S. S., Sivakumar, S., & Daluwatte, D. (2018). Economic loss of fisheries due to the 
post harvest quality loss and assessment of the quality loss in fish. Global Scientific 
Journal, 6 (9), 115–124. 
Terentjeva, M., Eizenberga, I., Novoslavskij, A., Strazdiņa, V., Valciņa, O., Ošmjana, J., & 
Bērziņš, A. (2015). BACTERIAL MICROFLORA OF FRESHWATER FISH 
ORIGINATED FROM USMAS LAKE IN LATVIA. J Microbiol Biotech Food Sci, 4(1), 
74–77. https://doi.org/10.15414/jmbfs.2015.4.ispecial1.74-77 
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Traore, N. M. (2014). Abondance et importance des espèces de poissons frais du Mali vendues au 
marché de Médina Coura [Master Population Environnement Gestion Durable des 
Ressources Naturelles]. Institut Supérieur de Formation et de Recherche Appliquée 
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1605(96)01139-7 
Yamaguti, S. (1963). Parasitic Copepoda and Branchiura of fishes. New York, Interscience 
Publishers. 
Zanin, L., Cunha, D., Stedefeldt, E., & Capriles, V. (2015). Seafood safety: Knowledge, attitudes, 
self-reported practices and risk perceptions of seafood workers. Food Research 
International, 67, 19–24. https://doi.org/10.1016/j.foodres.2014.10.013 
 
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APPENDICES 
 
DEPARTMENT OF NUTRITION AND FOOD SCIENCE 
UNIVERSITY OF GHANA, LEGON 
 
MICROBIAL DIVERSITY OF ECONOMICALLY IMPORTANT UNPROCESSED 
FRESHWATER FISHES SOLD AT THE MEDINA COURA MARKET IN BAMAKO, 
MALI 
 
Dear respondent, this questionnaire aims to collect information on the origin of the fish, The flow 
time, the handling, storage, knowledge of food quality and safety of the fish on Medina Coura 
market in Bamako and various area of sampling. It is part of a PhD food science thesis, 
microbiology option. The information you provide in this document will be treated as confidential 
and used for academic purposes only. Thank you. 
Appendix 1A: Fish sellers questionnaire at Medina Coura Market 
 
Date: _______________________  
Location: ____________________  
Respondent’s Code 
Kindly tick (√) the responses that apply to you. Where appropriate, write out your own responses 
in the spaces provided. 
 
 
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BACKGROUND INFORMATION RESPONSE 
[For interviewer use only]  
1. Sex:  
1=Male                                                                                      
2=Female                                                                                                                   
2.Ethnic Group 
1=Fulani 
2=Bozo 
3=Bambara 
4= Malinke 
5= Songhai 
6=Soninke 
3. Age 
1=30 – 40 years  
2=41– 50 years 
3=51 – 60 years 
4=61 – 70years 
4. How long (year) have you been doing this fishing activity? 
1=1-10 years 
2=11-20years 
3=21-30 years 
4=31-40 years 
5=41-50 years 
6=51-60 years 
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5. Education level 
1= Primary 
2=Secondary 
3=High school 
4=No educated 
6. How will you define your retail business?  
1=Wholesaler 
2=Middleman 
3=Retailer 
7. Where does your fish come from? 
1=Mopti  -Markala 
2=Mopti-Selingue 
3=Mopti- Segou- Manantali 
4=Mopti- Selingue –Gao-Manantali 
8. What is your means of transporting fish? 
1=Car 
2=Refrigerated truck 
9. How to display the fish for sale? 
1= On a mat on the floor  
2= On a table 
10. How long does the fish last? 
1= 1 day 
2= 2-3 days 
3= 4-5 days 
4= 6-7 days 
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11. How do you store fish? 
1= With ice 
2= Without ice 
12.What measurement do you use to weigh your fish? 
1= In weight (Kg) 
2= In 300 Kg basket] 
13. In what condition the fish arrives on the market. 
1=In the basket with ice 
2= In the basket without  
14. How much fish do you receive? 
1= 1-3 Baskets  
2= 4-6 Baskets 
3= 1-7 Tones 
15. How often do you receive fish per week? 
1= 2-3 days 
2= 4-5 days 
3= 6- 7 days 
16. Do you know a spoiling fish?  
1= Yes 
2= No 
17. What is the cause of the spoiling? 
1= Lack of ice 
2= Broken down vehicle 
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18. Do you think handling can contribute to the spoilage of fish? 
1= Yes 
2=No 
19.How do you recognize a spoiled fish? 
1= Texture change 
2= Change in eye color  
3= Change in texture, swelling  
4= Change in eye color, darkening of gills 
20. Do you often encounter spoiled fish? 
1= Yes  
2= No 
21.What do you do with spoiled fish? 
1= Loss sale to processors  
2= Transform yourself  
22. In your opinion, do spoiled fish cause health problems? 
1= Yes 
2= No 
23. What do you suggest to avoid losing the fish? 
1=Clean-up workplaces  
2= Need financial assistance 
3. Need refrigerated truck for transportation 
4. Vehicle stop by customs for long time 
5. Need a factory to manufacture ice, cold room 
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Appendix 1B: Fishermen questionnaire at the four capture point 
 
Date: _______________________  
Location: ____________________  
Respondent’s Code 
Kindly tick (√) the responses that apply to you. Where appropriate, write out your own responses 
in the spaces provided. 
 
