Estimation of Variation in Oreochromis niloticus and
Sarotherodon galilaeus using Morphometric, Merisitic,
Quality Characteristics and Molecular Markers
By
Omeima Mohammed Omer Mohammed
B. Sc. (Honours) Natural Resources and Environmental Studies (Fisheries
Sciences), University of Juba, 1994.
M. Sc. in Environmental Studies, Institute of Environmental Studies, University of
Khartoum, 2001.
A Thesis submitted to the University of Khartoum for
the Fulfillment of requirement for the Degree of Doctor of Philosophy in Zoology
(Genetics and Molecular Biology)
Supervisor Prof. Zuheir Nour El Dayem Mahmoud
Co-supervisor Dr. Abd El Wahab Hassan Abdalla
Department of Zoology,
Faculty of Science
July, 2017
I
Dedication
This work is dedicated
To
My mother
My brothers and sisters
My husband
And
The memory of my father
II
Acknowledgements
I would like to express my sincere gratitude to my supervisors:
Professor Zuheir Nour El Daim Mahmoud and Dr. Abd El Wahab Hassan
Abdalla.
I would like to thank Dr. Marmar El Sidig and Dr. Mai Masri for
helping in molecular data analysis, Miss. Huda Ahmed; Dr. Amna Taj Elsir
and Ayaa Abd Al Gadir for helping in PCR work and Dr. Elsadig Arbab
Hagar for support especially in the field work.
I offer my thanks and regards to the colleagues in fisheries
administrations in the different states of Sudan for their all co-operation to
get my research samples and field work.
This work was supported by funds from Ministry of Agriculture and
Animal Wealth and Irrigation, Khartoum State.
III
Contents
Title Page
Dedication ……………………………………………………...…… i
Acknowledgement …………………………………………...……... ii
Contents ………………………………………………...………….. iii
List of tables …………………………………………...……………
List of figures ……………………………………………………….
vi
viii
List of plates …………………………………………...……………
List of appendices……………………………………………………
ix
x
List of acronyms...…………………………………...……………… xi
Abstract ……………………………………………...……………… xii
Abstract in arabic …………………………………...…………….... xiv
Chapter one: Introduction ……………………..……………….… 1
Chapter two: Literature review ……………………...……...…..
2.1. Tilapia spp ……………………………………………..
2.2. Fish genetic variability and diversity ………………….....
2.2.1. RAPD technique………………………………………..
2.2.2. Application of RAPD technique………………………..
2.3. Aquaculture ………………………………………………
2.4. Quality traits ……………………………………..…….
5
5
7
9
10
11
14
Chapter Three: Materials and methods …………………………
3.1. Samples and origin of experimental fish ……………….
3.2. Morphometric and meristic parameters …………….......
3.3. Quality traits - chemical composition ……………...........
3.4. Molecular method………………………………………...
3.4.1. Sample preparation ………………………………........
16
16
17
23
23
23
IV
3.4.2. Quantification of DNA samples ………………….......
3.4.3. Primers ……………………………………………......
3.4.4. Amplification of DNA ………………………………...
3.5. Statistical analysis……………………………………….
3.5.1. Statistical analysis for morphometric characteristic,
meristic count and chemical traits…………………………...
3.5.2. Scoring and analysis of RAPDs ………………………
23
24
25
26
26
26
Chapter four Results ……………………………………………..
4.1. Morphometric and meristic parameters …………………
4.1.1. Body weight……………………………………………
4.1.2. Total length…………………………………………….
4.1.3. Standard length ………………………………………...
4.1.4. Body depth ……………………………………………..
4.1.5. Head length …………………………………………….
4.1.6. Head depth ……………………………………………..
4.1.7. Snout length ……………………………………………
4.1.8. Base length of dorsal fin ………………………………
4.1.9. Posterior end of the dorsal fin to dorsal origin of the
caudal fin …………………………………….………….
4.1.10. Length of the anal fin………………………………….
4.1.11. Base length of the anal fin ……………………………
4.1.12. Length of the pelvic fin………………………………..
4.1.13. Caudal peduncle length ……………………………….
4.1.14. Caudal peduncle depth ………………………………..
4.1.15. Eye diameter ………………………………………….
4.1.16. Mouth gape …………………………………………...
4.1.17. Predorsal distance …………………………………….
4.1.18. Prepelvic distance ……………………………………
28
28
28
28
29
29
30
30
30
31
31
32
32
33
33
33
34
34
35
35
V
4.1.19. Preanal distance ………………………………………
4.1.20. Prepectoral distance …………………………………..
4.1.21. Lower jaw length ……………………………………..
4.1.22. Premaxilary pedical length …………………………...
4.1.23. Number of the lateral line scales……………………...
4.1.24. Number of the predorsal scales………………………..
4.1.25. Number of the postdorsal scales ……………………...
4.1.26. Number of scales surrounded the caudal peduncle …...
4.1.27. Number of the rays in the dorsal fin ………………….
4.1.28. Number of the spines in the dorsal fin ………………..
4.1.29. Number of rays in the anal fin ………………………..
4.1.30. Number of spines in the anal fins …………………….
4.1.31. Number of rays in the pectoral fin ……………………
4.1.32. Number of rays in pelvic fin ………………………….
4.1.33. Number of rays in caudal fin …………………………
4.1.2. Correlation coefficients ………………………………..
4.1.2.1. Length-body weight relationship…………………….
4.1.2.2. Correlation between some traits …………………….
4.1.3. Morphometric and meristic cluster analysis …………..
4.2. Chemical compositions of O. niloticus and S. galilaeus
from different locations ………………………………….…..
4.2.1. Crude protein …………………………………………...
4.2.2. Crude fat ………………………………………………..
4.3.1. Genetic variability in RAPD loci ……………………
4.3.2. Genetic diversity among and within populations ………
34
36
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37
37
38
38
38
39
39
40
40
40
40
41 ]
54
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59
62
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64
70
70
VI
4.3.3. Genetic distance and dendrogram …………………….
Chapter Five: Discussion …………………………………………
Conclusions and Recommendations ………………........................
73
95
References …………………………………………………………
97
Appendices…………………………………………………………..
112
VII
List of tables
Table number Page
1. Sample location and GPS related information of O. niloticus
and S. galilaeus populations…………………………………
16
2. The sequence of eight primers used in RAPD analysis…….. 25
3.a
3.b
Summary of ANOVA tables for morphometric characters of
O. niloticus and S. galilaeus over locations…………………
Summary of ANOVA tables for meristic characters of O.
niloticus and S. galilaeus over locations…………………...
42
43
4. Descriptive statistics (mean and SD) for morphometric and
meristic characters of O. niloticus and S galilaeus in all
locations……………………………………………………..
44
5. Correlation coefficient between body weight (g) and
standard length (cm) of O. niloticus and S. galilaeus at
different site along Blue Nile, White Nile and River
Nile………………………………………………………..
57
6. Correlation coefficient between body depth (cm) and
Standard length (cm) of O. niloticus and S. galilaeus at
different sites along Blue Nile, White Nile and River Nile…
57
7. Correlation coefficient between head depth (cm) and head
length (cm) of O. niloticus and S. galilaeus at different sites
along Blue Nile, White Nile and River Nile………………..
58
8. Correlation coefficient between caudal depth (cm) and
caudal length (cm) of O. niloticus and S. galilaeus at
different sites along Blue Nile, White Nile and River
Nile………………………………………………………….
58
9. Correlation coefficient between BDF (cm) and RD of
O.niloticus and S. galilaeus at different sites along Blue
Nile, White Nile and River Nile…………………………….
58
VIII
10. Correlation coefficient between BDF and SD of O. niloticus
and S. galilaeus at different sites along Blue Nile, White
Nile and River Nile………………………………………….
59
11. Correlation coefficient between RD and SDF of O.
niloticus and S. galilaeus at different sites along Blue
Nile, White Nile and River Nile………………………...
59
12. Correlation coefficient between RA and BA (cm) of O.
niloticus and S. galilaeus at different sites along Blue Nile,
White Nile and River Nile………………………………..
59
13. ANOVA for chemical composition (crude protein and crude
fat) of O. niloticus and S. galilaeus……………….
63
14. Mean protein content (%) of O. niloticus and S. galilaeus
from the different sites along the BN, WN and
RN………………………………………………………..
63
15. Mean fat content of O. niloticus and S. galilaeus from the
different sites along the BN, WN and RN…………………
64
16. O. niloticus and S. galilaeus RAPD profiles obtained by
eight random molecular markers………………………….
66
IX
List of Figures
Figure Page
1. Dendrogram generated by clustering using arithmetic
average for O. niloticus and S. galilaeus from the
different sites based on morphometric and meristic
characters………………………………………………
61
2. RAPD patterns obtained from Oreochromis niloticus
using primer RAPD1, RAPD3, RAPD4, RAPD5,
RAPD6, and RAPD7. Lane M: 100 bp DNA ladder,
lane 1-24: Al Kalakla…………………………………..
67
5. RAPD patterns obtained from O. nilotics using primer
RAPD1, RAPD2, RAPD3, RAPD4, RAPD5 and
RAPD6. Lane M: 100 bp DNA ladder, lane 1-16: Ad
Damazain……………………………………………….
68
6. RAPD patterns obtained from O. niloticus using primer
RAPD1, RAPD2, RAPD3, RAPD4, RAPD5 and
RAPD6. Lane M: 100 bp DNA ladder, lane 1-24:
Shendi………………………………………………..
69
7. UPGMA dendrogram of population O. nilotiucs and S.
galealleaus based on values of genetic distance
calculated from data for all 8 primers.……………….
72
X
List of plates
Plate 1 Oreochromis niloticus………………………………… 20
Plate 2 Sarotherodon galilaeus. ……………………………… 21
Plate 3 Morphometric measurements… ……………………… 22
XI
List of appendices
1. Location map of the studies area…………………………………112
2. Similarity matrix between different populations…………………113
XII
Acronyms
ANOVA: Analysis of variance
DNA: Deoxy Nucleic Acid
PAST: Paleontological statistics software package for education and data
analysis.
PCR: Polymerase chain reaction
RAPD: Random Amplified polymorphic DNA
SPSS: Statistical Package for Social Sciences
Taq: Enzyme Isolated from the thermophilic thermus aquaticus
TBE: Trise Base EDTA
TE: Trise – EDTA
UPGMA: Unweighted Pair Group Method with Arithmetic Mean.
UV: Ultra Violet
XIII
ABSTRAT
The study aimed to estimate the genetic variability of two tilapia
species from different populations. Fifteen populations (423 specimens) of
Oreochromis niloticus and Sarotherodon galilaeus were collected from
eight sites representing the White Nile (Gitaina, JebalAulia, Al kalakla);
Blue Nile (Ad Damazain, Sennar, Wad Madani) and the River Nile (Al
Mawrada, Shendi). Following standard methods, 22 morphological
characters and 11 meristic counts were recorded for each specimen. Two
quality traits protein and fat contents were determined following the
standard methods of the American Official Analytical Chemist. For quality
trait three specimens from each population were randomly selected. Tissue
samples from gills and dorsal fin were removed from individual specimens
and preserved separately in absolute ethanol prior to molecular analysis by
RAPD-PCR using eight primers. For morphometric and quality trait
characters, analysis of variance was used to compare similarities and
differences between the populations. The molecular data was analyzed by
PAST software. Statistical analysis showed highly significant differences (p
≤ 0.01) in most morphometric characters among populations and within
each population in the different sites. Area has important effect on 21
characters and the response of the species to the effect of area was different
in 25 characters. Analysis of variance showed that the White Nile was most
favourable for the development of most characters and Jebel Aulia was the
most conducive site for characters selection if proper breeding program has
to be followed. Out of 11 characters, seven showed high values of
correlation coefficient indicating that these characters are more stable over
XIV
the different environments. Such stable correlation can be applied as
selection criteria for these characters. Analysis of variance showed highly
significant differences (p ≤ 0.01) in protein and fat content indicating that
the site has an important effect on them. The response of different species to
the change of site was different. Al Mawrada was the most conducive site
(17.62%) for protein and Gitaina (1.16%) for fat content. With respect to the
interaction, S. galilaeus from Wad Madani had the highest (17.96%) protein,
whereas S. galilaeus in Al Kalakla (1.19%) had the highest fat content. With
respect to the species, O. niloticus was the most productive (17.11%) for
protein and S. galilaeus (1.13%) for fat. DNA analysis using the eight
primers namely: OPA-04, OPA-13, OPA-03, OPA-06, OPA-07, OPA-09,
OPA-10 and RAPD-8 produced different bands for each (strong, faint or
sharp distinct). The total bands generated by primer one to eight were: 17,
16, 18, 12, 12, 14, 14 and 17, respectively. They are in the range of 100 to
1020 bp. Levels of variability were estimated by the proportion of
polymorphic bands obtained by each primer within a population. O.
niloticus was highly variable (46.0 to 91.7) compared with S. galilaeus (56.2
to 83.3). The study concluded that there was a significant effect of sites on
variability of characters and genetic diversity among and within populations.
It also concluded the usefulness of RAPD-PCR as a tool for estimating
variability. To promote tilapia production, the study recommended
increasing genetic variation within brood stocks by crossing high similarity
breeds with lower similarity ones.
XV
مستخلص
ي خسخ ػشش انجهط انجبنه ذفذ انذساسخ نزمذش انزجب انساث ف أسبن انجهط انه
انم األصسق (انكالكهخ ء،ججم أنب انمطخ،) يالغ رثم انم األثطحػ ي ثبيجزؼب نم
صفخ يسفيزشخ 22رى لبط . (شذ انسدح) ش انم (اديذ سبس، ،انذيبص)
رى اخزبسانجشر انذ كصفز ي . صفخ ػذدخ نكم ػخ ثبرجبع انطشق انمبسخ11حسبة
ثبنسجخ . صفبد انجدح لذسد انست انئخ ثبرجبع غشق انكبئ األيشك انشسخ نهزحبنم
نهذساسخ األحبئخ انجضئخ رى أخز . نصفبد انجدح رى اخزبس ثالس ػبد ػشائخ ي كم يجزغ
لجم (%100)ػبد يفصهخ ي انضػبف انخبشى حفظذ كم ػخ ف انكحل اإلثه انطهك
رحههب ثطشمخ انزعبػف انؼشائ يزؼذد انألشكبل نسهسهخ انحط ان ثبسزخذاو ثبخ ثبدئبد
اسزخذو رحهم انزجب نهصفبد انشفيزشخ صفبد انجدح نمبسخ اإلخزالفبد انزشبث . ػشائخ
أظحذ زبئج .PAST software زبئج انجببد انجضئخ رى رحههب ثبسزخذاو .ث انجزؼبد
ف يؼظى انصفبد انشفيزشخ ف (p≤0.01)انزحهم اإلحصبئ جد فشلبد يؼخ ػبنخ
صفخ يسفيزشخ لبسخ كبذ اسزجبثخ االاع 21 ػه يىانالغ نب رأثش. انبغك انخزهفخ
ث رحهم انزجب أ انم األثط أكثش انالغ يالئخ ن . صفخ25نزأثش انطمخ يخزهفخ ف
يؼظى انصفبد أ ججم أنبء أالكثش يسبخ ف اخزبس انصفبد ػذ ارجبع ثشبيج صحح
يؼبيم اسرجبغ كجش يب ذل نب صفخ ػشش إحذي ث أظحذ انزبئج أ سجغ صفبد .نهزفشخ
ازخبةك رطجك زا االسرجبغ انسزمش كؼبش . أب أكثش أسزمشاسا ػه انجئبد انخزهفخػم
ف يحز انجشر (p≤0.01)شش انزحهم االحصبئ نجد رجب ػبن انؼخ .انصفبدنز
اسزجبثخ األاع نزغش انلغ د ف ح كبذ ا ز انصف ػميىرأثش ر نلغ اأ انذ
. نحز انذ (1.16%) ثب انمطخ نهجشر(17.62%)الئخ سدح أكثش ونىكبذ ا. يخزهفخ
ثشر يحز أػه ثبنزفبػم ث انلغ انع، كب نهجهط انجبنه ف اد يذ فب زؼهك
فب زؼهك ثبألاع، . (1.19% ) انذ نهجهط انجبنه ثبنكالكهخيحز أػه ثب (%17.96)
انألػه ثبنسجخ نهذ انجهط انجبنهنهجشر (17.11%) األكثش إزبجخ انجهط انهكب
ثبسزخذاو ثبخ ثبدئبد ػشائخ (RAPD)رحهم انحط ان أظح (.%1.13)
OPA-04 ،OPA-13 ،OPA-03 ،OPA-06 ،OPA-07 ،OPA-09 ،OPA-10:رحذذا
XVI
RAPD-8 12، 12، 18، 16، 17 :كبذ (، يزضححلخ، خبفذ)يزفبرخ حضو ازج كم يب ،
حضورى رمذش يسزبد انزجب ثسجخ ال. .bp 1020 إن 100، ػه انزان ف طبق 17 14، 14
يجزؼبد انجهط انه، كبذ أكثش . كم يجزغ ظ ثبدئخ ػهب كم ديزؼذدح األشكبل انز حصم
خهصذ انذساسخ (.83.3-%56.2)يمبسخ يغ انجهط انجبنه (%91.7-46)رجبب نحصنب ػه
كب . نجد رأثش يؼ نهلغ ػه انزجب ف انصفبد انزع انج ث داخم انجزؼبد
كأداح نمبط انزعبػف انؼشائ يزؼذد انألشكبل نسهسهخ انحط انأكذد انذساسخ أخ رمخ
ي أجم انض ثبزبجخ انجهط الزشحذ انذساسخ صبدح انزجب انج ث األيبد راد . انزع
.لماأل يؼبيم رشبث نهزكبثش يغ رادػبلالرشبث اللخ يؼبيم
1
CHAPTER ONE: INTRODUCTION
Tilapia is the common name for nearly 70 species of cichlid fish that
are native to the fresh waters of tropical Africa. Tilapia is divided into three
main genera Tilapia, Sarotherodon and Oreochromis. However, only a few
of these species are commercially important, and fewer still are of
aquaculture significance (Shelton and Popma, 2006). Oreochromis niloticus
is a widespread species used in fresh water aquaculture in tropics and
subtropics because of its palatability, relative ease for culture and breeding
in a variety of aquaculture systems (Ladewig-de and Schwantes, 1984).
In cultured fishes, which are selectively bred and maintained in low
population size, individuals may be subjected to deleterious effects of
breeding because potential mates are more likely to be closely related. The
low and instability of production could be attributed to abiotic and biotic
factors in which lack the suitable high yielding varieties is at the fore front.
Abiotic factors might affect the genetic structure of population in different
ecological zones and the comparison of diversity within and among fish
populations should reflect the ecological performance (Fuerst et al., 2000).
The future of tilapia stock improvement will rely on appropriate stock
choice, development of sound management techniques and selective
breeding. The basis of this approach is the ability to characterize and
monitor tilapia genetic resources under culture conditions, provide a sound
knowledge of genetic characteristics of each stock and to examine the
effects of management practices on the gene pools of each stock (Appleyard
and Mather, 2000). Small populations tend to present low genetic
variability, with inbreeding resulting in a reduction in the fecundity and
2
viability of individuals. Such variation tends to occur when the
environments experienced by populations of a given species differ among
distinct locations within the distribution range of a given species (Mills,
2004). Genetic variation in fishes has proven valuable in aquaculture and
fisheries management, for identification of stocks, in discrete breeding
population and for estimating contribution to stock mixture. Moreover, an
efficient use of biological resources requires thorough knowledge of the
amount and distribution of genetic variability within the species considered
(Dinesh et al., 1996). Therefore, knowledge of genetic variation in cultured
and natural populations is important for the success of aquaculture and
fisheries management practice.
Morphometric, biochemical and genetic analysis are considered vital
tools to determine the variability between different populations.
Morphometric and meristic methods remains the simplest and most direct
way among methods of species identification (Dinesh et al., 1996).
According to them both methods provide useful results describing their
spatial distribution and have been widely used as a powerful technique for
the determination of morphological relationships between the populations of
a species. The crude protein and crude fat composition variation determines
and identifies the nutritional value of each population and compares the
flesh quality between different populations. However, the evaluation of Nile
tilapia results in selection of genotype suitable for aquaculture.
Genetic markers have been used to detect selection and estimate
effective population size. In addition they have been used to determine
parentage, sex, mating system, population structure and to detect
introgression (Frankham et al., 2002). Several molecular techniques were
3
applied to detect DNA markers and to reflect the genetic background of fish
populations (Meyer, 1993; Beaumont, 1994). Hence, DNA markers will be a
reliable tool to confirm morphological and biochemical features. RAPD
fingerprinting is a useful tool for assessment of genetic variability and can
be applied to breeding programmes in aquaculture. This approach of DNA
polymorphism which is based on PCR amplification of DNA segment using
single primers of arbitrary nucleotide sequences has been developed by
(Williams et al., 1990). Successful breeding programmes depend on
complete knowledge and understanding of the genetic diversity within and
among genetic resources. This enable fish breeder to choose parental
sources for hybrid production or for generation of diverse population for
selection. According to Babiker and Elhakeem (1979) little work has been
done in comparative biochemical or genetic studies in Nile fishes in Sudan.
Using RAPD fingerprinting on fish has been limited. In the current study,
this technique was applied to analyze the genetic relationships among
Tilapia spp. populations. Genetic variability estimation of some tilapia
species from different populations is a perquisite in improvement
programmes of tilapia.
The objectives of this study were to:
1- Estimate variability of morphometric and meristic characters in
population of O. niloticus and S. galilaeus from eight sites along the Blue
Nile, White Nile and River Nile.
2- Determine the interrelationship between the characters in the different
populations.
3- Evaluate the magnitude of variability in the quality parameters.
4
4- Estimate the genetic diversity among the different Tilapia populations
using RAPD molecular markers technique.
5
CHAPTER TWO: LITERATURE REVIEW
2.1. Tilapia spp.
Tilapia is the common name for nearly 70 species of cichlid fish that
are native to fresh waters of tropical Africa. The natural distribution of
tilapias is restricted to Africa, Jordan, and Israel, where 112 species and
subspecies of the genera Oreochromis, Sarotherodon, and Tilapia have been
identified (Trewavas, 1983; McAndrew, 2000 and El-Sayed, 2006).
All the three genera can spread along some brackish coast lines
between rivers (Nelson and John, 2006). Several characteristics distinguish
these three genera, but possibly the most critical characteristics relates to
reproductive behaviour. Both female and male of Sarotherodon and only
female Oreochromis, are mouth brooders (Trewavas, 1983). In all
Oreochromis spp the male excavated a nest (Trewavas, 1983).
Tilapias are boney fish, with cycloid scales and two incomplete lateral
lines, the jaws not projecting, teeth in two more series, maxillary usually
more or less completely hidden under the pre-orbital when the mouth is shut
(Abu Gideiri, 1984 and Bailey, 1994).
Oreochromis niloticus inhabits the Nile and its tributaries and many
natural and man-made inland water bodies. Body is compressed, scales
cycloid, dorsal fin with 15-18 spines and 11-19 soft rays, anal fin with 3
spines and 10-11 rays (Trewavas, 1983). Colour is yellowish brown or grey
to dark olive, or silvery. Black or grey colour in the edges of anal, dorsal
and caudal fins. Most distinguishing characteristic is the presence of regular
vertical stripes throughout depth of caudal fin (Trewavas, 1983), which used
to identify the purity of the strain (Yousif, 2012). After spawning female
6
leave the nest to rear her clutch in safety. Fry brooded up until free
swimming (Abu Gideiri, 1984 and Bailey, 1994). Oreochromis niloticus is
cultured in tropical and subtropical countries and can contribute to protein
supply in numerous developing countries (Agnese et al., 1997). It comprised
92% of the tilapia catch in Sudan (Abu Gideiri et al., 2004).
S. galilaeus inhabits the same habitat of O. niloticus. The colour is
yellowish to brownish or olive-green, uniform or with small dark spots, or
with ill-defined darker streaks. Dorsal fin with 15-17 spines and 12-13 soft
rays, anal fin with 3 spines and 9-11 soft rays (Trewavas, 1983). Eggs and
fry brooded in oral cavity up until they are ready for releases (Abu Gideiri,
1984 and Bailey, 1994).
