Characterization of Nile Tilapia (Oreochromis niloticus) Farming Intensities in Liberia

Abstract

Fish farming is a rapidly growing food sector in developing nations. Liberia is an example of a least developed country with a large population facing high poverty levels. This has led to the adoption of aquaculture as one of the most important strategies for solving malnutrition and food security problems. However, since the introduction of fish farming, fish yields have been persistently low. To address the shortcomings in fish yields in Liberia, a study was conducted to provide information on fish farming intensities, types, and quality of feeds used by farmers in the culture of O. niloticus in Bong, Lofa, Nimba, and Grande Gedeh counties. Using stratified purposive sampling, 120 farmers were interviewed, and their fish feeds were sampled for proximate nutrient analyses. The results demonstrated that fish farming of O. niloticus in Liberia is mostly semi-extensive (81.6%), mainly practiced in paddy, barrage, and earthen ponds. On average, farmers produce 165.7 kg ha⁻¹ of O. niloticus annually, translating to USD 414.25. Farmers use mixed feeding regimes, comprising farmer-made, kitchen waste, and blended commercial feeds. Farmers, on average, spend 43% of their operation cost on feeds, which makes it unsustainable to maintain semi-intensive systems. The main feed ingredients used by Liberian fish farmers are rice bran, wheat bran, corn, palm kernel, and fishmeal. Crude protein levels in feed ingredients are as follows: rice bran (3.7 ± 1.3%), wheat bran (16.4 ± 1.5%), corn (6.3 ± 1.1%), palm kernel cake (14.8 ± 1.4%), and fishmeal (63.8 ± 1.3%). Crude proteins were low in formulated feeds, ranging from 8–15% CP. From this study, poor yields and the slow growth of O. niloticus can be attributed to low-protein diets, rendering farming ventures unprofitable and unsustainable for resource-poor farmers in Liberia.

1. Introduction

The depletion of marine fish stocks and increasing global food insecurity have fueled the rapid growth of aquaculture systems across the world [1,2,3]. Aquaculture, which encompasses the rearing of fish and other aquatic organisms [4], is currently the fastest-growing food sector in the world [5,6], such that in a span of 15 years from the year 2000 to 2015, production rose from 41,724,569.75 to 106,004,183.75 metric tons, with a whopping 154% growth [7]. Despite the impressive growth record, Africa only contributed 2.5% to global production, while the least developed sub-Saharan Africa (SSA) nations contributed less than 1.0% [8]. The latter has a large percentage of the human population, estimated at 960 million, considered malnourished [9,10]. Thus, embracing fish farming in these countries is critical in alleviating hunger and widening the income base and, therefore, achieving economic empowerment [11,12]. Generally, there has been a slow adoption of aquaculture in some parts of the African continent [13]. The poor aquaculture productivity, particularly in the poverty-stricken region, is underscored by several factors, including a lack of policy framework [14], weak supportive structures and infrastructure [11], inadequate aquaculture management skills, and most importantly, poor-quality feeds [15].

Aquaculture enterprises have high input demands, with feeds making up more than 50% of the total expenses in fish farming [16]. For a farmer to strike a significant profit in a shorter time, high-quality and nutritionally balanced feeds are paramount [17]. However, the high cost of quality feeds impedes its accessibility by the low-resource-based fish farmers [18]. Furthermore, the low quality and high cost of feeds make the sector less sustainable for large-scale productions, particularly in rural areas. According to [19], most rural farmers settle for low-quality fish feeds sourced from kitchen waste and agro-industry residues. Such feeds not only retard fish growth, lengthen the time to reach market size, and reduce the resilience of fish to bio-physical stress but also degrade the quality of pond water [20].

O. niloticus is ranked as the primary culture fish species and is preferred by tropical sub-Saharan Africa (SSA) farmers because of its versatility in feeding and fast attainment of market size, particularly with all-male populations [21]. However, it requires feeds of adequate nutritional balance to achieve the target size within a farming season [21]. According to [22], if the pond is sufficiently fertilized, it can sustain the juveniles for up to 80 days of grow-out, after which formulated feeds are needed to promote rapid growth [23]. The low-quality feeds used by farmers have also been shown to contain high antinutritional factors (ANFs), thus reducing the feed conversion rates and inhibiting growth [24].