BACKGROUND INFORMATION RESPONSE 
1. Sex:  
 1=Male  
 2=Female 
2.Ethnic Group 
1= Fulani 
2= Bozo 
3=Bambara 
4= Malinke 
5= Songhai 
6=Soninke 
3. Age 
1=30 – 40 years  
2=41– 50 years 
3=51 – 60 years 
4=61 – 70years 
 
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4. How long (year) have you been doing this fishing activity? 
1=1-10 years 
2=11-20 
3=21-30 
4=31-40 
5=41-50 
6=51-60 
5. Education level 
1= Primairy 
2=Secondary 
3=High school 
4=No educate 
6. What fishing gear do you use for fishing? 
1= Gill nets 
2= Fishing net 
3=Cast net 
4=Seine net 
7. What kinds of canoe do you use for fishing? 
1= Motorized canoe 
2=Non-motorized canoe 
8. How does your fishing activity take place? 
1=The nets are left at 4 p.m. and collected overnight (1 a.m.) 
2= Spend 4 to 5 days in the lake 
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3= Spend 5 to 7 days in the lake 
4=Going in the lake and at the same time return 
5= Going on the lake every hour  
9. What species (3 species more caught) of fish are you Caught in this period? 
1=Oreochromis niloticus,Hydrocynus brevis,Lates niloticus 
2=Lates niloticus,Oreochromis niloticus,Synodontis schall 
3=Brycinus leuciscus,Lates niloticus,Oreochromis niloticus 
4=Brycinus nurse, Brycinus leuciscus, Oreochromis niloticus 
5=Brycinus leuciscus, Oreochromis niloticus,Clarotes laticeps 
10. What is the most successful fishing period? 
1= February to September  
2= June to August 
3= November to January 
11. What is your average harvest in an expedition? 
1= 1-20 Kg 
2=21-40 Kg 
3= 41-60 Kg 
4= 61-80 Kg 
5=>100 Kg 
12.How often do you go fishing? 
1= 2 days 
2= 3-5 days 
3= 7 days 
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13. On average, how much time do you spend on each shipment? 
1= Less than 2 hours 
2= 2 to 6 hours  
14. Do you have refrigeration systems on the canoe? 
1= Yes 
2= No 
15. If not, please describe how you handle your catch to avoid spoilage? 
1= Speed  
2= Ice] 
3= Nothing 
16. Do you sometimes lose fish? 
1= Yes 
2= No 
17.How do you market your catch? 
1=Our women come to take to sell  
2= Wholesalers come to buy to resell 
3= Retailers come to buy to resell 
4= Wholesalers and Retailers come to buy to resell 
18. How long do you take to market your catch? 
1= Less than 2 hours 
2= 2 to 6 hours 
19. What do you do with fish that are deteriorating? 
1= Dried 
2= Others 
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20. What are the difficulties you encounter in your work? 
1= Pesticide in water by miners (cyanide, Mercury)] 
2= Lack of fish in the water  
3= Lack of means of preservation (cold room, ice) 
4= Theft of fishing gear 
5= Insecurity in northern Mali  
6= No problem  
7= Difficulty in transport 
Appendix 2: Chemical composition of the culture media used 
 
Peptone Buffered Water (formula: g/l) 
Disodium Hydrogen Phosphate Dehydrate……………………………….7.2 
Sodium Chloride……………………………………..……………………..,3 
Potassium Dihydrogen phosphate…………………………………….…..3.6 
Pancreatic Digest of caseine………………………………………………….1 
pH: ………………………………………………………………7.0±0.2 à 25°C                                            
 
Plate Count Agar (formula: g/l) 
Casein peptone……………………………………………………………….5.00 
Yeast extract……………………………………………………….…………2.50 
Dextrose……………………………………………………………..………..1.00 
Agar…………………………………………………………………..……...15.00 
pH: ………………………………………………………………7±0,2 à 25°C                                            
 
Violet Red Bile Lactose Agar (VRBA) (formula: g/l) 
Peptone…………………………………………………………………………...7   
Yeast extract …………………………………………………………………..3  
Lactose ……………………………………………………………………..…10   
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Sodium chloride ………………………………………………..………….5  
Bile Salts No.3 ……………………………………………………………0.5  
Cristal violet ……………………………………………………………...0.002   
Neutral red ………………………………………….…………………...0.03  
Agar-agar ………………………………………………….………………....15 
pH: ………………………………………………………………7±0.2 - 25°C                                            
 
King A Agar(formula: g/l)  
Magnesium Chloride …………………………………………………….…...1.4            
Potassium Sulfate …………………………………………………..…………10.0           
Agar …………………………………………….…………....13.6            
pH………………………………………………………………….7.0±0.2 - 25°C                                           
  
King B Agar (Formula: g/l)                                                   
Peptone ………..…………………………………………………………..20.0 
Proteose peptone No. 3 ……………………………………………………..20.0 
Dipotassium phosphate…………………………………………..…………15.0  
 Magnesium sulfate……………………………………………….………….1.5 
 Agar …………………………………………...……………………………14    
pH : …………………………………………...………………..7.0±0.2 - 25°C 
Reinforced Clostridial MediumRCM(Formule: g/l)  
Yeast extract…………………………………………………………….     13.0 
Peptone…………………………………………………………………..     10 
Glucose……………………………………………………………………..5.0 
Soluble starch……………………………………………………………….1.0 
Sodium chloride……………………………………………………..5.0 
Sodium acetate………………………………………………………       3.0 
Cysteine hydrochloride………………………………………………………    0.5 
Agar………………………………………………………………………….13.5 
pH :………………………………………………………………….6.8±0.2 C 
 
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Mannitol Salt Agar (Chapman Agar) (formula: g/l)  
Meat extract………………………………….………………………………..1 
Caseine pepton……………………………………….……………………….5 
Meat pepton…………………………………………….…………………….5 
Sodium chloride………………………………….…………………………..75 
D mannitol…………………………………………………………………….10 
Phenol red………………………………………………………………….0.025 
Agar……………………………………………………………………………15 
pH: …………………………………………………………………7.0±0.2 -25°C 
 