Oreochromis spp. exhibits valuable culture characteristics, such as
disease resistance, increased environmental tolerances, easy reproduction
and efficient use of low-protein diets, and high palatability, marketability
and nutrient content (Hassanien and Gilbey, 2005; Teichert-Coddington et
al., 1997). They are especially well-suited for culture in developing
countries due to their fast growth and short generation time, tolerance to a
wide range of environmental conditions, resistance to stress and disease,
ability to reproduce in captivity, and their acceptance of artificial feeds right
after yolk-sac absorption (El Sayed, 1985). However, only a few of these
species are commercially important, and fewer are of aquaculture
importance. O. niloticus, O. aureus, and various hybrids of these with O.
mossambicus are regarded as the most important aquaculture species.
7
2.2. Fish genetic variability and diversity.
Genetic variations and diversity of fish species are valuable tools in
aquaculture and fisheries management in identification of stocks, in discrete
breeding populations and in estimating stock mixtures (Dinesh et al., 1996).
Identification of sub-population (stock) provides biologically meaningful
attributes for assessing a number of parameters, including genetic diversity
(Hesham and John, 2005). Knowledge of fish stock structure is critical to
stock enhancement or supportive breeding programmes (Ryman and Laikre,
1991). Domingos et al. (2014) noted that evaluation of the population
genetic structure of a given species provides a genetic overview about the
populations and among individuals. These data are associated with
knowledge about effective population size, gene flow and mating systems
which are important in management actions (David, 2001).
The observable variation present in a character in a population arises
due to genetic and environmental affects. Such knowledge allows the
definition of geographic boundaries for monitoring post-supplementation
effects on genetic effective population size and/or assessing
supplementation success (Blankenship and Leber, 1995). Population’s
movement over a wide range of habitat or different environmental
conditions may lead to effect in gene structure. Klug and Cummings (1997)
stated that of population dynamic may lead to changes in the genetic pool
over time. However, small populations tend to present low genetic
variability, with inbreeding resulting in reduction in the fecundity and
viability of individuals. The influences of environmental parameters on
morphometric characters have been well discussed by several authors
(Samaee et al., 2006; AnvariFar et al., 2013; Swain and Foote, 1999). These
8
morphological differences may be solely related to body shape variation and
not to size effects which were successfully accounted for by allometric
transformation. Saber et al. (2014) reported that physio-chemical parameters
are approximately the same in the studied rivers and probably similar
environment conditions cause similar morphologically populations.
Morphological characteristics can show high plasticity in response to
differences in environmental conditions (Saber et al., 2014). Therefore, the
distinctive environmental conditions of studied areas may underline the
morphological differentiation among these sites. Such variation tends to
occur when the environments experienced by populations of a given species
differ among distinct locations within the distribution range of a given
species (Mills, 2004). For example, Wu et al. (1999) study of the habitat of
Astat oreochromis alluaudi throughout Lake Victoria Basin and found little
population differentiation, whereas Hassanein and Gilbey (2005) detected
only modest levels of differentiation among O. niloticus populations
separated by more than 100 km. According to Carvalho (1993) and Dinesh
et al. (1996) individuals with greater genetic variability have higher growth
rates, developmental stability, viability, fecundity and resistance to
environmental stress and disease.
The combined application of different tools for the characterization of
populations such as morphometric analysis, DNA marker analysis, the
chemical traits analysis and karyotypic structure or chromosome banding are
of value in evaluation. George (2012) noted that in plants some genetic
variation is mainly manifested as visible variation in morphological traits
(eg. height, colour, size) while compositional or chemical trait (e.g. protein
and sugar content) require various tests or devices for evaluation.
9
2.2.1. RAPD technique.
Genetic analysis of organisms at the molecular level is a very
important and widely practiced scientific tool. One important PCR-based
genetic analysis is random amplified polymorphic DNA analysis (RAPD).
In the 1980s, the development of the polymerase chain reaction (PCR)
dramatically simplified access to genomic information, facilitating both
basic research studies and a wide variety of applications ranging from
clinical diagnostics to forensic analyses (White et al., 2007). Starting with a
DNA or RNA template, repeated cycles of denaturation, primer annealing
and polymerase-mediated primer extension generate an exponential
accumulation of a specific targeted fragment that can be analyzed by a
variety of methods. RAPD is a method of producing a biochemical
fingerprint of a particular species and useful tool for identifying DNA
polymorphism, estimation of genetic diversity of an individual by using
random primers, difference of related species in fish and means of creating a
biochemical fingerprint of an organism (Ambak et al., 2006). The RAPD
analysis is also employed in differentiating sex chromosome (Iturra et al.,
1998), genetic inheritance (Elo et al., 1997), gene mapping (Liu et al., 1999)
and fish conservation (Fritzch and Rieseberg, 1996; Dioh et al., 1997).
PCR-RAPD consists in the amplification, by PCR, of random
segments of genomic DNA using a single short primer of arbitrary
sequence, thus one can expect to scan the genome more randomly than using
conventional techniques. The two main advantages of using RAPD are (a) it
does not require previous knowledge of DNA sequences and (b) it targets
many sequences in the DNA of the sample, producing DNA patterns that
allow comparison of many loci simultaneously (Williams et al., 1990).
10
2.2.2. Applications of RAPD technique.
RAPD fingerprinting has been used for differentiation of different
species of fishes (Dinesh et al., 1993). Bardakci and Skibinski (1994) used
RAPD protocol to differentiate the Indian major Carp Labeo rohita, L.
calbasu, Catla catla and Cirrhinus mrigala. Protein electrophoresis was
used to discriminate tilapias and their hybrids based on their genetic
diversity by Takagi and Taniguchi (1995); Dinesh et al. (1996); Nei and Li
(1979); Heist and Gold (1999) and Jong-Man (2001). DNA fingerprinting
offers great potential in aquaculture and in fisheries as a tool for
identification of individuals and population genetics (Hallerman and
Beckmann, 1988; D’Amato and Corach, 1996; Bielawski and Pumo, 1997
and Smith et al., 1997). DNA fingerprinting was obtained for O. niloticus,
Barbus terazona and Poecilla reticulata by Harris et al. (1991). Mamuris et
al., 1998 noted that RAPD exhibits more pronounced effect in populations
of Mullus surmuletus. RAPD fingerprinting has been used for detection of
DNA polymorphisms in colour mutant varieties of guppy, Poecilia
reticulate, and tiger barb, Barbus tetrazona (Dinesh et al., 1993). In
addition, DNA-based genetic polymorphisms generated by RAPD
fingerprinting have been used to construct a genetic linkage map for the
zebra fish, Dania rerio (Johnson et al., 1996).
The findings of Hassanien et al. (2004) helped in understandimg the
broard-scale population structuring of O. niloticus, tilapia phylogeography
and the nature and extent of its biodiversity. This knowledge will aid the
development of management strategies, which have a better chance of
conserving such diversity and ensuring the continued existence of the
various sub-populations.
11
2.3. Aquaculture.
The contribution of aquaculture to global fisheries has increased
sharply especially in the last decade. Global aquaculture production of
tilapias increased from 28,000 tonnes to over 3 million tonnes from 1970 to
2010 (Fitzsimmons, 2010). The total worldwide production of tilapia is
composed primarily of Oreochromis spp (Bhassu et al., 2004). Most
aquaculture activity was based on O. niloticus which accounts for over 80%
of tilapia production, followed by O. aureus. Worldwide harvest of farmed
tilapia has now surpassed 800,000 metric tons and tilapia is the second only
to carps as the most widely farmed freshwater fish in the world (De Silva et
al., 2004). It is widely accepted that successful aquaculture development in
Africa requires improvements in feed quality and quantity, business and
marketing models, and local technical capacity. Another important factor
that should be considered is the effective utilization and management of fish
genetic resources (Lind et al., 2014 and Ponzoni et al., 2011). Genetic
markers in fish aquaculture have become an important tool providing
information regarding parentage relationships and the performance of lines
in breeding programmes (Garcia de Leon et al., 1997 and Rowena et al.,
2004).
According to FAO (2016) the national average fish consumption in
Africa is less than 10 kg/person/year in comparison with that of the world
(more than 19 kg). Therefore, the best ways for increasing of fish
consumption is to increase production and availing fish at a competitive
price. Therefore, study of the constraints of fish culture and how to
overcome these constraints are deemed to be of paramount importance.
12
Despite the importance of Nile tilapia as a food fish worldwide,
knowledge on the genetic background of natural populations is generally not
very extensive (Agnese et al., 1999). Knowledge of the population structure
of Nile tilapia is economically important for several issues pertinent to
future development of aquaculture strains and management of a fishery.
Practices require the genetic management of population groupings from
which the aquaculture strains originated. Several large scale selection
experiments and breeding programmes, aiming at increasing growth rate,
were conducted in O. niloticus. Major genetic improvement programmes
included genetically improved farmed tilapia or GIFT and the GMT/YY-
supermale were implemented in Asia, particularly in the Philippines (Eknath
et al., 1993; Mair et al., 1995 and Fitzsimmons, 2000). The success of GIFT
project was due to use of selective breeding of a diverse synthetic base
population (El-Sayed, 2006). The genetically improved aquaculture stocks
developed by these projects are currently being promoted in the region
(Rowena et al., 2004). Only a few commercially aquaculture species have
been improved by cross-breeding. Variable proportions of crossbreds
showing heterosis for growth rate have been obtained in the channel catfish;
rainbow trout; common carp and the Pacific oyster. Heterosis was also
found in survival, disease resistance and reproductive traits (Hulata, 2001).
A major challenge in selective breeding is to estimate an individual’s
breeding value based on its own phenotype and/or the phenotypes of its
relatives (Worldfish, 2004). Little work was done in Africa to enhance the
genetic improvement through selective breeding. Mickett et al. (2003) stated
that understanding genetic variation within domestic catfish populations is a
main requirement for maximizing the suitable breeding requirements of the
13
catfish species. Moreover, analysis of catfish genetic resources is also
important for establishing data for both genetic enhancement programmes
and genetic conservation programmes.
Most of the genetically improved strains reaching the aquaculture
industry were developed through traditional selective breeding (selection,
crossbreeding, and hybridization). Selection is usually a viable approach for
tilapia genetic improvement where sufficient genetic variation exists (Lutz,
2006). According to Ponzoni et al. (2007), selective breeding has a number
of advantages over other genetic approaches: continuous genetic gain is
possible, genetic gains can be passed from one generation to the next, and
gains in a nucleus can be multiplied and expressed in millions of individuals
in the production sector. Emerging more modern technologies for genetic
manipulation seem to take 10–20 years from being established
experimentally until applications at the industry level. Thus, chromosome-
set and sex manipulations started to affect the industry during the 1980’s
and 1990’s. DNA marker technology and gene manipulations have yet
hardly affected the industry. The former have not matured yet, but hold
much promise (Ponzoni et al., 2008). An efficient way to study changes in
morphometric traits due to selection for weight gain is the genetic
parameters and genetic change estimates, which are essential when
establishing guidelines for breeding programmes. The evaluation of genetic
progress over time can provide results that serve as indicators for future
action (Hershberger et al., 1990).
Fresh water fish culture in Sudan is primarily based on the pond
culture of the native species O. niloticus. Fish culture did not yet develop
into vertical-integrated economic activity, despite the fact that the
14
prerequisites for it are available. In Sudan, the consumption per capita for
fish was 1.64kg/year (FAO, 2010). This low consumption is attributed
partially to low production from aquaculture. Many difficulties, obstacles
and challenges are facing fish farmers. One of these is constraints
concerning reliable supply of good quality brood stock and fish fry and/or
fingerlings for on-growing. Problems in fish management still arise in tilapia
production because of its capacity to over breeding to overcrowding in
pond, thus limiting the growth of individual fish. In spite of its importance
the breeding research on tilapia species is limited in Sudan. Hence the
information on the wild population and their crosses, the inheritance of
qualitative as well as quantitative phenotypes; strain evaluations;
heritability's; inbreeding; environmental factors that influence genetic
studies and interspecific hybridization to produce all male populations is
needed to enhance production from aquaculture.
2.4. Quality traits.
Flesh quality has gained importance in the aquaculture industry as its
evaluation from different populations can result in a genotype suitable for
aquaculture. The nutritional value of fresh water fish was found to differ
between geographical locations. Information on meat composition can help
to create or maintain water conditions conducive for rearing a quality fish
meat carcass (Boyd and Tucker, 2009). Therefore, the quality of water is
considered as one the main attributes in fish quality and the effect of
different water sources is varied. The production from fish farms by
producers give due consideration to processors and consumers. However,
the quality of farmed fish has occasionally been reported as being lower
than that of wild fish and the acceptability for it is greater than that of
15
farmed fish (Sylvia et al., 1995) and genetic improvement for flesh quality
traits has been almost neglected in breeding programs for aquaculture
species due to large number of traits involved (El-Zaeem et al., 2012;
Gjedrem, 1997). Due to the importance of flesh quality to the aquaculture
industry, an attempt was made to define and analyze flesh quality and its
relation to carcass characteristics. Optimization of the quality of fish
farming production may lead to improvement of consumer acceptance
(Rasmussen, 2001). Some of the quality traits vary within the carcass.
Therefore, the genetic gain will increase when more families are tested in
each generation (El-Zaeem et al., 2012).
16
CHAPTER THREE: MATERIALS AND METHODS
3.1. Samples and origin of experimental fish.
Samples of O. niloticus and S. galilaeus (Plates 1 and 2) were
collected from eight sites. These were: Al kalakla (K), Jebel Aulia (J),
Gitaina (G) representing the White Nile; Wad Madani (Md), Sennar (Sn),
Ad Damazin (D) representing the Blue Nile and Shendi (S) and Al Mawrada
(M) representing the River Nile (Table 1, (Appendix1 map). Fifteen
different sub-populations (eight of O. niloticus and seven S. galilaeus) were
randomly collected (423 adults) from fishing sites. Samples were measured
for morphological, meristic characters, quality traits and molecular marker
characters with the objective of determining the genetic diversity within and
among O. niloticus and S. galilaeus populations.
Table 1. Sample location and GPS related information of O. niloticus and
S. galilaeus populations. Rivers Sites GPS readings Sample number
Latitude Longitude O. niloticus S. galilaeus
White Nile
Al kalakla 15.4622 32.4807 37 35
Jebel Aulia 15.2286 32.5260 39 25
Gitaina 14.3094 32.4467 40 38
Blue Nile
Wad Madani 14.3931 33.5392 8 6
Sennar 13.0317 33.9750 31 31
Ad Damazin 11.7855 34.3421 19 30
Rive Nile Shendi 16.6743 33.4496 38 6
AL Mawrada 15.6476 32.4807 40 0
Total 252 171
17
3.2 Morphometric and Meristic parameters.
For the study of morphometric characteristics and meristic counts,
measurements were taken from 423 specimens of O. niloticus and S.
galilaeus (Plates 1 and 2). 22 morphometric characters and 11 meristic
counts were measured following Murta (2000); Barel et al. (1977); Sneoks
(1994) and Ebraheem (2012). Each specimen was investigated for the
following parameters:
(a) Morphometric characters:
1- Body weight (BW).
2- Total length (TL): distance from tip of snout to posterior tip of the lower
lobe of the caudal fin.
3- Standard length (SL): distance from tip of snout to the caudal fin base at
articulation.
4- Body depth (BD): maximum vertical depth of the body depth situated in
between anterior base of dorsal fin and origin of pelvic fin.
5- Head length (HL): distance from tip of snout to body posterior margin of
operculum.
6- Head depth (HD): maximum vertical depth of the head in front of
operculum.
7- Snout length (SnL): distance from tip of snout to boney anterior margin
of eye.
8- Base length of dorsal fin (BDF): distance between the most anterior and
posterior point of dorsal fin base.
9- Posterior end of the dorsal fin to dorsal origin of the Caudal fin (PDDC).
10- Length of the anal fin (LA): from base to tip of the anal fin.
18
11- Base length of the anal fin (BA): distance between the most anterior and
posterior point of anal fin base.
12- Length of the pelvic fin (LP): from base to tip of the pelvic fin.
13- Caudal peduncle length (CL): horizontal distance between most
posterior point of caudal fin at articulation.
14- Caudal peduncle depth (CD): minimum vertical depth of caudal
peduncle.
15- Eye diameter (ED): maximum eye length from the most anterior point to
the most posterior point of the orbit.
16- Mouth gape (MG).
17- Predorsal distance (PRD): distance from tip of snout to base of first
dorsal fin ray.
18- Preanal distance (PAD): distance from tip of snout to base of first anal
fin ray.
19- Prepectoral distance (PRP): distance from tip of snout to base of first
pectoral fin ray.
20- Prepelvic distance (PRV): distance from tip of snout to base of first
pelvic fin ray.
21- Lower jaw length (LJL): from the snout tip to the ventro-caudal tip of
the lower jaw.
22- Premaxillary pedical length (PPL): from the nostril tip of the upper jaw
to the tip of the ascending process of premaxilla.
(a) Meristic characters.
1- Number of the lateral line scales (LS): number of scales on upper lateral
line plus the number of scales on the lower lateral line which lie caudal to
the last per lateral line scale.
19
2- Number of the predorsal scales (PrS).
3- Number of the postdorsal scales (PoS).
4- Number of scales surrounded the caudal peduncle (SCP).
5- Number of the rays in the dorsal fin (RD).
6- Number of the spines in the dorsal fin (SDF).
7- Number of the rays in the anal fin (RA).
8- Number of spines in the anal fin (SA).
9- Number of rays in the pectoral fin (RPec).
10- Number of rays in pelvic fin (Rpel).
11- Number of rays in caudal fin (RC).
20
Plate 1. Oreochromis niloticus.
21
Plate 2. Sarotherodon galilaeus.
22
Plate 3. Diagram of morphometric measurements.
(No. 2-TL, 3-SL, 4-BD, 5-HL, 6-HD, 7-SnL, 8-BDF, 9-PDDC, 10-LA, 11-BA, 12-LP, 13-CL,
14-CD, 15- ED, 16- MG, 17-PRD, 18-PAD, 19-PRP, 20-PRV, 21-LJL, 22-PP).
2
8
17
7
3
22
21
20
19
18
10
11
9
5 15
12
13
14 4
6
16
23
3.3. Quality traits - chemical composition.
From each of the fifteen population studied, three fishes were chosen
randomly for measurement of crude protein and crude fat content following
A.O.A.C. (1990) methods. All analyses were made in triplicate.
3.4. Molecular method.
3.4.1. Sample preparation.
Four random seleted fishes from each of the fifteen populations
including both O. niloticus and S. galilaeus were used in molecular analysis.
From each fish, tissues of fins and gills were removed and prepared for
molecular studies as suggested in similar studies (Ebraheem, 2012). For this
purpose, 0.5 g of muscle were removed from each individual and placed
separately in absolute ethanol for DNA extraction.
3.4.2. Quantification of DNA samples.
DNA Extraction using the potassium acetate protocol (KAC):
The removed tissues (0.1g dorsal fin), individual sample were soaked
separately in 100 µl extraction buffer (1% Sodium dodecyl sulfate (SDS),
50mM Tris/HCL, 25 mM NaCl (pH 8.0 and autoclaved) and 25mM EDTA
(Ethylene diamine tetra acetic acid) pH 8.0) ) for 10 minutes and then
homogenized with glass rod in 1.5 ml eppendorf tube gently and
thoroughly.
Then Added 100 µl extraction buffer and then the tube were quickly
moved to a 68 ºC water bath for 15 minutes. After that 100 µl of (KAC)
0.099M (9.8 g of potassium acetate dissolved in 100 ml of autoclaved
distilled water) was added and the mixture was transferred to ice box for
(30-60 minutes) 45 minutes, and the tubes were inverted occasionally. The
24
tube was spun in a microfuge at 14.000 rpm for 10 minutes to collect the
cellular debris and proteins precipitated by KAC in to a pellet. The
supernatant was then transferred to a fresh tube and the tubes containing the
pellet were discarded. The last step was repeated. Then 600µl of absolute
ethanol was added to the solution (supernatant). The solution was left at -20
ºC for at least 2 hours or overnight to precipitate the fish DNA.
To collect the nucleic acids, the tubes were spined in a microfuge for
15 minutes at maximum speed. This time the supernatant was discarded.
Nucleic acids were washed by adding 100µl of 70% ethanol and spined as
before for 10 minutes. The ethanol was decanted after the last step and then
another wash was done by using 70% ethanol. The last wash was done using
absolute ethanol (100%). The tubes were then inverted on a tissue paper and
left to dry for at least 40 minutes. One hundred µl of double distilled H2O
were added to dissolve the DNA and then the samples were frozen at -20 ºC.
DNA concentration was assessed using a nanodrop (spectrophotometer ND-
1000).
3.4.3. Primers.
Eight primers contained 10 base oligonucleotide used for
amplification genomic DNA. Primers were randomly selected on the basis
of GC content (60-70%) Table 2.
25
Table 2.The sequence of eight primers used in RAPD analysis.
No. Primer name Current symbols Sequences GC%
1 OPA-04 RAPD1 AATCGGGCTG 60
2 OPA-13 RAPD2 CAGCACCCAC 70
3 OPA-03 RAPD3 AGTCAGCCAC 70
4 OPA-06 RAPD4 GGTCCCTGAC 70
5 OPA-07 RAPD5 GAAACGGGTG 60
6 OPA-09 RAPD6 GGGTAACGCC 70
7 OPA-10 RAPD7 GTGATCGCAG 60
8 - RAPD8 CCGGGAATCG 70
3.4.4. Amplification of DNA.
Samples were amplified in PCR premix kit (i-MAX 11) added to
1.5μl primer (10mM) and 0.5 μl templates DNA. The reaction was
completed to 20 μl with sterile distilled water. PCR amplification was
conducted following Dinesh et al. (1993). Amplification was run using a
Flexigene thermal cycling machine. The cycler was programmed for 37
cycles of 4 min. an initial step of denaturation at 94°C, 30 seconds low
stringency annealing at 36°C and 30 seconds primer extension at 72°C. At
the end, a final extension for 10 min was performed at 72°C.
1% agarose was prepared in 1XTBE buffer (0.089M Trisbase 0.89M
Boric acid and 0.002M EDTA) and ethidium bromide (10μg/100ml)
was added for visualization purposes. The mixture was stirred and
poured into a gel tray containing a comb. The gel was left for 20
min. to polymerize.
26
PCR products of 4μl were loaded. The first lane was loaded
with 2μl of DNA ladder (100bp). The gel was placed in
electrophoresis tank containing 300 ml 1X TBE running buffer at
80V for 40 min. Photographs were taken using an UVI-TECH gel
documentation system.
3.5. Statistical analysis
3.5.1. Statistical analysis for morphometric characteristic,
meristic count and chemical traits.
The collected data were subjected to analysis of variance then the
means of measurements were compared and tested by the method of LSD
significant differences (p≤0.05) following Gomez and Gomez (2010) using
the software package statistic SPSS version 20. Furthermore, the
interrelationships between different characters were determined using
correlation coefficient, As SL not liable to damage compared with the TL, it
used as correlate throughout. In addition, cluster analysis was done for
morphometric and meristic data, using PAST software package version
3.14. Then a Dendrogram was constructed based on Euclidean coefficient
using UPGMA cluster analysis of arithmetic averages following Hammer et
al. (2001).
3.5.2. Scoring and analysis of RAPDs.
The presence or absence bands were recorded on photograph. The
bright band was scored as present (1) and no band was as absence (0). The
percentage of polymorphic bands generated by each primer within each
population was calculated. Then data was input into data analysis package
PAST 3.14 program. The Jaccard matrix of genetic distance coefficients
27
among each pair of population and similarity index were calculated based on
pair wise comparison between the two tilapia species.
Euclidean coefficient dendrogram among populations derived from
distance matrix using the Neighbor-Joining Tree Program to produce the
desired tree or dendrogram of cluster analysis using similarity Index.
Neighbor joining phylogenetic tree were constructed based on UPGMA
cluster analysis using the PAST 3.14 program (Hammer et al., 2001).
28
CHAPTER FOUR: RESULTS
4.1. Morphometric and Meristic Parameters.
Using analysis of variance different patterns of variation were
detected in morphometric and meristic characters, among rivers (areas),
sites, species parameters and their interactions (Table 3).
4.1.1. Body weight (g).
Statistical analysis showed that there were highly significant
differences (p≤0.01) among the areas, as well as among the sites. On the
other hand, the difference between the species was not significant (Table 3).
