Performance Evaluation of African catfish (Clarias gariepinus) Fed Diets with Varying Dietary Inclusion Levels of Christmas Melon (Laganaria breviflorus) as a Partial Replacement for Wheat Offal

Abstract

This study evaluates the effects of Christmas melon (Laganaria breviflorus)-based diets on the growth and hematology of African catfish (Clarias gariepinus) after a 6 (six)-month feeding trial. A total of 240 C. gariepinus juveniles with an average weight of 10.68 g were procured from the Fisheries and Aquaculture Department Hatchery Unit for the feeding trial. After acclimating for a week (7 days) using 2.00 mm Coppens feed (45% CP) twice per day, the fish samples were randomly distributed into 12 tarpaulin tanks of 4 ft × 4 ft × 4 ft with a 200 L water holding capacity (four (4) different treatments presented in triplicate). Twenty (20) fish per tank were fed twice daily with the compounded feed with varying dietary inclusion levels of Christmas melon (0% (control), 5%, 10% and 15%). The weights and lengths of the sampled fish were measured biweekly to determine the growth performance, while hematological parameters, such as the packed cell volume, erythrocytes, hemoglobin, and leucocytes were determined midway through and at end of the feeding trial. The data collected were analyzed using ANOVA, and the results revealed the optimum growth and nutrient utilization and hematological and serum biochemical parameters of C. gariepinus in T3. The length–weight relationship results revealed that the fish exhibited an isometric growth pattern with B-values above 3 across the treatments. In conclusion, the results obtained in this study revealed that Christmas melon (L. breviflorus) could replace wheat offal by up to 10% in the diet of C. gariepinus without negative effects on the obtained optimal growth performance, hematological parameters, or serum biochemistry.

1. Introduction

An excellent diet ought to support maximum and superior health, including well-being and a strong immune system [1]. Protein for the common human has been identified as an essential nutrient to ensure good health [2]. In addition to producing cash and revenue, the aquaculture industry serves as the world’s main source of protein [3].

Clarias gariepinus, commonly known as the African catfish, is a popular species in aquaculture due to its fast growth and ability to tolerate a wide range of environmental conditions [4,5,6]. Its growth performance can vary based on several factors, including water quality, temperature, feeding practices, and management techniques [7]. This fish species has the potential for significant size and weight gain in a relatively short period [8]. Also, with proper feeding management, African catfish achieves feed conversion ratio (FCR) values of around 1.5 to 2.0 [9]. The survival rate is another important indicator of the health and adaptability of fish in their given farming conditions [6]. African catfish generally have a good survival rate, and under proper management, survival rates of 80% to 90% or even higher can be achieved [5].

Although numerous advantages have been attributed to the culture of C. gariepinus, a primary obstacle has hindered its increased production and sustainability. This is a result of the over-reliance on fishmeal and antibiotics, the two most costly components of the fish diet [3,4]. In a bid to address this challenge, numerous alternatives have been adopted to cut down the use of conventional ingredients, such as fishmeal, soyabean, and wheat offal, as well as the use of synthetic drugs. Plant-based ingredients, such as leaves, roots, seeds, and fruits, have been explored, mostly playing dual purposes (nutrient and immune-boosting) in the formulation of fish feed.

Christmas melon (CM) (Lagenaria breviflorus), a unique nutrient-rich plant with various antibiotic, antimicrobial, and antioxidant potentials, could be a dietary component for aquatic organisms. CM has smooth, pale green skin with faint stripes or patches of darker green. The skin is usually thick and protective, housing juicy flesh inside. Beneath the outer skin lies the juicy flesh of CM. It has a succulent texture similar to that of a cantaloupe or honeydew melon. Like many melons, CM contains a central seed cavity filled with seeds that are usually large, flat, and light brown. It can be found in tropical or subtropical areas in Nigeria.

Research has shown that CM meal is highly effective at controlling and preventing Newcastle disease in poultry birds [10], but it has never been experimented in fish. According to proximate analysis, CM contains the following nutritional composition: 9.71% moisture content, 7.38% ash, 19.00% crude fiber, 10.45% ether extract, 5.03% crude protein, and 48.43% nitrogen-free extract. A qualitative phytochemical screening of CM parameters and concentrations in mg/L showed 0.62 tannins++, 2.78 flavonoids++, 0.14 glycosides++, 0.36 phenols++, 0.56 saponins+, and 1.44 alkaloids+ [10].

Christmas melon, as a potential nutrient source, tends to influence the growth rate, weight gain, and overall size of C. gariepinus. By comparing the growth parameters between fish fed CM-based diets and those on conventional diets, we determined the dietary efficacy of CM in supporting fish growth. Christmas melon-based diets may also influence blood parameters, such as the red blood cell count, white blood cell count, hemoglobin levels, and hematocrit values. Monitoring these parameters can provide insights into the fish’s immune response, oxygen-carrying capacity, and overall health status [11].