The problems of slow up-scaling and out-scaling of fish farming are constrained by feeds and inadequate management skills among farmers, which frustrate SSA farmers [25]. The situation is worsened by political and socioeconomic factors, which compound to disadvantage the aquaculture sector, as in the case of Liberia [26]. The country has access to marine fisheries in the Atlantic Ocean. However, several counties are landlocked and rely on fishery products from those with access to the ocean. For decades, Liberia’s population has relied on wild fisheries for their fish protein requirements; however, disruption in supply caused by several factors, among others, civil war, Ebola epidemics, and a decline in wild catches, motivated the adoption of fish farming in landlocked counties to bridge the demand gap and offer high-quality fresh fish to consumers. Despite the multisectoral approach to promoting fish farming, no significant contribution from the sector has been recorded [27]. Among the challenges Liberian fish farmers face, fish feed-related constraints emerge as the main hindrance to optimizing farming activities. Although fish feeds challenges are widely acknowledged, information on the types and quality of feeds utilized by Liberian fish farmers is lacking. Thus, this study was conducted to provide information on the status of O. niloticus farming intensities and the various types and quality of feeds used by farmers in Liberia.

2. Material and Methods

2.1. Description of the Study Area

The survey and collection of commonly used fish feed samples were conducted in the four Liberian counties of Bong, Lofa, Nimba, and Grande Gedeh. The counties were selected due to their landlocked status and have historically been inaccessible to an adequate supply of fresh and quality fish from the coastal regions as shown by study map in Figure 1. Additionally, they also have significant aquaculture activities compared to other inland counties. Other landlocked counties were excluded from this study on the following basis: a small number of farmers from which no adequate comparative sample could be selected and a lack of experienced farmers in O. niloticus farming of more than five years.

The survey of aquaculture activities in the four counties was conducted using a mixed structured questionnaire with the cardinal objective of establishing the levels of aquaculture intensity, the types of fish feed commonly used by farmers in Liberia, and the levels of education of the households of fish farmers. Samples of fish feeds were also collected to determine the proximate composition of the feeds. A clustered purposeful sampling methodology was applied to identify fish farmers who participated in the survey. In each county, participants from youth (18–35 years), women, and adult men engaged in the farming of the O. niloticus were identified. Using the sample size formula by [28,29], $\eta =\frac{p\left(100-p\right)Z^2}{E^2}$, a total sample size of 120 farmers was determined, where

• η is the required sample size;
• p is the percentage occurrence of a state or condition (50);
• E is the maximum percentage error required (0.05);
• Z is the value corresponding to the level of confidence (1.96).

2.2. Feed Sample Collection and Crude Protein Analysis

Fish feed samples of 100 g were collected from each fish farmer in the target counties. The collected samples were mainly obtained from locally made feeds, either containing a single ingredient or compounded using more than one ingredient. Feed samples were dried at 60 °C for 24 h and ground to pass through a 1 mm sieve. The total nitrogen content of the samples was determined using the Kjeldahl method [30], and the results were multiplied by 6.25 to obtain the crude protein content, which was expressed as a percentage. Proximate analysis of the feeds was done at the Kenya Marine and Fisheries Research Institute (KEMFRI) and the University of Eldoret laboratories. Data collected were cleaned, arranged, and subjected to descriptive and nonparametric analysis. Significance comparisons were determined at p = 0.05 using Kruskal–Wallis (KW) and chi–square tests. All analyses were done using IBM Statistical Package for social science version 23.0, and Microsoft Excel 2016.

3. Results

3.1. Fish Farmers’ Characteristics and Demographics

The study demonstrated that fish farming in Liberia is mainly dominated by farmers of more than 35 years of age, representing 81.6% of the farmers in all the four counties studied. The level of aquaculture is mostly semi-intensive, practiced at 79.2% subsistence level. However, a relatively smaller percentage of farmers, 21.8%, practice semi-commercial fish farming. Pond aquaculture constituted 98%, while cage and tank culture contributed 1.2% and 0.8%, respectively. Gender parity was found to be marked, whereby 75.7% of fish farmers were men; however, skewed gender disparities were found dominant among counties, especially in Nimba and Lofa counties, where less than 20% of women actively participated in fish farming, as shown in Figure 2.

3.2. Education Level of Fish Farmers

Less skilled farmers were found to dominate the aquaculture sector, with low basic education and little training in fish farming. The study indicated that 93% of fish farmers had acquired education up to secondary school and below. The literacy level significantly varied among counties, χ2 (12) = 27.48, p < 0.05. Fish farmers residing in Bong and Nimba had acquired a higher level of education and training in aquaculture compared to their counterparts in Lofa and Grand Gedeh, as shown in

Table 1. Percentage of education level of fish farmers in major farming counties of Liberia.

County	No Formal Education	Primary	Secondary	Vocational Training	University
Bong	31.0	37.9	27.6	3.4	0.0
Lofa	13.8	41.4	44.8	0.0	0.0
Grand Gedeh	16.7	46.7	36.7	0.0	0.0
Nimba	3.7	44.4	25.9	22.2	3.7

.