Salmonella- ShigellaS-S Agar(formula: g/l)  
Lactose ………………………………………………………………………10 
Bile Salts mixture……………………………………………………………8.5 
Sodium citrate ………………………………………………………………8.5 
Sodium Thiosulfate………………………………………………………    8.5  
Beef extract………………………………………………………………….5.0 
Peptone mixture……………………………………………………………..5.0 
Ferric citrate………………………..…………………………………………1 
Neutral red………………………………………………………………….0.025 
pH: …………………………………………………………………7.0±0.2 -25°C 
 
Trypton Soy Agar TSA(formula: g/l) 
Pancreatic digest of casein……………………………………………….17.0 
Papaic digest of soyabean meal………………………………………..3.0 
Sodium chloride………………………………………………………………….5.0 
Dextrose (Glucose)……………………………………………………………2.5 
Dipotassium hydrogen phosphate……………………………………………2.5 
Agar…………………………………………………………………………15.0 
pH: …………………………………………………………………7.0±0.2 -25°C 
Brain Heart Infusion (BHI) Agar(formula: g/l) 
HM infusion powder………………………………………………………………12.5 
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BHI powder…………………………………………………………………………..5.0 
Proteose peptone…………………………………………………………………….10.0 
Dextrose (Glucose)…………………………………………………………………...2.0 
Sodium chloride……………………………………………………………………….5.0 
Disodium phosphate…………………………………………………………………….2.5 
Agar…………………………………………………………………………………….15.0 
pH: …………………………………………………………………7.0±0.2 -25°C 
 
Appendix 3: Gram Staining 
It was developed by Danes Christian Gram in 1881, it is the most important and most used 
coloration of bacteria, and it allows to divide the bacterial world into two subgroups: 
Gram-positive bacteria: these organisms retain the primary dye, the crystal violet, after 
discoloration and appear dark blue when viewed under light microscopy since the counter-dye 
(safranin) cannot displace the primary dye. 
Gram-negative bacteria: where the primary dye is removed by washing with ethanol and replaced 
by the last dye used safranin. These bacteria will appear red to us under light microscopy. 
The variation in the ability to retain the primary dye (crystal-violet) is linked to differences in the 
chemical composition of the cell wall. 
Gram staining has four steps as shown in the following Gram staining table 
Réactif Effet Gram + Gram - 
Cristal violet Primary staining Blue Blue 
Lugol (iodine) Mordant * Blue Blue 
95% Ethanol  Differentiation agent Blue Incolore 
Safranine Against dye Blue Red 
 
*Iodine acts as a mordant because iodine forms with crystal violet an iodine-violet crystal complex, 
which is more easily retained by Gram + bacteria. 
Make the Gram preferably on young cultures (24 to 48 hours), because bacteria often show a Gram 
+ only when they are actively growing: they lose the ability to retain the crystal-violet-iodine 
complex when active growth stopped. This is particularly true for sporulated strains. 
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Method: 
 Prepare a smear from each bacterial species and fix it as described in the simple staining 
section. 
 Cover the smear with Hucker's purple crystal. Leave in contact for one minute before 
washing with water. At this stage it is necessary to avoid over washing because there may 
be discoloration, no more than 2-3 seconds. 
 Cover the smear with the iodine gram solution and allow to settle for one minute before 
washing with water. (At this stage crystal violet is complexified and cannot be removed by 
washing). 
 Keep the blade in an oblique position and bleach with 95% alcohol until the alcohol remains 
colorless, the duration of the bleaching depends on the thickness of the smear: 5-15 seconds 
for a thin smear, 15- 30 seconds for a thicker smear, rinse with water. 
 Apply the counter-dye (safranine) and leave in contact for one minute. Wash with water, 
lightly, because saffron can be washed out by excessive washing, and dry with blotting 
paper (without rubbing) before observing. 
 
Appendix 4: Microbial mean Log10 CFU g_ 1prevalence of Salmonella and pH of fish in 
sampling point in Selingue 
% pH of fish 
Cell concentration (Log10 CFU g_ 1) Prevalence 
Sampling (N=134) 
Fish species 
point Total Sulphite 
Total Fecal Staphylococcus Salmonella 
Viable Reducing 
Coliforms Coliforms aureus  spp. 
Bacteria Bacteria 
L. niloticus 6.85 6.38 6.3 0.39 2.71 100  6.44 
C. anguillaris 7.52 6.53 5.96 0.5 1.97 100  6.66 
Capture O. niloticus 7.13 6.41 6.28 0 1.05 75 6.39 
L. niloticus 6.76 5.71 5.63 0.53 3.7 75 6.65 
C. anguillaris 7.3 6.72 6.33 0 1.17 75 6.77 
Landing O. niloticus 7.16 6.5 6.25 0.64 2.72 100 6.76 
L. niloticus 6.65 4.57 4.31 1 1.64 100 6.56 
C. anguillaris 6.88 4.39 4.42 0.62 0 100 6.63 
Selling O. niloticus 6.53 4.11 3.64 1.47 0 50 6.64 
Standard 5   1  1  1  2 Absence/25g 6.8 - 7.6 
 