Understanding the impact of this novel dietary source on the physiological and molecular aspects of fish health is crucial for sustainable aquaculture practices and fish nutrition [12,13]. This study aims to contribute valuable insights into the effects of CM-based diets on the performance of C. gariepinus.

2. Materials and Methods

2.1. Study Area

This study was carried out at the Teaching and Research Farm of the Department of Fisheries and Aquaculture, Delta State University, Abraka. Abraka lies at the geographical coordinates of 5° 47′ 0° N, 6° 6° 0° E.

A total of 240 fish samples (Juveniles of C. gariepinus) were procured from the Department Hatchery Unit, acclimatized for one week (7 days) at a mean temperature of 28° C, and fed 2 mm conventional aquafeed (Coppens feed) (45% CP).

2.2. Experimental Design

Four (4) different treatments with three replicates were used for the experiment. A total of 12 tarpaulin tanks measuring 1.2 m × 1.2 m × 1.2 m with a 200 L capacity of water contained twenty (20) fish per tank. Prior to the experiment starting, all fish were deprived for a full day in order to boost their hunger and remove weight variations caused by food remnants in their stomachs.

For each treatment, three different compounded diets with CM at varying dietary inclusion levels (5%, 10%, and 15%) and a control diet (0%) were fed to the fish. The fish were fed twice daily, at 7:00 a.m. and 6:00 p.m., with 5% biomass of compounded feed for six months (December 2023 to June 2024). The feeds were gradually introduced to avoid overfeeding (feed wastage), and this measurement was used to regulate the amount of feed given.

2.3. Processing and Proximate Analysis of CM

For this purpose, Christmas melon was harvested from the wild, thoroughly washed, and dried under ambient temperature for 14 days. Afterward, the CM was ground into a fine powder, and its nutritional profile was assessed using proximate analysis [10]. This was also conducted on the formulated feeds and the sampled fish.

2.4. Proximate Analysis of CM

The proximate analysis of CM (

Table 1. Proximate compositions of CM.

Parameters (%)	CM	T1 (Control)	T2	T3	T4
Moisture content	9.71	1.73 + 0.25	1.51 + 0.00	2.23 + 0.25	1.23 + 0.24
Ash	7.38	3.47 + 0.04	6.54 + 0.97	5.18 + 3.20	6.65 + 2.71
Crude fiber	19.00	11.94 + 1.50	9.25 + 3.75	7.15 + 1.15	6.65 + 4.15
Ether extract	10.45	10.01 + 0.11	12.42 + 2.01	18.83 + 8.75	20.75 + 2.25
Crude protein	5.03	51.65 + 4.38	42.02 + 21.01	57.78 + 5.25	32.65 + 13.39
Nitrogen-free extract	48.43	22.21 + 2.21	28.29 + 16.22	8.84 + 1.09	32.09 + 17.77

The proximate analysis determined that CM contains the following nutritional composition: 9.71% moisture content, 7.38% ash, 19.00% crude fiber, 10.45% ether extract, 5.03% crude protein, and 48.43% nitrogen-free extract.

) was performed according to the method of Nwachi [10], as explained below:

The percentages of crude protein, crude fat, crude fiber, moisture content, and ash content were analyzed and calculated using the procedure and formula recommended by Khalili et al. [12].

• Crude Protein

  $$\mathrm{\%}\mathrm{C}\mathrm{r}\mathrm{u}\mathrm{d}\mathrm{e} \mathrm{p}\mathrm{r}\mathrm{o}\mathrm{t}\mathrm{e}\mathrm{i}\mathrm{n}=\mathrm{\%}\mathrm{N}\times 6.25.$$
  where
  N—nitrogen;

2.

Crude Fat

$$\mathrm{\%}\mathrm{C}\mathrm{r}\mathrm{u}\mathrm{d}\mathrm{e} \mathrm{f}\mathrm{a}\mathrm{t}={\displaystyle \frac{\mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{f}\mathrm{a}\mathrm{t}}{\mathrm{S}\mathrm{a}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{e} \mathrm{w}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}}}\times 100$$

3.

Crude Fiber

$$\mathrm{\%}\mathrm{C}\mathrm{r}\mathrm{u}\mathrm{d}\mathrm{e} \mathrm{f}\mathrm{i}\mathrm{b}\mathrm{r}\mathrm{e}={\displaystyle \frac{\mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{f}\mathrm{i}\mathrm{l}\mathrm{t}\mathrm{e}\mathrm{r} \mathrm{p}\mathrm{a}\mathrm{p}\mathrm{e}\mathrm{r} \mathrm{a}\mathrm{n}\mathrm{d} \mathrm{f}\mathrm{i}\mathrm{b}\mathrm{e}\mathrm{r}-\mathrm{w}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{o}\mathrm{n}\mathrm{l}\mathrm{y} \mathrm{f}\mathrm{i}\mathrm{l}\mathrm{t}\mathrm{e}\mathrm{r} \mathrm{p}\mathrm{a}\mathrm{p}\mathrm{e}\mathrm{r}}{\mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{s}\mathrm{a}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{e}}}\times 100$$

4.