Also the area×site, area×sp and area×site×sp interactions were highly
significant. However, site×sp interaction was not significant. With respect to
the interaction, the highest mean BW (124.17) was obtained for S. galilaeus
in Wad Madani in Blue Nile, while the lowest value (35) was obtained for
O. niloticus in Shendi in River Nile. For the area, the highest mean BW was
in White Nile (77.13) and the lowest one (47.99) was in River Nile. With
respect to the sites, the highest mean BW (106.92) was in Jebel Aulia, while
the lowest mean (35.09) was in Shendi (Table 4).
4.1.2. Total length (cm).
Analysis of variance showed that there were highly significant
differences (p≤0.01) among the areas, as well as among species. On the
other hand, the differences among sites were not significant (Table 3). Also
the area×site, area×sp and area×site×sp interactions were highly significant.
The site×sp interaction was not significant. With respect to the interaction,
the highest mean TL (18.66) was obtained for S. galilaeus in Wad Madani in
Blue Nile, while the lowest value (12.69) was obtained for O. niloticus in
29
Shendi in River Nile. Among the rivers, the highest TL mean (15.68) was in
White Nile and the lowest value (13.86) was in River Nile. Regarding the
sites, the highest TL mean value (17.30) was in Jebel Aulia and the lowest
one (12.69) was in Shendi (Table 4).
4.1.3. Standard length (cm).
Statistical analysis revealed highly significant differences (p≤0.01)
among the areas, as well as between the species, while the differences
among the sites were significant. Also the area×sites, area×sp interactions,
were significant (p≤0.05). However, the site×sp and area×site×sp
interactions were not significant (Table 3).With respect to the interaction the
highest mean (14.98) was obtained for O. niloticus in Jebel Aulia and the
lowest one (9.75) was obtained for O. niloticus in Shendi. With respect to
the areas, the highest mean SL (12.78) was in White Nile and the lowest one
(11.29) was in River Nile. Regarding the sites, the highest mean (14.17) was
in Jebel Aulia and the lowest one (9.80) was in Shendi.
4.1.4. Body depth (cm).
Statistical analysis indicated that there were highly significant
differences (p≤0.01) among the areas as well as among the species. On the
other hand, the differences among the sites were not significant (Table 3).
Also the area×site, area×sp and area×site×sp interactions were highly
significant. However, site×sp interaction was not significant. With respect to
the interaction, the highest mean BD (6.83) was obtained for S. galilaeus in
Wad Madani in Blue Nile, while the lowest value (3.95) was obtained for S.
galilaeus in Shendi in River Nile. The highest mean value (5.35) of BD was
in White Nile and lowest mean (4.42) was in River Nile.
30
4.1.5. Head length (cm).
Statistical analysis showed no significant variation (p<0.05) among
the areas, as well as among the sites and among the species. Also the site×sp
and area×site×sp interactions were not significant. On the other hand,
differences in the area×site and area×sp interactions were significant
(p>0.05). The interactions showed that the highest mean value was obtained
for S. galilaeus in Wad Madani and the lowest value (3.47) was obtained for
O. niloticus in Shendi. With respect to the areas, the highest mean value
(4.25) was in White Nile and the lowest mean (3.76) was in River Nile.
4.1.6. Head depth (cm).
Analysis revealed highly significance differences (p≤0.01) among the
areas and among the sites. The area×site, area×sp and area×site×sp
interactions were significant. The differences between the species were not
significant. Also site×sp interaction was not significant (p<0.05). With
respect to the interaction, the highest mean HD (6.20) was obtained for S.
galilaeus in Wad Madani and the lowest mean were recorded for S.
galilaeusin Shendi. Among the areas the highest mean (4.96) was in White
Nile and the lowest one (4.11) was in River Nile. With respect to the sites,
the highest mean (5.51) was in Jebel Aulia and the lowest one (3.62) was in
Shendi.
4.1.7. Snout length (cm).
Statistical analysis indicated the differences among the areas, among
the sites, as well as among the species were not significant (p<0.05). On the
other hand, the area×site and area×sp interactions were highly significant.
Also the area×site×sp interaction was significant (p≥0.05).The highest value
(1.38) was in White Nile and the lowest one (1.19) was in River Nile. With
31
respect to the interactions, the highest value (1.74) was obtained for O.
niloticus in Jebel Aulia and the lowest one (1.15) was obtained for O.
niloticus in Al Mawrada and Shendi.
4.1.8. Base length of dorsal Fin (cm).
Statistical analysis showed that there were highly significance
differences (p≤0.01) among the areas as well as among the sites, while the
differences among the species were significant. Also the area×site, area×sp
and area×site×sp interactions were highly significant. However, the site×sp
interaction was not significant (p<0.05). With respect to the interactions, the
highest mean BDF (9.15) was obtained for S. galilaeus in Wad Madani,
while the lowest value (5.67) was obtained for O. niloticus in Shendi in
River Nile. Regarding the areas, the highest mean (7.45) was in White Nile,
while the lowest one (6.37) was in River Nile. With respect to the sites, the
highest mean (8.34) was in Jabel Aulia, while the lowest one (5.67) was in
Shendi.
4.1.9. Posterior end of the dorsal fin to dorsal origin of the caudal fin
(cm).
Statistical analysis revealed that the differences (p<0.05) among the
areas and among sites and between the species were not significant.
Similarly the site×sp and area×site×sp interactions were not significant.
However, area×site and area×sp interactions were significant (p≥0.05). With
respect to the areas, the highest value (1.70) was in White Nile and the
lowest (1.40) was in River Nile. Among the sites, the highest value (1.80)
was in Jebel Aulia and the lowest one (1.24) was in Shendi. With respect to
the interaction, the highest mean PDDC (1.90) was obtained for S. galilaeus
32
in Wad Madani, while the lowest value (1.23) was obtained for O. niloticus
in Shendi.
4.1.10. Length of the anal fin (cm).
Statistical Analysis revealed that there were highly significance
differences (p≤0.01) among the areas as well as among the species. Also the
area×site and area×site×sp interactions were highly significant. While the
area×sp and site×sp were significant (p<0.05). On the other hand, difference
among the sites was not significant (p<0.05). The LA highest mean value
(2.96) was in Blue Nile and the lowest one (2.59) was in River Nile. With
respect to the sites, the highest LA value (3.68) was in Jebel Aulia and
lowest one (2.53) was in Shendi. Regarding the interactions, the highest LA
value (3.99) was obtained for O. niloticus in Jebel Aulia and the lowest one
(2.30) was obtained for S. galilaeus in Shendi
4.1.11. Base length of the anal fin (cm).
The analysis revealed that there were highly significant differences
(p≥0.01) among the sites. Also the area×site, area×sp and site×sp
interactions were highly significant. Whereas, the difference among the
areas was significant (p>0.05), as well as among the species and
area×site×sp interactions. With regard to the interactions, the highest mean
(3.07) was obtained for S. galilaeus in Wad Madani and the lowest one
(1.78) was obtained for O. niloticus in Shendi. With respect to the areas, the
highest mean (2.37) was in White Nile and the lowest one (1.99) was in
River Nile.
33
4.1.12. Length of the pelvic fin (cm).
Statistical analysis showed that there were highly significant
differences (p≥0.01) among the areas. Also the area×site, area×sp, and
area×site×sp interactions were highly significant. While the differences
among the sites, between the species and among the site×sp interactions
were significant (p≥0.05). With respect to the interaction, the highest LP
mean (4.87) was obtained for S. galilaeus in Wad Madani in Blue Nile and
the lowest one (2.79) was for O. niloticus in Shendi in River Nile. Among
areas, the highest mean (3.72) was in White Nile and the lowest one (3.12)
was in River Nile .With respect to the sites, the highest mean (4.24) was in
Wad Madani, while the lowest one (2.80) was in Shendi.
4.1.13. Caudal peduncle length (cm).
Statistical analysis showed that there is highly significance difference
(p≥0.01) among the areas as well as the area×site and the area×sp
interactions, while among the sites were significant (p>0.05). On the other
hand, the differences between the species, site×sp and area×site×sp
interactions were not significant. The highest CL mean (1.83) was in Blue
Nile and the lowest one (1.54) was in River Nile. With respect to the
interactions, the highest CL mean (2.27) was obtained for S. galilaeus in
Wad Madani and the lowest one (1.36) was in O. niloticus in Shendi.
4.1.14. Caudal peduncle depth (cm).
Statistical analysis showed highly significant differences (p≤0.01)
among the areas as well as among the sites. Also the area×site, area×sp and
area×site×sp interactions were highly significant, while the difference
between the species was significant (p>0.05). However, the difference
among site×sp interaction was not significant (p<0.05). With respect to the
34
interactions, the highest mean (2.68) was obtained for S. galilaeus in Wad
Madani and the lowest one (1.15) was obtained for O. niloticus in Shendi.
With respect to the areas, the highest CD mean (2.01) was in White Nile and
the lowest one (1.60) was in River Nile.
4.1.15. Eye diameter (cm).
Statistical analysis revealed that there were highly significant
differences (p>0.01) among the areas as well as area×site, site×sp
interactions. However, the differences among the site, among the species,
area×sp, site×sp and area×site×sp interactions, were not significant
(p<0.05). Among the areas, the highest value (1.30) was in Blue Nile and
the lowest one (1.11) was in River Nile. With respect to the interactions, the
highest mean (1.55) was obtained for S. galilaeus in Wad Madani and the
lowest one (1.07) was obtained for S. galilaeus in Shendi.
4.1.16. Mouth gape (cm).
Statistical analysis showed that there were highly significant
differences (p≥0.01) among the areas, as well as the area×site and area×
site×sp interactions. While the differences between the species, area×sp and
site×sp were significant. However, difference among the sites was not
significant. Among the areas, the highest mean value (1.64) was in Blue
Nile and the lowest one (1.39) was in River Nile. With respect to the sites,
the highest MG mean value (1.83) in Jebel Aulia and lowest one (1.36) was
in Al Kalakla. Regarding the interactions, the highest MG mean (1.99) was
obtained for O. niloticus in Jebel Aulia and the lowest one (1.37) was
obtained for O. niloticus and S. galilaeus in Shendi.
35
4.1.17. Predorsal distance (cm).
Statistical analysis showed highly significance different (p>0.01)
among the areas, as well as the area×site interaction. The differences among
the area×sp and area×site×sp interactions were significant (p>0.05). On the
other hand, the differences among the sites and among the species were not
significant (p>0.05). Also site×sp interaction was not significant. With
respect to the interactions, highest mean (5.38) was obtained for O. niloticus
in Jebel Aulia and the lowest one (3.65) was obtained for S. galilaeus in
Shendi. Regard to the areas, the highest mean value (4.65) was in White
Nile and the lowest mean (3.91) was in River Nile. Regarding the sites,
highest mean value (5.25) was in Jebel Aulia and the lowest one (3.66) was
in Shendi.
4.1.18. Prepelvic distance (cm).
Statistical analysis revealed that there were highly significant
differences (p<0.01) among the areas, as well as among the sites. Also the
area×sp and area×site×sp interactions were highly significant. The
differences between species and site×sp interaction were not significant
(p<0.05). The highest PRV mean (5.06) was in White Nile and the lowest
one (4.37) was in River Nile. Regarding the sites, highest mean (5.68) was
in Wad Madani and the lowest value (3.98) was in Shendi. With respect to
the interactions, highest mean value (6.35) was obtained S. galilaeus in Wad
Madani and the lowest (3.94) was obtained for O. niloticus in Shendi.
4.1.19. Preanal distance (cm).
Analysis showed that there were highly significant differences
(p≤0.01) among the areas, as well as among the sites. Also the area×site,
area×sp and area×site×sp interactions were highly significant. However, the
36
differences between the species and the site×sp interaction were not
significant (p<0.05). Among the areas, highest mean (9.01) was in White
Nile and the lowest one (7.86) was in River Nile. With respect to the sites,
the highest value (10.18) was in Wad Madani and the lowest one (7.02) was
in Shendi. With respect to the interactions, the highest mean (11.37) was
obtained for S. galilaeus in Wad Madani and the lowest one (6.97) was
obtained for O. niloticus in Shendi,
4.1.20. Prepectoral distance (cm).
Statistical analysis showed that there are highly significant differences
(p≤0.01) among the areas, as well as among the sites. Also the area×site,
area×sp, site×sp and area×site×sp interactions were significant. However,
the difference between species was not significant (p<0.05). With respect to
the areas, the highest mean (4.26) was in White Nile and the lowest one
(3.70) was in River Nile. Regarding the sites, the highest value (4.94) was in
Wad Madani and the lowest value (3.42) was in Shendi. Among the
interactions, the highest mean (5.67) was obtained for S. galilaeus in Wad
Madani and the lowest one (3.39) was obtained for O. niloticus in Shendi.
4.1.21. Lower jaw length (cm).
Statistical analysis showed that there were highly significant
differences (p>0.01) among the areas as well as the sites and between the
species. Also the area×site, area×sp and area×site×sp interactions were
highly significant. However, the difference among the site×sp interaction
was not significant (p<0.05). With regard to the areas, highest value (1.29)
was in White Nile and the lowest one (1.14) was in River Nile. With respect
to the interactions, the highest mean (1.49) was obtained for O. niloticus in
37
Jebel Aulia and the lowest one (1.00) was obtained for O. niloticus in
Shendi.
4.1.22. Premaxilary pedical length (cm).
Statistical analysis revealed that there were significant differences
(p≤0.05) among the areas, as well as among the sites. Also the site×sp and
area×site×sp interactions were significant. While the area×site and area×sp
interactions were highly significant (p≤0.01). On the other hands, the
difference among the species was not significant (p<0.05). For the three
areas, the highest mean value (0.9) was in White Nile followed by Blue Nile
(0.88), while the lowest one (0.75) was in River Nile. Regarding the sites,
the highest mean value (1.11) was in Jebel Aulia and the lowest one (0.74)
was in Al Mawrada. With respect to the interactions, the highest PP mean
(1.24) was obtained for O. niloticus in Jebel Aulia and the lowest one (0.74)
was obtained for O. niloticus in Al Mawrada
4.1.23. Number of scales in lateral line (cm).
The differences among the areas was statistically insignificant
(p>0.0). On the other hands, the difference among the sites as well as among
the species were highly significant (p≤0.01), also, the differences of the
area×site and area×sp interactions were highly significant. The differences
among the site×sp and area×site×sp interactions were significant p>0.05).
With respect to the areas, the highest mean 37.13 was in River Nile while
the lowest one 35.69 was in Blue Nile. The highest mean in the sites (38.18)
was in Al Mawrada and the lowest one (35.16) was in Ad Damazin. The
highest interaction mean (39.84) was obtained for O. niloticus in Al Kalakla
and the lowest mean (33.57) was obtained for S. galilaeus in Al Kalakla.
38
4.1.24. Number of the predorsal scales (cm).
Statistical analysis showed that there were highly significant
differences (p≤0.01) among the areas, the sites and between the species. The
differences of the area×site, area×sp and site×sp interactions were highly
significant (p≤0.01). However, the area×site×sp interaction was not
significant (p<0.05). Regarding the areas, the highest PrS mean (9.59) was
in the White Nile and the lowest one (8.71) was in Blue Nile. The highest
interactions mean (11.46) was obtained for O. niloticus in Al Kalakla and
the lowest one (8.13) was obtained for O. niloticus in Sennar. With respect
to the sites, highest mean (10.17) was in Al Kalakla while the lowest one
(8.28) was in Al Mawrada.
4.1.25. Number of the postdorsal scales (cm).
Statistical analysis showed that there were highly significant
differences (p≤0.01) among the areas, as well as among the sites and
between the species. Also the area×site, area×sp, site×sp and area×site×sp
interactions were highly significant. Among the areas, the highest value
(6.51) was in White Nile and the lowest one (5.77) was in the Blue Nile.
The highest interactions mean value (7.48) was obtained for O. niloticus in
Gitaina, while the lowest mean value (5.33) was obtained for S. galilaeus in
Shendi.
4.1.26. Number of scales surrounded the caudal peduncle (cm).
Statistical analysis showed that the differences among the areas, sites
and the species were not significant (p<0.05). Also the area×sp interaction
was not significant. On the other hand, area×site and area×site×sp
interactions were highly significantly different (p≤0.01), While the
differences among the site×sp was significant (p>0.05). The highest
39
interactions mean (9.69) was obtained for O. niloticus in Al Kalakla and the
lowest one (7.88) was obtained for O. niloticus in Wad Madani. Areawise,
the highest mean value (8.71) was in White Nile and the lowest one (8.44)
was in River Nile.
4.1.27. Number of the rays in the dorsal fin (cm).
Statistical analysis showed that there were significant differences
(p>0.05) among the areas, as well as between the species. Also the
difference among area×site interaction was significant. The area×sp
interaction was highly significant (p≤0.01). However, the difference among
the sites, the site×sp and area×site×sp interactions were not significant
(p<0.05). The areas highest mean value (12.48) was in River Nile and the
lowest one (12.07) was in White Nile. Regarding the sites, the highest mean
(17.25) was in Al Mawrada, while the lowest one (16.32) was in Al Kalakla.
Among the interactions, the highest mean (17.25) was obtained for O.
niloticus in Al Mawrada and the lowest one (15.68) obtained for S. galilaeus
in Sennar.
4.1.28. Number of the spines in the dorsal fin (cm).
The differences among the areas and among the sites were not
significant (p<0.05). Also the area×site, area×sp, site×sp and area×site×sp
interactions were not significant. However, the difference between the
species was highly significant (p≤0.01). Regarding the areas, the highest
SDF mean (17.08) was in River Nile, while the lowest one (16.34) was in
Blue Nile. For the sites, Al Mawrada showed the highest mean value
(17.25), while the lowest one (16.29) was in Sennar. The highest interaction
value (17.25) was obtained for O. niloticus in Al Mawrada and the lowest
one (15.68) was obtained for S. galilaeus in Sennar.
40
4.1.29. Number of rays in the anal fin (cm).
Statistical analysis indicated that the differences among the areas, as
well as among the sites, were not significant (p<0.05). Also the area×site,
area×sp, site×sp and area×site×sp interactions were not significant (p<0.05).
However, the difference between the species was highly significant
(p≤0.01). Among the areas, the highest mean (9.64) was in White Nile and
the lowest one (9.27) was in River Nile. With respect to the interactions, the
highest mean value (10.36) was obtained for S. galilaeus in Jebel Aulia and
the lowest one (8.79) was obtained for O. niloticus in Ad Damazin.
4.1.30. Number of spines in the anal fins (cm).
The number of anal fin spines was three in all studied sites.
4.1.31. Number of rays in the pectoral fin (cm).
Statistical analysis showed that the differences among the areas, as
well as among the sites were not significant (p<0.05). Also the area×sp,
site×sp and area×site×sp interactions were not significant. The differences
among the species was highly significant (p≤0.01), while the area×site
interaction was significant (p>0.05). With respect to the areas the highest
mean value (12.62) was in River Nile and the lowest one (12.33) was in
White Nile. With regard to the sites, the highest mean (12.69) was in Jebel
Aulia, while the lowest one (11.90) was in Al Kalakla. The highest
interactions mean value (12.90) was obtained for O. niloticus in Sennar and
the lowest one (11.86) was obtained for S. galilaeus in Shendi.
4.1.32. Number of rays in pelvic fin (cm).
The number of anal fin rays was five in all studied sites.
41
4.1.33. Number of rays in caudal fin (cm).
The statistical analysis revealed that there were significant differences
(p≤0.05) among the areas, as well as site×sp interaction. The differences
among the site, species as well as among area×site×sp interaction were
highly significant (p≤0.01). However, area×site and area×sp interactions
were not significant (p<0.05). Regarding the areas, the highest mean (16.60)
was in Blue Nile, while the lowest one (16.11) was in River Nile. With
respect to the sites, the highest mean (16.75) was in Sennar and the lowest
one (16.00) was in Al Mawrada. The highest interaction mean (16.76) was
obtained for O. niloticus in Al Kalakla in White Nile, while the lowest one
(15.67) was obtained for S. galilaeus in Ad Damazin in Blue Nile.
42
Table 3a. Summary of ANOVA tables for morphometric characters of O. niloticus and
S. galilaeus, over locations Characters Area Site Spp Area*Site Area*Spp Site*Spp Area*Site*Spp Error
F value F value F value F value F value F value F value
BW 21.216 ** 17.435** 1.126 ns 96.662** 22.088** 0.003 ns 16.495** 457.441
TL 8.957** 4.998 ns 6.770* 33.335** 13.562** 2.533 ns 8.322** 4.796
SL 13.136** 3.986* 21.123** 47.417** 9.600** 4.255* 3.333* 2.834
BD 30.176** 20.704* 1.438 ns 100.158** 26.454** 1.303 ns 26.277** 0.318
HL 0.754ns 1.937 ns 0.496 ns 2.739* 4.648* 0.120 ns 2.792 ns 4.110
HD 16.305** 9.753** 0.824 ns* 45.995** 10.013** 0.402 ns 11.321** 0.512
Snl 0.285 ns 1.125 ns 1.739 ns 10.793** 14.181** 3.650* 2.100 ns 0.127
BDF 25.079** 9.157** 9.997* 75.595** 28.660** 5.236ns 15.806** 0.629
PDDC 2.668 ns 1.941 ns 0.742 ns 3.265* 3.136* 0.492 ns 0.882 ns 0.359
LA 16.101** 2.547 ns 13.222** 58.055** 3.847* 4.168* 8.114** 0.281
BA 4.667* 13.449** 4.820* 69.014** 33.810** 20.786** 4.454* 4.454
LP 20.063** 7.506* 4.362* 60.401** 18.019** 4.508* 24.955** 0.251
CL 11.862** 5.319* 1.345 ns 12.958** 16.040** 0.345 ns 5.137 ns 0.138
CD 24.962** 10.792** 10.429* 63.067** 18.396** 1.936 ns 16.082** 0.065
ED 35.578** 0.542 ns 7.636 ns 44.109** 4.727 ns 10.289** 1.910 ns 0.019
MG 30.428** 2.670 ns 9.085* 53.799** 3.321* 5.275* 7.957** 0.048
PRD 19.435** 1.635 ns 0.975 ns 42.297** 7.375* 0.061 ns 4.020* 0.404
PRV 12.732** 10.510** 0.028 ns 59.729** 17.735** 2.533 ns 11.501** 0.377
PRA 17.007** 12.631** 1.197 ns 77.997** 23.921** 4.800 ns 15.237** 0.975
PR 22.769** 9.011** 0.289 ns 82.220** 24.635** 8.358* 17.276** 0.204
JLJ 11.634** 12.020** 20.232** 30.307** 10.509** 1.430 ns 8.514** 0.028
PP 3.982* 4.312* 1.308 ns 31.978** 9.329** 3.462* 6.849* 0.040
** Highly significant differences at p<0.01,* significant differences at p<0.05, ns=not significant.
43
Table 3b. Summary of ANOVA tables for meristic characters of O. niloticus and S. galilaeus, over locations Characters Area Site Spp Area*Site Area*Spp Site*Spp Area*Site*Spp Error
F value F value F value F value F value F value F value
LS 2.882 ns 13.955** 74.732** 8.332** 8.104** 3.084* 5.498* 4.106
Prs 29.438** 8.048** 35.739** 23.225** 30.366** 19.893** 2.867 ns 0.707
Pos 20.402** 15.309** 42.287** 9.443** 28.961** 8.710** 15.095** 0.746
Scp 2.366 ns 2.678 ns 3.335 ns 6.776** 5.042 ns 3.374* 10.630** 0.788
RD 6.336* 4.772 ns 6.681* 5.289* 8.641** 0.797 ns 0.073 ns 0.073
SDF 1.017 ns 0.906 ns 77.659** 2.146 ns 0.131 ns 2.241 ns 0.337 ns 0.532
RA 2.825 ns 2.575 ns 61.503** 1.361 ns 0.682 ns 2.255 ns 1.590 ns 0.718
Rp 0.694 ns 2.787 ns 23.109** 5.403* 0.216 ns 2.439 ns 0.707 ns 0.579
RC 5.462* 12.675** 10.706** 1.087ns 1.866ns 3.965* 13.937** 0.479
**Highly significant differences at p<0.01,* significant differences at p<0.05, ns=not significant.
44
Table 4. Descriptive statistics (Mean±SD) for morphometric and meristic
characters of O. niloticus and S. galilaeus in all locations.