3.3. Type of Pond Systems Adopted and Fish Species Reared

Pond type and size are key factors when evaluating the progress and production of aquaculture systems. The study found that barrage and paddy ponds were extensively adopted in Bong, Lofa, and Nimba, with more than 60% of farmers adopting the two as their preferred pond systems, while in Grand Gedeh, 65.5% preferred pit ponds. Few farmers used concrete ponds, as indicated in

Table 2. Adoption (%) of pond types the Bong, Lofa, Nimba, and Grande Gedeh counties of Liberia.

	Paddy Pond	Barrage Pond	Concrete Pond	Pit Pond
Bong	31.10	35.00	23.80	10.30
Lofa	33.30	25.00	14.30	20.70
Grand Gedeh	2.20	0.00	47.60	65.50
Nimba	33.30	40.00	14.30	3.40
Average size (m2)	1531.1	1503.7	478.6	710.3
Mean ranks	71.89	81.08	25.5	44.07

. The pond sizes also varied significantly using the Kruskal–Wallis (KW) test; χ2 (3) = 42.812, p < 0.001.

Besides rearing O. niloticus, farmers also farmed Tilapia mossambicus, Tilapia zilli, Heterotis niloticus, and Catfish (Clarias gariepinus), as reported by 21.1%, 26.7%, 45.6%, and 6.7% of farmers, respectively. The species were reared under polyculture systems, rice co-culture, or monoculture in semi-intensive systems. Other species included silverfish (Oreochromis niloticus L.), which was integrated into many aquaculture systems in Grand Gedeh County.

Table 3. Fish species contribution (%) to fish farming in Bong, Lofa, Nimba, and Grande Gedeh counties.

Counties	Clarias gariepinus	Tilapia mossambicus	Oreochromis niloticus L.	Tilapia zilli	Heterotis niloticus
Bong	11.5	11.5	0.0	23.1	61.5
Lofa	0.0	26.1	0.0	13.0	60.9
Grand Gedeh	0.0	9.1	31.8	22.7	36.4
Nimba	15.8	42.1	0.0	52.6	15.8

shows different fish types reared by Liberian O. niloticus farmers.

3.4. Influence of Fish Pond Size on Yield of O. niloticus

The relationship between pond size and O. niloticus yield is shown in Figure 3. Pond size positively and significantly correlated (R-squared = 0.72, p = 0.001) to the production of O. niloticus. Big-sized ponds tended to have higher fish yields compared to small ponds.

3.5. Types of Fish Feeds Used by Farmers in the Production of O. niloticus

Liberian fish farming can be categorized as semi-intensive, where fish farmers use on-farm-made feeds, including kitchen wastes and locally made feeds. Imported feeds are mainly sourced from Ghana and Sierra Leon. Locally made fish feed was the main type utilized by 67.2% of farmers, while only 32.8% of farmers used blends of imported feeds in their fish feeds. Fish feed types used by farmers per county is indicated in

Table 4. Types of feeds (%) used in O. niloticus farming in Bong, Lofa, Nimba, and Grande Gedeh counties.

	Type of Feeds Used
County	Local Made	Household Left Overs	Imported
Bong	80	44	60
Lofa	48	56	36
Grand Gedeh	56.7	63.3	70
Nimba	61.9	52.4	57.1

.

The study also demonstrated that farmers used agro-industry-sourced by-products as their main feeds. The feeds were either fed to fish as a single ingredient or blended (formulated). The commonly used feeds included rice bran, palm kernel, wheat bran, corn, fishmeal, and associated blends. Both single and blended feeds had significantly varying crude protein levels in each county investigated. For instance, rice bran, an extensively utilized fish feed ingredient in all the counties under investigation, was found to have an average crude protein content of 3.7%, 4.0%, 2.9%, and 2.3% in Nimba, Bong, Grand Gedeh, and Lofa, respectively. Other feeds collected from the farmers and their respective %CP are indicated in

Table 5. Levels of crude protein (%) in fish feeds.

Feed Type	Feed Ingredient	Mean % Crude Protein (Mean ± Standard Deviation)	Range
Single-ingredient feeds	Rice bran	3.7 ± 1.3	2.3–5.7
	Wheat bran	16.4 ± 1.5	14.0–18.1
	Corn	6.3 ± 1.1	5.0–6.8
	Palm kernel cake	14.8 ± 1.4	12.9–16.4
	Fishmeal	63.85 ± 1.3	62.5–65.4
Blended feeds	Ricebran + Soybean	8.264 ± 5.4	3.4–16.4
	Ricebran + Cowpea	9.45 ± 3.9	4.6–14.2
	Ricebran + Corn	6.99 ± 2.6	4.4–11.3
	Ricebran + Fishmeal	15.27 ± 10.6	5.1–32.2
	Ricebran + Palm kernel cake + Fishmeal	19.34 ± 7.8	10.2–28.3

.