Moisture Content

$$\mathrm{\%}\mathrm{m}\mathrm{o}\mathrm{i}\mathrm{s}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{e}={\displaystyle \frac{\mathrm{L}\mathrm{o}\mathrm{s}\mathrm{s} \mathrm{i}\mathrm{n} \mathrm{w}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}}{\mathrm{S}\mathrm{a}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{e} \mathrm{w}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}}}\times 100$$

5.

Ash Content

$$\mathrm{\%}\mathrm{A}\mathrm{s}\mathrm{h} \mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{n}\mathrm{t}={\displaystyle \frac{\mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{a}\mathrm{s}\mathrm{h}}{\mathrm{S}\mathrm{a}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{e} \mathrm{w}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}}}\times 100$$

2.5. Quantitative Phytochemical Analysis

A phytochemical analysis was carried out to ascertain the quality and quantity of saponins, alkaloids, tannins, flavonoids, glycosides, and phenols, as recommended by Lawal et al. [14].

2.6. Fish Diet Formulation and Processing

Four diets were formulated with varying dietary inclusions of CM meal (0% (control), 5%, 10%, and 15%) to partially replace the equal weight of wheat offal, as shown in

Table 2. Dietary compositions with varying inclusion levels of CM.

Ingredients (%)	T1 (Control)	T2	T3	T4
Maize	18	18	18	18
GNC	10	10	10	10
Fish meal	30	30	30	30
Soyabean	16.3	16.3	16.3	16.3
Wheat offal	14.5	13.77	13.05	12.32
CM	0	0.73	1.45	2.18
Blood meal	5	5	5	5
Palm oil	3	3	3	3
Bone meal	1.5	1.5	1.5	1.5
Oyster shell	1	1	1	1
Vit. premix	0.5	0.5	0.5	0.5
Salt	0.2	0.2	0.2	0.2

.

2.7. Determination of Fish Growth Performance

The weights and lengths of the fish were measured biweekly using an analytical scale in grams (g), while a properly calibrated meter rule was used to measure the length in centimeters (cm). Following the methods illustrated by Oluwalola [8] in terms of percentage weight gain (PWG), survival rate (%/d), specific growth rate (SGR), and feed conversion ratio (FCR), the growth indices were calculated.

Specific growth rate (SGR) [8]:

$$\mathrm{S}\mathrm{G}\mathrm{R}={\displaystyle \frac{\mathrm{L}\mathrm{n} (\mathrm{f}\mathrm{i}\mathrm{n}\mathrm{a}\mathrm{l} \mathrm{w}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t})-\mathrm{L}\mathrm{n} (\mathrm{i}\mathrm{n}\mathrm{i}\mathrm{t}\mathrm{i}\mathrm{a}\mathrm{l} \mathrm{w}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t})}{\mathrm{T}\mathrm{i}\mathrm{m}\mathrm{e} \mathrm{i}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{r}\mathrm{v}\mathrm{a}\mathrm{l} \mathrm{i}\mathrm{n} \mathrm{d}\mathrm{a}\mathrm{y}\mathrm{s}/\mathrm{d}\mathrm{a}\mathrm{y}\mathrm{s} \mathrm{o}\mathrm{f} \mathrm{f}\mathrm{e}\mathrm{e}\mathrm{d}\mathrm{i}\mathrm{n}\mathrm{g}}}\times 100$$

where

Ln—natural logarithm.

Weight gain (WG) [5]:

$$\mathrm{W}\mathrm{G}=\mathrm{F}\mathrm{i}\mathrm{n}\mathrm{a}\mathrm{l} \mathrm{w}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}-\mathrm{i}\mathrm{n}\mathrm{i}\mathrm{t}\mathrm{i}\mathrm{a}\mathrm{l} \mathrm{w}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}$$

Survival rate (SR) [6]:

$$\mathrm{S}\mathrm{R}={\displaystyle \frac{\mathrm{N}\mathrm{o}. \mathrm{o}\mathrm{f} \mathrm{f}\mathrm{i}\mathrm{s}\mathrm{h} \mathrm{a}\mathrm{t} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{e}\mathrm{n}\mathrm{d} \mathrm{o}\mathrm{f} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{e}\mathrm{x}\mathrm{p}\mathrm{e}\mathrm{r}\mathrm{i}\mathrm{m}\mathrm{e}\mathrm{n}\mathrm{t}}{\mathrm{N}\mathrm{o}. \mathrm{o}\mathrm{f} \mathrm{f}\mathrm{i}\mathrm{s}\mathrm{h} \mathrm{a}\mathrm{t} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{b}\mathrm{e}\mathrm{g}\mathrm{i}\mathrm{n}\mathrm{n}\mathrm{i}\mathrm{n}\mathrm{g} \mathrm{o}\mathrm{f} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{e}\mathrm{x}\mathrm{p}\mathrm{e}\mathrm{r}\mathrm{i}\mathrm{m}\mathrm{e}\mathrm{n}\mathrm{t}}}\times 100$$