Site Sp BW (g) TL (cm) SL (cm)
Mean± SD N Mean± SD N Mean± SD N
BN
Ad Damazin
O. niloticus 68.47 ± 12.43 19 16.00± 1.01 19 12.84 ± 0.76 19
S. galilaeus 73.57± 13.31 30 15.49± 0.82 30 12.54 ± 0.57 30
Mean 71.59 ± 13.09 49 15.69± 0.92 49 12.65 ± 0.66 49
Sennar
O. niloticus 48.90 ± 12.76 31 15.31 ± 4.01 31 12.48 ± 3.26 31
S. galilaeus 46.40 ± 16.06 30 13.49 ± 1.60 31 10.75± 1.23 31
Mean 47.67 ± 14.41 61 14.40 ± 3.16 62 11.61 ± 2.59 62
Wad Madani
O. niloticus 84.63 ± 56.08 8 16.09± 2.69 8 12.66± 2.58 8
S. galilaeus 124.17 ± 41.09 6 18.66 ± 1.43 6 12.00± 5.24 6
Mean 101.57 ± 52.49 14 17.19 ± 2.54 14 12.38± 3.77 14
Mean
O. niloticus 60.24 ± 26.39 58 15.64 ± 3.13 58 12.62 ± 2.57 58
S. galilaeus 65.82 ± 28.98 66 14.85 ± 2.00 67 11.66 ± 1.91 67
mean 63.21± 27.83 124 15.22 ± 2.60 125 12.11 ± 2.28 125
WN
Gitaina
O. niloticus 63.13 ± 15.66 40 15.31 ± 1.33 40 12.57 ± 1.14 40
S. galilaeus 48.56 ± 19.30 41 13.70± 1.74 41 11.22± 1.40 41
Mean 55.75 ± 18.96 81 14.50 ± 1.74 81 11.89 ± 1.44 81
Jebel Aulia
O. niloticus 109.46 ± 25.44 35 18.28± 1.53 36 14.98 ± 1.31 36
S. galilaeus 103.36 ± 14.24 25 15.88 ± 0.67 25 13.01± 0.54 25
Mean 106.92 ± 21.56 60 17.30 ± 1.72 61 14.17± 1.44 61
Al Kalakla
O. niloticus 99.97 ± 38.64 37 17.58 ± 2.23 36 14.51± 1.90 36
S. galilaeus 51.37 ± 9.70 35 13.61 ± 2.99 35 10.61± 0.74 35
Mean 76.35 ± 37.42 72 15.63 ± 3.29 71 12.59± 2.44 71
Mean
O. niloticus 89.78 ± 34.37 112 17.00 ± 2.14 112 13.97± 1.81 112
S. galilaeus 63.10 ± 27.74 101 14.21 ± 2.30 101 11.45± 1.39 101
Mean 77.13 ± 34.06 213 15.68 ± 2.6 213 12.78 ± 2.05 213
RN
Al Mawrada O. niloticus 62.18 ± 13.67 40 15.14 ± 1.23 40 12.98 ± 1.70 39
Shendi
O. niloticus 35.03 ± 22.74 38 12.69 ± 3.57 38 9.75± 1.86 38
S. galilaeus 35.50 ± 7.66 6 12.73 ± 0.91 6 10.10± 0.84 6
Total 35.09 ± 21.26 44 12.69 ± 3.32 44 9.80± 1.76 44
Mean
O. niloticus 48.95 ± 23.02 78 13.94 ± 2.90 78 11.38 ± 2.40 77
S. galilaeus 35.50 ± 7.66 6 12.73 ± 0.91 6 10.10± 0.84 6
Mean 47.99 ± 22.52 84 13.86 ± 2.82 84 11.29 ± 2.35 83
5% LSD:
BW: AREA= 1.684701, SITES=1.684701, SP=1.126644, A*SIT=5.007305, A*SP=3.401188, S*SP=3.401188.
TL: AREA=0.035406, SITES=0.035406, SP=0.023678, A*SIT=0.105235, A*SP=0.07148, S*SP=0.07148.
SL: AREA=0.023278, SITES=0.023278, SP=0.015567, A*SIT=0.069186, A*SP=0.046995, S*SP=0.046995.
45
Table 4. Continued
Site SP BD (cm) HL (cm) HD (cm)
Mean± SD N Mean± SD N Mean± SD N
BN
Ad Damazin
O. niloticus 5.09±0.52 19 4.40±0.31 19 4.58±0.45 19
S. galilaeus 5.38±0.32 30 4.39±0.35 30 4.82±0.35 30
Mean 5.27±0.43 49 4.39±0.33 49 4.73±0.41 49
Sennar
O. niloticus 4.54±0.55 31 3.97±0.42 31 4.16±0.43 31
S. galilaeus 4.51±0.53 31 3.81±0.44 31 4.17±0.46 31
Mean 4.53±0.53 62 3.89±0.43 62 4.17±0.45 62
Wad Madani
O. niloticus 5.16±0.98 8 4.31±0.64 8 4.83±0.99 8
S. galilaeus 6.83±0.63 6 5.82±0.81 6 6.20±0.82 6
Mean 5.88±1.19 14 4.96±1.03 14 5.41±1.14 14
Mean
O. niloticus 4.81±0.67 58 4.16±0.46 58 4.39±0.59 58
S. galilaeus 5.11±0.82 67 4.25±0.72 67 4.64±0.74 67
Mean 4.97±0.77 125 4.21±0.61 125 4.52±0.68 125
WN
Gitaina
O. niloticus 4.910±0.52 40 4.24±0.32 40 4.56±0.64 40
S. galilaeus 4.61±0.67 41 3.78±0.58 41 4.56±1.70 41
Mean 4.76±0.62 81 4.01±0.52 81 4.56±1.29 81
Jebel Aulia
O. niloticus 6.00±0.46 36 5.08±0.41 36 5.50±0.43 36
S. galilaeus 6.07±0.38 25 4.26±0.63 25 5.53±0.31 25
Mean 6.03±0.43 61 4.74±0.65 61 5.51±0.38 61
Al Kalakla
O. niloticus 5.98±0.60 35 5.72±6.76 36 5.38±0.70 36
S galilaeus 4.91±0.85 35 3.59±0.24 35 4.48±0.36 35
Mean 5.45±0.91 70 4.67±4.90 71 4.94±0.72 71
Mean
O. niloticus 5.60±0.74 111 4.99±3.86 112 5.13±0.73 112
S. galilaeus 5.08±0.90 101 3.83±.56 101 4.77±1.19 101
Mean 5.35±0.86 212 4.44±2.88 213 4.96±0.99 213
RN
Al Mawrada O. niloticus 4.95±0.35 40 4.07±0.37 40 4.64±0.35 40
Shendi
O. niloticus 3.95±0.61 38 3.47±0.50 38 3.63±0.54 38
S. galilaeus 3.97±0.35 6 3.60±0.35 6 3.57±0.34 6
Mean 3.95±0.58 44 3.48±0.48 44 3.62±0.52 44
Mean
O. niloticus 4.46±0.70 78 3.77±0.53 78 4.15±0.68 78
S. galilaeus 3.97±0.35 6 3.60±0.35 6 3.57±0.34 6
Mean 4.42±0.69 84 3.76±0.52 84 4.11±0.67 84 5% LSD:
BD: AREA=0.003609, SITES=0.003609, SP=0.002413, A*SIT=0.010726, A*SP=0.007286, S*SP=0.007286.
HL: AREA=0.002705, SITES=0.002705, SP=0.001809, A*SIT=0.008041, A*SP=0.005462, S*SP=0.005462.
HD: AREA=0.002908, SITES=0.002908, SP=0.001945, A*SIT=0.008643, A*SP=0.005871, S*SP=0.005871.
46
Table 4. Continued
Site SP SnL (cm) BDF (cm) PDDC (cm)
Mean± SD N Mean± SD N Mean± SD N
BN
Ad Damazin
O. niloticus 1.31±.19 19 7.55±.56 19 1.63±.23 19
S. galilaeus 1.35±0.34 30 7.23±.42 30 1.67±.22 30
Mean 1.33±0.29 49 7.36±.50 49 1.66±.22 49
Sennar
O. niloticus 1.23±0.20 31 7.03±.81 31 1.55±.17 31
S. galilaeus 1.18±0.22 31 6.32±.78 31 1.38±.24 31
Mean 1.20±0.21 62 6.68±.87 62 1.47±.22 62
Wad Madani
O. niloticus 1.48±0.25 8 7.63±1.53 8 1.65±.44 8
S. galilaeus 1.62±0.25 6 9.15±78 6 1.90±.24 6
Mean 1.54±0.25 14 8.28±1.45 14 1.76±.38 14
Mean
O. niloticus 1.29±0.22 58 7.28±.90 58 1.59±.24 58
S. galilaeus 1.29±0.31 67 6.98±1.03 67 1.56±.29 67
mean 1.29±0.27 125 7.12±.98 125 1.57±.27 125
WN
Gitaina
O. niloticus 1.30±0.21 40 7.38±.72 40 1.87±1.36 38
S. galilaeus 1.31±0.69 41 6.60±.93 41 1.47±.27 41
Mean 1.30±0.51 81 6.98±.92 81 1.66±.98 79
Jebel Aulia
O. niloticus 1.74±0.29 36 8.87±.72 36 1.91±.24 36
S. galilaeus 1.35±0.42 25 7.58±.49 25 1.64±.21 25
Mean 1.58±0.40 61 8.34±.90 61 1.80±.26 61
Al Kalakla
O. niloticus 1.46±0.36 36 8.09±1.08 36 1.79±.30 35
S. galilaeus 1.15±0.23 35 6.22±.36 35 1.50±1.32 35
Mean 1.31±0.34 71 7.17±1.24 71 1.64±.96 70
Mean
O. niloticus 1.49±0.34 112 8.08±1.05 112 1.86±.83 109
S. galilaeus 1.26±0.51 101 6.71±.85 101 1.52±.80 101
Mean 1.38±0.44 213 7.43±1.18 213 1.70±.83 210
RN
Al Mawrada O. niloticus 1.15±0.13 40 7.14±.57 40 1.58±.16 40
Shendi
O. niloticus 1.15±0.27 38 5.67±1.09 38 1.23±.20 38
S. galilaeus 1.68±1.14 6 5.67±1.16 6 1.30±.15 6
Mean 1.22±0.50 44 5.67±1.08 44 1.24±.19 44
Mean
O. niloticus 1.15±0.21 78 6.42±1.13 78 1.41±.25 78
S. galilaeus 1.68±1.14 6 5.67±1.16 6 1.30±.15 6
Mean 1.19±0.37 84 6.37±1.14 84 1.40±.25 84 5% LSD:
SnL: AREA=0.000344, SITES=0.000344, SP=0.00023, A*SIT=0.001023, A*SP=0.000695, S*SP=0.000695.
BDF: AREA=0.008196, SITES=0.008196, SP=0.005481, A*SIT=0.02436, A*SP=0.016546, S*SP=0.016546.
PDDC: AREA=0.000411, SITES=0.000411, SP=0.000275, A*SIT=0.001223, A*SP=0.00083, S*SP=0.00083.
47
Table 4. Continued
Site SP LA BA LP
Mean± SD N Mean± SD N Mean± SD N
BN
Ad Damazin
O. niloticus 3.44±0.71 19 1.83±0.51 19 4.10±0.75 19
S. galilaeus 2.99±0.70 29 2.54±0.41 30 3.50±0.50 30
Mean 3.17±0.73 48 2.26±0.57 49 3.73±0.67 49
Sennar
O. niloticus 2.90±0.58 31 2.15±0.26 31 3.38±0.48 31
S. galilaeus 2.46±0.41 31 2.08±0.29 31 3.15±0.41 31
Mean 2.68±0.55 62 2.12±0.28 62 3.27±0.46 62
Wad Madani
O. niloticus 3.35±0.82 8 2.58±0.43 8 3.78±0.86 8
S. galilaeus 3.70±0.22 6 3.07±0.35 6 4.87±0.41 6
Mean 3.50±0.64 14 2.79±0.46 14 4.24±0.88 14
Mean
O. niloticus 3.14±0.70 58 2.10±0.45 58 3.67±0.70 58
S. galilaeus 2.80±0.66 66 2.38±0.47 67 3.46±0.65 67
mean 2.96±0.70 124 2.25±0.48 125 3.56±0.68 125
WN
Gitaina
O. niloticus 2.65±0.40 40 2.17±0.33 40 3.55±0.33 40
S. galilaeus 2.57±0.68 41 2.10±0.39 41 3.31±0.57 41
Mean 2.61±0.56 81 2.14±0.36 81 3.43±0.48 81
Jebel Aulia
O. niloticus 3.99±0.73 36 2.94±0.39 36 4.53±0.44 36
S. galilaeus 3.22±0.59 25 2.51±0.16 25 3.85±0.58 25
Mean 3.68±0.77 61 2.76±0.38 61 4.25±0.60 61
Al Kalakla
O. niloticus 3.08±0.42 36 2.56±0.41 36 4.09±0.65 36
S. galilaeus 2.37±0.26 35 2.09±0.28 35 3.09±0.36 35
Mean 2.73±0.50 71 2.33±0.42 71 3.60±0.73 71
Mean
O. niloticus 3.22±0.77 112 2.54±0.49 112 4.04±0.63 112
S galilaeus 2.66±0.64 101 2.20±0.36 101 3.37±0.58 101
Mean 2.95±0.76 213 2.37±0.46 213 3.72±0.69 213
RN
Al Mawrada O. niloticus 2.66±0.28 40 2.19±0.26 40 3.47±0.41 40
Shendi
O. niloticus 2.56±0.43 37 1.78±0.32 38 2.79±0.44 38
S. galilaeus 2.30±0.42 6 1.98±0.26 6 2.90±0.60 6
Mean 2.53±0.43 43 1.80±0.32 44 2.80±0.46 44
Mean
O. niloticus 2.61±0.36 77 1.99±0.36 78 3.14±0.54 78
S. galilaeus 2.30±0.42 6 1.99±0.26 6 2.90±0.60 6
Mean 2.59±0.37 83 1.99±0.35 84 3.12±0.55 84 5% LSD:
LA: AREA=0.001658, SITES=0.001658, SP=0.001109, A*SIT=0.004927, A*SP=0.003347, S*SP=0.003347.
BA: AREA=0.001035, SITES=0.001035, SP=0.000692, A*SIT=0.003077, A*SP=0.00209, S*SP=0.00209.
LP: AREA=0.002167, SITES=0.002167, SP=0.001449, A*SIT=0.00644, A*SP=0.004374, S*SP=0.004374.
48
Table 4. Continued
Site SP CL CD ED
Mean± SD N Mean± SD N Mean± SD N
BN
Ad Damazin
O. niloticus 1.90±0.26 19 1.92±0.24 19 1.35±0.10 19
S. galilaeus 1.99±0.73 29 2.11±0.17 30 1.38±0.13 30
Mean 1.96±0.59 48 2.04±0.22 49 1.37±0.12 49
Sennar
O. niloticus 1.72±0.22 31 1.75±0.20 31 1.22±0.10 31
S. galilaeus 1.68±0.46 31 1.79±0.42 31 1.24±0.19 31
Mean 1.70±0.36 62 1.77±0.33 62 1.23±0.15 62
Wad Madani
O. niloticus 1.79±0.27 8 2.00±0.35 8 1.24±0.18 8
S. galilaeus 2.27±0.20 6 2.68±0.29 6 1.55±0.05 6
Mean 1.99±0.34 14 2.29±0.47 14 1.37±0.21 14
Mean
O. niloticus 1.79±0.25 58 1.84±0.25 58 1.26±0.12 58
S. galilaeus 1.87±0.61 66 2.02±0.41 67 1.33±0.18 67
mean 1.83±0.48 124 1.94±0.35 125 1.30±0.16 125
WN
Gitaina
O. niloticus 1.98±0.52 40 1.89±0.21 40 1.20±0.08 40
S. galilaeus 1.67±0.28 41 1.78±0.26 41 1.17±0.21 41
Mean 1.82±0.44 81 1.83±0.24 81 1.18±0.16 81
Jebel Aulia
O. niloticus 2.09±0.31 36 2.23±0.21 36 1.41±0.14 36
S. galilaeus 1.85±0.21 25 2.32±0.23 25 1.38±0.22 25
Mean 1.99±0.30 61 2.27±0.22 61 1.40±0.18 61
Al Kalakla
O. niloticus 2.01±0.38 36 2.12±0.37 36 1.12±0.11 36
S. galilaeus 1.46±0.23 35 1.86±0.22 35 1.20±0.08 35
Mean 1.74±0.42 71 1.99±0.33 71 1.16±0.11 71
Mean
O. niloticus 2.03±0.42 112 2.08±0.31 112 1.24±0.17 112
S. galilaeus 1.64±0.29 101 1.94±0.32 101 1.23±0.20 101
Mean 1.84±0.29 213 2.01±0.32 213 1.24±0.18 213
RN
Al Mawrada O. niloticus 1.74±0.20 40 1.76±0.17 40 1.14±0.08 39
Shendi
O. niloticus 1.36±0.33 38 1.44±0.23 38 1.08±0.12 38
S. galilaeus 1.37±0.15 6 1.60±0.11 6 1.07±0.12 6
Mean 1.36±0.31 44 1.46±0.22 44 1.08±0.12 44
Mean
O. niloticus 1.55±0.33 78 1.61±0.26 78 1.11±0.11 77
S. galilaeus 1.37±0.15 6 1.60±0.11 6 1.07±0.12 6
Mean 1.54±0.32 84 1.60±0.25 84 1.10±0.11 83 5% LSD:
CL: AREA=0.000461, SITES=0.000461, SP=0.000309, A*SIT=0.001371, A*SP=0.000931, S*SP=0.000931.
CD: AREA=0.000503, SITES=0.000503, SP=0.000337, A*SIT=0.001496, A*SP=0.001016, S*SP=0.001016.
ED: AREA=0.000195, SITES=0.000195, SP=0.000131, A*SIT=0.00058, A*SP=0.000394, S*SP=0.000394.
49
Table 4. Continued
Site SP MG PRD PRV
Mean± SD N Mean± SD N Mean± SD N
BN
Ad Damazin
O. niloticus 1.91±0.26 19 4.81±0.44 19 5.19±0.47 19
S. galilaeus 1.67±0.18 30 4.78±0.30 30 5.18±0.29 30
Mean 1.76±0.24 49 4.79±0.35 49 5.18±0.36 49
Sennar
O. niloticus 1.59±0.27 30 4.19±0.53 31 4.61±0.49 31
S. galilaeus 1.44±0.14 31 4.18±0.51 31 4.35±0.51 31
Mean 1.51±0.23 61 4.18±0.51 62 4.48±0.52 62
Wad Madani
O. niloticus 1.76±0.41 8 4.76±0.89 8 5.18±1.06 8
S. galilaeus 1.73±0.10 6 5.37±1.51 6 6.35±0.64 6
Mean 1.75±0.31 14 5.02±1.18 14 5.68±1.06 14
Mean
O. niloticus 1.72±0.32 57 4.47±0.63 58 4.88±0.65 58
S. galilaeus 1.57±0.20 67 4.56±0.69 67 4.90±0.74 67
mean 1.64±0.27 124 4.52±0.66 125 4.89±0.70 125
WN
Gitaina
O. niloticus 1.45±0.13 40 4.39±0.70 40 4.84±0.46 40
S. galilaeus 1.43±0.23 41 4.18±0.81 41 4.53±0.60 41
Mean 1.44±0.18 81 4.28±0.76 81 4.69±0.56 81
Jebel Aulia
O. niloticus 1.99±0.27 36 5.38±0.47 36 5.83±0.43 36
S. galilaeus 1.60±0.18 25 5.06±0.26 25 5.35±1.49 25
Mean 1.83±0.30 61 5.25±0.42 61 5.63±1.02 61
Al Kalakla
O. niloticus 1.40±0.31 36 4.94±0.18 36 5.48±0.74 36
S. galilaeus 1.33±0.17 35 4.15±0.32 35 4.50±0.28 35
Mean 1.36±0.25 71 4.55±0.95 71 4.99±0.74 71
Mean
O. niloticus 1.61±0.36 112 4.89±0.92 112 5.36±0.69 112
S. galilaeus 1.44±0.22 101 4.39±0.69 101 4.72±0.91 101
Mean 1.53±0.31 213 4.65±0.85 213 5.06±0.86 213
RN
Al Mawrada O. niloticus 1.42±0.17 40 4.19±0.37 40 4.80±0.39 40
Shendi
O. niloticus 1.37±0.20 38 3.66±0.57 38 3.94±0.56 38
S. galilaeus 1.37±0.20 6 3.65±0.34 6 4.20±0.31 6
Mean 1.37±0.10 44 3.66±0.54 44 3.98±0.53 44
Mean
O. niloticus 1.39±0.19 78 3.93±0.54 78 4.38±0.64 78
S. galilaeus 1.37±0.20 6 3.65±0.34 6 4.20±0.31 6
Mean 1.39±0.19 84 3.91±0.54 84 4.37±0.63 84 5% LSD:
MG: AREA=0.000424, SITES=0.000424, SP=0.000284, A*SIT=0.001261, A*SP=0.000857, S*SP=0.000857.
PRD: AREA=0.002898, SITES=0.002898, SP=0.001938, A*SIT=0.008612, A*SP=0.00585, S*SP=0.00585.
PRV: AREA=0.003362, SITES=0.003362, SP=0.002248, A*SIT=0.009992, A*SP=0.006787, S*SP=0.006787.
50
Table 4. Continued
Site SP PRA PR JLJ
Mean± SD N Mean± SD N Mean± SD N
BN
Ad Damazin
O. niloticus 9.32±0.67 19 4.46±0.41 19 1.41±0.18 19
S. galilaeus 9.17±0.47 30 4.34±0.31 30 1.24±0.13 30
Mean 9.23±0.55 49 4.39±0.35 49 1.31±0.17 49
Sennar
O. niloticus 8.49±0.72 31 3.98±0.51 31 1.28±0.18 31
S. galilaeus 7.77±0.91 31 3.79±0.40 31 1.07±0.15 31
Mean 8.13±0.89 62 3.89±0.47 62 1.18±0.19 62
Wad Madani
O. niloticus 9.29±1.77 8 4.40±0.91 8 1.29±0.35 8
S. galilaeus 11.37±0.68 6 5.67±0.56 6 1.35±0.23 6
Mean 10.18±1.73 14 4.94±1.00 14 1.31±0.30 14
Mean
O. niloticus 8.87±0.98 58 4.20±0.59 58 1.32±0.21 58
S. galilaeus 8.72±1.29 67 4.20±0.65 67 1.17±0.17 67
mean 8.79±1.16 125 4.20±0.62 125 1.24±0.21 125
WN
Gitaina
O. niloticus 8.69±0.72 40 4.14±0.35 40 1.33±0.16 40
S galilaeus 8.00±1.06 41 3.85±0.49 41 1.20±0.18 41
Mean 8.34±0.97 81 3.99±0.45 81 1.26±0.18 81
Jebel Aulia
O. niloticus 10.53±1.04 36 5.01±0.42 36 1.49±0.17 36
S. galilaeus 9.40±1.35 25 4.56±0.32 25 1.26±0.09 25
Mean 10.07±1.29 61 4.83±0.44 61 1.40±0.18 61
Al Kalakla
O. niloticus 9.79±1.54 36 4.41±0.44 36 1.42±0.24 36
S. galilaeus 7.89±0.53 35 3.77±0.30 35 1.05±0.10 35
Mean 8.86±1.50 71 4.09±0.55 71 1.23±0.26 71
Mean
O. niloticus 9.64±1.37 112 4.50±0.58 112 1.41±0.20 112
S. galilaeus 8.31±1.17 101 4.00±0.51 101 1.16±0.16 101
Mean 9.01±1.17 213 4.26±0.60 213 1.29±0.22 213
RN
Al Mawrada O. niloticus 8.77±0.74 40 4.02±0.33 40 1.29±0.14 40
Shendi
O. niloticus 6.97±1.24 38 3.39±0.63 38 1.00±0.17 38
S. galilaeus 7.33±0.39 6 3.62±0.33 6 1.05±0.10 6
Mean 7.02±1.16 44 3.42±0.60 44 1.00±0.16 44
Mean
O. niloticus 7.90±1.35 78 3.71±0.59 78 1.15±0.21 78
S. galilaeus 7.33±0.39 6 3.62±0.33 6 1.05±0.10 6
Mean 7.86±1.31 84 3.70±0.58 84 1.14±0.21 84
5% LSD:
PRA: AREA=0.01117, SITES=0.01117, SP=0.00747, A*SIT=0.0332, A*SP=0.022551, S*SP=0.022551.