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Appendix 5: Microbial count, prevalence of Salmonella and pH of fish in sampling 
point in Manantali 
Cell concentration (Log10 CFU g_ 1) 
Sampling  Total Sulphite 
Fish species Total Fecal Staphylococcus pH of fish 
point Viable Reducing Salmonella spp. 
Coliforms Coliforms aureus. 
Bacteria Bacteria 
L. niloticus 5.82 6.75 7.04 0.51 3.07 100 6.47 
Capture C. anguillaris 7.03 6.89 6.28 0.49 2.61 75 6.42 
O. niloticus 5.83 5.71 5.16 0.15 2.15 75 6.55 
L. niloticus 6.8 7.29 6.52 0.26 2.43 75 6.48 
Landing C. anguillaris 6.55 7.49 6.62 0.68 1.82 100 6.44 
O. niloticus 6.28 7 6.91 0 1.58 100 6.48 
L. niloticus 7.36 6.47 4.95 0 5.01 100 6.66 
Selling C. anguillaris 7.5 6.23 5.85 0.075 2.17 100 6.52 
O. niloticus 7.5 6.23 5.85 0 2.85 100 6.51 
Standard 5 1 1 1 2 Absence/25g 6.8 - 7.6 
 
Appendix 6: Microbial count, Prevalence of Salmonella and pH of fish in sampling point in 
Markala 
 
Cell concentration (Log10 CFU g_ 1) 
Sampling 
Fish species Total Sulphite pH of fish 
point Total Fecal Staphylococcus Salmonella 
Viable Reducing 
Coliforms Coliforms aureus spp. 
Bacteria Bacteria 
L. niloticus 5.23 5.56 4.9 0.69 0.22 100 6.69 
C. anguillaris 5.93 6.2 5.37 0.26 0.41 100 6.59 
Capture O. niloticus 5.6 6.36 6.4 1.74 0.12 100 6.25 
L. niloticus 6.46 6 5.68 1.05 0 100 6.63 
C. anguillaris 7.7 6.39 5.5 0 1.74 100 6.22 
Landing O. niloticus 6.35 6.49 5.23 0.19 1.13 100 6.43 
L. niloticus 7.03 6.5 6.18 1.34 1.71 100 6.28 
C. anguillaris 7.33 7.1 7.5 1.65 2.65 100 6.41 
Selling O. niloticus 7.17 7.01 6.82 1.1 2.9 100 6.32 
Standard 5 1 1 1 2 Absence/25g 6.8 - 7.6 
 
 
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Appendix 7: Microbial count, Prevalence of Salmonella and pH of fish in sampling 
point in Mopti 
Cell concentration (Log10 CFU g_ 1) 
Total Sulphite 
Sampling point Fish species Total Fecal Staphylococcus Salmonella pH of fish 
Viable Reducing 
Coliforms Coliforms aureus. spp. 
Bacteria Bacteria 
L. niloticus 6.06 5.92 5.5 0 0 100 6.53 
C. 
6.25 6.2 5.05 0 0 100 6.6 
anguillaris 
Capture O. niloticus 6.36 6.43 6.22 1.51 0.1 100 6.72 
L. niloticus 7.01 6.75 6.41 0.2 1.65 100 6.65 
C. 
7.42 7.23 6.8 0.1 1.67 100 6.58 
anguillaris 
Landing O. niloticus 7.83 6.76 6.28 0.075 1.33 100 6.64 
L. niloticus 6.72 6.54 6.47 6.05 2.33 100 6.54 
C. 
6.83 6.95 6.4 0.56 1.83 75 6.4 
anguillaris 
Selling O. niloticus 6.91 6.76 6.73 0.19 1.87 75 6.5 
Standard 5 1 1 1 2 Absence/25g 6.8 - 7.6 
 
  
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Appendix 8: Macroscopy observation for the spoilage microorganisms 
Areas Season Sampling Macroscopy observation 
point Relief Diameter Color 
Flat Convex Large Small Tiny Colorless Yellow White 
Selingue Cold Capture 21 6 9 8 10 15 4 8 
Landing 26 8 6 11 7 11 19 4 
Hot Capture 8 12 1 10 7 13 1 6 
Landing 10 6 4 5 7 5 5 6 
Selling 5 7 2 5 5 5 - 7 
Manantali Cold Capture 9 6 3 5 7 6 1 8 
Landing 11 - 3 4 4 8 1 2 
Selling 11 1 1 8 3 5 1 6 
Hot Capture 6 12 4 5 9 12 1 5 
Landing 6 12 2 4 12 5 1 12 
Selling 3 9 2 2 8 6 2 4 
Markala Cold Capture 5 13 4 5 9 5 5 8 
Landing 8 9 1 6 10 2 6 9 
Selling 5 5 2 4 4 7 1 2 
Hot Capture 8 5 2 3 8 7 - 6 
Landing 7 13 1 5 10 5 1 10 
Mopti Cold Capture 8 8 5 2 9 10 1 5 
Landing 9 8 6 1 10 6 5 6 
Selling 4 8 1 5 6 6 1 5 
Hot Capture 6 12 6 7 5 6 4 8 
Landing 6 11 2 4 11 8 1 8 
Selling 7 5 2 6 6 8 2 2 
Total 189 176 69 115 167 161 63 137 
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Appendix 9: Microscopy observation and biochemical test for the spoilage 
microorganisms 
Areas Season Sampling Microscopy observation Biochemical Test 
point 
Shape Mode of grouping Gram Catalase Oxydase 
Rods Cocci In pair Chain Cluster Neg Pos Neg Pos Neg Pos 
Selingue Cold Capture 12 12 18 4 2 24 - - 24  24 
Landing 10 23 27 4 2 33 - - 33 - 33 
Hot Capture 14 6 2 - 18 20 - - 20 - 20 
Landing 7 9 3 1 12 16 - - 16 - 16 
Selling 11 1 4 3 5 12 - - 12 - 12 
Manantali Cold Capture 15 - 14 1  15 - - 15 - 15 
Landing 8 3 9 1 1 11 - - 11 - 11 
Selling 10 2 5 4 3 12 - - 12 - 12 
Hot Capture 12 0 3 - 9 12 - - 12 - 12 
Landing 14 4 5 3 10 18 - - 18 - 18 
Markala Cold Capture 19 4 8 1 14 23 - - 23 - 23 
Landing 9 8 9 - 8 17 - - 17 - 17 
Selling 9 1 8 - 2 10 - - 10 - 10 
Hot Capture 10 3 6 2 5 13 - - 13 - 13 
Landing 5 11 1 - 15 16 - - 16 - 16 
Mopti Cold Capture 9 1 7 - 3 10 - - 10 - 10 
Landing 16 1 9 1 7 17 - - 17 - 17 
Selling 11 1 8 - 3 12 - - 12 - 12 
Hot Capture 18 - - - 18 18 - - 18 - 18 
Landing 16 1 - - 17 17 - - 17 - 17 
Selling 11 1 - - 12 12 - - 12 - 12 
Total 246 92 146 25 166 338   338  338 
 