The specific growth rate was determined as described by Irabor et al. [5].

$$\mathrm{S}\mathrm{G}\mathrm{R}={\displaystyle \frac{(\mathrm{l}\mathrm{o}\mathrm{g} \mathrm{W}2-\mathrm{l}\mathrm{o}\mathrm{g} \mathrm{W}1)}{\mathrm{C}\mathrm{u}\mathrm{l}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{e}\mathrm{d} \mathrm{p}\mathrm{e}\mathrm{r}\mathrm{i}\mathrm{o}\mathrm{d}}}\times 100$$

where

W1—initial weight;

W2—final weight.

The feed intake was estimated as the addition of the daily mean feed intake of fish in each treatment throughout the experimental duration.

The feed conversion ratio was estimated with the equation below:

$$\mathrm{F}\mathrm{C}\mathrm{R}={\displaystyle \frac{\mathrm{T}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l} \mathrm{f}\mathrm{e}\mathrm{e}\mathrm{d} \mathrm{f}\mathrm{e}\mathrm{d}}{\mathrm{T}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l} \mathrm{w}\mathrm{e}\mathrm{t} \mathrm{w}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{g}\mathrm{a}\mathrm{i}\mathrm{n}\mathrm{e}\mathrm{d}}}$$

The protein efficiency ratio was estimated with following the equation:

$$\mathrm{P}\mathrm{E}\mathrm{R}={\displaystyle \frac{\mathrm{W}\mathrm{e}\mathrm{t} \mathrm{w}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{g}\mathrm{a}\mathrm{i}\mathrm{n}\mathrm{e}\mathrm{d} \left(\mathrm{g}\right)}{\mathrm{A}\mathrm{m}\mathrm{o}\mathrm{u}\mathrm{n}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{p}\mathrm{r}\mathrm{o}\mathrm{t}\mathrm{e}\mathrm{i}\mathrm{n} \mathrm{f}\mathrm{e}\mathrm{d} \left(\mathrm{g}\right)}}$$

The protein intake was determined as the proportion of protein in the total feed consumed by the fish. PI = Total feed fed × percentage protein fed (40%).

2.8. Length and Weight Relationship

The length-weight relationship was determined using the equation described by Olapade and Conteh [15].

The formula used was as follows [15]:

$$\mathrm{W}=\mathrm{a}{\mathrm{L}}^{\mathrm{b}}$$

where W = the weight of the fish in (g);

L = the total length (TL) of the fish in (cm);

a = the constant;

b = the length exponent.

2.9. Condition Factor (k)

The condition factor was used as a quantitative metric to assess the physiological health of the fish, reflecting their suitability to the experimental environment in terms of growth and body weight. This was examined using the formula described by Irabor et al. [16].

$$\mathrm{K}={\displaystyle \frac{100\times \mathrm{w}}{\mathrm{L}\mathrm{b}}}$$

2.10. Water Quality Determination

Throughout the experiment, physicochemical parameters were monitored in the several experimental tanks using the tools and procedures described by APHA [17] and Ekelemu and Adagha [18].

The total dissolved solid was measured via gravimetric methods, the dissolved oxygen was measured using the titrimetric method, and all analyses were carried out according to [17].

2.11. Determination of Hematological Parameters

Hematological analysis of the red blood cell count, white blood cell count, hemoglobin concentration, and packed cell volume was carried out using the method described by Jain and Schalm [19].

2.12. Packed Cell Volume (PCV)

Using commercially available 75 mm heparin capillary tubes, the PCV (hematocrit) was calculated using Wintrobehaematocrit, filled to the 10 mark, following Wintrobes and Westergran’s procedures as described by Jain and Schalm [19]. This was performed to prevent bubbles. Further measurements were obtained after centrifuging the hematocrit for 30 min at 3000 rpm. Since the readings were not the same, centrifugation was carried out twice until two consecutively similar readings were obtained. To pack the cell on this specific centrifuge, it was taken out of the red cell column, noted, and placed at the bottom of the buffy layer. After dividing the tube into 100 sections, the height of the red cell column was measured and represented as a percentage of the total blood.

PCV = height of red blood cell column x 100% divided by total height of blood column.

