Assessment of Length-Weight Relationship and Condition Factor of Nile Tilapia (Oreochromis Niloticus) in Cage and Open Waters in Winam Gulf of L. Victoria, Kenya
Steve Omari Ngodhe* and Okeyo Owuor-JB
Department of Environmental Science, Rongo University, Kenya
Submission: September 03, 2019; Published: November 08, 2019
*Corresponding author: Steve Omari Ngodhe, Department of Environmental Science, Rongo University P.O Box 103-40404, Rongo, Kenya
How to cite this article: Steve Omari Ngodhe, Okeyo Owuor-JB. Assessment of Length-Weight Relationship and Condition Factor of Nile Tilapia
(Oreochromis niloticus) in Cage and Open Waters in Winam Gulf of L. Victoria, Kenya. Int J Environ Sci Nat Res. 2019; 22(3): 556088. DOI: 10.19080/IJESNR.2019.22.556088
The study aimed at investigating the difference in relationship between the Length and Weight together with the Fulton’s condition factor of O. niloticus within the open waters (wild) and cages of the winam gulf of L.Victoria, Kenya. This relationship and the condition factor ‘K’ were determined by taking the total length and weight of fish samples both from the cage and the open waters. The slope “b” of the regression analysis in both habitats revealed a positive allometric growth (3.16 and 3.09) for wild and cage respectively while the value of condition factor (K) for O. niloticus in wild and cage were found to be 1.44±0.1 and 1.38±0.15 respectively. Though O. niloticus performed well both in the wild and cage, there was a significant statistical difference in their health and general wellbeing. This was attributed to ecological differences between the two habitats. The assessment also showed that the culture of this Nile tilapia species in cages within winam gulf of L. Victoria can be economically sustainable if water quality parameters are properly monitored and point and non-point sources of pollution controlled.
Keywords: Length-Weight, Oreochromis niloticus, Wild, Cage, Winam gulf, L. Victoria, Kenya
Information on some of the biological aspects of O. niloticus such as the relationship between the length and weight is very essential while doing a study on fish ecology. According to Morey et al.  the relationships between length and weight is a very powerful tool which can be applied to predict weight of fish from length measurements taken during the stock assessment and monitoring. During various stages in growth, fish can attain various forms of growth according to Riedel et al. . They can either record an isometric growth, negative or positive allometric growth. Isometric growth is whereby the fish does not change the shape of its body as it continues to grow while negative allometric growth shows the fish becomes thinner as its body weight increases as opposed to a positive allometric growth which implies that the fish becomes relatively broader and fatter as its length increases. The relationship between length and weight in any given study is very vital biological study because it shows the change of two equations: growth-in-length and growth in-weight equations, which are very useful in fisheries management such as stock assessment models and it further allows the estimation of biomass from length observations by fisheries managers as stated by Moutopoulos & Stergiou . Arslan et al.  further reported that the value of the regression coefficient b (slope) in the Length-Weight relationship of fish is an important bioindicator in revealing the
amount of food intake and the pattern in which the fish is growing which varies depending on the ecological conditions of the ecosystem.
The condition factor on the other hand according to Blackwell et al.  indicates the degree of well-being of the fish in their ecological niche as shown by length – weight factor. This factor is an indication of different environmental (Biotic and abiotic) and biological factors such as fitness, gonad development and the suitability of the environment with regard to the feeding condition. Higher value of the condition factor shows that the fish is healthy and growing positively. Khallaf et al.  indicated that the condition factor of fish can be influenced by different ecological and biological factors such as stress, sex, season, availability of feeds, and other water quality parameters. Fulton’s condition factor, K, can be calculated from the mathematical equation: K = (W×100)/L3, where, W is the weight (g) of fish and L is the total length (cm) of fish; the factor 100 is normally used to bridge the gap between ‘K’ and the value of one. It assumes isometric growth Cooney & Kwak . In case there is no isometric growth during fish stock assessment and monitoring, which rarely occurs, then K is likely to be different depending on the fish length. Comparison of the condition factor between different species is still a challenge since it’s very difficult to register the same growth pattern which is a necessity for the comparison to be valid. To make comparisons
possible and easier, Le Cren  introduced another aspect i.e. the
relative condition factor, which takes care for the variation in form
or condition with increase in length, and therefore estimates the
deviation of an Individual fish from the mean weight for length in
the respective sample: Kn = W/aLb, where, W is the weight of fish
and aLb is the mean weight predicted from relationship between
the length and weight. , Le Cren  further revealed that the explanation
of the fish condition factor is difficult and vulnerable to
The assessment was done in winam gulf which is an extension
of L. Victoria towards the inland areas of the former Nyanza province
of Kenya (Figure 1). The extension is from East to West at approximately
100km and also from North to South at about 50km.
The gulf’s shoreline covers about 550km. The Gulf is generally
shallow; Hughes & Hughes  recorded a maximum and mean
depth of 68m and 6m respectively (Figure 1). The water temperature
at the surface of the entire gulf range between 23.50C and
29.0°C. Currents which results from wind blowing from inshore
to offshore influence water mixing in the gulf. During the study
by Osumo , Water turbidity ranged between 35 to 155cm and
productivity is limited to the photic zone where photosynthetic
organisms thrive . Fish sampling for both cages and wild was
done between January and September 2018. Cages were lifted
and hand nets used to obtain the caged fish while wild fish were
bought from the fishermen while they are still at the lake fishing.
The team used engine boats to follow the fishermen onshore at
monthly intervals for eight months. A total of 240 samples were
sampled in cages and a similar numbers was also analyzed from
the wild. Excess water from the samples was removed by a serviette
before they were weighed in order to enhance accuracy and
precision Anderson & Gutreuter . The measurements of both
the weight and length were taken at the end of every sampling
session. Weight and length of each individual fish sample was
measured by using a very sensitive weighing balance and a measuring
board respectively. The length was taken distance from the
mouth-tip to the tip end of the tail fin.
The length and weight relationship were analyzed
by using the mathematical model W= aLb as was proposed
by Pauly .
W= Fish weight (gram)
L= Fish length (cm)
a = intercept
b = slope
The above model was used to estimate ‘a’ and ‘b’ values. Isometric
growth pattern usually occurs when the value ‘b’ is three
(3) but when it’s not equal to 3, then it automatically shows another
growth pattern known as allometric, which can either be
positive if ‘b’ is more than 3 or negative if it’s less than 3.
The condition factor ‘K’ which indicates the degree of well-being
of the fish in their ecological system was calculated by using
the model, K = 100W/ Lb according to Gomiero and Braga .
In this study the relationship between length and weight of O.
niloticus in the wild revealed a positive allometric growth where
it recorded a ‘b’ value of 3.16 (Figure 2). In the cages, the same
growth was experienced i.e. positive allometric with a value of
‘b’ being 3.09 (Figure 3). The regression slope b was significantly
different between the wild and cage samples (ANCOVA: F=23.15, p=0.002). On the other hand, the value of K for O. niloticus in both
wild and cage were 1.44±0.1 and 1.38±0.15 respectively (Figure
4). There was also a significant statistical difference in mean ‘K’
values between the wild and cage samples (F=36.05, p=0.001).
Both O. niloticus in the wild and cage showed a positive allometric
growth in winam gulf, L. Victoria with a ‘b’ value of 3.16
and 23.09 respectively. According to Riedel et al.  this implies
that it becomes relatively broader and fatter with the increase in
length. This is also supported by Yongo  who also reported
a positive allometric growth of R. argentea of L. Victoria, Kenya.
However, Bala et al.  reported a negative allometric growth
for Tilapia. zillii species in inland waters recording a ‘b’ value of
2.91. Limuwa et al.  during his study found a negative isometric
growth in Opsaridium microlepis from Linthipe River in Central
Malawi while Imam et al.  just like Bala et al.  also recorded
a negative allometric growth recording a ‘b’ figure in Tilapia.
zillii of 1.53 and 2.5 for rainy and hot seasons respectively while
on the other hand Haruna  figures were 2.7 to 3.2. The values
obtained for O.niloticus from this when compared with other similar
studies shows that it falls within the range obtained by Haruna
 but slightly higher than that obtained by Imam et al. . The
variation in growth pattern could be due to different ecological
parameters during the study periods which comprises of several
biotic and abiotic interactions depending on seasonality.
The mean condition factor for O.niloticus both in wild and cage
was more than 1 with ‘K’ values of 1.44±0.1 and 1.38±0.15 respectively.
Ibrahim et al.  recorded the ‘K’ value of 1.94 for Tilapia.
zillii in brackish water. The K values obtained in both cases were
more than 1 which indicates that the fish was in healthy and biologically
active. In comparison, the ‘K’ value of T. zillii obtained by
Imam et al.  recorded in inland waters ranged from 2.63-3.4 in
hot and cold climate while on the other hand,  values ranged
between 1.6603 to 2.0190 and 1.6354 to 2.134. The variation
which could be as a result of unfavourable physico-chemical water
quality parameters such as temperature in ponds containing
T. zilli which might have been higher due to the small surface area
compared to a gulf which is bigger and therefore most of the heat
from the sun get absorbed by soil and other particles which enters
into the system through run-off. These spatio-temporal differences
in temperature between this study and other studies might
have affected other environmental variables such as dissolved
oxygen, total dissolved solids, pH, conductivity among others and
that is why in the other studies, temperature seemed not to be
within the optimal range for growth of tilapia.
Differences in regression value ‘b’ in the relationship (L-W)
and condition factor value ‘K’ between the wild and cage samples
could be as a result of the shadow effects caused by the cages as
this block the heat from reaching directly into the water surface
of the caged fish and therefore the temperature could have been
lower in cages than in the wild. As stated, earlier temperature
controls other ecological aspects of the habitat apart from the biological
aspects of fish and therefore the difference could be as
a result of ecological differences. In cages, fish have very limited
room to move as the stocking density is higher compared to fish in
the wild which has a whole lake to move. This overcrowding could
also have affected the general condition of the fish as the resources
unlike in the wild were limited. Depth at which fish lives is also
an important aspect which could have resulted into difference in
growth rate and general fish condition in the two habitats. Fish in
the wild feed from the deeper areas which are well aerated, less
polluted and disturbed than the fish from the cages which feed
from very few meters from the shore.
Based on the results obtained from this study, fish health and
well-being can be achieved if water quality parameters are well
managed. This study revealed a positive allometric growth both
in the wild and the cages. The wild fish was better in overall condition
than their caged counterpart and therefore water quality
management must be maintained for maximum growth and yield
in cage culture system in winam gulf. In order to enhance cage culture
in the winam gulf of L. Victoria, Kenya more studies are still
required especially on specific environmental parameters that directly
or indirectly affect the fish-growth, nutrient levels. Information
on nutritional requirement and economic suitability will be
useful to primary stakeholders along the gulf and other investers
who are involved in semi intensive and intensive aquaculture. The
present study had a limited scope as it only focused on O. niloticus
within the Winam gulf. This study therefore recommends that
the future studies should include other species of fish in different
aquatic ecological systems. The study further recommends a longer
study period for assessment of the relationship between the
length and weight together with the condition factors to take care
of seasonality and other environmental variables.
The authors would like to thank the University of Eldoret, Kenya
for provision of laboratory and technical support. We would
also express our gratitude to the national research fund (NRF) for
providing financial support.