 
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Appendix 10: Macroscopy observation for the pathogenic microorganisms 
Areas Season Sampling Macroscopy observation 
point Relief Diameter Color 
Flat Convex Small Tiny Colorless CBC Yellow Black Pink 
Selingue Cold Capture 10 5 3 7 6 - - 2 2 
Landing 8 - 5 3 7 - - 1  
Hot Capture - 8 - 8 1 2 1 - 4 
Landing 1 5 3 3 2 - - - 4 
Selling - 5 - 5 3 2 - - - 
Manantali Cold Capture 3 - - 3 2 1 - - - 
Selling 6 - - 5 4 2 - - - 
Hot Capture - 9 2 7 4 2 - - 3 
Landing - 9 1 8 3 4 1 - 2 
Markala Cold Capture 1 3 - 4 1 3 - - - 
Landing 1 3 - 4 1 1 - - 2 
Selling 4 2 1 5 3 2 - - 1 
Hot Capture - 2 - 2 -  1 - 1 
Landing 1 4 - 4 - 2 1 - 1 
Mopti Cold Capture 1 8 3 6 4  2 - 3 
Landing 1 6 - 7 - 4 2 1 - 
Selling - 3 - 3 1 1 - - 1 
Hot Capture 3 4 - 7 1 2 - - 4 
Landing 5 4 1 8 - 1 4 2 2 
Selling - 2 - 2 - 1 - - 1 
Total 44 76 19 101 43 30 12 6 31 
CBC: Colorless with black center 
  
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Appendix 11: Microscopy observation and biochemical test for the pathogenic 
microorganisms 
Areas Season Sampling Microscopy observation Biochemical Test 
point Shape Mode of grouping Gram Catalase Oxydase 
Rods Cocci In Chain Cluster Neg Pos Neg Pos Neg Pos 
pair 
Selingue Cold Capture 9 1 5 3 2 10 - - 6 - 10 
Landing 6 2 3 1 4 8 - - 8 - 8 
Hot Capture 8 - 1 - 7 8 - - 8 - 8 
Landing 5 1 - 2 4 6 - - 6 - 6 
Selling 5 - 1 - 4 5 - - 5 - 5 
Manantali Cold Capture 3 - 2 - 1 3 - - 3 - 3 
Selling 5 1 - - - 6 - - 6 - 6 
Hot Capture 9 - - 1 8 9 - - 9 - 9 
Landing 9 - 3 - 6 9 - - 6 - 9 
Markala Cold Capture 4 - 3 - 1 4 - - 4 - 4 
Landing 4 - - - 4 4 - - 4 - 4 
Selling 6 - 2 - 4 6 - - 6 - 6 
Hot Capture 2 - 1 - 2 2 - - 2 - 2 
Landing 4 - - 2 2 4 - - 4 - 4 
Mopti Cold Capture 7 2 7 - 2 9 - - 9 - 9 
Landing 7 - 3 - 4 7 - - 7 - 7 
Selling 3 - - - 3 3 - - 3 - 3 
Hot Capture 7 - - 2 5 7 - - 7 - - 
Landing 9 - - - 9 9 - - 9 - 9 
Selling 5 - 2 - 3 5 - - 5 - 5 
Total 117 8 32 11 75 124   117  117 
132 
 
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Appendix 12: API 20NE reading 
 
Appendix 13: API 20E reading 
 
 
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Vol. 06, No. 05; 2021 
ISSN: 2456-8643 
PARASITES IN FRESHWATER FISH ALONG VALUE CHAIN OF MEDINA COURA 
MARKET IN BAMAKO, MALI 
 
Aminata Sissoko1,2, Fassé Samaké3, Kwaku Tano-Debrah1, Angela Parry-Hanson Kunadu1, Ibrahima 
Mariko2, Felix Kwashie Madilo1,4, Boubacar Madio dit Aladiogo Maïga2, Saidou Tembely2 
1Department of Nutrition and Food Science, University of Ghana, Legon, Accra, Ghana 
2Central Veterinary Laboratory (CVL), Bamako, Mali 
3Microbiology and Microbial Biotechnology Research Laboratory, Departement of Biology, University of Sciences, 
Techniques and Technology of Bamako, Bamako, Mali 
4Department of Food Science and Technology, Faculty of Science and Technology, Ho Technical University, Ho, 
Ghana 
 
https://doi.org/10.35410/IJAEB.2021.5669  
 
 
 