PRP: AREA=0.002512, SITES=0.002512, SP=0.00168, A*SIT=0.007467, A*SP=0.005072, S*SP=0.005072.
JLJ: AREA=0.000236, SITES=0.000236, SP=0.000158, A*SIT=0.000701, A*SP=0.000476, S*SP=0.000476.
51
Table 4. Continued
Site SP PP LS PrS
Mean± SD N Mean± SD N Mean± SD N
BN
Ad Damazin
O. niloticus 0.96±0.16 19 36.79±3.77 19 8.89±0.46 19
S. galilaeus 0.90±0.16 30 34.13±2.67 30 8.83±0.79 30
Mean 0.93±0.16 49 35.16±3.37 49 8.86±0.68 49
Sennar
O. niloticus 0.81±0.14 31 36.65±2.07 31 8.13±1.09 31
S. galilaeus 0.80±0.13 31 34.97±2.71 31 8.97±0.55 31
Mean 0.80±0.14 62 35.81±2.54 62 8.55±0.95 62
Wad Madani
O. niloticus 0.98±0.18 8 37.88±1.36 8 9.00±0.76 8
S. galilaeus 1.03±0.16 6 35.83±1.72 6 8.83±0.41 6
Mean 1.00±0.17 14 37.00±1.80 14 8.93±0.62 14
Mean
O. niloticus 0.88±0.17 58 36.86±2.67 58 8.50±0.96 58
S. galilaeus 0.87±0.16 67 34.67±2.65 67 8.90±0.65 67
mean 0.88±0.17 125 35.69±2.87 125 8.71±0.83 125
WN
Gitaina
O. niloticus 0.77±0.14 40 38.75±0.90 40 10.20±1.16 40
S. galilaeus 0.77±0.25 41 36.39±1.73 41 8.85±0.88 41
Mean 0.77±0.20 81 37.56±1.82 81 9.52±1.23 81
Jebel Aulia
O. niloticus 1.24±0.26 36 37.25±2.18 36 9.14±0.76 36
S. galilaeus 0.92±0.13 25 33.80±1.73 25 8.84±0.37 25
Mean 1.11±0.27 61 35.84±2.63 61 9.02±0.65 61
Al Kalakla
O. niloticus 0.98±0.38 36 39.84±0.96 37 11.46±1.19 37
S. galilaeus 0.76±0.09 35 33.57±1.09 35 8.80±0.72 35
Mean 0.87±0.29 71 36.79±3.31 72 10.17±1.66 72
Mean
O. niloticus 0.98±0.33
5 112 38.63±1.78 113 10.27±1.41 113
S. galilaeus 0.80±0.19 101 34.77±2.03 101 8.83±0.72 101
Mean 0.90±0.29 213 36.81±2.71 214 9.59±1.35 214
RN
Al Mawrada O. niloticus 0.74±0.14 40 38.18±1.45 40 8.28±0.68 40
Shendi
O. niloticus 0.75±0.15 38 36.29±2.65 38 9.29±0.61 38
S. galilaeus 0.85±0.21 6 35.50±2.43 6 8.67±1.37 6
Mean 0.76±0.16 44 36.18±2.61 44 9.20±0.76 44
Mean
O. niloticus 0.74±0.14 78 37.26±2.31 78 8.77±0.82 78
S. galilaeus 0.85±0.21 6 35.50±2.43 6 8.67±1.37 6
Mean 0.75±0.15 84 37.13±2.35 84 8.76±0.86 84 5% LSD:
PP: AREA=0.000202, SITES=0.000202, SP=0.000135, A*SIT=0.0006, A*SP=0.000407, S*SP=0.000407.
LS: AREA=0.102223, SITES=0.102223, SP=0.068361, A*SIT=0.303829, A*SP=0.206374, S*SP=0.206374.
PrS: AREA=0.006436, SITES=0.006436, SP=0.004304, A*SIT=0.019129, A*SP=0.012994, S*SP=0.012994.
52
Table 4. Continued
Site SP Pos Scp RD
Mean± SD N Mean± SD N Mean± SD N
WN
Ad Damazin
O. niloticus 5.63±0.50 19 9.16±0.83 19 11.32±0.67 19
S. galilaeus 5.87±1.33 30 8.33±1.06 30 12.13±0.78 30
Mean 5.78±1.09 49 8.65±1.05 49 11.82±0.83 49
Sennar
O. niloticus 5.90±0.70 31 8.39±1.12 31 11.94±0.63 31
S. galilaeus 5.68±0.54 31 8.94±0.77 31 12.58±1.20 31
Mean 5.79±0.63 62 8.66±0.99 62 12.26±1.01 62
Wad Madani
O. niloticus 5.63±1.06 8 7.88±1.25 8 11.75±0.89 8
S. galilaeus 5.67±0.52 6 8.50±0.55 6 12.67±0.52 6
Mean 5.64±0.84 14 8.14±1.03 14 12.14±0.86 14
Mean
O. niloticus 5.78±0.70 58 8.57±1.13 58 11.71±0.73 58
S. galilaeus 5.76±0.97 67 8.63±0.93 67 12.39±1.00 67
mean 5.77±0.85 125 8.60±1.02 125 12.07±0.94 125
WN
Gitaina
O. niloticus 7.48±1.09 40 8.50±0.88 40 12.15±0.53 40
S. galilaeus 5.85±1.01 41 8.32±0.52 41 12.22±0.76 41
Mean 6.65±1.32 81 8.41±0.72 81 12.19±0.65 81
Jebel Aulia
O. niloticus 5.92±0.81 36 8.86±0.68 36 12.75±0.69 36
S. galilaeus 5.56±0.51 25 8.48±0.87 25 12.52±0.71 25
Mean 5.77±0.72 61 8.70±0.78 61 12.66±0.70 61
Al Kalakla
O. niloticus 8.49±1.35 37 9.69±1.28 36 12.35±0.59 37
S. galilaeus 5.37±0.49 35 8.40±0.55 35 12.34±1.24 35
Mean 6.97±1.87 72 9.06±1.18 71 12.35±0.95 72
Mean
O. niloticus 7.31±1.51 113 9.00±1.09 112 12.41±0.65 113
S. galilaeus 5.61±0.77 101 8.39±0.63 101 12.34±0.94 101
Mean 6.51±1.48 214 8.71±0.95 213 12.37±0.80 214
RN
Al Mawrada O. niloticus 6.63±0.67 40 8.20±0.52 40 12.63±0.59 40
Shendi
O. niloticus 5.82±0.46 38 8.66±1.15 38 12.34±0.81 38
S. galilaeus 5.33±0.52 6 8.67±1.03 6 12.33±0.52 6
Mean 5.75±0.49 44 8.66±1.12 44 12.34±0.78 44
Mean
O. niloticus 6.23±0.70 78 8.42±0.90 78 12.49±0.72 78
S. galilaeus 5.33±0.52 6 8.67±1.03 6 12.33±0.52 6
Mean 6.17±0.73 84 8.44±0.91 84 12.48±0.70 84 5% LSD:
PoS AREA=0.002417, SITES=0.002417, SP=0.001616, A*SIT=0.007183, A*SP=0.004879, S*SP=0.004879.
ScP :AREA=0.006877, SITES=0.006877, SP=0.004599, A*SIT=0.020439, A*SP=0.013883, S*SP=0.013883.
RD: AREA=0.012538, SITES=0.012538, SP=0.008385, A*SIT=0.037266, A*SP=0.025313, S*SP=0.025313.
53
Table 4. Continued
Site SP SDF RA SA
Mean± SD N Mean± SD N Mean± SD N
BN
Ad Damazin
O. niloticus 16.79±0.54 19 8.79±0.92 19 3.00±0.00 19
S. galilaeus 16.10±0.61 30 9.70±1.06 30 3.00±0.00 30
Mean 16.37±0.67 49 9.35±1.09 49 3.00±0.00 49
Sennar
O. niloticus 16.90±0.54 31 9.06±0.57 31 3.00±0.00 31
S. galilaeus 15.68±1.11 31 9.81±0.70 31 3.00±0.00 31
Mean 16.29±1.06 62 9.44±0.73 62 3.00±0.00 62
Wad Madani
O. niloticus 16.88±0.35 8 9.00±1.07 8 3.00±0.00 8
S. galilaeus 16.00±0.00 6 10.33±1.51 6 3.00±0.00 6
Mean 16.50±0.52 14 9.57±1.40 14 3.00±0.00 14
Mean
O. niloticus 16.86±0.51 58 8.97±0.77 58 3.00±0.00 58
S. galilaeus 15.90±0.87 67 9.81±0.96 67 3.00±0.00 67
mean 16.34±0.87 125 9.42±0.97 125 3.00±0.00 125
WN
Gitaina
O. niloticus 16.88±0.65 40 9.33±0.53 40 3.00±0.00 40
S. galilaeus 16.15±0.48 41 9.68±0.69 41 3.00±0.00 41
Mean 16.51±0.67 81 9.51±0.63 81 3.00±0.00 81
Jebel Aulia
O. niloticus 17.11±0.52 36 9.39±0.49 36 3.00±0.00 36
S. galilaeus 16.12±0.33 25 10.36±0.64 25 3.00±0.00 25
Mean 16.70±0.67 61 9.79±0.73 61 3.00±0.00 61
Al Kalakla
O. niloticus 16.78±1.44 37 9.11±0.52 37 3.00±0.00 37
S. galilaeus 15.83±0.57 35 10.29±0.75 35 3.00±0.00 35
Mean 16.32±1.20 72 9.68±0.87 72 3.00±0.00 72
Mean
O. niloticus 16.92±0.96 113 9.27±0.52 113 3.00±0.00 113
S. galilaeus 16.03±0.50 101 10.06±0.76 101 3.00±0.00 101
Mean 16.50±0.89 214 9.64±0.75 214 3.00±0.00 214
RN
Al Mawrada O. niloticus 17.25±0.50 40 9.28±0.45 40 3.00±0.00 40
Shendi
O. niloticus 17.11±0.73 38 9.11±0.45 38 3.00±0.00 38
S. galilaeus 15.83±0.75 6 10.33±1.75 6 3.00±0.00 6
Mean 16.93±0.85 44 9.27±1.70 44 3.00±0.00 44
Mean
O. niloticus 17.18±0.62 78 9.19±1.20 78 3.00±0.00 78
S. galilaeus 15.83±0.75 6 10.33±1.75 6 3.00±0.00 6
Mean 17.08±0.71 84 9.27±1.26 84 3.00±0.00 84 5% LSD:
SD: AREA=0.022713, SITES=0.022713, SP=0.015189, A*SIT=0.067509, A*SP=0.045855, S*SP=0.045855.
RD: AREA=0.006241, SITES=0.006241, SP=0.004174, A*SIT=0.018549, A*SP=0.012599, S*SP=0.012599.
SA: AREA=0.000629, SITES=0.000629, SP=0.000421, A*SIT=0.00187, A*SP=0.00127, S*SP=0.0012
54
Table 4. Continued
Site SP Rp Rpel RC
Mean± SD N Mean± SD N Mean± SD N
BN
Ad Damazin
O. niloticus 12.47±0.61 19 5.00±0.00 19 16.68±1.11 19
S. galilaeus 12.00±0.69 30 5.00±0.00 30 15.67±1.03 30
Mean 12.18±0.70 49 5.00±0.00 49 16.06±1.16 49
Sennar
O. niloticus 12.90±0.60 31 5.00±0.00 31 16.42±.87 31
S. galilaeus 12.13±0.88 31 5.00±0.00 31 16.72±.87 30
Mean 12.52±0.84 62 5.00±0.00 62 16.75±.84 61
Wad Madani
O. niloticus 12.75±0.71 8 5.00±0.00 8 16.00±0.00 8
S. galilaeus 12.17±1.17 6 5.00±0.00 6 16.33±0.52 6
Mean 12.50±0.94 14 5.00±0.00 14 16.14±0.36 14
Mean
O. niloticus 12.74±0.64 58 5.00±0.00 58 16.45±.88 58
S. galilaeus 12.07±0.82 67 5.00±0.00 67 16.20±1.04 66
mean 12.38±0.81 125 5.00±0.00 125 16.60±.97 124
WN
Gitaina
O. niloticus 12.70±0.52 40 5.00±0.00 40 16.05±0.32 40
S. galilaeus 12.20±0.87 41 5.00±0.00 41 15.97±0.28 38
Mean 12.44±0.76 81 5.00±0.00 81 16.01±0.30 78
Jebel Aulia
O. niloticus 13.06±0.58 36 5.00±0.00 36 16.59±0.88 39
S. galilaeus 12.16±0.90 25 5.00±0.00 25 16.20±0.41 25
Mean 12.69±0.85 61 5.00±0.00 61 16.43±0.74 64
Al Kalakla
O. niloticus 11.95±1.00 37 5.00±0.00 37 16.76±0.95 37
S. galilaeus 11.86±0.73 35 5.00±0.00 35 16.00±0.00 35
Mean 11.90±0.87 72 5.00±0.00 72 16.39±0.78 72
Mean
O. niloticus 12.57±0.85 113 5.00±0.00 113 16.45±0.81 116
S. galilaeus 12.07±0.84 101 5.00±0.00 101 16.04±0.28 98
Mean 12.33±0.88 214 5.00±0.00 214 16.27±0.66 214
RN
Al Mawrada O. niloticus 12.80±0.46 40 5.00±0.00 40 16.00±0.00 40
Shendi
O. niloticus 12.55±0.83 38 5.00±0.00 38 16.26±0.83 38
S. galilaeus 11.83±1.47 6 5.00±0.00 6 15.83±0.41 6
Mean 12.45±0.95 44 5.00±0.00 44 16.20±0.79 44
Mean
O. niloticus 12.68±0.67 78 5.00±0.00 78 16.13±0.59 78
S. galilaeus 11.83±1.47 6 5.00±0.00 6 15.83±0.41 6
Mean 12.62±0.77 84 5.00±0.00 84 16.11±0.58 84 5% LSD:
RP: AREA=0.013335, SITES=0.013335, SP=0.008918, A*SIT=0.039634, A*SP=0.026921, S*SP=0.026921.
RPel: AREA=0.001723, SITES=0.013335, SP=0.008918, A*SIT=0.039634, A*SP=0.003479, S*SP=0.003479.
RC: AREA=0.020168, SITES=0.020168, SP=0.013488, A*SIT=0.059945, A*SP=0.040717, S*SP=0.040717.
55
4.1.2. Correlation coefficients.
4.1.2.1. Length body weight relationship.
The estimate of correlation coefficients (r) between weight and standard
length showed different patterns at phenotypic level. Body weight of O.
niloticus detected highly significant and high positive phenotypic
correlation with the standard length (p>0.05, r=0.785) in blue Nile,
(p>0.05, r=0.939) for O. niloticus in White Nile, (p>0.05, r=0.927) for O.
niloticus in River Nile, (p>0.05, r=0.965) for S. galilaeus in Blue Nile
and (p>0.05, r=0.851) for S. galilaeus in White Nile (Table 5).
The value of b (regression coefficient) was ≠3 (where it was 2.83 for
O. niloticus in Blue Nile, 2.78 for O. niloticus in White Nile, 2.15 for O.
niloticus in River Nile, 2.91 for S. galilaeus in White Nile and 3.30 for S.
galilaeus in Blue Nile indicating that the growth in both species is
allometric.
4.1.2.2. Correlation between some traits.
In general, the estimate of correlation coefficients (r) among body
characters of the two species in the different locations showed different
patterns at phenotypic levels.
The correlation coefficients (r) estimated between body depth and
standard length was significant and positive in the three locations
of O. niloticus, body depth detected highly significant and high
positive phenotypic correlation with the standard length (p>0.05,
r=0.789) in Blue Nile, (p>0.05, r=0.897) in White Nile and
(p>0.05, r=0.927) in River Nile. S. galilaeus showed medium
correlation in Blue Nile (p>0.05, r=0.413) and in White Nile
(p>0.05, r=0.477) between the two character as given in (Table 6).
56
The Head depth of O. niloticus also was highly associated with
head length in Blue Nile (p>0.05, r=0.873), White Nile (p>0.05,
r=0.642) and River Nile (p>0.05, r=0.907). S. galilaeus in Blue
Nile (p>0.05, r=0.813) also showed strong correlation between the
two character while in White Nile there was a weak relation
(p>0.05, r=0.286) (Table 7).
In O. niloticus the correlation between caudal depth and caudal
length was highly significant in Blue Nile (p>0.05, r=0.634),
White Nile (p>0.05, r=0.457) and River Nile (p>0.05, r=0.742). S.
galilaeus showed highly significant correlation between the two
character (p>0.05, r= 0.688) in Blue Nile and (p>0.05, r=0.403) in
White Nile (Table 8).
Base length of dorsal fin of O. niloticus was a weak and not
significantly associated with number of the Rays in the Dorsal fin
(p≤0.05, r=0.149) in Blue Nile, (p≤0.05, r=0.238), in White Nile
and (p≤0.05, r=0.258) in River Nile. Also in S. galilaeus BDF
showed weak association (p<0.05, r=0.193) in Blue Nile and
(p<0.05, r=0.217) in White Nile with RD fin (Table 9).
Similarly the correlation between base length of dorsal fin with the
number of spines in dorsal fin was a weak and not significantly
associated for O. niloticus (p≤0.05, r=0.341) in Blue Nile, (p≤0.05,
r=0.026) in White Nile and (p≤0.05, r=0.123) in River Nile. In S.
galilaeus the correlations were (p≤0.05, r=0.023) in Blue Nile and
(p≤0.05, r=0.255) in White Nile (Table 10).
The correlation between number of rays in dorsal fin and the
number of spines in dorsal fin in O. niloticus population was a
weak correlations in Blue Nile (p≤0.05, r=0.219), White Nile
57
(p≤0.05, r=0.048) and River Nile, (p≤0.05, r=0.230). In S.
galilaeus high correlation (p>0.05, r=0.577) was found in Blue
Nile and weak correlation (p>0.05, r=0.235) was in White Nile
(Table 11).
The number of anal rays in O. niloticus showed significant
correlation (p>0.05, r=0.480) for Blue Nile, but it is very weak
(p≤0.05, r=0.185) in White Nile, (p>0.05, r=0.232) in River Nile,
also for S. galilaeus (p≤0.05, r=0.054) in Blue Nile and (p≤0.05,
r=0.129) in White Nile with the anal base (Table 12).
Table 5. Correlation coefficient between body weight (g) and standard
length (cm) of O. niloticus and S. galilaeus at different site along Blue
Nile, White Nile and River Nile.
Location No. Ln a b K X±SD r R2
O. niloticus
Blue Nile 57 -3.08 2.83 3.08±0.79 0.785 0.617
White Nile 114 -2.88 2.78 3.20±0.41 0.939 0.882
River Nile 78 -1.40 2.15 3.30±0.86 0.926 0.859
S. galilaeus
Blue Nile 64 -3.08 2.91 3.74±0.41 0.965 0.931
White Nile 98 -3.95 3.30 4.13±1.00 0.851 0.725
Table 6. Correlation coefficient between body depth (cm) and Standard
length (cm) of O. niloticus and S. galilaeus at different sites along Blue
Nile, White Nile and River Nile.
Location
No. Ln a b r R
2
O. niloticus
Blue Nile 57 -1.273 1.129 0.789 0.622
White Nile 114 - 0.800 0.956 0.897 0.804
River Nile 78 - 0.286 0.733 0.927 0.859
S. galilaeus
Blue Nile 64 0.798 0.336 0.413 0.171
White Nile 98 -1.097 1.109 0.477 0.227
58
Table 7. Correlation coefficient between Head depth (cm) and head
length (cm) of O. niloticus and S. galilaeus at different sites along
Blue Nile, White Nile and River Nile.
Location
No. Ln a b r R
2
O. niloticus
Blue Nile 57 0.112 0.959 0.873 0.761
White Nile 114 0.322 0.853 0.642 0.413
River Nile 78 -0.045 1.103 0.907 0.822
S. galilaeus
Blue Nile 64 0.398 0.786 0.813 0.661
White Nile 98 1.114 0.322 0.286 0.082
Table 8. Correlation coefficient between caudal depth (cm) and caudal
length (cm) of O. niloticus and S. galilaeus at different sites along Blue
Nile, White Nile and River Nile.
Location
No. L n a b r R2
O. niloticus
Blue Nile 57 0.216 0.709 0.634 0.402
White Nile 114 0.489 0.337 0.457 0.209
River Nile 78 0.232 0.548 0.742 0.550
S. galilaeus
Blue Nile 64 0.360 0.545 0.688 0.474
White Nile 98 0.466 0.383 0.403 0.162
Table 9. Correlation coefficient between BDF (cm) and RD of
O..niloticus and S. galilaeus at different sites along Blue Nile, White
Nile and River Nile.
Location
No. L n a b r R2
O. niloticus
Blue Nile 57 2.322 0.072 0.149 0.022
White Nile 114 2.325 0.093 0.238 0057
River Nile 78 2.376 0.080 0.258 0.066
S. galilaeus
Blue Nile 64 2.314 0.103 0.193 0.037
White Nile 98 2.203 0.162 0.217 0.047
59
Table 10. Correlation coefficient between BDF (cm) and SDF of O.
niloticus and S. galilaeus at different sites along Blue Nile, White Nile
and River Nile.
Location
No.
L n a
b
r
R2
O. niloticus
Blue Nile 57 2.986 -0.083 0.341 0.116
White Nile 114 2.797 0.014 0.026 0.001
River Nile 78 2.799 0.024 0.123 0.015
S. galilaeus
Blue Nile 64 2.782 -0.009 0.023 0.001
White Nile 98 2.653 0.064 0.255 0.065
Table 11. Correlation coefficient between RD and SDF of O. niloticus
and S. galilaeus at different sites along Blue Nile, White Nile and
River Nile.
Location
No.
Ln a
b
r
R2
O. niloticus
Blue Nile 57 3.688 - 0.434 0.219 0.048
White Nile 114 2.618 - 0.036 0.048 0.002
River Nile 78 3.567 - 0.367 0.230 0.053
S. galilaeus
Blue Nile 64 4.661 - 0.777 0.577 0.332
White Nile 98 4.448 - 0.699 0.235 0.055
Table 12. Correlation coefficient between RA and BA (cm) of O.
niloticus and S. galilaeus at different sites along Blue Nile, White
Nile and River Nile.
Location
No.
Ln a
b
r
R2
O. niloticus
Blue Nile 57 2.050 0.201 0.480 0.230
White Nile 114 2.174 0.057 0.185 0.034
River Nile 78 2.176 0.079 0.232 0.054
S. galilaeus
Blue Nile 64 2.254 0.028 0.054 0.003
White Nile 98 2.258 0.062 0.129 0.017
60
4.1.3. Morphometric and Meristic cluster analysis.
The hierarchical cluster dendrogram analysis (Fig. 1) identified two main
groups describing the relationships among populations. Oreochromis
niloticus from Al Kalakla cluster in separate branch and the second
cluster contain three groups, O .niloticus and S. galilaeus from Jebel
Aulia and S. galilaeus from Wad Madani cluster under group one. The
second group consists of two sub clusters, O. niloticus from Ad Damazin,
Gitaina, Al Mawrada and S. galilaeus from Ad Damazin clustering in one
sub cluster and O. niloticus from Wad Madani cluster in the second sub
cluster. The third group showed relation between six populations of O.
niloticus from Sennar and Shendi, S. galilaeus from Al Kalakla, Sennar
and Shendi. Among the different clustering groups, O. niloticus and S.
galilaeus from Shendi were most close, as well as S. galilaeus from
Sennar and Gitaina. The populations of O. niloticus from Al Mawrada
and Gitaina are close together.
61
Fig.1. Dendrogram generated by clustering using arithmetic average for
O. niloticus and S. galilaeus from the different sites based on
morphometric and meristic characters. O = O. niloticus S = S. galilaeus
O S O S S S O O O O S S O S O
S S Sn Sn G K Md G M D D Md J J K
62
4.2. Chemical compositions of O. niloticus and S. galilaeus from
different locations.
The proximate composition (crude protein and crude fat) of the
tilapia species were analyzed separately and averaged to obtain a
reference value.