2.13. Hemoglobin Estimation

The cyanomet–hemoglobin technique was used to assess the concentration of hemoglobin. A pipette was used to remove 20 µL of blood from the lithium heparinized tube. It was completely mixed with 4.0 mL of Drabkin’s solution by slowly inverting the tube 20 times. Subsequently, the test tube was placed inside a calorimeter for measurement.

The final hemoglobin result was calculated using the formula described by Jain and Schalm [19].

$$\mathrm{H}\mathrm{b}={\displaystyle \frac{\mathrm{T}\times \mathrm{C}\times \mathrm{D}\mathrm{F}\mathrm{G}/100 \mathrm{m}\mathrm{L}}{\mathrm{A}\times 1000}}$$

where

T = the test observation;

A = the standard observation;

C = the concentration of cyanmet–hemoglobin;

DF = the dilution factor.

2.14. Red Blood Cells (Erythrocytes)

For the red blood cell count (RBCC), readily accessible diluents were utilized, such as a solution of formed citrate. To obtain a final solution of 1 in 20 L, the blood sample was diluted by washing 20 µL of blood into a shell back pipette and 4.0 mL of modified Drabkins fluid. Afterward, the diluted sample was combined and put into the hemocytometer. Following the sedimentation of the cells, the number located on 5.5 of the 0.04 mm² area was fixated and counted by charging the Neubauer chamber, examining it under a microscope, and then counting the cells. The number of cells per liter was the final value stated. This was evaluated using the formula described by Adegbesan and Abdulraheen [20].

RBC = Number of cell counted divided by 100

where

N = the number of cells counted;

DF = the dilution factor;

A = the area of the chamber counted;

D = the depth of the chamber.

2.15. White Blood Cells (Leucocytes)

A blood sample of about 20 µL of was extracted using a pipette, placed in a test tube, and combined with 0.38 mL of diluent solution. The red blood cells were destroyed by the produced diluents, which also increased the visibility of the white blood cells.

Other parameters, such as the mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC), were determined using Campbell’s [21] and Schmidt & Schmidt [22] formulas.

2.16. Statistical Analysis of Data

The data obtained in this study are presented graphically as the mean ± standard deviation. Before the data were subjected to one-way ANOVA, the Shapiro–Wilk test was used to ascertain the normality, and Levene’s test was used for the homogeneity of variance. Duncan’s multiple range tests were used in SPSS statistical software (version 22.0 for Windows SPSS Inc., Chicago, IL, USA) to detect the significant differences among the treatments. Differences were considered to be statistically significant at probability levels less than 0.05 (p < 0.05).

3. Results

The results of the quantitative and qualitative phytochemical screening of CM are presented in

Table 3. Quantitative and qualitative phytochemical screening results of CM.

Parameters	Concentration	Concentration mg/L
Tannins	0.62	++
Flavonoids	2.78	++
Glycosides	0.14	++
Phenol	0.36	++
Saponins	0.56	+
Alkaloid	1.44	+

+ Slightly present; ++ moderately present.

.

3.1. Physicochemical Parameters

The results for the physicochemical parameters are presented in

Table 4. Mean monthly variations in physicochemical water parameters among treatments.

Parameters	T1 (Control)	T2	T3	T4
Temperature	28.33 + 0.21 b	28.37 + 0.14 ab	28.41 + 0.15 a	27.83 + 0.72 c
pH	6.42 + 0.07 b	6.48 + 0.07 ab	6.74 + 0.07 a	6.34 + 0.08 c
DO	5.78 + 0.15 d	6.03 + 0.12 b	6.24 + 0.12 a	5.91 + 0.11 c
Conductivity	202.83 + 0.91 b	204.25 + 0.83 a	204.50 + 0.75 a	202.75 + 0.82 b
Transparency	15.33 + 0.33 a	15.08 + 0.25 b	14.33 + 0.23 c	14.58 + 0.29 d

Means along the same row with the same superscripts are not significantly different (p ≤ 0.05).

.

As shown in Table 4, T4 accounted for the lowest mean values of 27.83 ± 0.72 °C, 6.34 ± 0.08 and 202.75 ± 0.82 for temperature, pH, and conductivity, respectively, while T3 accounted for the highest mean values of 28.41 ± 0.15° C, 6.74 ± 0.07, and 204.50 ± 0.75. There were significant differences among the treatments in conductivity, but no significant difference (p > 0.05) among the treatments in pH.

It was revealed for DO that T1 accounted for the lowest mean value of 5.78 ± 0.15, while T3 accounted for the highest mean value of 6.24 ± 0.12. There were significant differences (p > 0.05) among T4, T2, and T1, but no significant difference (p > 0.05) between T1 and T3.

The mean value of 14.33 ± 0.23 for transparency recorded in T3 was the lowest, while T1 had the highest mean value of 15.33 ± 0.33.

The growth performance and feed utilization was evaluated and results for the various parameters were reported as shown in

Table 5. Growth and nutrient utilization parameters of sampled fish.

Parameters	T1 (Control)	T2	T3	T4
FW (g)	1327.30 ± 14.61 c	1367.60 ± 6.67 b	1450.10 ± 57.74 a	1291.60 ± 2.96 d
IW (g)	10.81 ± 0.43 b	10.42 ± 0.20 d	10.62 ± 0.09 c	10.88 ± 0.11 a
WG (g)	1367.49 ± 8.82 b	1357.18 ± 3.33 c	1439.48 ± 3.51 a	1280.72 ± 0.98 d
FTL (cm)	50.59 ± 0.79 b	48.71 ± 0.36 c	51.43 ± 0.49 a	47.63 ± 1.00 d
ITL (cm)	11.07 ± 0.32 b	10.44 ± 0.20 d	11.44 ± 0.32 a	10.79 ± 0.07 c
FSL (cm)	43.89 ± 0.03 b	42.12 ± 0.42 d	43.78 ± 0.12 c	44.02 ± 0.31 a
ISL (cm)	7.68 ± 0.06 a	7.35 ± 0.13 d	7.66 ± 0.03 b	7.41 ± 0.14 c
SGR (%/d)	2.70 ± 0.03 b	2.77 ± 0.03 a	2.71 ± 0.09 b	2.67 ± 0.01 c
TFI (g)	2777.0 ± 3.33 c	2872.0 ± 3.33 b	2954.1 ± 8.82 a	2686.2 ± 6.11 d
FCR	2.35 ± 0.03 a	2.16 ± 0.03 c	1.89 ± 0.03 d	2.26 ± 0.08 b
PER CF SR (%)	0.54 ± 0.04 b 1.25 ± 0.01 d 88.00 ± 0.01 c	0.48 ± 0.01 d 1.26 ± 0.01 c 90.77 ± 2.67 b	0.56 ± 0.01 a 1.28 ± 0.01 b 92.14 ± 0.33 a	0.49 ± 0.01 c 1.39 ± 0.03 a 85.67 ± 0.33 d

FW: final weight; IW: initial weight; WG: weight gained; FTL: final total length; ITL: initial total length; FSL: final standard length; ISL: initial standard length; SGR: specific growth rate; TFI: total feed intake; FCR: feed conversion ratio; PER: protein efficiency ratio; CF: condition factor; SR: survival rate. Means along the same row with the same superscripts are not significantly different (p ≤ 0.05).

.

3.2. Length–Weight Relationship

The results of the length–weight relationship analysis show that the ‘b’ values of C. gariepinus were 3.03 (T2), 3.05 (T1), 3.08 (T3), and 3.06 (T4) respectively. The length–weight relationships and logistic length–weight relationships of C. gariepinus in T1, T2, T3, and T4 are shown in Figure 1, Figure 2, Figure 3 and Figure 4. The relationship between the SL and BW was significant (p < 0.001). The “b” values of 3.03 (T2), 3.05 (T1), 3.08 (T3), and 3.06 (T4) were not negative and indicate the isometric growth pattern of C. gariepinus in the four treatments.

3.3. Haematological Analysis of Sampled Fish

The haematological parameters of the sampled fish was analyzed and results presented in

Table 6. Hematological analysis of sampled fish.

Parameters	T1 (Control)	T2	T3	T4
PCV	28.67 ± 3.84 c	33.00 ± 1.00 b	40.67 ± 0.58 a	33.67 ± 10.97 b
Hemoglobin	9.39 ± 1.08 d	10.99 ± 0.22 c	13.52 ± 0.08 a	12.74 ± 0.94 b
RBC	1.28 ± 0.01 d	1.61 ± 0.47 c	3.35 ± 0.23 a	2.53 ± 0.29 b
WBC	7750.00 ± 3.51 d	14,175.00 ± 3.63 b	17,600.00 ± 3.2 a	12,825.00 ± 1.78 c
MCV	1.54 ± 1.09 c	1.91 ± 3.26 b	2.35 ± 10.97 a	1.32 ± 8.52 d
MCH	51.86 ± 0.30 c	62.66 ± 1.62 b	81.46 ± 0.69 a	33.49 ± 0.1 d
MCHC	33.60 ± 0.12 b	33.37 ± 0.03 d	33.77 ± 0.34 a	33.39 ± 0.01 c

PCV: pack cell volume; RBC: red blood cell; WBC: white blood cell; MCV: mean corpuscular volume; MCH: mean corpuscular hemoglobin; MCHC: mean corpuscular hemoglobin concentration. Means along the same row with the same superscripts are not significantly different (p ≤ 0.05).

.