ABSTRACT 
Parasitic infestations of 120 specimens of three freshwater fish species, comprising of Lates 
niloticus (44), Clarias anguillaris (40) and Oreochromis niloticus (36) sold at the Medina Coura 
market in Mali, were investigated. The fresh fish samples were taken during two seasons (cold 
and hot) in four fish production areas (Niger Central Delta in Mopti, Selingue, Manantali, 
Markala) and from the Medina Coura market. In each area, the samples were taken at three 
points (capture, landing and sale), using standard methods and procedures. A dissection was 
performed on each fish sample and the conditions of the skin, flesh, gills and abdominal cavity 
were observed for the detection of infestations. Three species of parasites were detected, namely, 
Salmincola edwardsii (crustacea) at the gills, and Philonema sp. and Raphidascaris sp. 
(Nematodes) in the abdominal cavity. An overall prevalence of 10% (12/120) parasitic 
infestation was observed. Prevalence was lower during the cold season, (5.2% of the fish) than in 
the hot season (14.5%). The highest prevalence of infestation was observed in Oreochromis 
niloticus (Tilapia) at 16.7% followed by Lates niloticus (Nile Perch) (9.1%) and Clarias 
anguillaris (Catfish) (5.0%). Research finding showed that infection prevalence and diversity of 
parasites were relatively low. 
Keywords: Parasites, fresh fish, freshwater, Niger river, Senegal river. 
1. INTRODUCTION 
Fish is one of the best sources of animal protein for human health. According to the Food and 
Agriculture Organization (Djiré, 2007), fish is an important source of nutrients, because of its 
protein, vitamin A and D, phosphorus, lysine, sulphur and essential amino acids composition. 
Cholesterol level is also low in fish meat (Fagbenro et al., 2005; Aremu et al., 2013; Ayeloja et 
al., 2013; Oladipo and Bankole, 2013; Khalili Tilami & Sampels, 2017). 
All fish species are vulnerable to various parasitic infections depending on the species of fish and 
the type of watercourses inhabited (Oniye et al., 2004). Various parasites are associated with 
freshwater fish; they cause morbidity, mortality and economic losses in Africa (Oniye et al., 
2004; Ayanda, 2009). When the parasite infects the fish, they usually cause chronic damage that 
can be tolerated by the fish (Bamidele, 2015). Factors favoring parasitic infection in fish include 
reduction of the oxygen content of water, an increase of organic matter and poor environmental 
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conditions (Edema et al., 2008). Fresh or undercooked infected fish can cause zoonotic 
infections, which are a real public health problem (Dorny et al., 2009; Bouchriti et al., 2014). 
In Mali, food safety risks associated with the presence of parasites in fishery products are 
poorly known by professionals and consumers. Parasitic fish must be rejected, if it is not 
sufficiently cooked since its penetration into the upper digestive tract may be a threat to the 
health of the consumer. Therefore, it is important to sensitize the population about fish hygiene 
practices to minimize the impact of the parasite on public health. 
The present study was conceived to determine the prevalence and seasonal distribution of 
parasites in economically important and popular freshwater fish species: Lates niloticus, Clarias 
anguillaris, and Oreochromis niloticus sold on the Medina Coura market in Bamako. 
2. MATERIAL AND METHODS 
Study Area   
In Mali, fishing is practiced in almost all water bodies in the country. It is the largest freshwater 
fishing country in the world. Fishing is practiced in two river basins lakes, ponds and flood 
plains (Quensiere, 1994). The main fishing areas are Central Delta of Niger (about 80% of total 
freshwater fish production), Selingue Lake, Markala Lake and Manantali Lake (Figure1). 
The Central Niger Delta is a vast region of about 30 000 km2, in the Center of Mali. The annual 
production varies between 45 000 and 100 000 tones according to the importance of the floods 
(Quensiere, 1994). About 140 km South of Bamako, Selingue The dam is 348 m long and the 
lake covers 409 km2 and contains 2.2 billion m3 of water. However, its depth does not exceed 20 
m (Paugy & Leveque, 2006). By year, the lake produces about 4000 tons of fish (Miller, 2006). 
Manantali Lake provides both irrigation and hydroelectric power. 208m long with an area of up 
to 500 km2, it contains 11 billion m3 of water. The depths of the medium and maximum dam are 
respectively 20 m and 50 m (Miller, 2006). Per year, fish production is about 1,500 tons, 
Markala dam was built in 1943, located 250 km downstream from Bamako in Mali to store water 
for irrigation (Miller, 2006). The "Office du Niger" zone, aims to develop agriculture. 
 
 
 
Figure 1: Map showing the different sampling points 
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Sampling procedure 
Three freshwater fish species sold on the Medina Coura market, a major fish market in Bamako 
were sampled for this study. These were Nile perch: Lates niloticus, vernacular name in Bambara 
(Saalen); Catfish: Clarias anguillaris, vernacular name in Bambara (Maanogo Blen) and Tilapia: 
Oreochromis niloticus, vernacular name in Bambara (N'teben fin). These fishes were selected 
because of their economic importance and popularity in Mali. All samples were obtained from 
harvest and landing sites, from four (4) areas (Selingue, Manantali, Markala, Mopti) and a selling 
site in Medina Coura market. 
Two (2) specimens of each of the three (3) species of fish were sampled for parasitic 
assessments. 
Sample size 
The Samples were taken during the cold season (December - February) and the hot season 
(March-May) (table1). 120 randomly selected fresh specimens of 44 Lates niloticus, 40 Clarias 
anguillaris, and 36 Oreochromis niloticus, were purchased at capture point, at the landing point 
where the fishes are packed for the market and at Medina Coura market, which is selling point. 
The samples were transported directly to the helminthology laboratory of the Central Veterinary 
Laboratory of Bamako in a cooler, where they were subjected to parasite analyses. 
Table 1: Distribution of fish species collected by sampling site 
Areas  Seasons L. niloticus C. anguillaris O. niloticus Total 
Selingue Cold  4  4  4  30 
  Hot  6  6  6  
Manantali Cold  6  4  4  30 
  Hot  6  6  4  
Markala Cold  6  4  4  26 
  Hot  4  4  4  
Mopti  Cold  6  6  6  34 
  Hot  6  6  4  
Total    44  40  36  120 
  
The parasitological examination was made on fish by its lateral decoupage through the 
mouth. The alimentary canals were removed and cut into different parts, such as the stomach, 
large intestine, and small intestine. This was done on a petri dish with normal saline for parasite 
recovery. The intestines were carefully cut to promote the emergence of parasites. 
The macroscopic examination involved observation of the general state of each sample, 
the level of deterioration of the skin, the state of the gills by the appreciation of the color, and the 
signs of attack. The fish were also examined under the Olympus BO61 binocular magnifier for 
cysts, larvae in the flesh and the abdominal cavity. The results were analysed for prevalence 
according to Margolis et al., 1982: 
Prevalence (%) = number of infected hosts × 100 / total number of hosts examined 
Crustacea identification was based on morphological features according to Yamaguti, 1963. 
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Data analysis method 
The one-way analysis of variance (ANOVA) was applied to determine the significance of 
changes in the prevalence of infection between the two seasons in 4 areas of the study period. 
The percentages of infestation were compared by the chi-square χ2 test. 
SPSS 23.0 Software was used for data analysis with a confidence interval of 95%. 
3. RESULTS  
Of the 120 fish samples analyzed, parasites were present in fishes at the capture points, the 
landing point at Selingue, Manantali, Markala, Mopti and at the selling point Medina Coura 
market. 
Prevalence of infected fish species 
Parasite infestation has varied from one species to another. A low infestation rate was observed 
(10%) in our fish samples. The highest parasite infestation was observed in Oreochomis niloticus 
with an infestation rate of 16.7% followed by Lates niloticus 9.1% and Clarias anguillaris 5.0% 
during both seasons. A no significant difference in prevalence between fish species examined 
was observed chi-square χ2 = 0.87, (p> 0.05). It showed a lower variation of prevalence of 
parasites among the fish species in this study 
Table 2: Prevalence of parasites by fish species 
Fish species   Number examined Number infected Prevalence (%) 
Lates niloticus   44   4   9,1 
Clarias anguillaris  40   2   5 
Oreochromis niloticus 36   6   16,7 
Total    120   12   10 
Variation of parasitism according to the organs of the fish and areas of sampling 
The skin, flesh, gills, and abdominal cavity were observed macroscopically. The most 
affected internal organs of the fish were the gills with the presence of Salmincola edwardsii 
(crustaceans) and the abdominal cavity with the presence of nematodes Rhaphidascaris sp. and 
Philonema sp.. These parasites belonging to different taxonomic groups were recovered from 12 
positives sampled fish. 
The frequency distribution of parasites among the three fish species (Lates niloticus, 
Clarias anguillaris, and Oreochromis niloticus) per sampling area is presented in Table 3. 
Philonema sp. (12.5%) was the most frequently found parasite in Markala followed by 
Raphidascaris sp. Which were recovered from the abdominal cavity in 10% and 8.82% 
respectively of fishes sampled in Selingue and Mopti. Salmincola edwardsii was found in the 
gills at 4.16% of the fish sampled at Markala. These results show that there is no significant 
difference between parasite variation and prevalence at the sampling areas (χ2 = 0.821, p> 0.05). 
 
 
 
 
 
 
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Table 3: Prevalence of parasites per infected organs and areas 
 
Parasites  Inf. Organs Selingue Manantali Markala Mopti 
     NOP P(%) NOP P(%) NOP P(%) NOP P(%)  
Raphidascaris sp. Abd. cavity 3 10 1 3.57 0 0 3 8.82 
Philonema sp.  Abd. cavity 0 0 0 0 3 12.5 2 5.88 
Salmincolaedwardsii Gill  0 0 1 4.16 0 0 0 0 
Key: NOP – Number of positive; P – Prevalence; Inf. – Infected; Abd– Abdominal 
Seasonal variation offish parasites per sampling areas 
To assess the seasonal prevalence of parasites in the cold and hot seasons, 58 and 62 
samples were examined for hot and cold seasons respectively of which 3 (5.17%) and 9 
(14.52%) were infested respectively. 
The parasite frequency distribution per season and the per area have shown that the high 
parasite infestation was observed during the hot season in Selingue with 25% prevalence 
followed by Mopti 20%, Manantali 16.66%, and Medina Coura 1.66%. In the cold season fish 
sampled from the selling point had parasite infestation rate of 10%, followed by Manantali and 
Markala with 8.33% in a landing point. The seasonal variation on parasites of fish species 
samples per area was not significantly different (χ2= 0.363, p> 0.05) from each other during the 
different seasons. 
Table 4: Prevalence of fish infested with parasites per areas and season 
Seasons Sampling Site  No. Examined No. Infected Prevalence (%) 
Cold season Selingue  12  0  0 
  Manantali  12  1  8.33 
  Markala  12  1  8.33 
  Mopti   12  0  0 
  MCM   10  1  10 
  Total   58  3  5.17 
Hot season Selingue  12  3  25 
  Manantali  12  2  16.66 
  Markala  12  0  0 
  Mopti   10  2  20 
  MCM   16  1  1.60 
  Total   62  9  14.52 
TOTAL    120  12  10 
Key: Medina Coura Market 
3.4 Prevalence of infected fish species at each sampling point 
Table 5 shows the prevalence of each species of fish in each area at the sampling points. 
Parasite prevalence varied from one fish species to another. The highest prevalence of the 
parasite in Oreochromis niloticus was observed at Mopti at the selling point (50%) followed by 
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Vol. 06, No. 05; 2021 
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Lates niloticus 25% while the other species of fish have a prevalence of 0% at the same point of 
sale. 
 
Table 5: Prevalence of infected fish species at each sampling point 
 
Sampling Site Fish Species Capture point  Landing point  Selling point 
    NE NI P(%) NE NI P(%) NE NI P(%)  
Selingue L. niloticus 4 0 0 4 1 25 2 0 0 
  C. anguillaris 4 0 0 4 0 0 2 0 0 
  O. niloticus 4 1 25 4 1 25 2 0 0 
Manantali L. niloticus 4 0 0 4 0 0 4 0 0 
  C. anguillaris 4 0 0 4 0 0 2 0 0 
  O. niloticus 4 0 0 4 1 25 0 0 0 
Markala L. niloticus 4 0 0 4 0 0 2 0 0 
  C. anguillaris 4 1 25 4 1 25 0 0 0 
  O. niloticus 4 1 25 4 0 0 0 0 0 
Mopti  L. niloticus 4 1 25 4 1 25 4 1 25 
  C. anguillaris 4 0 0 4 0 0 4 0 0 
  O. niloticus 2 0 0 4 0 0 4 2 50 
Total    42 4 9.5 44 5 11.4 26 3 11.5 
Key: NE – Number examined; NI – Number infected; P – Prevalence 
4. DISCUSSION 
Our study revealed an overall rate of parasite infestation of 10% in Lates niloticus, 
Clarias anguilaris, Oreochromis niloticus species. The preliminary investigation of the parasite 
fauna of fish in Okhuo River in Benin City, Nigeria done by obtained 6.94% infestation rate. 
These were rather very low as compared to other similar work such as(Amare et al., 2014a)who 
reported 47.8%prevalence of parasites, in Lake Lugo (Hayke), Northeast Ethiopia, and 
Olofintoye (2006) who observed 62.6% in his study on a parasitofauna in some freshwater fish 
species in Ekiti States, Nigeria suggesting that the distribution of parasites can be varied from 
one habitat to the other due to host parasite relationship and abiotic factors like dissolved 
oxygen, temperature and pH. This depends on a number of factors which include among other 
things, the nature of the water which is reflected in the human use and the endemicity of 
infection in the area. 
The prevalence of parasites was higher in Oreochromis niloticus 16.7% followed by Lates 
niloticus 9.1% and Clarias anguillaris 5%. In the present study prevalence finding are lower than 
Amare et al., 2014b in Lake Lugo (Hayke), Northeast Ethiopia who found a prevalence rate of 
50.22% in Oreochromis species. 
The study showed that, the prevalence of nematodes was higher than crustacea. The higher rate 
of nematode infestation may be due to the low host specificity of the adult stage of these 
parasites, or the ability of different genera and species of the nematode to infect the fish species 
studied, and the availability of the different host required for the completion of the life cycle of 
these parasites Yamaguti, 1963. 
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The prevalence of Salmincola edwardsii is 4.16% observed only in Manantali on 
Oreochromis niloticus in the gills. Salmincola edwardsii belong to the Arthropoda Phylum, 
subphylum Crustacea, family Lernaeopodidae, and are commonly called "gill lice" or "gill fly" 
Alteen, 2009 and Boucenna et al., 2015 also detected the presence of this parasite in the gills. 
They inferred that this parasite can cause swelling around the site of attachment of the bubble, 
with heavy parasite loads. The presence of this crustacean reduces the feeding activity of the host 
fish by weakening the host fish and negatively affecting its weight gain, reproduction, and 
therefore growth. According to Folefack et al.,(2019a) the frequency of gill infestation by these 
parasites is may be because gills have a close relationship with the aquatic environment where 
fish live. It is observed that Oreochromis niloticus collected at the point of sale in the Mopti area 
during the hot season has a much higher prevalence (50%) than other species. These parasites are 
capable of absorbing nutrients, vitamins, micro and macronutrients in the digestive tract of fish. 
According to Bichi & Dawaki (2010), these parasites develop metabolic wastes that have a 
negative impact on the physiology and reproduction of fish. 
5. CONCLUSION 
The study allowed us to determine the parasites present in the 5 areas (Selingue, 
Manantali, Markala, Mopti, and Medina Coura market) for freshwater fresh fishes from harvest 
capture to sale. The prevalence of parasites among fish in rivers in Mali was low.  
However, parasites should not be neglected in fish, they are important enough to reduce the 
number of fish per death, reduce their market value, and may cause human infections when live 
cysts or matured parasites are ingested. 
6. DECLARATION  
Funding: This study was funded by Borlaug High Education for Agricultural Research 
(BHEARD). The authors are also grateful to Central Veterinary Laboratory (CVL), Mali where 
the laboratory analysis was carried out and the collaborating institution, Department Nutrition 
and Food Science, University of Ghana. 
Conflict of interest: Not applicable  
Ethical approval: Ethical clearance was obtained from the Ethics Committee of the National 
Institute of Research in Public Health (INRSP). The provisions relating to ethics have been 
observed and respected according to the provisions of Law No. 2013-015 of 21 May 2013 on the 
Protection of Personal Data in the Republic of Mali and the Declaration of 'Helsinki 5 version 
2013 to establish fact sheet, a free and informed consent form. 
Consent for publication: Not applicable 
Consent to participate: Written informed consent was obtained from the participants. 
Availability of data and material: All available data supporting the study have been included in 
the write-up 
Code of availability: Not applicable 
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AUTHOR CONTRIBUTION  
Aminata Sissoko designed the topic, collected data, and wrote the manuscript, while Fassé 
Samaké, Tano Debrah Kwaku, and Angela Parry-Hanson Kunadu approved the topic, supervised 
and reviewed the manuscript, Felix Kwashie Madilo and Boubacar Madio dit Aladiogo 
Maïga1conducted the data analysis, and formatted the manuscript.  Ibrahima Mariko conducted 
the laboratory analysis. 
 
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