4.2.1. Crude protein.
Analysis of variance (Table 13) showed highly significant
differences (p≤0.01) among the locations, as well as between the species
and Location×site interaction. According to the locations, the highest
mean value (17.62) was in Al Mawrada, while the lowest value (16.08)
was in Gitaina. The highest interaction mean value (17.96) was obtained
for S. galilaeus in Wad Madani and the lowest value (15.91) was
obtained for O. niloticus in Al Kalakla. Regarding to the species, the
highest mean value (17.11) was obtained for O. niloticus the S. galilaeus
showed lower value (16.86) (Table 14).
4.2.2. Crude Fat.
Statistical analysis (Table 13) showed significant differences
among the locations (p<0.05), as well as between the species. The
location×sp interaction was not significant (p>0.05). With respect to the
locations, the highest mean value (1.16) was in Jebal Aulia, while the
lowest value (1.01) was in Al Mawrada. With reference to the
interactions, the highest mean value (1.19) was obtained for S. galilaeus
in Gitaina and the lowest value (1.01) was obtained for O. niloticus in Al
Mawrada. With respect to species, the highest value (1.13) was obtained
for S. galilaeus, while O. niloticus showed the lowest mean value (1.08)
(Table 15).
63
Table 13. ANOVA for chemical composition (crude protein and crude fat)
of O. niloticus and S. galilaeus.
Source of variation Sum of
Squares
df Mean Square F-ratio Sig.
Crude protein Location 10.77234 7 1.538906 757.667 0.000
0.000
0.000 Sp 0.690367 1 0.690367 339.8961
Location×Sp 6.606083 6 1.101014 542.0747
Total 18.12972 44
Crude fat Location 0.086813 7 0.012402 5.482178 0.001
0.020
0.056 Sp 0.024703 1 0.024703 10.91989
Location×Sp 0.020897 6 0.003483 1.539547
Total 0.20028 44
Table 14. Mean protein content (%) of O. niloticus and S. galilaeus
from the different sites along the BN, WN and RN.
Locations Samle No. O. niloticus S. galilaeus Site mean
Ad Damazin 3 17.41±0.01 17.12±0.01 17.26±0.16
Sennar 3 17.32±0.01 16.99±0.01 17.15±0.18
Wad Madani 3 17.15±0.01 17.96±0.01 17.56±0.44
Jebel Aulia 3 16.43±0.01 16.49±0.01 16.46±0.03
Al Kalakla 3 17.88±0.15 15.91±0.15 16.89±1.08
Gitaina 3 15.94±0.01 16.23±0.02 16.08±0.16
Shendi 3 17.12±0.09 17.33±0.01 17.22±0.12
Al Mawrada 3 17.62±0.01 - 17.62±0.01
Species mean 17.11±0.61 16.86±0.67 16.99±0.64 5%LSD Location=0.053, 5%LSD Species = 0.027 and 5%LSD L×S = 0.075.
64
Table 15. Mean fat content of O. niloticus and S. galilaeus from the
different sites along the BN, WN and RN.
.
Locations O. niloticus S. galilaeus Site mean
Ad Damazin 1.11±0.01 1.11±0.02 1.11±0.01
Sennar 1.03±0.06 1.07±0.06 1.05±0.06
Wad Madani 1.07±0.06 1.14±0.05 1.11±0.06
Jebel Aulia 1.14±0.07 1.17±0.06 1.16±0.06
Al Kalakla 1.07±0.06 1.18±0.05 1.13±0.08
Gitaina 1.12±0.01 1.19±0.05 1.15±0.05
Shendi 1.11±0.01 1.03±0.06 1.07±0.06
Al Mawrada 1.01±0.01 - 1.01±0.01
Species mean 1.08±0.06 1.13±0.07 1.10±0.07 5%LSD Location=0.056, 5%LSD Species=0.028 and 5%LSD L×S=0.079.
RAPD amplification.
4.3.1. Genetic variability in RAPD loci.
Among the fifteen (O. niloticus and S. galilaeus) populations, all
selected primers (eight) produced strong, faint, sharp distinct bands. The
profiles are shown in Figs. 2, 3 and 4. The total bands generated by the
primers 1-8 are: 17, 16, 18, 12, 12, 14, 14 and 17 bands, respectively. The
primers generated bands were in the range of 100 to 1020 bp. However,
only the repeatable major bands ranging from 100 to 600 bp were scored
for consistency. A total of 50 reproducible bands were obtained in the 15
populations for the eight primers (Table 16).
Analysis of PCR product by gel electrophoresis showed that different
primers and various populations gave different numbers of bands (Table
16).
Using primer 1, the amplification products of O. niloticus DNA by
application of RAPD technique showed 15 bands of molecular weights
65
150-1020 bp and 10 bands in S. galilaeus of molecular weight 100-600
bp.
The RAPD-PCR products using primer 2 revealed 14 bands in O.
niloticus of molecular weights 100-1000 bp. and 12 bands in S. galilaeus
of molecular weight 100-600 bp.
In primer 3, O. niloticus produced 15 bands, 100-800 bp.; whereas in S.
galilaeus 12 bands appeared at 100-600 bp.
Primer 4 revealed 10 bands ranging in molecular weight between 200
and 1000 bp. in case of O. niloticus, but produced seven bands of
molecular weight ranging between 200 and 600 bp. in case of S.
galilaeus.
The amplification products of RAPD-PCR using primer 5 produced 10
bands in O. niloticus and S. galilaeus DNA. Their molecular weights
were in the range of 100-700 bp. and 100-500 bp., respectively.
Primer 6 produced 11 bands in the amplification of O. niloticus DNA
with molecular weights from100 to 700 bp. In S. galilaeus the molecular
weights of the 11 amplified bands ranged from 100 to 700 bp.
With primer seven both species produced nine bands. The molecular
weight was 150 to 800 bp for O. niloticus and 100-500 bp. for S.
galilaeus.
Using primer eight, six bands with molecular weights ranging from 100
to 1020 bp appeared in O. niloticus and 10 bands of (100-900 bp) in case
of S. galilaeus.
66
Table 16. O. niloticus and S. galilaeus RAPD profiles obtained by eight random molecular markers.
Primers
O. niloticus S. galilaeus Total bands
per primer
%
polymorp
hic DNA
bands
No. of
bands
MWT
bp.
% Poly-
morphic
bands
No. of
bands
MWT
bp.
% Polymorphic
bands
RAPD 1 15 150-1020 88.20 10 100-600 58.20 17 53.00
RAPD2 14 100-1000 81.30 12 100-600 56.20 16 56.20
RAPD 3 15 100-800 82.30 12 100-800 53.00 18 53.00
RAPD 4 10 200-1000 91.70 7 200-600 41.70 12 41.00
RAPD 5 10 100-700 83.30 10 100-500 83.30 12 66.67
RAPD 6 12 100-700 85.70 11 100-600 78.60 14 57.14
RAPD 7 9 150-800 64.30 9 100-500 78.6 14 57.14
RAPD 8 14 100-1020 87.50 10 100-900 62.5 17 50.00
67
Fig. 2. RAPD patterns obtained from O. niloticus using primer RAPD1, RAPD3, RAPD4,
RAPD5, RAPD6, and RAPD7. Lane M: 100 bp DNA ladder, lane 1-24: Al Kalakla.
500→ 1
MM 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
68
Fig. 3. RAPD patterns obtained from O.nilotics using primer RAPD1, RAPD2, RAPD3,
RAPD4, RAPD5 and RAPD6. Lane M: 100 bp DNA ladder, lane 1-16: Ad Damazin.
500→ 1
MM 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
69
Fig. 4. RAPD patterns obtained from O.niloticus using primer RAPD1, RAPD2, RAPD3,
RAPD4, RAPD5 and RAPD6. Lane M: 100 bp DNA ladder, lane 1-24: Shendi.
500→ 1
MM 1 2 3 4 5 6 7 8 9 10 11 1 13 14 15 16 17 18 19 20 21 22 23 24
70
4.3.2. Genetic diversity among and within populations.
Different pattern of diversity were obtained among the sub population
as well as within each population in the different sites. The percentage of
polymorphic bands generated by each primer within each population was
calculated. They were 53, 56.2, 53, 41, 66.67, 57.14, 57.14, and 50.00% for
RAPD1, RAPD2, RAPD3, RAPD4, RAPD5, RAPD6, RAPD7 and RAPD8
respectively. The polymorphic bands among the O. niloticus populations
were 88.2, 81.3, 82.3, 91.7, 83.3, 85.7, 64.3 and 87.5%. While in S.
galilaeus populations these were 58.2, 56.2, 53, 41.7, 83.3, 78.6, 78.6 and
62.5% for RAPD1, RAPD2, RAPD3, RAPD4, RAPD5, RAPD6, RAPD7
and RAPD8, respectively (Table 16).
4.3.3 Genetic distance and dendrogram.
The Jaccard matrix of genetic distance coefficients among each pair
of population and similarity index were shown in appendix 2. The distance
between fifteen populations of O. nilotics and S. galilaeus ranged from 0.02
to 0.27. The highest interspecies value (0.27) was obtained for O. niloticus
from Wad Madani and from Ad Damazin, also between O. niloticus from
Sennar and O. niloticus from Jebel Aulia populations. On the other hand, the
lowest value (0.02) was obtained for S. galilaeus from Al Kalakla with O.
nilotics from Al Kalakla; also O. niloticus from Al Kalakla with S. galilaeus
from Sennar got the same value of similarity index indicated by a
comparatively high overall interspecies pairwise divergence. The
intraspecies similarity coefficients obtained by pair wise comparisons of the
individuals in each species ranged from 0.35 to 0.94 and 0.42 to 0.80 for O.
nilotics and S. galilaeus, respectively. The highest similarities value (0.94)
was obtained for O. nilotics from Shendi and Ad Damazin. The lowest value
(0.15) was from Jebel Aulia for S. galilaeus the highest similarities value
71
(0.80) was from Shendi and also Ad Damazin, while the lowest value
(0.06) was in Gitaina individuals.
Euclidean coefficient dendrogram among populations presented in
Fig. 5 was derived from distance matrix. The populations were grouped into
22 clusters, S. galilaeus from Shendi, Wad Madani and some individuals of
O. niloticus from Sennar were grouped together. Oreochromis niloticus
from Jebel Aulia, Ad Damazin, Shendi, Gitaina, Al Mawrada, Wad Madani
and Al Kalakla populations fell in different clusters. Similarly S. galilaeus
from Jebel Aulia, Sennar, Gitaina, Ad Damazin and Al Kalakla populations
also grouped in different clusters. Furthermore some individuals from the
same site expressed a high degree of divergence and grouped with
individual from a different site (Fig. 5).
The populations of O. niloticus and S. galilaeus from each of Wad
Madani and Sennar fell in the same cluster. Among these, O. niloticus and S.
galilaeus from Wad Madani population and S. galilaeus from Sennar
population fell in the same subcluster. Oreochromis niloticus from Al
Kalakla expressed a high level of divergence from all other tilapia
populations.
72
6.0
5.4
4.8
4.2
3.6
3.0
2.4
1.8
1.2
0.6
0.0
Distance
S.g
1 K
S.g
4 K
S.g
2 K
S.g
3 K
O.n
4 J
O.n
3 K
S.g
3 J
S.g
4 J
S.g
2 G
O.n
2 M
dS
.g2
Md
S.g
1 S
nS
.g2
Sn
S.g
3 M
dO
.n4
Sn
O.n
1 M
dS
.g1
SS
.g2
SS
.g3
SS
.g4
SS
.g1
DS
.g2
DS
.g3
DS
.g4
DS
.g4
GO
.n3
Md
O.n
4 M
dS
.g1
Md
O.n
3 S
nO
.n1
MO
.n2
MO
.n4
MO
.n3
MO
.n1
GO
.n2
GO
.n3
GO
.n4
GS
.g1
GS
.g3
GS
.g3
Sn
S.g
4 S
nO
.n1
SO
.n2
SO
.n3
SO
.n4
SO
.n1
Sn
O.n
2 S
nO
.n1
DO
.n2
DO
.n3
DO
.n4
DO
.n1
JO
.n3
JO
.n2
JS
.g1
JS
.g2
JS
.g4
Md
O.n
2 K
O.n
4 K
O.n
1 K
Fig. 5. UPGMA dendrogram of population O. niloticus and S. galilaeus based on
values of genetic distance calculated from data for all 8 primers.
73
CHAPTER FIVE: DISCUSSION
In the present study, 33 morphometric and meristic characters of O.
niloticus and S. galilaeus in the eight locations, showed different patterns
of variation, between rivers, sites, species and their interactions in the
studied parameters.
The significant differences which were detected in body weight
indicated that area and site has important effects on this character. For the
areas, White Nile was favourable for growth in body weight (77.13)
whereas River Nile (47.99) was the least one. With respect to the eight
sites, the conducive site (106.92) was Jebel Aulia, while the least one
(35.09) was Shendi. The response of species to the effect of area, as
indicated by area ×species interaction, was significant. This indicates that
the response of the different species to the variation in the area was
different. The response of species to the effect of the site, as indicated by
site×species, determined very narrow range of variability. The differences
among the area and site combinations could be attributed to the differences
in the environmental conditions. The results of the present work are
consistent with the ranges reported by several other investigators who
worked on Tilapia species in various water sources. Ponzoni et al. (2005),
Gjedrem (2000) and Hallerman (2003) observed large variability in live
weight for two production environments were used to grow-out the
progeny. At approximately seven months of age females’ live weight was
84% that of males, whereas live weight in cages was 83% of that in ponds.
The greater weight in ponds than in cages is most likely a reflection of the
density of the fish in both environments and of the availability of natural
food. Fouzi et al. (2016) indicated that O. niloticus collected from
74
upstream from Sennar, Jebel Aulia and Merowe dams showed variations in
the total weight between the different populations.
Scapini et al. (1999) who worked on the amphipod Talitrus saltator;
Maltagliati et al. (2003) who worked on Trachurus trachurus; Yusuf and
Ali (2009) who worked on T. trachurus reported that variation in
morphological characters within species may have occurred due to
environmental factors such as temperature.
The significant differences in total length indicated that the area has
an important role on this character. For the three areas, White Nile was the
most favourable for the development in total length (15.68cm), whereas
River Nile was the least one (13.86). The response of species to the effect
of area was significantly as indicated by area × species interaction.
Regarding the eight sites, the conducive site (17.30) was Jebel Aulia,
whereas the least one (12.69) was Shendi. The variability of White Nile
habitats is exemplified by floating plants in Kosti area, typical lake
conditions from the dam body southwards and rapid flow from dam
northwards. These factors made Jebel Aulia site a conducive one. With
respect to Shendi site in the Nile proper, the site was least conducive
because its water characteristics as well as its content of plankton and fish
species are product of variability in its tributaries. The response of species
to the change in site was similar, as indicated by insignificant site× species
interaction. The differences among the areas could be attributed to the
differences in the environmental conditions. The results obtained in the
present study are in agreement with the results reported by other workers.
Wimberger (1992) reported that fishes are more susceptible to
environmentally induced morphological variation which might reflect
different feeding environments, prey types, food availability or other
75
features. Also Barlow (1961); Swain and Foote (1999) indicated that the
variation occur in growth, which may change between different locations,
thus they considered the TL an important character affected by growth rate
and the interactions between genetical and environmental factors. Cadrin
(2000) reported that sometimes it is difficult to explain the causes of
morphological variances between populations. On the other hand, Poulet et
al. (2004) and Chaklader (2016) suggested that genetics and environment,
and their interactions determine the morphological characteristics of fish.
The significant differences which were obtained in standard length
indicated that area and site had important effects on SL. For the three areas,
White Nile was the most conducive for the development in standard length
(12.78) whereas River Nile was the least one (11.29). The most favourable
site (14.17) was Jebel Aulia and the least one (9.80) was Shendi. The
response of species to the effect of area, as indicated by area×species
interaction, as well as the effect of site which indicated by site×species
were significant. This indicates that the response of different species to the
variation in the area and site were different. It could be an important
character for differentiation of species. The differences in SL among the
areas and sites could be attributed to the differences in the environmental
conditions. These results are in agreement with Ebraheem (2012) and
Samaradivakara et al. (2012) worked in morphological variation of tilapia
species populations in selected reservoirs in four sites in Sudan and Sri
Lanka, respectively. They reported that in discriminant analyses, SL
contributed heavily in discrimination of fish populations.
The significant differences which were detected in body depth
indicated that the area and site has an important effect on this character.
For the three areas, White Nile was the most conducive for development in
76
body depth and the least one (4.42) was in River Nile. According to the
sites, Jebel Aulia was the most favaourble (6.03), whereas the least one
(3.95) was in Shendi. The response of species to the effect of area was
significantly different, as indicated by area×species interaction. The
differences among the areas and the sites could be attributed to the
differences in the environmental conditions. These results are in agreement
with Haddon and Willis (1995); Samaradivakara et al. (2012) who reported
that body depth have an important character for discrimination of fish
populations, for example Angler fish (Lophius vormernus), Pacific herring
(Clupea pallasi) and Orange roughy (Hoplostethus atlanticus).
The insignificant differences in head length indicated that area and site
has no important role on this character. Despite of this fact, for the three
areas, White Nile was the most favourable for development in head length
(4.25), whereas River Nile was least one (3.76). With respect to the sites,
Wad Madani was the most conducive site (4.96), whereas Shendi was least
one (3.48). The response of species to the effect of area, as indicated by
area×species interaction, which was significant, showed that the response
of the different species to the variation in the area was different. This
character contribute in the morphometric variation as indicated by Yusuf
and Ali (2009), who found that morphometric differentiation between the
samples was largely due to differences in the head characters of fish.
Statistical analysis showed insignificant differences in head depth.
This indicated that area and site has no important effects on this character.
With respect to the three areas, White Nile was the most favourable for
development in head depth (4.96) and the least one (4.11) was in River
Nile. According to the sites, Jebel Aulia was the most conducive site
(5.51), whereas the least one (3.62) was Shendi. The response of species to
77
the effect of area, as indicated by area×species interaction, which was
significant, this indicated different performance of the different species to
the variation in the area. Yusuf and Ali (2009) reported that morphometric
differentiation between the samples was largely due to differences in the
head characters of fish. They stated that the head character was the most
important characters for discrimination of fish populations. Chaklader et al.
(2016) reported that when intraspecies variation in morphometric and
meristics characters of Ompok pabda was assessed and described, the head
depth significantly differed to varying degree among samples from four
rivers in Bangladesh.
The insignificant differences obtained in snout length, indicates that
area and site has no important effect on this character. With respect to the
three areas, SnL in White Nile was the most conducive (1.38) and the least
one (1.19) was detected in the River Nile samples. According to the sites,
Jebel Aulia was the most favourable (1.58), whereas the least one (1.15)
was in Al Mawrada. The response of species to the effect of area, as
indicated by area×species interaction was significant. This indicate that the
performance of different species to the area were different. This study
agreed with the work of Chaklader et al. (2016) who assessed and
described intraspecies variation in morphometric and meristics characters
of Ompok pabda from four different rivers in the southern coastal waters of
Bangladesh, and reported that SnL character significantly differed to
varying degrees among samples.
The exhibited significant differences in base length of dorsal fin,
indicates that the area and site has an important effect on this character. For
the three areas, White Nile was the most conducive for development in
BDF (7.45) and the least one (6.37) was River Nile. According to the sites,
78
Jebel Aulia was the most favourable site (8.34), whereas the least one
(5.67) was Shendi. The performance of species to the effect of area, as
indicated by area×species interaction was significant and the performances
of the different species to the variation were different. The performances of
species to the effect of site, as indicated by area×site interaction were
similar in both species. This result is in agreement with Ebraheem (2012)
who worked on O. niloticus from three rivers in Sudan and Chaklader et al.
(2016) in their study in Bangladesh. The results of their univariate statistics
(ANOVA) revealed that the length of dorsal base and morphometric
measurements significantly differed to varying degrees among samples.
The length of dorsal base of Baleswer, Payra and Halda river population
showed significant variation compared with Tentulia river population.
With respect to the posterior end of the dorsal fin to dorsal origin of
the caudal fin the non significant result obtained, indicated that the area
and site has no important role on this character. For the three areas, White
Nile was the most conducive (1.70) and the least one (1.40) was River
Nile. According to the sites, Jebel Aulia was the most favourable (1.80),
whereas least one (1.24) was Shendi. The response of species to the change
in area, as indicated by area×species interaction, which was significant,
indicates that the different species response differently to the variation in
the area. This result is in agreement with Samaradivakara et al. (2012) who
worked on morphological variation of four tilapia populations in selected
reservoirs in Sri Lanka and indicated that PDDC contributed heavily in
discrimination of fish populations.
Statistical analysis indicated that the area has an important effect on
Length of the anal fin. For the three areas, the most conducive for
development of anal fin (2.96) was the Blue Nile and the least one (2.59)
79
was River Nile. Among the sites, the most favourable (3.68) was Jebel
Aulia and least one (2.53) was Shendi. The response of species to the effect
of area and site as indicated by the area×species and site×species
interactions, were significant, this indicates that the species response
differently to the variation in the site and area and thus contribute in the
differences between populations. This result is in agreement with
Samaradivakara et al. (2012) who reported that the length of the anal fin
contributed heavily in discrimination of fish populations. The results are
also in agreement with Chaklader et al. (2016) whose work on Ompok
pabda indicated that the length of anal fin significantly differed to varying
degrees among samples.
The significant differences in base length of the anal fin indicated that
the area and site has an important effect on this character. For the three
areas, White Nile was the most conducive (2.38) and the least one (1.99)
was in River Nile. According to the sites, Wad Madani was the most
favourable (2.79), whereas the least one (1.80) was in Shendi. The
response of species to the change in area and site as indicated by
area×species and area×site interaction, which were significant indicates
that this character contributes to the differences between populations.
The significant differences which were detected in caudal peduncle
length indicated that the area and site has important role on this character.
For the three areas, Blue Nile was the most favaroubale for development in
CL (1.84) and the least one (1.54) was in River Nile. According to the
sites, Wad Madani and Jebel Aulia were the most conducive site (1.99),
whereas the least one (1.36) was in Shendi. The response of species to the
effect of area, as indicated by area×species interaction, was significant
indicating the importance of this character in variation. The influences of
80
environmental parameters on morphometric characters are well discussed
by several authors Samaee et al. (2006), AnvariFar et al. (2013) and Swain
and foote (1999).
The significant differences which were detected in caudal peduncle
depth indicated that the area and site have important effects on this
character. For the three areas, White Nile was the most conducive for
development in CD (2.01) and the least one (1.60) was in River Nile.
According to the sites, Wad Madani was the most conducive site (2.29),
whereas least one (1.46) was in Shendi. The response of species to the
effect of area, as indicated by area×species interaction, which was
significant, indicates the response of species to the effect of area. The
area×site interaction showed different pattern of variation between the
different species. The variability showed in this character agreed with
Ebraheem (2012) who worked on three tilapia species and identified CD as
one of the separating characters when applied discriminant analysis to
sample from Kosti area in White Nile. He successfully separated the
different groups of O. niloticus, S. galilaeus and T. zilli based on CD.
The significant differences in eye diameter indicated that the area
has an important effect on this character. For the three areas, Blue Nile was
the most favourable (1.37) and the least one (1.11) was in River Nile.
According to the sites, Jebel Aulia was the most conducive site (1.40),
whereas the least one (1.08) was in Shendi. The response of species to the
effect of area, as indicated by area×species interaction, as well as the effect
of site which is indicated by site×species was significant. This result is in
agreement with Yusuf and Ali (2009), who worked on T. trachurus
populations and reported that ED contributed mostly for the variance in the
data and population differentiation.
81
The significant differences detected in mouth gape indicated that
the area has important effects on this character. For the three areas, White
Nile was the most favaourble (1.64) and the least one (1.39) was in River
Nile. According to the sites, Jebel Aulia was the most conducive to
development of mouth gape (1.83), whereas least one (1.36) was in Al
Kalakla. The response of species to the change in area, as indicated by
area×species interaction was significant indicating that the species
response varies between areas. The insignificant performances of species to
the change in site, as assessed by site×species interaction indicated that the
response was similar. Sometimes it is difficult to explain the causes of
morphological variances between populations (Cadrin, 2000). However,
genetics, environment and their interaction determine the morphological
characteristics of fish as suggested by Poulet et al. (2004).