3.4. PCV

T1 had the lowest mean value (28.67 ± 3.84) while T3 had the highest mean value (40.67 ± 0.58). There were no significant differences (p > 0.05) among the treatments. The results reveal that the PCV increased as the level of CM inclusion increased to 10% replacement and declined at the 15% inclusion level. However, the T4 value recorded was slightly higher than that of T1 but lower than the value recorded in T3. There was no significant (p < 0.05) difference in the PCV between the fish fed control diet and the fish fed the test diets.

3.5. Hemoglobin

T1 recorded the lowest mean value (9.39 ± 1.08), while T3 had the highest mean value (13.52 ± 0.08). There was a significant difference (p > 0.05) between the treatments and the control. As the inclusion level of CM increased, there was a trend of higher hemoglobin levels observed, peaking at the 10% inclusion level (13.52). The hemoglobin level slightly decreased at the 15% inclusion level (12.74), though it remained higher than that of the control.

3.6. RBC

The lowest mean value (1.28 ± 0.01) was observed in T1, while T3 accounted for the highest mean value (3.35 ± 0.23). The RBC count drastically increased to 3.35 in T3, and in T4, the RBC count decreased to 2.53. There were significant differences (p > 0.05) among the treatments.

3.7. WBC

T1 recorded the lowest mean value (7750.00 ± 3.51), while T3 had the highest mean value (17,600.00 ± 3.2). There were significant differences (p > 0.05) among the treatments. In T1, the WBC count stood at 7750 but increased as the inclusion level of CM increased. T2 demonstrated a substantial increase in mean value (14,175), although T3 had a higher mean value (17,600) compared to T1 and T2. However, when the inclusion level was pushed to 15% (T4), a decrease in the mean value (12,825) was observed.

3.8. MCV

In T4, the lowest mean value (1.32 ± 8.52) was recorded, while T3 had the highest mean value (2.35 ± 10.97). There were significant differences (p > 0.05) among the treatments. An increase in MCV from T1 to T2 was observed. Further increases were observed as the dietary inclusion levels increased across the treatments.

3.9. MCH

T4 recorded the lowest mean value (33.49 ± 0.1) while the highest mean value (81.46 ± 0.69) was observed in T3. There was a significant difference (p > 0.05) across treatments. While lower concentrations (5% and 10% inclusion) showed positive effects, higher concentrations (15% inclusion) might have adverse effects on MCH levels.

3.10. MCHC

T1 recorded the lowest mean value (33.60 ± 0.12), while T3 accounted for the highest mean value (33.77 ± 0.34). Although there was no significant difference (p > 0.05) among the treatments, by comparing the values in MCHC among the treatments, it is evident that fluctuations were observed with varying inclusion levels of CM in the diet. Compared to T1, T2 showed a slight decrease in MCHC by 0.23 units, although in T3, there was a notable increase in MCHC by 0.17 units compared to that of T1, while T4 showed a decrease in MCHC by 0.21 units compared to T3.

4. Discussion

The water parameters monitored in this study were all within the acceptable standard, and the results are similar to the findings of Ekelemu and Adagha [18].

The proximate compositions of the diets showed the different crude protein levels at varying dietary inclusion levels of CM. The feeds with varying dietary inclusion levels of CM were well utilized by the fish, which resulted in good fish performance in their weight and length. The growth and nutrient utilization of the sampled fish in this study increased as the inclusion level increased but decreased at a 15% inclusion level. The results obtained in this study confirm those of Mahamoud et al. [23], who fed M. oleifera aqueous extract to Nile tilapia and obtained the same trend. Also, the result of this study agrees with that of Dienye and Olumuji [24], who fed M. oleifera leaf meal to C. gariepinus and recorded a decrease in weight as the inclusion levels exceeded 10%.

The total feed intake in this study decreased as the inclusion level of the test ingredient increased. This aligns with the findings of Omitoyin et al. [25], who fed C. gariepinus and recorded the same trend. Also, the same was observed in a study carried out by Bello [26], where C. gariepinus were fed varying dietary inclusions of M. oleifera leaf meal. However, the results of this study are not in line with those of Irabor et al. [6], who fed M. oleifera to C. gariepinus at a higher dietary inclusion level (20%) and obtained an optimum performance. However, in this study, it can be concluded that the use of CM did not negatively affect feed attractiveness.

The specific growth rate in this study increased as the dietary level of inclusion of CM meal increased, but decreased at a 15% inclusion level of CM meal. The best SGR was obtained in T3. The results obtained in this study confirm those of Mahamoud et al. [23], who recorded the same trends in C. gariepinus and Nile tilapia fed M. Oleifera. However, the feed conversion ratio in this study was optimal at a 10% dietary inclusion level of CM meal. The results of this study follow the same trend as the results obtained by Hekmatpour et al. [27], who fed sesame seed cake to C. gariepinus. However, the results disagree with those of Mahamoud et al. [23], Dienye and Olumuji [24], Siyanbola et al. [25], and Bello [26], who obtained different trends in their works.