3.6. Fish Feeding Challenges

The study identified high cost as the major constraint to the use of high-quality commercial fish feeds. Despite farmers adopting extensive and semi-intensive systems, feeds still accounted for 42.98% of total input costs. In addition to the high cost of quality feeds, the spread of disease and pollution of fish environments were ranked by 18.3% and 31.3%, respectively, by farmers.

4. Discussion

4.1. Fish Farmer Characteristics

The results presented herein demonstrate low education levels among farmers in the fish farming sector in Liberia. These findings are expected as the country has the lowest literacy levels in Africa, attributed to the long period of war that disrupted and decimated the education system for more than 14 years from 1989 to 2003. According to [31], the average literacy in Liberia as of 2020 was 48.3%, and the value dropped down to an average of 4% for the rural population with upper secondary school level. These results indicate that the fish farming sector is dominated by farmers who have attained primary or secondary education. O. niloticus farming is also dominated by mature people of more than 35 years of age, which is explainable by the high resource and time demands required by the venture. Young Liberians’ have not accumulated enough resources to invest in businesses, including fish farming. Similar observations were made by [32]. They demonstrated that fish farming is an expensive undertaking requiring surmountable resources and high-level management skills to operate, which many youths in developing countries lack. On the other hand, mature or older farmers adopt fish farming as their old age investment, as reported by [33]. Moreover, older farmers are in a better position to access bank financing compared to the youth.

4.2. Pond Characteristics and Influence on O. niloticus Production

The pond fish culture is the main O. niloticus mode of farming in Liberia, and this type of aquaculture is common in other sub-Saharan countries [12,34]. The current study established that the adoption of ponds varied by Counties. Nimba, Bong, and Lofa counties use large-sized semi-intensive earthen pond types, including barrage and paddy ponds. In contrast, Grand Gedeh O. niloticus farmers have embraced small pond farming mostly in concrete and pit ponds. The variation in types of ponds adopted across the counties could be explained by the fact that fish farming in Liberia originated in the former three counties. Hence, farmers settled for multipurpose, big-sized ponds that were affordable to construct, as in the case of paddy ponds as found by [35]. One interesting finding revealed by the current study is that O. niloticus yields increased proportionally to the size of the ponds. A possible explanation for this finding is that the size of the pond is essential in regulating water quality, and in small ponds, water deteriorates faster and has a low recovery rate.

Similarly, small ponds have less oxygen available to the fish, hence compromising growth. Big ponds such as Barrage and Paddy ponds offer stable water quality [36], therefore, quality characteristics such as ammonia, dissolved oxygen, and pH are constantly regulated [37]. When well fertilized, the barrage and paddy ponds will have high plankton levels, the primary fish food [34].

4.3. Feed Types, Quality, and Challenges

O. niloticus farming in Liberia is mainly semi-intensive, utilizing locally available agro-industry waste products such as rice bran. More than 60% of farmers in each county depend on the by-products of milling as the primary feed for their fish, and this dependency is influenced by cost. For instance, brans of different cereals are cheap and easily accessible to farmers, increasing their usage. Refs. [2,11] reported that more than 80% of fish farmers rely on locally sourced feeds dominated by cereal brans. O. niloticus farmers also use imported feeds to complement the locally sourced feeds. More than 40% of farmers in each county blend imported feed with the locally sourced products, surpassing the use of locally sourced feeds in some counties. The findings are supported by findings by [16], who found that fish farmers in Benin highly depended on imported feeds because of the insufficient supply of feeds by the local system. The results indicated that, on average, all agro-industry cereal brans and other plant-based by-products utilized by farmers are significantly lower in crude protein compared to findings by [38], who reported 9.3%, 13.1%, and 15.5% of crude protein in rice bran, maize bran, and palm kernel, respectively. These values are three times higher than those found in the present study. The low quality of feeds in Liberia can be attributed to adulterations, which include the addition of sand and other nutritionally poor materials [11,38]. The fish feed industry in Liberia is poorly developed. Currently, no industry is engaged in manufacturing commercial fish feeds in the country. Imported feeds are very expensive, which hinders their use in Liberia; as [39] explained, imported feeds are highly taxed, hence transferring the cost to the resource-constrained farmers with low purchase capacity.

5. Conclusions

The present study demonstrates that O. niloticus farming in Liberia is constrained by farmers’ inadequacies and the poor quality of feeds. The bulk (79%) of the Liberian fish farmers are in semi-intensive subsistence farming.

6. Recommendations

The aquaculture government and nongovernmental organizations in Liberia should strive to improve the quality of fish feeds and introduce best management practices in fish farming through capacity building.