The differences in PRD were significant indicating that the area has
an important effect on this character. For the three areas, White Nile was
the most favourable for development in PRD (4.65) and the least one (3.91)
was River Nile. According to the sites, Jebel Aulia was the most conducive
site (5.25), whereas the least one (3.66) was Shendi. The response of
species to the effect of area and site as shown by area×species and
area×site interactions, which were significant, indicates that the response of
the different species to the variation in the area and site were different.
PRD was considered as a separating and influential character in tilapia
species as confirmed by Ebraheem (2012) findings.
The significant differences which were detected in PP indicated that
the area and site has an important effect on this character. For the three
areas, White Nile was the most favourable for development in prepelvic
distance (5.06) and the least one (4.37) was the River Nile. According to
82
the sites, Wad Madani was the most conducive site (5.68), whereas least
one (3.98) was Shendi. The response of species to the effect of area, as
indicated by area×species interaction was significant indicating different
response of the species to the variation in the area. The results in agreement
with Ebraheem (2012).
The significant differences detected in PAD indicated that the area
and site has important effects on this character. For the three areas, PRA
character in the White Nile was the most conducive for development in
preanal distance (9.01) and the least one (7.86) was River Nile. According
to the sites, Wad Madani was the most conducive site (10.18), whereas
least one (7.02) was Shendi. The response of species to the effect of area,
as indicated by area×species interaction, was significant confirming
Ebraheem (2012) findings.
The significant differences which were detected in PRP indicated that
area and site has important role on this character. For the three areas, White
Nile was the most conducive for the PRP (4.26) and the least one (3.70)
was River Nile. According to the sites, Wad Madani was the most
favourable (4.94), whereas the least one (3.42) was in Shendi. The
response of species to the effect of area and site as indicated by
area×species and area×species interaction, which were significant is in line
with Chaklader et al. (2016) whose work on Ompok pabda revealed that
PRP character significantly differed to varying degrees among samples.
The significant differences in the in LJL indicate that the area and
site has important effects on this character. For the three areas, White Nile
was the most conducive for development of LJL (1.29) and the least one
(1.14) was River Nile. According to the sites, Jebel Aulia was the most
favourable (1.40), whereas least one (1.00) was Shendi. The response of
83
species to the effect of area, as indicated by area×species interaction was
significant. This result agreed with Chaklader et al. (2016).
The differences detected in PP were significant. This indicated that
the area and site has important role on this character. For the three areas,
White Nile and Blue Nile was the most favorable for development in PP
(0.9) and the least one (0.75) was in River Nile. According to the sites,
Jebel Aulia was the most conducive site (1.11), whereas least one (0.74)
was Al Mawrada. The response of species to the effect of area and site as
indicated by area×species and area×site interaction were significant
indicating that the analysis successfully separated the different groups of
O. niloticus and S. galilaeus based on PP character. This is in agreement
with Ebraheem (2012) findings in tilapia samples from Kosti area.
The significant differences detected in the number of the LS
indicated that the site has important role on this character. For the three
areas, the most conducive for development in LS (37.13) in River Nile and
the least one (35.69) was Blue Nile. According to the sites, Al Mawrada
was the most favourable (38.18), whereas least one (35.15) was Ad
Damazin. The response of species to the effect of area and site as indicated
by area×species and area×site interactions were significant indicating that
the analysis successfully separated the different groups of O. niloticus and
S. galilaeus based on LS character. This is in agreement with Ebraheem
(2012) findings in tilapia samples from Kosti area.
Number of the predorsal scales: The significant differences in PrS
indicate that the area and site have important effects on this character. For
the three areas, the most favorable for the development in predorsal scales
(9.59) in White Nile and the least one (8.71) was Blue Nile. According to
the sites, Al Kalakla was the most conducive (10.17), whereas least one
84
(8.28) was Al Mawrada. The response of species to the effect of area and
site as indicated by area×species and area×site interaction, which were
significant, indicates that the response of the different species to the
variation in the area and site were different. These morphological
variations within species may have occurred due to environmental factors
such as differentiation related to predation pressures, salinity, temperature
and food availability as sugessted by Scapini et al. (1999); Maltagliati et
al. (2003); Yusuf and Ali (2009).
The significant differences detected in PoS in the number of the
postdorsal scales indicated that the area and site has important role on this
character. For the three areas, the most favourable for PoS (6.51) in White
Nile and the least one (5.77) was in Blue Nile. According to the sites, Al
Kalakla was the most conducive (6.97), whereas the least one (5.75) was
Shendi. The response of species to the effect of area and site as indicated
by area×species and area×site interaction, which were significant, indicated
that the response of the different species to the variation in the area and site
were different. This result is in agreement with Samaradivakara (2012)
who worked on morphological variation of four tilapia populations. His
canonical discriminant function coefficients obtained for meristic data
suggested that PoS character is one of the influential variables.
The statistical analysis detected in SCP was not significant,
indicating that the area and site has no important effects on this character.
For the three areas, SCP character was the most conducive (8.71) in White
Nile and the least one (8.44) was River Nile. According to the sites, Al
Kalakla was the most favourable site (9.06), whereas least one (8.14) was
Wad Madani. The response of species to the effect of area and site, as
indicated by area×species and site×species interaction were not significant.
85
This is in line with Misra and Carscadden (1987) and Murta (2000) who
considered meristic characters less useful than the morphometric data,
when comparing morphological variations.
The significant differences detected in RD indicated that the area has
important effects on this character. For the three areas, the most conducive
for development in RD (12.48) in River Nile and the least one (12.07) was
White Nile. According to the sites, Al Mawrada was most favourable
(15.68), whereas least one (16.32) was in Al Kalakla. The response of
species to the effect of area, as indicated by area×species interaction was
significant. This is in agreement with Ebraheem (2012) who sucessfuly
differentiated O. niloticus, S. galilaeus and T. zilli from Kosti. The
insignificant response of species to the effect of site, as indicated by
site×species interaction was in agreement with Yusuf and Ali (2009) who
suggested that enough mixing among locations may prevent differentiation.
Regarding the number of the spines in the dorsal fin: its result
indicates that area and site has no important effects on this character. For
the three areas, River Nile was the most favourable (17.08) and the least
one (16.34) was White Nile. According to the sites, Al Mawrada was the
most conducive site (17.25), whereas least one (16.69) was Sennar. The
response of species to the effect of area and site, as indicated by
area×species and site×species interactions was not significant, implying
that the performances of the different species to the variation in the area
and site were similar rendering this character less informative. Vidalis et
al. (1994) argued that meristic characters may follow a predetermined
variability at a very narrow range, because divergence of the meristic
counts from a standard range could be fatal for the individual.
86
The statistical analysis of the number of rays in the anal fin showed
no significant differences indicating that area and site have no important
effects on this character. For the three areas, White Nile was the most
conducive for development in RA (9.64), whereas River Nile least (9.27)
According to the sites, Jebel Aulia was the most favorable site (9.79),
whereas Shendi least one (9.27). The response of species to the change in
area and site, as indicated by area×species and site×species interaction,
were not significant. Indicated less informative and low or no variability
between the different species. This result is in agreement with the findings
of Vidalis et al. (1994).
Statistical analysis indicated that the area and site have no important
role on the number of rays in the pectoral fin. For the three areas, the White
Nile was the most favourable (12.62), whereas River Nile least one
(12.33). According to the sites, Jebel Aulia was the most conducive site
(12.69), whereas Shendi was the least one (11.90). The response of species
to the effect of area and site, as indicated by area×species and site×species
interaction were not significant. The present findings agreed with Misra
and Carscadden (1987); Murta (2000) and Munasinghe and Thushari
(2010) who considered meristic characters less useful than the
morphometric data.
The analysis indicated that the area and site has no important effects on
the number of rays in caudal fin. For the three areas, Blue Nile was the
most conducive (16.60), whereas River Nile was the least one (16.11).
According to the sites, Sennar was the most favourable site (12.69),
whereas Al Mawrada least one (16.00). The response of species to the
effect of area and site, as indicated by area×species and site×species
interaction were not significant. Indicates that the response of the different
87
species to the variation in the area and site were similar. This result is in
agreement with Vidalis et al. (1994) as explained earlier.
For the meristic characters, the number of spines in the anal fins and
the number of rays in pelvic fin were constant between the species and
sites and consequently were not of value as discriminating character.
The positive correlation coefficient between the standard length with
each of body weight and body depth in O. niloticus and S. galilaeus from
the Blue Nile, White Nile and River Nile indicated medium to high
association of SL with both of characters. In River Nile the SL was
positively correlated with these characters in O. niloticus only.
From Length weight relationship the heavier fish at a given length is in
better condition (Bolger and Connolly, 1989), hence indicating
favourable the better its condition. Similar results were reported in
Eutropius niloticus by El Sayed (1985), in Labeo niloticus by Idris and
Mahmoud (2001) and in Tilapia nilotica by Tave (1986). The
differences were attributed to the effect of eutrophication and pollution
on growth and other biological aspects of O. niloticus as suggested by
Khallaf et al. (2003). Similar findings were reported by Bhuiyan and
Biswas (1982) in Puntius chola. The present findings showed that
length-weight relationship was allometric in both species due to
contribution of many factors in this correlation.
The high positive correlation between head length with head depth in
Blue Nile, White Nile and River Nile was found in O. niloticus; a positive
correlation in the Blue Nile samples, while a weak correlation between the
two characters was found in White Nile samples in S. galilaeus. Thus the
association of HL with HD was more stable over the different
88
environments and can be used as indictor of these characters. This result is
in agreement with Saroniya et al. (2013) findings, in Puntius spp. and with
Brraich and Akhter (2015) in Garra gotyla gotyla.
High positive correlation was found between the CD and CL in Blue Nile
and in River Nile, while it was medium correlation in White Nile for O.
niloticus. The correlation was high in S. galilaeus samples from the two
sites. This stable correlation with in agreement Brraich and Akhter (2015)
worked in Crossocheilus latius latius and Garra gotyla gotyla and with
Saroniya et al. (2013), in Puntius conchonius.
The weak correlation coefficient between the BDF with each of RD and
SDF, was weakly correlated for both species at the studied sites. These
findings are in harmony with the findings of Umoh et al. (2015) in hybrid
Catfish from selected fish farms in Southern Nigeria. However, Friedman
and Wainwright (2015) displayed considerable variation in fin spines, body
depth and width relationship, which indicates some relationship between
morphometric and meristic traits especially in predatory fish.
In O. niloticus, the weak correlation between the RD with SDF indicates
its weak association and instability in Blue Nile, White Nile, and River
Nile. In S. galilaeus the medium positive correlation in Blue Nile and the
medium association was in White Nile. Indicates that these characters are
directly proportional to each other in S. galilaeus. This result agrees with
the findings of Umoh, et al. (2015) and Nlewadim and Omitogun (2005)
where the dorsal fin correlated positively and decreases as the adipose fin
increase in Heterobranchus and Clarias spp.
In both spp. the weak correlation between the RA with the BA indicates
a weak and unstable over the different environments. Standen and Lauder
89
(2005) reported that at any given point in time the spanwise curvature
along fin rays can differ between adjacent rays, suggesting that fish have a
high level of control over fin surface shape.
To investigate the phenotypic relationships between the examined
populations, a dendrogram was constructed based on both morphometric
and meristic characters using UPGMA cluster analysis. The analysis
revealed that tilapia spp collected from the eight locations, which represent
fifteen populations, clustered into fifteen distinct groups. These populatins
fall in two main groups, one population cluster in the first branch and three
groups cluster in the second branch. This indicates that morphometric and
meristic characters are more effective in detecting the variation among the
different populations.
Although O. niloticus from Sennar, Gitaina and Shendi, S. galilaeus
from Al Kalakla, Sennar and Shendi were within the same sub cluster, O.
niloticus and S. galilaeus from Shendi had high degree of similarity. Also
in the same pattern O. niloticus from Ad Damazin, Wad Madani, Gitaina,
Al Mawrada and S. galilaeus from Ad Damazin clustering together, but O.
niloticus from Gitaina and Al Mawrada were highly similar. This result
indicates that there may be enough mixing among these locations to
prevent differentiation. However, O. niloticus from Al Kalakla was clearly
distinct and diverged from other populations probably because of
difference in the habitat condition. This suggested that RAPD is a
confirmatory tool to detect the differences. Mwanja et al. (1996) and
Williams et al. (1990) reported that RAPD is a sensitive species
differentiating tool.
The significant differences which were detected for protein indicate that
the site has an important effect on protein content. For the eight sites, Al
90
Mawrada was the most conducive site (17.62) and the least one (16.08)
was Al Kalakla. With respect to the interaction, S. galilaeus in Wad
Madani in Blue Nile was most favorable (17.96), while O. niloticus in
Jebel Aulia was the least one (15.91).With respect to the species, O.
niloticus was the most productive (17.11), whereas least producer (16.86)
was S. galilaeus. The response of species to the effect of the site, as
indicated by location× species was significant; this indicates that the
response of different species to the change of site was different. The
differences among the sites could be attributed to the differences in the
environmental conditions. This result is in agreement with Flos et al.
(2002) who reported that the quality of fish is affected by food type, level
of dietary intake and growth.
The significant differences which were detected for crude fat indicate that
the site has an important effect on fat content. For the eight site, Gitaina
was the most favorable site (1.16) and the least one (1.01) was in Al
Mawrada. Refer to the interaction S. galilaeus in Al Kalakla was most
conducive (1.19), while O. niloticus in Al Mawrada was the least one
(1.01). According to the species S. galilaeus was the most productive
(1.13), whereas the least producer (1.08) was O. niloticus. The response of
species to the effect of the site, as indicated by location×species was
significant, indicating that the responses of the different species to the
variation in the site were different. The differences observed in the
chemical composition in this work compared to that reported in the
literature may be due to different places of origin and the freshness of the
raw material. The crude fat of O. niloticus collected from the three
different sites significantly differed. Fouzi et al. (2016) reported that the
91
effects of changing environmental conditions affect the chemical
composition, survival, and population within fish species.
RAPD total bands generated by the primers 1-8 are: 17, 16, 18, 12,
12, 14, 14 and 17 bands, respectively. The variation in RAPD bands (i.e.,
strong, faint and sharp bands) generated with each primer may indicate
different annealing temperature. Ambak et al. (2006) during explanation of
variation in RAPD bands stated that one or more copies of DNA may exist
per genome or may be attributed to the varying of the annealing process
polymorphism between the primer and the DNA. The problem of mixed
bands supposed the sensitivity of PCRs results (Bielawski et al., 1995).
RAPD 4 and RAPD 5 showed low polymorphism among the fish species
studied. The sequences of RAPD fragments generated by the other primers
reflected high degree of polymorphism which may be considered as more
conserved sequences. As stated by Soufy et al. (2011) conserved sequences
are most useful in higher taxonomic levels and evolutionary relationships.
These results also are in agreement with Baradakci and Skibinski (1994)
and Ambak et al. (2006) who stated that, patterns of similarities and
differences between populations showed broad agreement across primers
and the overall similarity level varied between primers.
The applied eight primers generated 50 analyzable bands with
variable percentage of polymorphic loci within and among the studied
species population from different geographical regions. The percentage of
polymorphic bands generated by each primer, were 53, 56.2, 53, 41, 66.67,
57.14, 57.14, and 50.00% for RAPD1, RAPD2, RAPD3, RAPD4, RAPD5,
RAPD6, RAPD7 and RAPD8, respectively. Levels of variability were
estimated by the proportion of polymorphic bands obtained by each primer
within a population. Among the O. niloticus, was most variable, having
92
88.2, 81.3, 82.3, 91.7, 83.3, 85.7, 78.6, 46 and 87.5%. While for S.
galilaeus was 58.2, 56.2, 53, 41.7, 83.3, 78.6, 78.6 and 62.5% of its bands
were polymorphic for RAPD1, RAPD2, RAPD3, RAPD4, RAPD5,
RAPD6, RAPD7 and RAPD8, respectively. A high level of polymorphism
is recommended for the identification of subspecies by Wilkerson et al.
(1993).
The optimal annealing temperature for the RAPD primer and DNA
polymerase in this experiment was found to be 36 C. The number of cycle
kept constant through all analysis , as were denaturation , annealing and
extension temperatures 37 cycles. The amplification reaction ended with 10
min at 72 C. The current PCR analysis was similar with Dinesh et al.
(1993), Ambak et al. (2006), with increase in number of cycles. RAPD
technology is a useful tool for identifying DNA polymorphism, estimation
of genetic diversity and difference of related species in fish. However, it is
essential to optimize RAPD amplified condition and ascertain the
reproducibility of RAPD markers for individual taxa prior to apply RAPD
fingerprinting to any genetic analysis (Ambak et al., 2006).
Similarity coefficient represents a measure of the shared bands by two or
more different species within the same, and different, primers. These are
important measurements that help to quantify the degree of relationships
between different species (Ambak et al., 2006). The distinct similarity
encountered may indicate interbreeding of tilapia species, for instance the
population of O. niloticus from Al Mawrada Vs Ad Damazin, also O.
niloticus from Al Kalakla Vs S. galilaeus from Sennar. The case of
possible interchanges in that one for example between S. galilaeus from Al
Kalakla Vs O. niloticus from Al Kalakla, also O. niloticus from Al Kalakla
Vs S. galilaeus from Sennar as similarity coefficient was less. RAPD
93
fingerprinting is a useful tool for assessment of genetic variability and can
be applied to breeding program in aquaculture. Reproductive program is
carried out based on similarity coefficient. It can be formulated to increase
genetic variation within brood stocks with high similarity coefficient value
by outcrossing with other breeds with lower similarity coefficient index
(Koh et al., 1999).
In comparison to the pattern of clustering obtained by the RAPD, the
dendrogram obtained differentiate the populations into 22 sub clusters,
indicating that RAPD method was more sensitive in detecting variation
among the different populations. Not all individuals from each population
were grouped in the same cluster of the same population.
The populations of O. niloticus and S. galilaeus from Wad Madani and
Sennar were clustered together, indicating a similarity between those
populations. Also O. niloticus and S. galilaeus from Wad Madani
population clustered together. Individuals of S. galilaeus from Sennar
population also showed a high similarity. However, O. niloticus from Al
Kalakla exhibited a high level of divergence level from all the-other tilapia
populations. This population showed similar result with morphometric
cluster analysis. High genetic variation (especially allele diversity)
theoretically promotes better adaptability of the populations (Allendorf,
1988).
According to Soufy et al. (2011) very high similarity between O.
niloticus and S. galilaeus leads to high probability of hybridization
between them. The different location of river impoundments can lead to an
enhancement of pre-existing genetic differences, providing a high
interpopulation structuring (Esguicero and Arcifa, 2010). Abumourod et al.
(2008) evaluated the common patterns of genetic variations or similarities
94
among three species of tillapine through DNA fingerprinting analysis using
RAPD PCR from EL Abbassa fish farm in Egypt. The comparison
depended on similarity coefficient which revealed many hybrids.
Hybridization between closely related species improves the genetic
characters and produces many strains related to the more tilapias species.
95
CONCLUSIONS AND RECOMMENDATIONS
Fifteen populations of O. niloticus and S. galilaeus were collected from
different site along the BN, WN and RN, with the objectives of estimating
the magnitude of variability in morphometric, meristic and quality
characters as well as determination of interrelationships between the
different characters. Furthermore, genetic diversity among the different
populations was carried out using molecular markers.
Based on the obtained results the following conclusions can be drawn:
1. Significant effect of sites and species as well as some of their
interactions on the extent of variability in most of studied characters.
The White Nile was the most favourable for development of most
characters, in which Jebel Aulia was the most conducive site.
2. Out of 12 characters, seven showed high values of correlation
coefficient indicating that these characters are more stable over the
different environments. Stable correlation coefficient with high value
can be applied as indictor for selection of these characters.
3. Genetic variation detected using the molecular markers and different
patterns of diversity were obtained among the populations as well as
within each population in the different sites.
4. A relatively high level of polymorphism and genetic diversity within and
between the studied Tilapia spp. were detected, a comparatively high
overall interspecies pairwise divergence.
5. O. niloticus and S. galilaeus populations from Shendi and Ad Damazin
exhibited the highest similarities value (0.94) and (0.80), respectively,
while the lowest value was detected in Jebel Aulia and Gitaina (0.15)
and (0.06), respectively.
96
6. The morphometric measurements and meristic counts and molecular
analysis confirmed that the population of O niloticus from Al Kalakla is
quite different from other populations.
7. RAPD-PCR could be a useful tool for estimating the genetic variability
and degree of similarity among fish species and subspecies.
Recommendations:
The study recommended the following:
1. Increase genetic variation within brood stocks with high similarity
coefficient value by outcrossing with other breeds with lower similarity
coefficient index.
2. Genetic assessment of Tilapias should be carried out prior to
impoundment and culture.
3. Further studies with other molecular methodologies are essential
to clarify and confirm genetic relationships among fish species derived
from morphometric characters and RAPDs.
97
References:
A.O.A.C. (1990). Official Methods of Analysis Association of Official
Analytical Chemi_Washigton D.C., USA, 1094pp.
Abu Gideiri, Y. B. (1984). Fishes of the Sudan, Khartoum, University Press,
Democratic Republic of Sudan, 122 p.
Abu Gideiri, Y. B.; Ali, M. E. and Mahmoud, Z. N. (2004). Review of
Research on the Nile Bulti, Oreochromis niloticus (Trewavas) in Sudan.
Ministry of Science and Technology, Fisheries Research Center. pp. 6-16.
Abumourod, I. M. K.; Sofy H. I. and Mohamed, L. A. (2008). Karyotypic
diversity of some tilapia species, Nature and Science, 6 (1).
Agnese, J.; Gourene, B.; Abban, E. K. and Fermon Y. (1997). Genetic
differentiation among natural populations of the Nile tilapia Oreochromis
niloticus (Teleostei Cichlidae). Heredity. 79:88-96.
Agnese, J.; Gourene, B.; Owino, J.; Pouyaud, L. and Aman, R. (1999). Genetic
characterization of a pure relict population of Oreochromis esculentus, an
endangered tilapia. Journal of Fish Biology 54:1119-1123.
Allendorf, F. W. (1988). Conservation biology of fishes. Conserv. Biol. 2:145–
148.
Ambak, M. A.; Abol-Munafi, A. B.; Patimah, I. and Bui, M. T. (2006).
Genetic Variation of Snakehead Fish (Channastriata) Populations Using
Random Amplified Polymorphic DNA. Biotechnology, 5:104-110.
AnvariFar, H.; Farahmand, H.; Silva, D. M.; Bastos, R. P. and AnvariFar, H.
(2013). Fourteen years after the Shahid-Rajae dam construction: an evaluation
of morphometric and genetic differentiation between isolated up-and
downstream populations of Capoeta capoeta gracilis (Pisces: Cyprinidae) in
the Tajan River of Iran. GMR, 12:3 465–3478.
98
Appleyard, A. and Mather, B. (2000). Investigation in to the mode of
inheritance of allozyme and random amplified polymorphic DNA markers in
Tilapia Oreochromis mossambicus (Peters). Aquaculture Research, 5(31):435-
445.
Babiker, M. M. and El Hakeem, O. H. (1979). Changes in blood characteristics
and constituents associated with aestivation in the African Lungfishes,
Protopterus annectnus (Owen). Zool. Anz. Jena. 202: 9-16.
Bailey, R. G. (1994). Guide to the fishes of the River Nile in the Republic of
the Sudan. J. Natural History, 28:937-970.
Bardakci, F. and Skibinski, D. O. F. (1994). Application of RAPD technique in
tilapia fish: Species and subspecies identification. Heredity, 73:117-123.
Barel, C. D. N.; Vanoijen, M. J. P.; Wirie, F. and Wirte–Maas, E. L. (1977).
Barlow, G. W. (1961). Causes and significance of morphological variations in
fishes. Syst. Zool. 10:105-117.
Beaumont, A. (1994). Genetics and evolution of aquatic organisms. London:
Chapman and Hall.
Bhassu, S.; Yusoff, K.; Panandam, J. M.; Embong, W. K.; Oyyan, S. and Tan,
S. G. (2004). The genetic structure of Oreochromis spp (Tilapia) populations
in Malaysia as revealed by microsatellite DNA analysis. Biochem. Genet.
42:217-229.
Bhuiyan, A. S. and Biswas, B. (1982). Studies on the morphometry of Puntius
cola (Hamilton-Buchnan) (Cyprinidae; Cypriniformes). University journal of
zoology. Bangladish 1:29-34.