The survival rate of the sampled fish in this study follows the same trend as in the works of Mahamoud et al. [23] and Hekmatpour et al. [27], where a higher survival rate was observed as dietary inclusion levels of the test ingredients increased across the treatments. However, a significant reduction was also observed at higher inclusion levels (over 10%).

The results obtained in this study for the length–weight relationship are similar to those of Olapade and Conteh [15], who also obtained isometric growth patterns in their work on the length–weight relationship of C. gariepinus fed diets with the dietary inclusion of Ansophyllea laurina seed meal as a substitute. The results of this study also agree with those of Fagbenro et al. [28], who fed dietary sunflower and sesame to C. gariepinus and observed a similar increase as the level of inclusion increased. The same trends were observed in the studies of James et al. [29], who fed diets enriched with bitter leaf meal to C. gariepinus broodstock, Lawal et al. [14], who fed dietary Bacillus subtilis to C. gariepinus, and Irabor et al. [5], who fed dietary M. oleifera to C. gariepinus. However, the results of this study disagree with those of Adegbesan and Abdulraheen [20], who fed dietary Aspilia africana leaves meal to C. gariepinus and recorded a decrease in the PCV as the inclusion level increased. Wasiu et al. [30] also reported decreased PCV values in C. gariepinus as the dietary inclusion level of fed Jatropha curcas seed meal increased. These results suggest that replacing CM, which is not edible by humans with wheat offal, had no harmful consequence on the blood parameters.

The results obtained in this work contradict those of Anene et al. [31], who recorded a decreased value for Hb in C. gariepinus fed diets with increased dietary inclusion levels of turmeric (Curcuma longa). In the same vein, Adegbesan and Abdulraheen [20] fed dietary Aspilia africana leaves meal to C. gariepinus and recorded decreased Hb values as the dietary inclusion level of A. africana increased. Lawal et al. [14] also recorded a decreased Hb value in C. gariepinus as the dietary inclusion level of Bacillus subtilie increased. Mahamoud et al. [23] reported the same trend of decreased Hb values in Nile tilapia as the dietary inclusion level of M. oleifera aqueous extracts increased. However, the findings of this study agree with those of Irabor et al. [32], who recorded increased Hb values in C. gariepinus as the dietary inclusion level of maize cob meal increased. However, the decrease observed at a 15% dietary inclusion level can be attributed to a possible saturation point or even negative effects at higher inclusion levels, which require further investigation. There were significant (p < 0.05) differences in the hemoglobin levels among the treatments.

The significant increase in RBC suggests a dose-dependent relationship between the CM inclusion levels and RBC production in C. gariepinus. The results of this study agree with those of Lawal et al. [14], who recorded an increase in the RBC value in C. gariepinus as the dietary inclusion level of B. subtilie increased. However, the results of this study disagree with the findings of Adegbesan and Abdulraheen [20], who fed dietary A. africana leaves meal to C. gariepinus and recorded a decreased RBC value as the inclusion level increased. The unexpected decrease in MCV at the 15% inclusion level suggests a possible adverse effect or saturation point, where higher concentrations of CM in the diet might hinder erythropoiesis or disrupt normal hematological parameters. This supports the report of Adegbesan and Abdulraheem [20], who recorded an increased MCV value in C. gariepinus fed increased dietary inclusion levels of A. africana leaves. Dienye and Olumuji [24] also reported an increase in the percentage of MCV in C. gariepinus fed increased dietary inclusion levels of M. oleifera leaf meal. The increased MCH observed in this study suggests the potential toxicological impact of the test ingredient, which agrees with the report of Omeje et al. [33], who fed pawpaw seed (Carica papaya) seed meal to O. niloticus and observed a similar trend. Also, a similar record was observed by Hekmatpour et al. [27], who recorded increased MCH in Cyprinus capio fed increased dietary inclusion levels of sesame seed meal.

The results obtained for other hematological parameters in this study are similar to those observed by Mahamoud et al. [23], who fed M. oleifera aqueous to C. gariepinus, and those of Hekmatpour et al. [27], who fed sesame seed cake to C gariepinus. They also agree with the results of Simon et al. [34], who fed graded dietary levels of boiled sunflower (Helianthus annuus) to C. gariepinus.

In general, the results obtained in this study for the various aspects considered are similar to those of Hekmatpour et al. [27], who fed varying dietary inclusions of sesame seed cake to C. gariepinus.

5. Conclusions

In conclusion, the results obtained from this study reveal that CM (L. breviflorus) can replace wheat offal at an inclusion level of up to 10% in the diet of C. gariepinus, with optimal growth performance and improved hematology, without adversely affecting the physicochemical parameters of the culture medium.

Although this study has established the positive impact of CM on the performance of C. gariepinus at a 10% dietary inclusion level, further investigation is needed to understand other aspects, such as the serum, gene alteration, and organoleptic assessment of the fish.