Bielawski, J. P. and Pumo, D. E. (1997). Randomly Amplified Polymorphic
DNA (RAPD) analysis of Atlantic Coast striped bass. Heredity, (78):32-40.
99
Bielawski, J. P.; Noach, K. and Pumo, D. E. (1995). Reproducible
amplification of RAPD markers from vertebrate DNA. Biotechniques, 12: 36-
39.
Blankenship, H. L. and Leber, K. M. (1995). A responsible approach to marine
stock enhancement. American Fisheries Society Symposium 15:167-175.
Bolger, T. and Conolly, P. L. (1989). The selection of suitable indices for the
measurement and analysis condition. Welly online library, 34:171-182.
Boyd, C. E. and Tucker, C. S. (2009). Pond aquaculture water quality
management, Springer international editor, 700 pp.
Brraich, O. S. and Akhter, S. (2015). Morphometric Characters and Meristic
Counts of a Fish, Garra gotyla gotyla (Gray) from Ranjit Sagar Wetland,
situated in the Himalayan foothills, India. Int. Res. J. Biological Sci. Vol.
4(5):66-72.
Cadrin, S. X. (2000). Advances in morphometric identification of fishery
stocks. Rev. Fish Biol. Fish. 10:91–112.
Carvalho, G. R. (1993). Evolutionary aspects of fish distribution: genetic
variability and adaptation. J. Fish Biol. 43:53-73.
Chaklader, M. R.; Muhammad, A. B.; Abu Hanif, A. E.; Ashfaqun, N.; Sultan,
M. and Marina, P. (2016). Morphometric and Meristic Variation of
Endangered Pabda Catfish, Ompok pabdam (Hamilton-Buchanan, 1822) from
Southern Coastal Waters of Bangladesh. J. Zoo., vol. 48:3 681-687.
D'Amato, M. E. and Corach, D. (1996). Genetic diversity of populations of the
freshwater shrimp Macrobrachium borelli (Caridae: Palaemonidae). J. Crustac.
Biol., (16):650-655.
David, S. W. (2001). Populations, species, and consevation genetics.
Encyclopedia of biodiversity, Vol. 4:811-829.
100
De Silva, S. S.; Subasinghe, R. P.; Bartley, D. M. and Lowther, A. (2004).
Tilapias as alien aquatics in Asia and the Pacific: a review. In: FAO Fisheries
Technical Paper, No. 453. FAO, Rome.
Dinesh, K. R.; Lim, T. M.; Chan, W. K. and Phang, V. P. (1993). RAPD
analysis: An efficient method of DNA fingerprinting in fishes. Zool. Sci.,
10:849-854.
Dinesh, K. R.; Lim, T. M.; Chan, W. K. and Phang, V. P. (1996). Genetic
variation inferred from RAPD fingerprinting in the three species of tilapia.
Aquaculture International 4:19-30.
Dioh, W.; Tharreau, D. and Lebrun, M.H. (1997). RAPD based screening of
genomic libraries for positional cloning. Nucleic Acid Res., 25:5130-5131.
Domingos, T. J.; Moraes, L. N.; Moresco R. M.; Margarido, V. P. and Venere,
P. C. (2014). Genetic and morphological diversity of Moenkhausia oligolepis
(Characiformes: Characidae) populations in the tributaries of the Araguaia
River, Brazil: implications for taxonomy and conservation. Genet. Mol. Res.
13 (3): 7979-7991.
Ebraheem, H. A. H. (2012). Morphometrics, Meristics and Molecular
Characterization of Oreochromis niloticus, Sarotherodon galilaeus and Tilapia
zilli (Cichlidae) from Kosti, Sennar, Khashm El Girba and Al Sabloga. Ph. D.
Thesis, Department of Zoology, Faculty of Science, University of Khartoum.
Eknath, A. E.; Tayamen, M. M.; Palada-de Vera, M. S.; et al. (1993). Genetic
improvement of farmed tilapias: The growth performance of eight strains of
Oreochromis niloticus tested in different farm environments. Aquaculture
111(1-4):171-188.
El Sayed, B. B. (1985). Studies on morphometric measurements and meristic
counts in Eutropius niloticus B. Sc. (Honours) Dissertation, Department of
Zoology, Faculty of Science, University of Khartoum.
101
Elo, K.; Ivanoff, S.; Vuorinen, J. A. and Piironen, J. (1971). Inheritance of
RAPD markers and detection of interspecific hybridization with brown trout
and Atlantic salmon. Aquaculture, 152:55-65.
El-Sayed, A. F. M. (2006). Tilapia Culture; CABI: Cambridge, M A, USA.
Esguicero, A. L. H. and Arcifa, S. A. (2010). Fragmentation of a Neotropical
migratory fish population by a century-old dam. Hydrobiologia, 638:41–53.
FAO (2010). State of World Fisheries and Aquaculture, World Review of
Fisheries and Aquaculture, Rome, Italy.
FAO (2016). State of World Fisheries and Aquaculture, World Review of
Fisheries and Aquaculture, Rome, Italy.
Fitzsimmons, K. (2000). Tilapia: the most important aquaculture species of the
21st century. In: Fitzsimmons, K., Carvalho, F. J. (Eds.), Tilapia Aquaculture in
the 21st Century. Proceedings from the Fifth International Symposium on
Tilapia in Aquaculture, vol. 1. Ministry of Agriculture, Rio de Janeiro, Brazil,
pp. 3– 10.
Fitzsimmons, K. (2010). Potential to increase global tilapia production. In
Global Outlook for Aquaculture Leadership; GOAL Conference: Kuala
Lumpur, Malaysia.
Flos, R.; Reig, L.; Oca, J. and Ginovart, M. (2002). In flunces of marketing
and different land based systems on gilthead sea bream (Sparusaurata) quality.
Aquact. Int. 10:189-206.
Fouzi, A. M.; Khogali, F. A.; Asaad, H. M.; Obany, O. D. and Mohammed, A.
A. (2016). Body weight characteristics and chemical composition of Nile
tilapia Oreochromis niloticus collected from three different Sudanese dams.
International Journal of Fisheries and Aquatic Studies 4(5):507-510.
Frankham, R. J.; Balluo, D. and Briscoe, D. A. (2002). Introduction to
conservation genetics. Cambridge University.
102
Friedman, S. A. S. and Wainwright, P. C. 2015. How predation shaped fish:
the impact of fin spines on body form evolution across teleosts. Proc. R.
Soc.
Fritzch, P. and Rieseberg, L. H. (1996). The use of Random Amplified
Polymorphic DNA (RAPD) in Conservation Genetics. In: Molecular Genetic
Approaches in Conservation, Smith, T.B. and R.K. Wayne (Eds.). Oxford
University Press, New York, USA. pp: 54-73.
Fuerst, P. A.; Mwanja, W. W. and Kaufman, L. (2000). The genetic history of
introduced Nile Tilapia of Lake Vectoria (Uganda E-Africa): The population
structure of Oreochromis niloticus (Pisces: Cichlidae) revealed by DNA
microsatellite markers. Proceeding of the Fifth International Symposium on
Tilapia in Aquaculture, Vol. 1, Ministry of Agriculture, Rio de Janeiro, Brazil.
Garcia de Leon, F. J.; Chikhi, I. and Bonhomme, F. (1997). Microsatelllite
polymorphism and population subdivition in natural population of European
sea bass. Mol. Ecoli. 6:51-62.
George A. (2012). Princple of plant genetic and breeding, second edition,
books in google play, John willey and sons.
Gjedrem, T. (2000). Genetic improvement of cold-water species. Aquaculture
Research. 31:25–33.
Gomez, C. O. and Gomez, A. A. (2010). Statistical procedures for Agriculture
Research. 2nd
. ed. John Wiley and Sons Inc., New York.
Haddon, M. and Willis, T. J. (1995). Morphometric and Meristic comparison
of orange roughy) Hoplosethus atlanticus: Trachichthyidae) from the Puysegur
Bank and Lord Howe Rise, New Zealand and its implications for stock
structure. Mar. Biol. 123:19-27.
103
Hallerman, E. M. (2003). Quantitative genetics. In: Hallerman, E. M. (Ed.),
Population Genetics: Principles and Applications for Fisheries Scientists.
American Fisheries Society, Bethesda, MD, USA, pp. 261–287.
Hallerman, E. M. and Beckmann, J. S. (1988). DNA-level polymorphism as a
tool in fisheries science. Can. J. Fish. Aquat. Sci., 45:1075-1087.
Hammer, Ø.; Harper, D. A.T., Rayan, P. D. (2001). Paleontological statistics
software package for education and data analysis. PalaeontologiaElectrica 4
(1):9.
Harris, A.; Biegers, S.; Soylw, R. W. and Wright, J. M. (1991). DNA
fingerprinting of tilapia, Oreochromis niloticus and its applications to
aquaculture genetics. Aquaculture, 92:157-163.
Hassanien, A. H.; Elnady, M.; Obeida, A. and Hania, I. (2004). Genetic
diversity of Nile Tilapia populations revealed by randomly amplified
polymorphic DNA (RAPD). Aquaculture Res. 35:587-593.
Hassanien, H. A. and Gilbey, J. (2005). Genetic diversity and differentiation of
Nile tilapia (Oreochromis niloticus) revealed by DNA microsatellites.
Aquaculture Research 36 (14):1450–1457.
Heist, E. J. and Gold, J. R. (1999). Genetic identification of sharks in the U.S.
Atlantic large coastal shark fisheries. Fish. Bull., 97:53-61.
Hershberger, W. K.; Myers, J. M.; Iwamoto, R. N.; Mcauley, W. C. and
Saxton, A. M. (1990). Genetic changes in the growth of Coho Salmon
(Oncorhynchus kisutch) in marine net-pens, produced by ten years of selection.
Aquaculture, Amsterdam 85:187-197.
Hesham, A. H. and John, G. (2005). Genetic diversity and differentiation of
Nile tilapia (Oreochromis niloticus) revealed by DNA, Microsatellites
Aquaculture Research. 36:1450-1457.
104
Hulata, G. (2001). Genetic manipulations in aquaculture: a review of stock
improvement by classical and modern technologies. Genetica (111):155–173.
Idris, M. A. and Mahmoud, Z. N. (2001). Study on morphometric
measurements and meristic counts on Lebeo niloticus (Forskal. 1775). Sudan
Journal of Natural Science. 1:91-108.
Iturra, P.; Medrano, J. F.; Bagley, M.; Lam, N.; Vergara, N. and Marin, J. C.
(1998). Identification of sex chromosome molecular markers using RAPDs and
fluorescent in situ hybridization in rainbow trout. Genetica, 101:209-213.
Johnson, A. L.; Gates, M. A.; Johnson, M.; Talpot, W. S.; Horne, S.; Baik, K.;
Rude, S.; Wong, J. R. and Postlethwait, J. H. (1996). Centeromere-linkage
analysis and consolidation of the zebra fish genetic map. Genetics 142:1277-
1288.
Jong-Man, Y. (2001). Genetic similarity and difference between common carp
and Israeli carp Cyprinus carpio based on random amplified polymorphic
DNAs analyses. Korean J. Biol. Sci., 5:333-340.
Khallaf, E. A.; Galal, M. and Authman, E. (2003). The biology of O. niloticus
in a polluted: Canal. Ecotoxicol. 12:405-416.
Klug, W. and Cummings, M. R. (1997). Concepts of Genetics. 5th edn.
Prentice Hall, Miami.
Koh, T. L.; Khoo, G.; Fan, L. Q. and Phang, V. P. E. (1999). Genetic diversity
among wild forms and cultivated varieties of Discus (Symphysodon spp) as
revealed by random amplified polymorphic DNA (RAPD) fingerprinting.
Aquaculture, 173:485-497.
Ladewig-de, P. and Schwantes, L. L. (1984). Loci that encode the lactate
dehydrogenase in 23 species belonging to order Cypriniformme, Siluriformes
and perciformes: Adaptive features. Comparative Biochem. Phviol., 77:867-
876.
105
Lind, C. E.; Brummett, R. E. and Ponzoni, R. W. (2014). Exploitation and
conservation of fish genetic resources in Africa: Issues and priorities for
aquaculture development and research. Rev. Aquac. 4:125–141.
Liu, Z. J.; Li, P.; Argue, B. J. and Dunham, R. A. (1999). Random Amplified
polynorphic DNA markers: Usefulness for gene mapping and analysis of
genetic variation of catfish. Aquaculture, 174:59-69.
Lutz, C. G. (2006). Recent directions in genetics. In Tilapia: Biology, Culture,
and Nutrition; Lim, C.E., Webster, C.D., Eds.; Haworth Press: Binghamton,
NY, USA, pp.139–180.
Mair, G. C.; Abucay, J. S.; Beardmore, J. A. and Skibinski, D. O. F. (1995).
Growth performance trials of genetically male (GMT) derived from YY-males
in Oreochromis niloticus L. On-station comparisons with mixed sex and sex
reversed male populations. Aquaculture 137:313-322.
Maltagliati, F.; Domenici, P.; Fosch, C. F.; Cossu, P.; Casu, M. and Castelli, A.
(2003). Small-scale morphological and genetic differentiation in the
Mediterranean killifish, Aphaniusfasciatus Cyprinodontidae, from a coastal
brackish-water pond and an adjacent pool in Northern Sardinia (Italy).
Oceanol. Acta, 26: 111-119.
Mamuris, Z.; Apostolitis, A. P.; Theodorou, A. J. and Triantaphyllidis, C.
(1998). Application of random amplified polymorphic DNA (RAPD) markers
to evaluate intraspecific genetic variation in red mullet Mullusbarbatus. Mar.
Biol., 132:171-178.
McAndrew, B. J. (2000). Evolution, phylogenetic relationships and
biogeography. In Tilapias: Biology and Exploitation; Beveridge, M.C.M.;
McAndrew, B. J., Eds.; Kluwer Academic: Dordrecht, the Netherlands; pp. 1–
32.
106
Meyer, A. (1993). Evolution of mt-DNA in Fishes. In Biochemistry and
Molecular Biology of Fishes. Amslerdom. Elsevier, pp: 1-38.
Mickett, K.; Morton, C.; Feng, J.; Simmons, L, P.; Cao, M.; Dunham, D.; Cao,
R. A. and Liu, Z. J (2003). Assessing genetic diversity of domestic populations
of channel catfish (Ictalurus punctatus) in Alabama using AFLP markers.
Aquaculture 228:91-105.
Mills, C. (2004). The Theory of Evolution: What it is, where it came from and
why it Works. John Wiley and Sons, New Jersey.
Misra, R. K. and Carscadden, J. E. (1987). A multivariate analysis of
morphometrics to detect differences in populations of capelin
(Mallotusvillosus). J. Cons. Int. Expl. Mer. 43:99-106.
Munasinghe, D. H. N and Thushari, G. G. N. (2010). Analysis of
morphological variation of four populations of Macrobracium rosenbergii
(Crustacea: Decapoda) in Sri Lanka. Cey. J Sci. Biol. Sci. 39:53-60.
Murta, A. G. (2000). Morphological variation of horse mackerel (Trachurus
trachurus) in the Iberian and North African Atlantic: implications for stock
identification. J. Mar. Sci. 57:1240-1248.
Mwanja, W.; Booton, G. C.; Kaufman, L.; Chandler. M. and Fuerst, P. (1996).
Population and stock characterization of Lake Victoria Tilapine fishes base on
RAPD marker. Department of Zoology, the Ohio state University 614:292-
4570.
Nei, M. and Li, W. H. (1979). Mathematical model for studying genetic
variation in terms of restriction endonucleases. Proc. Natl. Acad. Sci. USA.,
76:5269-5273.
Nelson, J. S. (2006). Fishes of the world, 4th edn. Wiley, New York.
107
Nlewadim, A. and Omitogun, O. G. (2005). Variation of dorsal fin characters
in hatchery raised hybrids of clariid catfishes. Journal of Sustainable Tropical
Agricultural Research. Vol 15: pp1-9.
Ponzoni, R. W.; Azhar, H.; Saadiah, T. and Norhidayat, K. (2005). Genetic
parameters and response to selection for live weight in the GIFT strain of Nile
Tilapia (Oreochromis niloticus) World Fish Center, Jalan Batu Maung, 11960
BatuMaung, Penang, Malaysia bnational Prawn Fry Production and Research
Center (NAPFRE), Malaysia, Aquaculture 247:203–210.
Ponzoni, R. W.; Nguyen, N. H. and Khaw, H. L. (2007). Investment appraisal
of genetic improvement programs in Nile tilapia (Oreochromis niloticus).
Aquaculture, 269:187–199.
Ponzoni, R. W; N. H. N.; Hooi, L. k.; Norhidayat, k.; Azhar H.; Khairul, R. A.
and Hoong, Y. Y. (2008). Genetic improvement of Nile tilapia (Oreochromis
niloticus) present and future. 8th
International Symposium on Tilapia in
Aquaculture, Cairo, Egypt, 1:33-52.
Ponzoni, R.W.; Nguyen, N. H.; Khaw, H. L.; Hamzah, A.; Bakar, K. R. A.;
Yee, H. Y. (2011). Genetic improvement of Nile tilapia (Oreochromis
niloticus) with special reference to the work conducted by the World fish
Center with the GIFT strain. Rev. Aquac. 3:27–41.
Poulet, N.; Berrebi, P.; Crivelli, A. J.; Lek, S. and Argillier, C. (2004). Genetic
and morphometric variations in the pike perch (Sander lucioperca L.) of a
fragmented delta. Archivfuer Hydrobiologie, 159:531–554.
Rasmussen, R. S. (2001). Quality of farmed salmonids with emphasis on
proximate composition, yield and sensory characteristics. Aquat. Res. 32:
767-786.
Rowena, M.; Romana-Equia, R.; Ikeda, M.; Basiao, Z. U. and Taniguch, N.
(2004). Genetic diversity in farmed Asian Nile and hybrid tilapia stock
108
evaluated from microsatellite and mitochondria DNA analysis. Aquaculture
236:31-150.
Ryman, N. and Laikre, L. (1991). Effects of supportive breeding on the
genetically effective population size. Conservation. Biology 3:325-329.
Saber, V.; Asghar, A.; Hossein, A. and Hamed M. (2014). Morphometric and
meristic characteristics and morphological differentiation among five
populations of Brown Trout Salmo trutta fario (Pisces: Salmonidae) along the
southern Caspian Sea basin Euro J Zool Res, 3(2):56-65.
Sylvia, G.; Morrissey, M.T.; Graham, T. and Garica, S. (1995). Organoleptc
qualities of farmed and wild salmon. J. Aquat. Food Prod. Technol. 4: 51-
64.
Samaee, S. M.; Mojazi-Amiri, B. and Hosseini-Mazinani, S. M. (2006).
Comparison of Capoeta capoeta gracilis (Cyprinidae, Teleostei) populations
in the south Caspian Sea River basin, using morphometric ratios and genetic
markers. Folia Zoologic, 55:323–335.
Samaradivakara, S. P.; Hirimuthugoda1, N. Y. and Gunawardana1, R. H. A.
(2012). Morphological Variation of Four Tilapia Populations in Selected
Reservoirs in Sri Lanka. Tropical Agricultural Research Vol. 23(2):105–116.
El-Zaeem, S. Y.; M. M.; Ahmed, M. M.; El-Sayed, S. and Walid, N. A. (2012).
Flesh quality differentiation of wild and cultured Nile Tilapia. population.
African journal of biotechnology vol. 11(17), pp. 4068-4089.
Saroniya, K. D.; Saksena, N. and Nagpure N. S. (2013).The morphometric and
meristic analysis of some puntius species from central India. Biolife, 1(3):144-
154.
Scapini, F.; Audoglio, M. and Campacci, F. (1999). Variation among natural
populations of Talitrus saltator (Amphipoda): Morphometric analysis,
Crustaceana, 72(7):659-672.
109
Shelton, W. L.; Popma, T. J. (2006). Biology in Tilapia: Biology, Culture, and
Nutrition; Lim, C.E., Webster, C. D., Eds.; Haworth Press: Binghamton, N Y,
USA, 2006; pp 1-49.
Smith, P. J.; Benson, P. G. and McVeagh, S. M. (1997). Comparison of three
genetic methods used for stock discrimination of orange roughy, Hoplostethus
atlanticus: Allozymes, mitochondrial DNA and random amplified
polymorphic DNA. Fish. Bull., 95:800-811.
Sneoks, J. (1994). The Haplochromines (Teleostie, Cichlidae) of Lake Kivu
(East Africa). Ann. Mus. Roy. Afr. Centr. Sc. Zool. 270: 221.
Soufy, H.; Laila, A. M. and Iman, M. K. A. (2011). Deploying RAPD-PCR for
DNA-Fingerprinting of Egyptian Tilapia. Saussurea. (1):pp 32–37.
Standen, E. M. and Lauder, G. V. (2005), Dorsal and anal fin function in
bluegill sunfish Lepomis macrochirus. Three-dimensional kinematics during
proulsion and maneuvering, Journal of experimental biology 208:2753-2763.
Swain, D. P. and Foote C. J. (1999). Stock and chameleons the use of
phenotypic variation in stock identification. Fisheries Research, 43:113–128.
Takagi, M. and Taniguchi, N. (1995). Random amplified polymorphic DNA
(RAPD) for identification of three species of Anguilla, A. japonica, A.
australis and A. bicolor. Fish Sci., 61:884-885.
Tave, D. (1986). A quantitative genetic analysis of 19 phenotypes in Tilapia
nilotica. Copeia. 672-679.
Teichert-Coddington, D.; Popma, T. and Lovshin, L. (1997). Attributes of
tropical pond-cultured fish. In Dynamics of Pond Aquaculture; Egna, H. S.,
Boyd, C. E., Eds.; CRC Press: Boca Raton, FL, USA, 1997; pp.183–198.
Trewavas, E. (1983). Tilapiine fishes of the Genera Sarotheredon,
Oreochromis and Danakilia. British Museum (Natural History), London, UK,
pp. 583.
110
Umoh, I. A.; Nlewadim, A.; Obuba, L. E. and Oguntade, O. R. (2015).
Morphometric and Meristic Characteristics of Hybrid Catfish from Selected
Fish Farms in Southern Nigeria. International Journal of Biotech Trends and
Technology.10:14-19.
Vidalis, K.; Markakis, G. and Tsimenides, N. (1994). Discrimination between
populations of picarel (Spicarasmaris L., 1758) in the Aegean Sea, using
multivariate analysis of phonetic characters. Fish Res. 30:191-197.
White, T. L.; Adams, W. T. and Neale, D. B. (2007). Forest genetics. CAB
ebook, pp 53.
Wilkerson, R. C.; parson, T. J.; Klein, T. A.; Gaffigian, T. V.; Bergo, E. and
Consolin, J. (1993). Diagnosis by random amplified polymorphic DNA
polymeras chain reaction of for cryptic species related to Anopheles
(Nyssorhymchus) albitarsis (Diptera: psychididae). From Paraguay, Argentina
and Barzil. Journal of Medical Entomology, 32:697-704.
Williams, J. G. K.; Kubelik, A. R.; Livak, K. J.; Ratalski, J. A. and Tingey, S.
V. (1990). DNA polymorphisms amplified by arbitrary primers are useful as
genetic markers. Nucleic acids Res., 18:6531-6539.
Wimberger, P. H. (1992). Plasticity of fish body shape, the effects of diet,
development, family and age in two species of Geophagus (Pisces: Cichlidae).
Biol. J. Linn. Soc. 45:197- 218.
Worldfish, (2004). GIFT Technology Manual: An aid to Tilapia selective
breeding. World Fish Center, Jalan Batu Maung, 11960 Batu Maung, Penang,
Malaysia national Prawn Fry Production and Research Center (NAPFRE),
Malaysia.
Wu, L. K.; Kaufman, L. and Fuerest, P. A. (1999). Isolation of microsatellite
marker in Astat chromis alluaudi and their cross-species applications in other
African cichlids. Molecular Ecology, 8:895-906.
111
Yousif, O. M. (2012). Basics of Tilapia culture. Red Sea Press. Vol. 1:19-30.
Yusuf, B. and Ali, O. B. (2009). Morphological Variation among Atlantic
Horse Mackerel, Trachurus trachurus Populations from Turkish Coastal
Waters. Journal of Animal and Veterinary Advances 3:511-517.
112
Appendices
1. Location map of the study areas:
113
2. Similarity matrix between different populations: