Post-Harvest Loss of Tuna in Urubo and Lido Fish Landing Centres, Mogadishu, Somalia

Post-Harvest Loss of Tuna in Urubo and Lido Fish Landing Centres, Mogadishu, Somalia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Post-Harvest Loss of Tuna in Urubo and Lido Fish Landing Centres, Mogadishu, Somalia Nor Daud Ibrahim, Dayah Abdi Kulmie This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9498967/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Post-harvest fish losses (PHFL) of tuna at Somalia’s Urubo and Lido landing sites seriously erode food supplies and fishing incomes, as they are major landing sites in the city. This mixed-methods study, combining structured interviews with 369 fishers, processors and traders, FGD, KII, field observations, and spreadsheet analysis, measured the magnitude and categories of loss, traced causal factors, assessed the economic and quality repercussions, and reviewed existing mitigation measures. Four types of loss dominate, including spoilage from delayed processing, physical damage or downgrading owing to size and handling, discarding of by-catches, and operational or market wastage when supply outstrips demand. Prolonged gear-soak times and limited handling knowledge each contribute 28% of total losses; irregular icing accounts for 20%, and limited buyers for surplus catch accounts for 14%. Consequences ripple along the value chain, reducing usable fish by 11%, depressing household earnings by 38%, and causing 17% of products to fail export quality standards. Current countermeasures remain rudimentary, including shading catches from sun and rain (41%), rapid sale while still fresh (52%), and minimal gut-and-chill practice (8%). PHFL thus represents a critical constraint demanding systemic action. The study recommends instituting a national PHFL and fish-quality policy, providing targeted training for all value-chain actors, constructing jetties equipped with reliable ice and cold-storage capacity, enforcing vessel registration with daily catch logs, and strengthening national and international market linkages to stimulate investment and sustainably curb losses and waste, improved governance and community participation are also vital for lasting results at every stage. Tuna value chain Cold-chain management Urubo Lido Fish handling practices Market access Income loss Quality standards Somalia Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1.0 Introduction Somalia, located in East Africa, is bordered by the Indian Ocean to the east, the Red Sea to the northeast, Djibouti to the north, Ethiopia to the northwest, and Kenya to the southwest (Addow et al., 2023) With a coastline of 3,898 km, the second-longest in Africa after Madagascar and an Exclusive Economic Zone (EEZ) covering approximately 1.2 million km², possessing with significant marine resources. Surveys show that the Somali Current marine ecosystem is one of the wealthiest fishing sites in the region due to its highly productive waters and large fish stocks. A significant seasonal upwelling system, in which monsoon winds from May to August deliver cold, nutrient-rich waters to the northeast coast, especially between Ras Asir and Ras Mabber, is primarily responsible for this production. These upwelling zones boost the commercial worth of fisheries by supporting high primary production and biomass(Agulhas, 2011). However, while bigger industrial vessels continue to operate offshore, the same monsoon period, which runs from May to September, brings strong winds and choppy seas that hinder port access for smaller vessels and impede coastal fishing activity. As the result, offshore fleets frequently modify their fishing locations, equipment, or target species, while artisanal fisheries normally run for 220–240 days a year(SNBS, 2025). According to the World Bank (2025), during the 18 pre-war, Somalia population was estimated 12,316,895 (UNFPA, 2014). Out of this population, Somalia’s Fisheries Communities are estimated around 10,000 part-time and full-time fishers, and 60,000 people are involved in different fishing economy including traders, processors, gear and vessel manufacturers(Ministry of Fisheries and Blue Economy, 2023). Somalia’s fisheries sector remains largely small-scale, relying on open fibreglass Volvo boats and skiffs between 2 and 10 meters long, mostly powered by outboard engines, as well as on traditional vessels like Houris (Secure Fisheries, 2021). Commonly harvested commercial marine species include tuna, billfish, groupers, snappers, goatfish, jacks, seabream, sharks, rays and skates (SAPPHIRE, 2019). Inland fisheries primarily occur in the Juba and Shabelle rivers, with catfish and Mullidae among the main species (UNIDO, 2020). According to inland fishing villagers' reports, rivers are frequently home to tilapia. However, these fish are extremely susceptible to recurrent droughts and water scarcity, which have an impact on river levels nationwide. Tilapia populations rise dramatically during times of plentiful water, yet overcrowding may limit the amount of natural food available. Tilapia are thought to be ideal for aquaculture and fish farming due to their versatility and quick growth, providing a workable way to maintain livelihoods when natural water sources diminish. Despite Somalia’s vast marine resources, the fisheries sector contributes only about 2–3% to Somalia's national GDP, reflecting its underdevelopment (Ibrahim et al., 2024). The country’s per capita fish consumption is one of the lowest in Africa, at only 3.3 kg (Hassan et al., 2026). Globally, fish provide approximately 17% of the intake of animal protein, highlighting their importance to food security and nutrition. However, fish postharvest losses (FPHLs) represent a serious challenge. In sub-Saharan Africa, FPHLs are estimated to cause annual financial losses of USD 2–5 billion (Abelti & Teka, 2024). These losses are defined as reductions in quantity, quality, or value of fish at any supply chain stage, undermining incomes, food security, and employment (Racioppo et al., 2021). Fish losses occur in various forms, including quality loss, physical loss, market force loss, and economic loss (Segun et al., 2022). Causes include spoilage, contamination, traditional processing methods, poor storage, insect infestation, and economic or logistical issues (Heidrich et al., 2022; Kruijssen et al., 2020). For instance, India’s fisheries sector alone employs around 14 million people, suffers postharvest losses worth ₹61,000 crores annually, demonstrating the economic scale of the issue (PS et al., 2022). Tuna, in particular, is a highly valued pelagic species, popular globally due to its taste and nutritional profile, rich in protein, omega-3 fatty acids, and essential vitamins (Science, 2018; Solo et al., 2023). Tuna is one of the most widely consumed fishes in Somalia, and is exported. Its high market value and migratory nature necessitate sustainable management and regional cooperation (Biji et al., 2016). Around 5 million tonnes of tuna annually generate USD 41 billion globally, underlining the importance of conservation (Solo et al., 2023). According to Somalia’s latest report to IOTC, national annual catch increased to 76,026 mt (Ministry of Fisheries and Blue Economy, 2025), while studies suggest that the fisheries sector could be valued at between US $ 350–940 million annually with proper management and development (Ministry of Fisheries and Blue Economy, 2023). In Sub-Saharan African Countries, tuna and other fish species experience postharvest quality losses ranging from 5% to 87%, depending on handling, species, weather, and processing. This translates to potential income losses exceeding 32% (Keerthana et al., 2022). In Somalia, postharvest fish losses range from 25% to 40%, primarily due to traditional processing methods (Julien et al., 2024; Abdikarim Gole, 2019, Bank, 2024). According to a model-based assessment from 2015, the overall sustainability predicted Fishery Production Potential for Somali waters is 835,100 MT, which includes 364,000 MT of demersal species, 335,000 MT of pelagic species/sardines, and 136,000 MT of tuna/coastal species (Minstry of Fisheries and Blue Economy, 2023). According to (SNBS, 2025), Somali annual catch productivity is estimated to be between 120,000 and 240,000 metric tons. According to the shores of Somalia has potential of harvesting 380,000 MT to 500,000 MT of fish annually with the Eastern coast compared to Northern coast share 90% of it (UNIDO, 2020). Despite the extent of the problem, limited documentation exists on postharvest losses of tuna fish in major Mogadishu landing sites (Urubo and Lido). Therefore, this study, which is the first of its kind conducted in Mogadishu and Somalia, aimed to assess the types, causes, impacts, and mitigation strategies related to postharvest tuna (fish) losses in these locations. 2.0 LITERATURE REVIEW The decline in fish quantity or quality during harvest, including handling, processing, storage, transportation, and marketing, is known as post-harvest fish loss (PHFL) (Ikbal et al., 2023). Approximately 10 to 12 million of tonnes of fish harvested worldwide are lost or squandered each year, accounting for around 10% to 30% of total fish production annually (Solo et al., 2023). as a result of insufficient cold storage, ineffective transportation, and technical advancements (Lako et al., 2019). The marine fishing industry in Somali IUU fishing alone has a substantial annual loss of $ 306 million due to several issues(Iddrisu & Senior, 2024,Minstry of Fisheries and Blue Economy, 2023). On another hand, the value chain of fisheries, women are essential, particularly in post-harvest operations including processing, marketing, and storage (Addis et al., 2012). Up to 90% of people participating in these activities are women in underdeveloped nations. However, they frequently encounter structural obstacles, such as restricted access to resources and platforms for decision-making, which results in PHFL's disproportionate effects (Obinna et al., 2018). 2.1 Types of Postharvest Losses There are several types of postharvest fish loss, such as physical loss, quality loss due to spoilage, insect infestation and breakage, market loss, operational loss, nutritional loss and etc. But here, we will talk about the three main types of postharvest fish loss. 2.1.1 Physical Loss Fish discarded or eaten by birds, insects, or other creatures are seen as physical losses. It is expressed as a loss of weight or monetary worth. When fish pieces are thrown away or eaten by animals, birds, or insects, it is considered a physical loss. The fish loses weight and value at this point (Ibrahim et al., 2023). Fish are physically lost in the supply chain when they are stolen, dropped, or eaten by wildlife. Additionally, a report claims that unhealthy conditions speed up the rotting process and that carelessly handled fish may suffer physical harm. High temperatures, incorrect processing, storage, and fish supplies are some of the factors that make fish more vulnerable to physical injury. The Tema Fishing Harbour in Ghana was the subject of a study to identify the types of post-harvest fish loss (PHFL) that occur at the landing site and during transit (Kumar and Datta, 2020). 50 fishermen (and carriers) received questionnaires at random. The report found that burritos, herrings, redfish, moonfish, mackerel, and tuna were the most frequently obtained fish. The least likely to spoil was tuna, whereas the most susceptible was herring. Inappropriate fish handling most of the time resulted in physical losses for the fisherman(Akongyuure, 2019) 2.1.2 Quality Loss Fish quality declines are attributed to physical damage or degeneration, yet the fish is still sold, sometimes at a reduced price. It is typically expressed in monetary terms. A decrease in fish quality lowers the fish grade and results in a loss of money. According to (Montojo et al, 2020), the Philippines evaluated the efficacy of ice-chilled carrier boats by estimating quality losses and producing data on the amount of post-harvest losses incurred in landed catch from high sea pockets using the exploratory Fish Loss Assessment Method and the Questionnaire Loss Assessment Method. For carrier boats with chilled ice, the anticipated loss of HSP-1's landing catch was 17.25%. A poor-quality catch represents a loss because it usually sells for less when utilized as raw materials for fishmeal processing, smoking, and canning. There was a positive correlation between fishing time and losses. Fish quality may suffer as a result of the current preservation technique utilized in carrier boats, according to the findings (Lailossa, 2015). 2.1.3 Market Loss Market-force losses occur when oversupply, competition, or gluts force fishers and traders to accept prices below expectations, resulting in a combination of financial, physical, and quality losses (Gyan et al., 2020). Over 35% of the world's fish production is lost post-harvest due to spoilage, damage, poor handling, and weak cold-chain infrastructure; these issues are particularly severe in developing countries. In India, the industry supports 14 million people, while studies from Bangladesh reveal 3–6% volume losses in cultured species and significant financial losses in capture fisheries, with hilsa and shrimp losing up to BDT 77,675 and 33,000 per t, respectively (Rashid & Sarkar, 2020). Handling procedures are crucial; it was observed that high dry-season demand in the Solomon Islands concealed quality deficiencies, and (Litaay et al, 2023) showed that a 1:1 ice-to-fish ratio kept skipjack tuna fresher than 1:2. Although they asked for uniform criteria, quality testing on Tanzanian tunas also confirmed good physico-chemical scores (Lujuo et al., 2022). The degradation of protein and micronutrient value due to spoiling or inadequate processing results in nutritional losses that go beyond obvious and monetary losses, compromising public health and food security (Jeyanthi, 2020). On the other hand, in Somalia, tuna species such as Yellowfin ( Thunnus albacares ), Skipjack ( Katsuwonus pelamis ), and Kawakawa ( Euthynnus affinis ) are cornerstone resources for the artisanal sector. Despite their abundance, there is a critical absence of localized laboratory data regarding the specific post-mortem muscle biochemistry of these fish in the Somali climate. Currently, there are no active bio-monitoring systems or specialized marine laboratories in Somalia dedicated to tracking the enzymatic degradation and metabolic heat generation of tuna during the "gear-soak" and "on-deck" phases. This lack of physiological data makes it difficult to set precise "time-to-ice" standards for Somali fishers. 2.1.5 Causes of Fish Loss During Harvesting and Handling Fish losses during harvesting and handling happen at several crucial points, starting with the actual fishing procedure. Destructive fishing techniques, including using chemicals or explosives, can harm fish, causing them to decay quickly and degrade their quality(UNIDO, 2022). Fish that fall from nets or are thrown away as unwanted bycatch can also be physically lost. Long intervals between placing and retrieving fishing gear might expose the catch to pollutants or heat, which can further deteriorate it. Additionally, on-board handling has a major role in quality degradation(One Earth Future, 2020). If you do not gut, clean, and chill the fish right away, it will be less fresh and have a shorter shelf life. Poor handling techniques, including walking on fish, can cause physical damage that results in bruises and render them unfit for sale(Abelti & Teka, 2024). Physical and qualitative degradation is accelerated when the catch is not landed while the fish are still exposed to high water temperatures. Prolonged conversations during the unloading stage, when fish are lying on the ground in direct sunlight, quickly degrade the quality. The fish become even more contaminated at landing ports due to poor sanitation. Theft while offloading and fish falling from baskets or crates onto the beach are two other instances of physical losses(Torell et al., 2020). Together, these elements drastically lower the amount and caliber of fish that are available for sale and eating. Post-harvest loss (PHL) drivers using fuzzy TOPSIS, identifying the main threats to quality as inadequate icing, fish overload during transportation, and a lack of equipment for small-scale vendors. Despite a study of worldwide preservation techniques by including canning, freezing, drying, salting, fermenting, smoking, and pickling, 10–12 million tons of fish still deteriorate annually as a result of damage and inadequate sanitation, undermining revenue and nutrition. According to Indian traders emphasize cold-chain upgrades by discarding inedible fish pieces that could be turned into fertilizer. Disruptions caused by COVID-19 made PHL worse by violating supply-chain quality standards. There are serious safety risks, discovered that while properly refrigerated fish remained within the 50ppm standard, histamine in Fiji tuna reached 192 ppm at 28°C. Inadequate post-harvest treatment ultimately weakens national food systems, decreases the availability of nutritious fish, and lowers community wages(Sheng & Wang, 2021). Table 1 Causes of Post-Harvest Fish Loss During Harvesting and Handling Stage of Loss Cause Type of Loss When Fishing Use of destructive fishing methods resulting in spoilage of fish Physical, Quality Dropping from the net and being thrown away as bycatch Physical Fish spoils when fishing equipment is left out for extended periods Physical, Quality Handling Fish On-board Not gutting, cleaning, and chilling the fish while on board Quality Physically harming fish like stepping on them Quality Delayed landing after fishing and exposure to high temperatures Physical, Quality Unloading Prolonged haggling while fish is exposed to sun and heat Quality Inadequate sanitation methods leading to pollution Quality Theft at landing site while offloading Physical Fish falling into the beach from baskets or crates Physical Sources : (Kaminski et al., 2020) 2.1.6 Causes of Fish Loss During Marketing, Processing, and Storage Poor handling, insufficient infrastructure, and a small market capacity are the main causes of post-harvest fish losses during marketing, processing, and storage. Fresh fish frequently experience physical and qualitative losses during the marketing stage as a result of inadequate ice utilization and a lack of insulated containers. Seafood can spoil if traders purposefully delay their purchases, particularly if they leave the fish out in the heat(Jeyanthi, 2020). The scarcity of ice, cold storage, and processing equipment exacerbates losses during bumper harvests, when catch is high. Market-related problems like limited consumer spending power, delayed market access, and insufficient marketing information can also lower fish value, resulting in both quality and physical loss as well as financial (market) loss(Pererat et al., 2000). Using damaged or subpar fish at the processing and packing stage causes additional deterioration. Insect infestations and microbiological contamination might result from unhygienic manufacturing conditions. Traditional drying techniques frequently expose fish to infection and harm, such as placing them on unhygienic surfaces like rocks or bare ground. Inadequate packing and excessive smoking because of unregulated smoking temperatures also result in quality and quantity losses(Keerthana et al. 2022). Microbial growth, discoloring chemical reactions, and insect or animal infestations are the most typical causes of storage-related losses. Inadequate or badly maintained storage facilities frequently exacerbate these problems. These issues collectively drastically lower the total value, safety, and usability of fish products at every level of marketing, processing, and storage(Kaminski et al., 2020). Table 2 Causes of Post-Harvest Fish Loss During Marketing, Processing, and Storage Stage of Loss Cause Type of Loss Marketing Fresh Fish Insufficient ice and no insulated container Physical, Quality Traders delaying seafood purchases Quality Limited preservation during bumper catches (ice, processing machines) Physical, Quality Inadequate cold storage and ice Physical, Quality Market timing issues Market Low consumer and buyer purchasing power Market Lack of market info or oversupply Market, Physical, Quality Fish Processing & Packaging Use of already spoiled or poor-quality fish Physical, Quality Unsanitary processing leading to insect infestation Physical, Quality Drying fish on unsanitary surfaces; poor packing techniques Physical, Quality Over-smoking due to improper temperature control Physical, Quality Damaged due to poor packaging materials Physical, Quality Storage Microbial spoilage Quality Chemical discoloration Quality Animal/insect infestations Physical, Quality Inadequate storage facilities Physical, Quality Resource: (Getu et al., 2015) 2.2 Species Composition and Primary Stocks of Tuna in Somalia The Somali Exclusive Economic Zone (EEZ) covers approximately 1.2 million km² and is home to some of the most productive tuna fishing grounds in the Western Indian Ocean. According to the Somalia National Report to the (IOTC, 2025) , the primary species harvested by the artisanal fleet include Yellowfin tuna ( Thunnus albacares ), Skipjack tuna ( Katsuwonus pelamis ), Kawakawa ( Euthynnus affinis ), Bigeye tuna ( Thunnus obesus) , Longtail tuna ( Thunnus tonggol) and Spanish mackerel ( Scomberomorus commerson) , as shown in Table 1 . Table 3 Primary Tuna Stocks in Somalia Scientific Name Common Name Local Importance Thunnus albacares Yellowfin tuna High (Primary export & local market) Katsuwonus pelamis Skipjack tuna High (Abundant in upwelling zones) Euthynnus affinis Kawakawa High (Artisanal sector staple) Thunnus obesus Bigeye tuna Moderate (Pelagic stock) Thunnus tonggol Longtail tuna Common in coastal landings Scomberomorus commerson Spanish mackerel High (Often classified with pelagic) Source: ( IOTC, 2025) 2.3 Annual Tuna Catch in Somalia Over the period, total reported tuna landings increased steadily, rising from approximately 18,000 t in 2019 to nearly 33,000 t in 2024. Yellowfin tuna consistently dominated the catch, accounting for the largest share in all years and showing a particularly sharp increase in 2024. Skipjack tuna remained an important component of the catch, although its contribution fluctuated, with a decline observed in 2023 followed by a recovery in 2024. Bigeye tuna landings increased gradually, indicating either improved targeting, changes in stock availability, or enhanced reporting coverage. Longtail tuna contributed relatively small but stable quantities throughout the period. The pronounced rise in total tuna catch in 2024 should be interpreted cautiously, as it likely reflects a combination of increased fishing effort, improved data collection, and expanded monitoring rather than stock-driven growth alone (Ministry of Fisheries and Blue Economy, 2025). According to the Ministry of Fisheries and Blue Economy 2025, Annual Tuna Catch by Species in Somalia (2019–2024) amount indicated to 18,049 with Yellowfin tuna contributing the largest share at 8,049 (about 44.6%), followed by Skipjack tuna with 6,500 (36.0%). Bigeye tuna accounts for 2,800 (around 15.5%), while Longtail tuna represents the smallest portion at 700 (about 3.9%). Yellowfin and Skipjack tuna dominate the catch, together making up more than 80% of the total, whereas Bigeye and Longtail contribute relatively smaller proportions. See the Fig. 2 of Annual Tuna Catch by Species in Somalia (2019–2024) (Ministry of Fisheries and Blue Economy, 2025 ). See Fig. 1 : Annual Tuna Catch by Species in Somalia (2019–2024) 2.4 Tuna Catch Monthly Trend Analysis The data reveal a significant upward trajectory in tuna catches over the three years, characterized by distinct seasonal volatility. The initial period (late 2018 through 2019) shows relatively low activity, bottoming out in September 2019 with nearly zero catches. However, starting in early 2020, the volume shifted to a higher baseline, with the peak occurring in February 2021 at approximately 98 units. While the graph shows sharp month-to-month fluctuations, likely due to migration patterns or weather conditions, the valleys in 2021 remain higher than the peaks of 2019, suggesting a long-term growth trend or increased fishing efficiency. The data concludes with a strong recovery in late 2021 after a mid-year dip, maintaining the overall elevated volume compared to the start of the study. See Fig. 2 , monthly Tuna catch trends (Ministry of Fisheries and Blue Economy, 2025). 2.5 Spatial Distribution of Fishing Effort in the Somali waters As shown in Fig. 6 below, it illustrates the distribution of fishing activity along the coast of Somalia for the period 2020–2021, showing apparent fishing hours per unit area. Fishing effort is widespread across the Exclusive Economic Zone (EEZ), but it is unevenly distributed, with the highest concentrations observed along the northern coast in the Gulf of Aden and in selected central and southern offshore areas. The map also highlights important maritime boundaries, including the EEZ and 12 and 24 nautical mile coastal buffer zones, which are critical for fisheries management. Additionally, bathymetric data indicate deeper offshore waters where some fishing activity occurs. Overall, the map suggests that fishing pressure is particularly intense in northern and nearshore regions, pointing to key areas that require focused monitoring, control, and sustainable management interventions (Global Fishing Watch, 2021. 2.5 Somali Regional Tuna Catch Species Distribution Analysis (Nov 2018 – Oct 2021 Project Kalluun) Table 2 below shows the frequency of catches across all eight species and highlights where the most fishing activity is occurring. This fish catch data reveals that Bosaso and Berbera are the primary hubs for fishing activity, collectively accounting for over 69% of the total volume with 573 and 568 units, respectively. Yellowfin Tuna (YFT) is the most dominant species across all regions, particularly in Mogadishu, which leads in YFT yield (184) despite having a lower overall species diversity. While Berbera stands out as the most balanced port, recording catches across all eight species, Kismayo shows significantly lower output at only 60 units. Overall, the northern regions maintain a high-volume, diverse catch, while southern regions like Mogadishu are more specialized toward high-value tuna varieties. On the other hand, the species Bigeye Tuna (BET), Albacore (ALB), Bullet Tuna (BLT), and Frigate Tuna (FRI) are missing from the Biomass Series for Comparative Graph (Total Weight in kg) table because the data provided focuses only on the top four species contributing the largest total biomass across all regions: Yellowfin Tuna (YFT), Skipjack Tuna (SKJ), Kawakawa (KAW), and Longtail Tuna (LOT) (Ministry of Fisheries and Blue Economy, 2025). Table 4 Catch Volume (Number of Individuals) Region YFT SKJ KAW LOT BET ALB BLT FRI Total Count Berbera 125 142 110 122 15 42 8 4 568 Bosaso 168 155 105 98 32 10 5 0 573 Mogadishu 184 126 90 45 6 0 0 0 451 Kismayo 22 7 5 21 5 0 0 0 60 TOTAL 499 430 310 286 58 52 13 4 1,652 Figure 5: indicates the map of distribution of fishing catch, by species, for the national fisheries, in the IOTC area of competence (average of the 5 previous years, 2020–2024). 2.6 Tuna Catch Biomass The Table 3 below indicates the total weight for the four-primary species. It highlights the economic and nutritional value of the catch. The Somali fishing sector is defined by a high-volume northern corridor and a high-biomass southern hub. Bosaso and Berbera lead in activity, managing 69% of the total catch count (1,141 fish). However, Mogadishu is the economic heavyweight; despite catching only 27% of the total individuals (451 fish), it produces 40% of the total biomass (4,348.1 kg). This is driven by Yellowfin Tuna (YFT), which is the industry’s anchor, accounting for 50% of total weight (5,420.5 kg) and 30% of total count. While the north, specifically Berbera, shows the highest ecological diversity by harvesting all eight recorded species (including rare Albacore and Frigate tuna), the south specializes in larger, more mature specimens. Mogadishu’s average fish weight is nearly double that of Berbera’s, indicating a specialised deep-water pelagic fishery. Kismayo remains a minor contributor, representing only 3% of total volume (345 kg), focusing primarily on Yellowfin and Longtail tuna. In summary, the northern ports provide diverse regional food security, while the southern ports drive commercial value through high-mass tuna exports (Ministry of Fisheries and Blue Economy, 2025). See the Table 3 below. Table 5 Catch Biomass (Weight in kg) Region YFT SKJ KAW LOT Total Weight (kg) Berbera 1,025.0 852.0 412.5 492.0 2,781.5 Bosaso 1,411.2 930.0 409.5 591.5 3,342.2 Mogadishu 2,822.3 819.0 387.0 319.8 4,348.1 Kismayo 162.0 35.0 25.0 123.0 345.0 TOTAL 5,420.5 2,636.0 1,234.0 1,526.3 10,816.8 3. Export Values of Tuna Fishery Products Tuna and tuna-like species constitute a central pillar of Somalia’s fisheries export economy, with the majority of export earnings derived from minimally processed products. As shown in Fig. 5, exports of fresh or chilled fish generated the highest revenues throughout the period, increasing steadily from USD 1.05 million in 2016 to USD 1.68 million in 2019 and averaging 32% of total fisheries export value. This trend reflects strong regional demand, particularly from Middle Eastern markets, and the limited domestic capacity for large-scale value addition. Exports of frozen fish also exhibited consistent growth, rising from USD 0.89 million in 2016 to USD 1.34 million in 2019 and contributing approximately 25% of total export earnings. Frozen products offer greater flexibility in storage and transport and are increasingly important for stabilising export flows amid infrastructure and cold-chain constraints. Higher value-added products, including fish fillets and meat and prepared or preserved fish, contributed a relatively smaller share of export value, averaging 10% and 4%, respectively. Although these categories showed gradual growth over the study period, their limited contribution highlights structural constraints within Somalia’s fisheries value chain, such as inadequate processing facilities, quality assurance systems, and compliance with international sanitary and phytosanitary standards. The export structure indicates a strong dependence on raw and semi-processed fish products, underscoring the need for targeted investments in processing infrastructure, cold storage, and certification systems to enhance value addition, diversify export products, and increase foreign exchange earnings from tuna and tuna-like fisheries (Ministry of Fisheries and Blue Economy, 2025). 4. Storage Infrastructure and Market Gaps in Mogadishu Fish Markets In Mogadishu, a city of over 4 million people, the storage landscape is characterized by a significant mismatch between demand and modern infrastructure. While large fishing companies exist, they mostly use standard refrigerators, which often fail to maintain the deep-freeze temperatures required for tuna. A few companies possess cold storage, but these are used strategically to store fish during "bumper harvests" and sell back during scarcity; they do not cover the city's total needs. Consequently, small-scale traders rely on fiber-made containers with non-standardized ice, which can only preserve fish for a week or less. This infrastructure gap contributes to post-harvest losses that are estimated to be as high as 60% in some artisanal sectors (Ministry of Fisheries and Blue Economy, 2025). 5. Estimated Annual IUU Fishing in Somali Waters and Economic Value Between 2019 and 2022, Somali waters experienced significant illegal, unreported, and unregulated (IUU) fishing, with an estimated 250 to 520 vessels operating annually. These vessels, both foreign and domestic, primarily targeted tuna, tuna-like species, sharks, reef, shallow-water finfish, and squid using gillnets, trawls, and mixed gear types. Total annual catches from IUU fishing were estimated at 25,940 to 105,920 metric tons, resulting in substantial economic losses. Iran and Yemen accounted for the largest portion of tuna and tuna-like catches, contributing 22,000 to 92,000 metric tons per year, with a potential landed value of $ 44 to $ 184 million annually. Other foreign fleets, including China and Egypt, focused on reef and shallow-water species, while domestic IUU activity in Somalia contributed 500 to 2,000 metric tons per year of reef species. Overall, the estimated total landed value of all IUU fishing in Somali waters ranged from $ 49.9 to $ 203.8 million per year, highlighting the considerable threat it poses to the national fisheries sector and coastal livelihoods (Ministry of Fisheries and Blue Economy, Somalia, 2023). See Table 4 below. Table 6 – estimated annual average IUU fishing (2019 to 2022) in Somali waters Flag State Key Species Gear Vessels Total Catch (mt/year) Value (USD/year) Iran Tuna & tuna-like Gillnet 120–260 12,000–52,000 24M–104M Yemen Tuna, sharks Mixed 100–200 10,000–40,000 20M–80M Egypt Reef finfish Trawl 10–20 1,000–4,000 1M–4M China Squid & finfish Trawl 5–10 500–2,000 0.5M–2M Somalia Reef species Trawl 5–10 500–2,000 0.5M–2M Other Mixed species Mixed 10–20 1,940–5,920 3.9M–11.8M Total 250–520 25,940–105,920 Source: (Ministry of Fisheries and Blue Economy, Somalia, 2023) . Tuna Fisheries Policy Landscape in Somalia Somalia’s tuna fisheries policy landscape is gradually evolving as the Federal Government works to reassert control over marine resources, curb illegal fishing, and align national governance with regional conservation frameworks (Somali Magazine, 2025; World Bank, 2019). Somalia’s large and productive EEZ supports valuable stocks of Yellowfin tuna, Skipjack tuna, Kawakawa, Bigeye tuna, Longtail tuna and Spanish mackerel, which are vital for livelihoods and export potential; however, prolonged weak governance has historically enabled widespread IUU fishing and significant economic losses. The Fisheries Law enacted in 2023 (N0.008 2023) provides the legal foundation for tuna management, including licensing, conservation, and monitoring, control, and surveillance, though implementation has been constrained by limited capacity, fragmented federal–state roles, and weak enforcement (IOTC, 2015). Recent reforms led by the Ministry of Fisheries and Blue Economy have introduced standardized licensing procedures to improve transparency, reduce IUU fishing, and encourage greater participation by Somali entities (MFBE, 2024). Somalia’s engagement with the Indian Ocean Tuna Commission further shapes policy direction, particularly through advocacy for equitable tuna allocation for coastal states (MFBE, 2024). Support from international partners such as FAO and the World Bank has strengthened data systems and institutional capacity (FAO, 2025; World Bank, 2019). While progress has been made toward more structured and internationally aligned tuna governance, challenges remain in enforcement, data quality, and coordination, which must be addressed to ensure sustainable tuna fisheries and maximize economic benefits (FAO, 2025; World Bank, 2019). Table 7 Somalia Tuna Fisheries Policy Landscape Policy Area Key Instruments Relevance to Tuna Fisheries National Vision National Transformation Plan (2025–2029) & Blue Economy Strategy (2023–2027) Positions tuna as key for growth, jobs, and food security Sector Planning Fisheries Master Plan & Food Safety Policy Guides sustainable use, investment, and value chains Legal Framework Fisheries Law No. 008 (2023) Provides legal basis for management, licensing, and conservation Regulations Fisheries Food Safety Regulations (2025) Ensures hygiene, certification, and export compliance MCS Fisheries MCS Strategy Strengthens control, monitoring, and IUU prevention International Alignment Indian Ocean Tuna Commission & Codex Alimentarius Commission Ensures compliance, market access, and global standards 3.0 METHODOLOGY The study was conducted at the Urubo and Lido fish landing centres in Mogadishu, Somalia. Urubo fish landing centre, established in 1990s, locates in Bondere district with coordinates of (Lat 2̊ 1’ 59. 27’ N; Long. 45̊ 20’ 37.74’ E) while Lido fish landing site, founded in the late 1930s by Italian residents in Mogadishu with Lat: 2° 2'20.44"N, long: 45°21'44.60"E locates in the Abdiaziz district southeast of Mogadishu. The study used a survey research approach to look into the many kinds of tuna fish losses at the Urubo and Lido fish landing sites in Mogadishu, as well as their causes, effects, and ways to mitigate them. Field visits were carried out every day (except Fridays), and structured and semi-structured questionnaires, interviews, and direct observations were used as data gathering methods. The study was conducted at two important fish landing sites in Mogadishu that are well-known for their high levels of fish production and commercial activity, Urubo in the Bondere district and Lido in the Abdiaziz district. Fish processors, retail and export fish vendors, and fishermen made up the target population. Through the use of simple random sampling, 369 respondents in all, 300 who answered surveys and 59 who took part in in-depth interviews, were chosen. The Improved Loss Assessment Methodology (ILAM) and Load Tracking (LT) were used to gather data on tuna fish losses at various supply chain stages from both Lido and Urubo fish landing sites. Data analysis was done using Microsoft Excel, producing tables and graphical summaries with descriptive statistics like percentages and frequencies. Through informed consent, participant confidentiality, and obtaining required approvals, ethical issues were upheld. 4.0 RESULTS AND DISCUSSION 4.1 Demographic information About two-thirds (69%) of all responders are Lido, and one-third (31%) are Urubo. A modest absolute movement in Urubo can appear enormous in percentage terms; this imbalance is only a reflection of the sample frame and should be considered when comparing percentages. Although men make up the majority of fishermen's livelihoods (76%) in both locations, women still make up about 25% of the workforce and work in jobs ranging from processing to the fish trade. Urubo's slightly greater male share (77%) than Lido's (75%) is negligible and might be due to work divides specific to each location rather than intentional exclusion. Although the industry is young, it nevertheless has seasoned older workers. About 42% are between the ages of 21 and 30, providing essential labour, and 21% are over 40, maintaining institutional memory. Similar age distributions at the two locations point to comparable employment retention and entry routes. Nearly half of the participants, particularly in Urubo (58%), report only informal education. Because artisanal fisheries mostly rely on implicit, passed-down information, this does not imply a lack of skill. Formal training shortages, however, may make it more difficult to adopt new technology or adhere to export regulations. The industry has a solid knowledge base because about one-third of respondents have more than ten years of experience. However, a fifth are new hires (less than three years old), indicating a high labour turnover rate and chances for focused capacity building. Fishers account for around 69% of the sample, reflecting the survey’s focus. Processors and traders together account for the remaining 31%, highlighting their importance to the value chain. The almost exact occupational division between the locations points to similar market functions. Married people make up the majority (61%) in line with local demographics. Intervention designs should take family responsibilities into account because they can affect risk tolerance and investment capacity. Table 8 Demographic information Variable Category Lido no Lido % Urubo n Urubo % Total % Landing site — 255 69 114 31 100 Sex Male 192 75.3 88 77.2 75.9 Female 63 24.7 26 22.8 24.1 Age (yr) < 20 26 10.2 11 9.6 10.0 21–30 110 43.1 47 41.2 42.5 31–40 63 24.7 34 29.8 26.2 ≥ 40 56 22.0 22 19.3 21.3 Education Informal 116 45.5 66 57.9 49.3 Primary 74 29.0 29 25.4 28.0 University 64 25.1 18 15.8 22.7 Experience 20 yr 92 36.1 44 38.6 37.8 Occupation Fisher 172 67.5 82 71.9 68.6 Processor 49 19.2 16 14.0 17.6 Trader 34 13.3 16 14.0 13.8 Marital status Married 156 61.2 70 61.4 61.0 Single 99 38.8 44 38.6 39.0 4.2.1 Type of Postharvest Tuna Fish Loss recorded As Table 3 indicates, four types of postharvest tuna fish losses were discovered in Lido and Urubo, physical loss is the most common form, making about 33% of losses in Lido and 15% in Urubo. This suggests that handling, storage, and transportation, particularly in Lido, have serious problems. Following this, there is a 20% quality drop in Lido and an 8% loss in Urubo, indicating that Lido has more impaired seafood freshness and marketability. Economic loss is also more common in Lido (10%) than in Urubo (4%), indicating a decline in revenue as a result of poorer product quality and inefficient markets. Despite being the least recorded, market loss nevertheless presents difficulties, with 6% in Lido and 4% in Urubo. Lido experiences more postharvest losses overall in all categories, underscoring the necessity of focused enhancements in market accessibility, cold chain systems, and infrastructure to promote fish value retention and fisher livelihoods. In fisheries, these losses comprise material losses of harvested fish resulting from spoilage, grading, size breakage, bycatch discards, and operational losses(Assefa et al., 2018, Cheke & Ward, 1998). The study which is the first of its kind conducted Mogadishu fish landing sites assessed the types of postharvest loss of fish, more specifically tuna fish, the causes of postharvest losses of tuna fish, impact of postharvest loss of tuna fish in both Lido and Urubo fish landing sites in Mogadishu. The Somali government has made concerted paper work efforts to address gaps in fisheries regulations through the development of key policy documents, including the National Blue Economy Strategy (2023), the Fisheries Law No. 008 (2023), and the Fisheries Master Plan (2023). These initiatives prioritize infrastructure development, capacity building, and regulatory frameworks, fisheries sector investment attractions to minimize losses and improve the value chain. For instance, the Fisheries Law emphasizes sustainable practices, co-management, and fish quality assurance systems​​​. The Master Plan underscores the need for modern fish handling, storage, and national and international market access improvements, while the National Blue Economy Strategy integrates these efforts into a broader framework of sustainable economic growth and environmental stewardship (Somalia Fisheries Law, 2023, Somalia Blue Economy Strategy, 2023, Ministry of Fisheries, 2023 ). In the global context, FAO addressed post-harvest fish loss through the Voluntary Guidelines for Securing Sustainable Small-Scale Fisheries in the Context of Food Security and Poverty Eradication, developed in 2015. These guidelines emphasise minimising post-harvest losses and waste by promoting investments in infrastructure, capacity development, and environmentally sustainable practices. The FAO encouraged the to use best practices for reducing post-harvest fish loss, emphasising the importance of cold chains, hygiene, and proper handling techniques, use of traditional, cost-efficient technologies, equitable market access, and value addition while ensuring the participation of women and marginalised groups in decision-making processes. These national and international efforts were part of a broader strategy to enhance food security, equitable development, and sustainable fisheries management​ (May & Bueno, 2023). On the other hand, several studies related to the same issues documented from Mogadishu landing sites have been done by (Kristófersson, 2012), assessing the cost-effective management strategy to reduce dagaa post-harvest loss in Tanzania and found a high level of post-harvest loss (comprising physical and quality losses with approximately 59%, while (Gyan et al., 2020) studied the post-harvest fish losses in the case study of Albert Bosomtwi-Sam fishing harbour, Western Region, Ghana. An estimated 92 tons of fish were lost postharvest, and three different forms of losses were identified, namely, quality losses (50%), physical losses (32%), and Market losses (12%), which are slightly different from the current study due to seasonal, geographical or technological differences. Table 9 Type of Postharvest Tuna Fish Loss Row Labels Lido (respondents) Lido % Urubo (respondents) Urubo % Market loss 24 6% 16 4% Economic loss 38 10% 14 4% Quality loss 72 20% 29 8% Physical loss 121 33% 55 15% 4.2.1.1 Fish loss generated through load tracking records The data in Table 10 presents information regarding various species of fish, including their initial and final weights, weight loss during a specified period, and the initial internal and external temperatures recorded for each species. The species listed are Bigeye tuna (jedar-ilweyn), Yellowfin tuna (balcagar), Kawakawa (dhiglow), and Skipjack tuna (sanuuro). Weight loss analysis was done as follows: The Initial Weight of Bigeye tuna was 45.1 Kg, and the Final Weight was 24.7 Kg, whereas the total loss was 20.4 Kg. Yellowfin tuna (balcagar) had an Initial Weight of 55.2 Kg and a final weight was 31.2 Kg, resulting in loss was 24.4 Kg. Kawakawa (dhiglow)’s Initial Weight was 10.9 Kg and its final weight was 5.8 kg, resulting then a loss was 5.1 Kg. Skipjack Tuna (sanuuro)’s initial weight was 10.3 Kg and final weight was 5.2 Kg as well as a loss which was 5.1 Kg. From this analysis, it is evident that the Yellowfin tuna experienced the highest weight loss at 24.4 Kg, followed by the Bigeye tuna with a loss of 20.4 Kg. Temperature analysis was also providing initial internal and external temperatures for each species with the following results: Bigeye Tuna’s internal temperature was 13.1 ∘°C and external temperature was 12.2∘°C, Yellowfin tuna (balcagar)’s internal temperature was 14.7∘°C while external Temp was 18.7∘°C. Kawakawa (dhiglow)’s internal temperature was 17.6∘°C, and its external temperature was 16.9∘°C. Last but not least, Skipjack tuna (sanuuro)’s internal temperature was 15.1∘°C while the external temperature was 16.9∘°C. The temperature data indicate that there is variability in both internal and external temperatures among different species, which could potentially influence their metabolic rates and weight changes over time. Table 10 Fish loss generated through load tracking Species of fish Initial weight (Kg) Final weight (Kg) Loss (Kg) Initial temperature Final external Temperature Bigeye tuna 45.1 24.7 20.4 13.1 12.2 Yellow fin tuna (balcagar) 55.24 31.2 24.4 14.7 18.7 Kawakawa (dhiglow) 10.90 5.8 5.1 17.6 16.9 Skipjack tuna (sanuuro 10.35 5.25 5.1 15.1 16.9 4.2.1.2 Fish Value Chain Loss The Table 11 shows the overall fish value chain loss in Urubo and Lido fish landing sites. A significant portion of fish is lost across various stages of the supply chain for both Lido and Urubo. The total loss is quite high, indicating a need for improvement in fish handling and distribution practices. The highest loss for both Lido and Urubo occurs during the Market, waiting customers wait to purchase the fish. This suggests that there were issues with market infrastructure, storage, and handling practices. The loss during Sea (after catch before landing site) was also substantial, indicating potential issues with fishing practices, vessel conditions, and post-catch handling. Losses during transportation and distribution, and during landing before the market, were also significant and require attention. There were differences; while both Lido and Urubo experienced significant losses, the distribution of losses across different stages varies slightly. Lido seems to have a higher percentage of losses during the market stage, while Urubo has a more evenly distributed loss across stages. Table 11 Fish value chain loss Fish value chain loss Frequency (Lido) Frequency (Urubo) Percentage loss (Lido) Percentage loss (Urubo) Sea (after catch before landing site) 62 26 24.3% 22.8% During landing before the market 42 28 16.5% 24.5% During transportation and distribution 58 19 22.7% 16.7% During the Market waiting customers to purchase the fish 56 31 22% 27.2% Other, please specify 37 10 14.5% 8.8% 4.2.2 Major causes of post-harvest loss of tuna fish As shown Table 12 , long hours of setting gear before hauling the catch were a significant cause of tuna fish loss, particularly in Lido (21%), making it the largest single factor. Lack of knowledge on fish handling practices 18% in Lido and 11% in Urubo. Irregular use of ice for fish preservation was another major factor, contributing around 20%, with the majority from Lido. Other factors, such as high temperature, hygiene, and lack of cold storage facilities, contribute smaller percentages individually (1–3%). Long hours of setting gear, lack of knowledge on fish handling practices and irregular use of ice accounted for the majority of postharvest losses, making up 75% of the total loss. Similar studies carried out by (Gyan et al, 2020) identified that the leading causes of postharvest fish losses in their study included inadequate ice (10%), extended stay at the harbour (33%), poor processing technique (30%) and gear-related injuries (28%). On the other hand, in Mogadishu, the storage landscape is characterized by a significant gap between demand and available infrastructure. While several large fishing companies operate within the city, their reliance on standard refrigerators for fish storage often falls short of maintaining the necessary deep-freeze temperatures required for long-term tuna preservation. A small number of companies possess dedicated cold storage facilities, but these are frequently noted for poor operational standards. These companies typically utilize their capacity strategically, storing surplus fish during high-landing periods and re-introducing them to the market during seasons of scarcity. However, this capacity is insufficient to meet the needs of Mogadishu’s growing population, which now exceeds 4 million people according to the government report. Consequently, small-scale fish traders and informal fish businesspeople are forced to rely on makeshift solutions. They commonly store tuna for a week or less using fibre-made containers filled with large quantities of non-standardized ice, as well as limited refrigerators. This lack of standardized cooling, combined with irregular icing practices, which currently account for more than 20% of total losses, significantly increases the risk of both physical and qualitative spoilage before the product reaches the final consumer. Table 12 Major causes of post-harvest loss of tuna fish Major causes of post-harvest loss of tuna fish Freq, Lido %, Lido Freq, Urubo %Urubo High temperature (weather conditions) 4 1% 4 1% Hygiene and sanitation 7 2% 4 1% Fishing-gear for predatory damage 7 2% 4 1% Lack of ice-cooling techniques when transporting fish to suppliers 8 2% 4 1% Lack of fish cold-storage facilities 8 2% 4 1% Lack of fish-preservation tools used by small retailers 22 6% 14 4% Irregular use of ice by fishers during fishing and landing 55 15% 18 5% Lack of knowledge of correct fish-handling practices 66 18% 40 11% Long hours of setting gear before hauling the catch 78 21% 22 6% 4.2.2.1 Types of boats operating in Lido and Urubo Fish landing sites As Table 13 indicates, different types of boats operating in Mogadishu landing sites, along with their specifications and operational details, are three distinct types of boats, namely Volvo, Skiffs (farboorto), and Houri. Each has unique characteristics that cater to different fishing needs. The lengths of the boats vary 8.8 m (Volvo), 6.5 m (Skiffs-farboorto), and 3–4 m (Hour). The length correlates with its capacity, stability, and suitability for various fishing conditions. The materials used for constructing these boats are primarily made of (Volvo), which is from the fibre class, known for durability and resistance to corrosion, Skiffs (farboorto), constructed from the fibre class, and Houri from the wood/fibre class, suggesting a blend that may offer traditional aesthetics alongside modern performance features. Volvo operates multi-day fishing trips, suggesting it is designed for longer excursions, Skiffs (farboorto) for daily fishing activities, indicating quick turnaround times mostly targeting local fish stocks less than 12nm, while Houris operate daily but with a shorter length, which limits its range or capacity compared to the other two types. The other bigger fishing boats (Xariin) can operate for months and harvest a large number of fish for several weeks. More than seventy-six Volvo and 390 skiffs are available in Lido, suggesting a significant investment in larger vessels capable of extended trips. There are 180 Skiffs (farboorto) and nearly 15 Houris operating recorded in Lido, indicating that big boats cannot operate in Urubo fishing. As (SHELEMO, 2024), (Moge et al. 2018), (UNIDO, 2020b) indicate, the types of boats are mostly similar in Somalia. On the other hand, several studies, including, (Munga et al., 2014), and (Eissler & Heckert, 2024) in the East African region, indicate that most types of fishing technologies/gears are similar. Table 13 boats operating in Lido and Urubo Fish landing sites Type of Boat Length of Boat Material of Boat Fishing Activities No. Boats (Lido) No. Boats (Urubo) Volvo 8.8 meters Fiberglass Multi-day fishing 104 0 Skiffs 6.5 meters Fiberglass Daily fishing 390 180 Houri 3–4 meters Wooden/Fiberglass Daily fishing 0 15 4.2.2.2 Types of fishing gear used by fishermen Tuna alone, there are several fishing gears recorded in both Lido and Urubo fishing communities, including Floating gillnet (FG), Handline (HL), Longline (LL), Bottom gillnet (BG) and Horizontal longline (HLL). Gill nets are the most widely used gear, accounting for 50% of the total, with significant usage in both Lido (32%) and Urubo (19%). Long lines are the second most commonly used, accounting for 24% of the total, with higher usage in Lido (22%) than in Urubo (7%). Handlines are also a notable gear type, contributing 21% overall, with most usage in Lido (16%). Somali fishermen usually operate in territorial waters close to the offshore. They are characterised by the use of gillnets (shabaag), longlines (jeesto), handline (fiilo) and small fishing boats (skiffs, volvo, and a very small number of houris boats). Several studies made by (Maklago et al., 2024, Munga et al., 2014, Eissler & Heckert, 2024) in the region indicate that most types of fishing technologies/gears are similar. See Fig. 8 below of fishing gear technologies available in Urubo and Lido Fish landings 4.2.3 The Impact of Postharvest Loss of Tuna Fish Reduction in income for fisheries people, which leads to increased poverty levels, is the most significant impact, accounting for 38% overall, with a major portion (32%) from Lido. Fish products failing to meet international quality standards are another major issue, particularly in Urubo (11%), contributing 17% overall. Wastage of catch due to excess and lack of market, leading to discarding, is also significant, making up 14% of the total impact. Other notable impacts include fish value losses (6%) and rapid deterioration of fish quality, resulting in market price reductions and forced discard (10%). As (Getu et al. 2015; Torell et al. 2020) studied, postharvest fish losses lead to reduced fish quality, low availability of fish products, and low societal income. It also results in a low diet or low nutritional value, which gives an unhealthy and poor population. One of the PHFL impacts included insect infestation by house fly, blowfly, and beetle fly larvae, which up to 30% of the fish product being lost, which seems similar to these findings, may be due to the similarity of the technological and handling skills gaps. See Fig. 8 , indicating the impacts of postharvest fish loss. According to the regional fish loss and waste impact analysis, almost all information from the research data and the previous information matches. For instance, at the Kuruwitu landing location in Kenya (Molla, 2023), the socioeconomic effects and causes of post-harvest fish losses (PHL) were examined, and PHL data showed a high correlation between income and handling habits. The research directed fishermen and processors toward more economical, efficient handling methods. (Bukola, 2018) modelled PHL for croaker, catfish, and shrimp by surveying 400 small-scale fishermen in 20 localities in Ondo State, Nigeria. Average losses during transportation were 8.15%, 7.76%, and 7.57%, respectively, due to a lack of ice, covers, and storage. Fishing trip length, age, education, experience, credit availability, previous training, and storage/transport availability were all significant predictors of PHL, according to regression analysis. In northeastern Nigeria, Segun et al. (2022) confirmed that artisanal losses were considerable, with 23.15% of daily catch ruined. Reduced infrastructure, low literacy, poor management, longer fishing cycles, little packaging, and more fishing days per week were all associated with increased PHL, according to multiple linear regression. To prevent losses and lower expensive fish imports, the authors reiterated (Acharjee et al, 2021) in urging regulations, infrastructure, and ongoing fisher training. In Zambia, (Kaminski et al, 2020) used a combination of approaches to investigate gendered PHL. Compared to men, women suffered much greater losses, mostly from handling and processing. Though technological limitations and constrictive gender norms increased loss disparities, flexible choices (fresh vs. dry sales) helped reduce risk. See Fig. 9 : Impact of postharvest loss of fish. 4.3 Conclusion and Recommendations At the Lido and Urubo landing sites in Somalia, post-harvest fish loss (PHFL) continues to be a major bottleneck. This study, which surveyed 369 fishermen, merchants, and processors and analysed mixed-method data in MS Excel, discovered that over half of the landed tuna is lost physically (48%) and qualitatively (23%), with market-driven and direct economic losses contributing an additional 11%. The main causes are operational, uneven icing (20%), inadequate handling skills (28%), and equipment left soaking for an extended period (28%), combined with low market demand (14%). These reductions lower household income by 38%, cut supply along the value chain by 11%, and keep 17% of items from meeting export requirements. Skiff operators rarely carry ice, fish are dragged across the ground, and landings remain un-iced until purchasers arrive, all of which prevent entry to prestigious international markets. These observations verified the lack of quality-control mechanisms. Unplanned shading (41%), speedy sale (52%), and basic gut-and-chill (8%) are the mainstays of current mitigation, although they are insufficient to stop degradation. Somalia can reduce fish losses after harvest by: (1) increasing research to determine loss levels and cost-effective solutions throughout the country; (2) training fishers and processors in on-board icing, hygienic handling, and rapid chilling; (3) implementing a politically supported PHFL policy with enforceable quality standards; (4) installing fishing jetties, enhancing ice plants, and cold stores at landing sites; (5) daily catch logs for traceability; (6) simplifying export certification and connecting traders with international fish markets; and (7) providing microcredit, particularly to low income and women’s organizations, for fuel-wood plots, renewable-energy dryers, and small refrigeration units. Declarations Author Contributions Both Nor Daud Ibrahim and Dayah Abdi Kulmie collaborated on the conceptualization, methodology, validation, formal analysis, investigation, data curation, review and editing, visualization, and supervision of Mr Dayah Abdi Kulmie, and project management. Each author made an equal contribution to this work, and they have both read and approved the manuscript's final draft. Funding This research did not receive any financial support from any funding agency, organization, or individual ethical approval was not required for this review article, as it does not involve direct data collection from human participants or animals. Data Availability Since no new data were generated or examined for this paper, data sharing is not applicable. The manuscript properly cites all previously published data and literature, which form the basis of this investigation. 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Eating more sardines instead of fish oil supplementation : Beyond omega-3 polyunsaturated fatty acids , a matrix of nutrients with cardiovascular benefits . April , 1–10. https://doi.org/10.3389/fnut.2023.1107475 Ministry of Fisheries and Blue Economy. (2025). Somalia National Report to the Scientific Committee of the Indian Ocean Tuna Commission , 2025 . Minstry of Fisheries and Blue Economy. (n.d.). THE PRODUCTIVE SECTOR DEVELOPMENT PROGRAMME ( UNJP / SOM / 063 / UNJ FISHERIES MASTER PLAN PREPARED BY THE MINISTRY OF FISHERIES AND BLUE ECONOMY OF THE FEDERAL GOVERNMENT OF SOMALIA AND THE FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS Table of . September 2023 . Moge, A.-Y. O. (2018). SOMALI COASTAL D E V ELOPM ENT OPPORTUNITIES PROJECT BADWEYN PAPER SERIES : OPPORTUNITIES . Munga, C. N., Omukoto, J. O., Kimani, E. N., & Vanreusel, A. (2014). Propulsion-gear-based characterisation of artisanal fisheries in the Malindi-Ungwana Bay, Kenya and its use for fisheries management. Ocean and Coastal Management , 98 , 130–139. https://doi.org/10.1016/j.ocecoaman.2014.06.006 Pererat, W. M. K., Jayasooriyai, S., Achchi, H., Nara, A., & Island, C. (2000). Handling practices and post-harvest losses of tuna catches from multi-day boats operating from fish landing site Negombo ,; Sri Lanka and Development . 5 , 87–95. Racioppo, A., Speranza, B., Campaniello, D., Sinigaglia, M., Corbo, M. R., & Bevilacqua, A. (2021). Fish Loss/Waste and Low-Value Fish Challenges: State of Art, Advances, and Perspectives . SHELEMO, A. A. (2024). Assessment of Community fishing needs to support increased production of fishing households during early recovery in selected landing sites in Somalia. Introduction. Nucl. Phys. , 13 (1), 104–116. Sheng, L., & Wang, L. (2021). The microbial safety of fish and fish products: Recent advances in understanding its significance, contamination sources, and control strategies. Comprehensive Reviews in Food Science and Food Safety , 20 (1), 738–786. https://doi.org/10.1111/1541-4337.12671 SNBS. (2025). NATIONAL TRANSFORMATION PLAN ( NTP ) . 2025–2029. Solo, M. K., Lako, J., Mani, F., & Brodie, G. (2023). Assessment of Postharvest Practices of Tuna Sold at the Honiara Fish Market in the Solomon Islands. International Journal of Food Science , 2023 . https://doi.org/10.1155/2023/6594017 Somalia, M. of F. and B. E. of. (2023). Fisheries Monitoring control and surveillance strategy . http://securefisheries.org/sites/default/files/SecuringSomaliFisheries-FullReport.pdf Torell, E. C., Jamu, D. M., Kanyerere, G. Z., Chiwaula, L., Nagoli, J., Kambewa, P., Brooks, A., & Freeman, P. (2020). Assessing the economic impacts of post-harvest fisheries losses in Malawi. World Development Perspectives , 19 (June), 100224. https://doi.org/10.1016/j.wdp.2020.100224 UNFPA. (2014). POPULATION ESTIMATION SURVEY 2014 (Issue October). UNIDO. (2020a). Mapping & Value Chain Analysis of the Fishery Sub-Sector in Somalia . January , 1–43. UNIDO. (2020b). Mapping & Value Chain Analysis of the Fishery Sub-Sector in Somalia . January , 1–43. https://open.unido.org/api/documents/21174737/download/2_UNIDO_MoCI Report Fishery subsector_final.pdf UNIDO. (2022). Training Manual on Improved Fish Handling and Preservation Techniques Funded by : The European Union UNIDO Project on Enhanced Local Value Addition and . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9498967","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":638027285,"identity":"6953e421-1ae1-47cf-b3b4-6a75d1ea9ff0","order_by":0,"name":"Nor Daud Ibrahim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArUlEQVRIiWNgGAWjYFCCBAYGngowy4AULWdI1sLbRooWc/bkZxJv59klNrA3b5Ng+GNDWItlzzMzybnbkhMbeI6VSTC2pRHWYnAjwUyad9uBxAaJHDMJxobDxGhJ/ybNOweoRf6NGdBhRGnJAdrSALKFB6iFjRgtZ94UW845lmzcxpNWbJFIlF+Op2+88abGTraf/fDGGx+ICTE4YAMRCSRoGAWjYBSMglGABwAANxA2MLC8IZgAAAAASUVORK5CYII=","orcid":"","institution":"City University of Mogadishu","correspondingAuthor":true,"prefix":"","firstName":"Nor","middleName":"Daud","lastName":"Ibrahim","suffix":""},{"id":638027286,"identity":"1c3c1576-ef27-42a1-ab8d-7687404094c5","order_by":1,"name":"Dayah Abdi Kulmie","email":"","orcid":"","institution":"City University of Mogadishu","correspondingAuthor":false,"prefix":"","firstName":"Dayah","middleName":"Abdi","lastName":"Kulmie","suffix":""}],"badges":[],"createdAt":"2026-04-22 16:53:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9498967/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9498967/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109228720,"identity":"1db239f3-0ea7-44b2-bb2e-98e69e6ace78","added_by":"auto","created_at":"2026-05-14 02:13:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":437644,"visible":true,"origin":"","legend":"\u003cp\u003eHistoric annual catch by species, IOTC area\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9498967/v1/589e4c69e4a4b1c24f4ce135.png"},{"id":109228721,"identity":"8f0320af-26f7-4f8f-be6d-4480f282ab3b","added_by":"auto","created_at":"2026-05-14 02:13:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":336793,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly Tuna Catch Trends (Nov 2018 – Oct 2021).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9498967/v1/7dc5d1d6fad2adca1dee019e.png"},{"id":109249553,"identity":"a8bd3294-5704-4de5-9b32-2cc74f979bcc","added_by":"auto","created_at":"2026-05-14 08:56:06","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":738876,"visible":true,"origin":"","legend":"\u003cp\u003eApparent fishing hours for fishing vessels (2020-2021)\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9498967/v1/ba9da41803cf5d41ae95c131.jpeg"},{"id":109249527,"identity":"79262373-e254-47ee-9efb-17d47679122c","added_by":"auto","created_at":"2026-05-14 08:55:21","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":153496,"visible":true,"origin":"","legend":"\u003cp\u003ebelow shows the map distribution of fishing catch, by tuna species, for the national fisheries areas of recent years.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9498967/v1/2d27c7ceedd1364800d42896.jpg"},{"id":109249505,"identity":"29cf1a9a-2a4c-4dee-823d-b36f5f9d9a33","added_by":"auto","created_at":"2026-05-14 08:54:43","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":105353,"visible":true,"origin":"","legend":"\u003cp\u003eindicates the map of distribution of fishing catch, by species, for the national fisheries, in the IOTC area of competence (average of the 5 previous years, 2020–2024).\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9498967/v1/068c41cd1c4819a04bff0256.jpg"},{"id":109228724,"identity":"3deaec3e-0a8d-4b10-99f1-c4c6b34c8bc7","added_by":"auto","created_at":"2026-05-14 02:13:53","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":306439,"visible":true,"origin":"","legend":"\u003cp\u003eExport Values of Fishery Products\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9498967/v1/12ff735154a81a176985df00.jpg"},{"id":109228727,"identity":"ebcdd159-04ba-48d2-9bff-563e32df73f6","added_by":"auto","created_at":"2026-05-14 02:13:53","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":142555,"visible":true,"origin":"","legend":"\u003cp\u003eMap of Mogadishu Fish landing sites\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9498967/v1/2953085ad8abf58888b14009.jpg"},{"id":109249587,"identity":"ad428cf4-f3a6-418a-88c0-9313ab06310a","added_by":"auto","created_at":"2026-05-14 08:57:03","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":363280,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePercentage and Frequency of Fishing Gear Use in Lido and Urubo\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-9498967/v1/b2621206c3bbe5b54afc4d05.png"},{"id":109249498,"identity":"738a1d83-a61a-4b6e-91bf-8f643254b1e4","added_by":"auto","created_at":"2026-05-14 08:54:25","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":92805,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImpact of postharvest loss of fish\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9498967/v1/baf3f4f3eb26c160bb6c31c2.jpg"},{"id":109250104,"identity":"64c10628-e392-488a-bd9d-65b57956b5d8","added_by":"auto","created_at":"2026-05-14 09:06:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2885529,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9498967/v1/fc7d1c2c-2c74-4224-b8a9-85240b3a6902.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Post-Harvest Loss of Tuna in Urubo and Lido Fish Landing Centres, Mogadishu, Somalia","fulltext":[{"header":"1.0 Introduction","content":"\u003cp\u003eSomalia, located in East Africa, is bordered by the Indian Ocean to the east, the Red Sea to the northeast, Djibouti to the north, Ethiopia to the northwest, and Kenya to the southwest (Addow et al., 2023) With a coastline of 3,898 km, the second-longest in Africa after Madagascar and an Exclusive Economic Zone (EEZ) covering approximately 1.2\u0026nbsp;million km\u0026sup2;, possessing with significant marine resources. Surveys show that the Somali Current marine ecosystem is one of the wealthiest fishing sites in the region due to its highly productive waters and large fish stocks. A significant seasonal upwelling system, in which monsoon winds from May to August deliver cold, nutrient-rich waters to the northeast coast, especially between Ras Asir and Ras Mabber, is primarily responsible for this production. These upwelling zones boost the commercial worth of fisheries by supporting high primary production and biomass(Agulhas, 2011). However, while bigger industrial vessels continue to operate offshore, the same monsoon period, which runs from May to September, brings strong winds and choppy seas that hinder port access for smaller vessels and impede coastal fishing activity. As the result, offshore fleets frequently modify their fishing locations, equipment, or target species, while artisanal fisheries normally run for 220\u0026ndash;240 days a year(SNBS, 2025). According to the World Bank (2025), during the 18 pre-war, Somalia population was estimated 12,316,895 (UNFPA, 2014). Out of this population, Somalia\u0026rsquo;s Fisheries Communities are estimated around 10,000 part-time and full-time fishers, and 60,000 people are involved in different fishing economy including traders, processors, gear and vessel manufacturers(Ministry of Fisheries and Blue Economy, 2023). Somalia\u0026rsquo;s fisheries sector remains largely small-scale, relying on open fibreglass Volvo boats and skiffs between 2 and 10 meters long, mostly powered by outboard engines, as well as on traditional vessels like Houris (Secure Fisheries, 2021). Commonly harvested commercial marine species include tuna, billfish, groupers, snappers, goatfish, jacks, seabream, sharks, rays and skates (SAPPHIRE, 2019). Inland fisheries primarily occur in the Juba and Shabelle rivers, with catfish and Mullidae among the main species (UNIDO, 2020). According to inland fishing villagers' reports, rivers are frequently home to tilapia. However, these fish are extremely susceptible to recurrent droughts and water scarcity, which have an impact on river levels nationwide. Tilapia populations rise dramatically during times of plentiful water, yet overcrowding may limit the amount of natural food available. Tilapia are thought to be ideal for aquaculture and fish farming due to their versatility and quick growth, providing a workable way to maintain livelihoods when natural water sources diminish. Despite Somalia\u0026rsquo;s vast marine resources, the fisheries sector contributes only about 2\u0026ndash;3% to Somalia's national GDP, reflecting its underdevelopment (Ibrahim et al., 2024). The country\u0026rsquo;s per capita fish consumption is one of the lowest in Africa, at only 3.3 kg (Hassan et al., 2026). Globally, fish provide approximately 17% of the intake of animal protein, highlighting their importance to food security and nutrition. However, fish postharvest losses (FPHLs) represent a serious challenge. In sub-Saharan Africa, FPHLs are estimated to cause annual financial losses of USD 2\u0026ndash;5\u0026nbsp;billion (Abelti \u0026amp; Teka, 2024). These losses are defined as reductions in quantity, quality, or value of fish at any supply chain stage, undermining incomes, food security, and employment (Racioppo et al., 2021). Fish losses occur in various forms, including quality loss, physical loss, market force loss, and economic loss (Segun et al., 2022). Causes include spoilage, contamination, traditional processing methods, poor storage, insect infestation, and economic or logistical issues (Heidrich et al., 2022; Kruijssen et al., 2020). For instance, India\u0026rsquo;s fisheries sector alone employs around 14\u0026nbsp;million people, suffers postharvest losses worth ₹61,000 crores annually, demonstrating the economic scale of the issue (PS et al., 2022). Tuna, in particular, is a highly valued pelagic species, popular globally due to its taste and nutritional profile, rich in protein, omega-3 fatty acids, and essential vitamins (Science, 2018; Solo et al., 2023). Tuna is one of the most widely consumed fishes in Somalia, and is exported. Its high market value and migratory nature necessitate sustainable management and regional cooperation (Biji et al., 2016). Around 5\u0026nbsp;million tonnes of tuna annually generate USD 41\u0026nbsp;billion globally, underlining the importance of conservation (Solo et al., 2023).\u003c/p\u003e \u003cp\u003eAccording to Somalia\u0026rsquo;s latest report to IOTC, national annual catch increased to 76,026 mt (Ministry of Fisheries and Blue Economy, 2025), while studies suggest that the fisheries sector could be valued at between US\u003cspan\u003e$\u003c/span\u003e350\u0026ndash;940\u0026nbsp;million annually with proper management and development (Ministry of Fisheries and Blue Economy, 2023). In Sub-Saharan African Countries, tuna and other fish species experience postharvest quality losses ranging from 5% to 87%, depending on handling, species, weather, and processing. This translates to potential income losses exceeding 32% (Keerthana et al., 2022). In Somalia, postharvest fish losses range from 25% to 40%, primarily due to traditional processing methods (Julien et al., 2024; Abdikarim Gole, 2019, Bank, 2024). According to a model-based assessment from 2015, the overall sustainability predicted Fishery Production Potential for Somali waters is 835,100 MT, which includes 364,000 MT of demersal species, 335,000 MT of pelagic species/sardines, and 136,000 MT of tuna/coastal species (Minstry of Fisheries and Blue Economy, 2023). According to (SNBS, 2025), Somali annual catch productivity is estimated to be between 120,000 and 240,000 metric tons. According to the shores of Somalia has potential of harvesting 380,000 MT to 500,000 MT of fish annually with the Eastern coast compared to Northern coast share 90% of it (UNIDO, 2020). Despite the extent of the problem, limited documentation exists on postharvest losses of tuna fish in major Mogadishu landing sites (Urubo and Lido). Therefore, this study, which is the first of its kind conducted in Mogadishu and Somalia, aimed to assess the types, causes, impacts, and mitigation strategies related to postharvest tuna (fish) losses in these locations.\u003c/p\u003e"},{"header":"2.0 LITERATURE REVIEW","content":"\u003cp\u003eThe decline in fish quantity or quality during harvest, including handling, processing, storage, transportation, and marketing, is known as post-harvest fish loss (PHFL) (Ikbal et al., 2023). Approximately 10 to 12\u0026nbsp;million of tonnes of fish harvested worldwide are lost or squandered each year, accounting for around 10% to 30% of total fish production annually (Solo et al., 2023). as a result of insufficient cold storage, ineffective transportation, and technical advancements (Lako et al., 2019). The marine fishing industry in Somali IUU fishing alone has a substantial annual loss of \u003cspan\u003e$\u003c/span\u003e306\u0026nbsp;million due to several issues(Iddrisu \u0026amp; Senior, 2024,Minstry of Fisheries and Blue Economy, 2023). On another hand, the value chain of fisheries, women are essential, particularly in post-harvest operations including processing, marketing, and storage (Addis et al., 2012). Up to 90% of people participating in these activities are women in underdeveloped nations. However, they frequently encounter structural obstacles, such as restricted access to resources and platforms for decision-making, which results in PHFL's disproportionate effects (Obinna et al., 2018).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Types of Postharvest Losses\u003c/h2\u003e \u003cp\u003eThere are several types of postharvest fish loss, such as physical loss, quality loss due to spoilage, insect infestation and breakage, market loss, operational loss, nutritional loss and etc. But here, we will talk about the three main types of postharvest fish loss.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1 Physical Loss\u003c/h2\u003e \u003cp\u003eFish discarded or eaten by birds, insects, or other creatures are seen as physical losses. It is expressed as a loss of weight or monetary worth. When fish pieces are thrown away or eaten by animals, birds, or insects, it is considered a physical loss. The fish loses weight and value at this point (Ibrahim et al., 2023). Fish are physically lost in the supply chain when they are stolen, dropped, or eaten by wildlife. Additionally, a report claims that unhealthy conditions speed up the rotting process and that carelessly handled fish may suffer physical harm. High temperatures, incorrect processing, storage, and fish supplies are some of the factors that make fish more vulnerable to physical injury. The Tema Fishing Harbour in Ghana was the subject of a study to identify the types of post-harvest fish loss (PHFL) that occur at the landing site and during transit (Kumar and Datta, 2020). 50 fishermen (and carriers) received questionnaires at random. The report found that burritos, herrings, redfish, moonfish, mackerel, and tuna were the most frequently obtained fish. The least likely to spoil was tuna, whereas the most susceptible was herring. Inappropriate fish handling most of the time resulted in physical losses for the fisherman(Akongyuure, 2019)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2 Quality Loss\u003c/h2\u003e \u003cp\u003eFish quality declines are attributed to physical damage or degeneration, yet the fish is still sold, sometimes at a reduced price. It is typically expressed in monetary terms. A decrease in fish quality lowers the fish grade and results in a loss of money. According to (Montojo et al, 2020), the Philippines evaluated the efficacy of ice-chilled carrier boats by estimating quality losses and producing data on the amount of post-harvest losses incurred in landed catch from high sea pockets using the exploratory Fish Loss Assessment Method and the Questionnaire Loss Assessment Method. For carrier boats with chilled ice, the anticipated loss of HSP-1's landing catch was 17.25%. A poor-quality catch represents a loss because it usually sells for less when utilized as raw materials for fishmeal processing, smoking, and canning. There was a positive correlation between fishing time and losses. Fish quality may suffer as a result of the current preservation technique utilized in carrier boats, according to the findings (Lailossa, 2015).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.1.3 Market Loss\u003c/h2\u003e \u003cp\u003eMarket-force losses occur when oversupply, competition, or gluts force fishers and traders to accept prices below expectations, resulting in a combination of financial, physical, and quality losses (Gyan et al., 2020). Over 35% of the world's fish production is lost post-harvest due to spoilage, damage, poor handling, and weak cold-chain infrastructure; these issues are particularly severe in developing countries. In India, the industry supports 14\u0026nbsp;million people, while studies from Bangladesh reveal 3–6% volume losses in cultured species and significant financial losses in capture fisheries, with hilsa and shrimp losing up to BDT 77,675 and 33,000 per t, respectively (Rashid \u0026amp; Sarkar, 2020). Handling procedures are crucial; it was observed that high dry-season demand in the Solomon Islands concealed quality deficiencies, and (Litaay et al, 2023) showed that a 1:1 ice-to-fish ratio kept skipjack tuna fresher than 1:2. Although they asked for uniform criteria, quality testing on Tanzanian tunas also confirmed good physico-chemical scores (Lujuo et al., 2022). The degradation of protein and micronutrient value due to spoiling or inadequate processing results in nutritional losses that go beyond obvious and monetary losses, compromising public health and food security (Jeyanthi, 2020). On the other hand, in Somalia, tuna species such as Yellowfin (\u003cem\u003eThunnus albacares\u003c/em\u003e), Skipjack (\u003cem\u003eKatsuwonus pelamis\u003c/em\u003e), and Kawakawa (\u003cem\u003eEuthynnus affinis\u003c/em\u003e) are cornerstone resources for the artisanal sector. Despite their abundance, there is a critical absence of localized laboratory data regarding the specific post-mortem muscle biochemistry of these fish in the Somali climate. Currently, there are no active bio-monitoring systems or specialized marine laboratories in Somalia dedicated to tracking the enzymatic degradation and metabolic heat generation of tuna during the \"gear-soak\" and \"on-deck\" phases. This lack of physiological data makes it difficult to set precise \"time-to-ice\" standards for Somali fishers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.1.5 Causes of Fish Loss During Harvesting and Handling\u003c/h2\u003e \u003cp\u003eFish losses during harvesting and handling happen at several crucial points, starting with the actual fishing procedure. Destructive fishing techniques, including using chemicals or explosives, can harm fish, causing them to decay quickly and degrade their quality(UNIDO, 2022). Fish that fall from nets or are thrown away as unwanted bycatch can also be physically lost. Long intervals between placing and retrieving fishing gear might expose the catch to pollutants or heat, which can further deteriorate it. Additionally, on-board handling has a major role in quality degradation(One Earth Future, 2020). If you do not gut, clean, and chill the fish right away, it will be less fresh and have a shorter shelf life. Poor handling techniques, including walking on fish, can cause physical damage that results in bruises and render them unfit for sale(Abelti \u0026amp; Teka, 2024). Physical and qualitative degradation is accelerated when the catch is not landed while the fish are still exposed to high water temperatures. Prolonged conversations during the unloading stage, when fish are lying on the ground in direct sunlight, quickly degrade the quality. The fish become even more contaminated at landing ports due to poor sanitation. Theft while offloading and fish falling from baskets or crates onto the beach are two other instances of physical losses(Torell et al., 2020). Together, these elements drastically lower the amount and caliber of fish that are available for sale and eating.\u003c/p\u003e \u003cp\u003ePost-harvest loss (PHL) drivers using fuzzy TOPSIS, identifying the main threats to quality as inadequate icing, fish overload during transportation, and a lack of equipment for small-scale vendors. Despite a study of worldwide preservation techniques by including canning, freezing, drying, salting, fermenting, smoking, and pickling, 10–12\u0026nbsp;million tons of fish still deteriorate annually as a result of damage and inadequate sanitation, undermining revenue and nutrition. According to Indian traders emphasize cold-chain upgrades by discarding inedible fish pieces that could be turned into fertilizer. Disruptions caused by COVID-19 made PHL worse by violating supply-chain quality standards. There are serious safety risks, discovered that while properly refrigerated fish remained within the 50ppm standard, histamine in Fiji tuna reached 192 ppm at 28°C. Inadequate post-harvest treatment ultimately weakens national food systems, decreases the availability of nutritious fish, and lowers community wages(Sheng \u0026amp; Wang, 2021).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003ctable id=\"Tab1\" border=\"1\"\u003e \u003ccaption\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCauses of Post-Harvest Fish Loss During Harvesting and Handling\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003c/colgroup\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\"\u003e \u003cp\u003eStage of Loss\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eCause\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eType of Loss\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" rowspan=\"3\"\u003e \u003cp\u003eWhen Fishing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUse of destructive fishing methods resulting in spoilage of fish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical, Quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eDropping from the net and being thrown away as bycatch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eFish spoils when fishing equipment is left out for extended periods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical, Quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" rowspan=\"3\"\u003e \u003cp\u003eHandling Fish On-board\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNot gutting, cleaning, and chilling the fish while on board\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eQuality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysically harming fish like stepping on them\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eQuality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eDelayed landing after fishing and exposure to high temperatures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical, Quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" rowspan=\"4\"\u003e \u003cp\u003eUnloading\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eProlonged haggling while fish is exposed to sun and heat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eQuality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eInadequate sanitation methods leading to pollution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eQuality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTheft at landing site while offloading\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eFish falling into the beach from baskets or crates\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eSources\u003c/b\u003e: (Kaminski et al., 2020)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.1.6 Causes of Fish Loss During Marketing, Processing, and Storage\u003c/h2\u003e \u003cp\u003ePoor handling, insufficient infrastructure, and a small market capacity are the main causes of post-harvest fish losses during marketing, processing, and storage. Fresh fish frequently experience physical and qualitative losses during the marketing stage as a result of inadequate ice utilization and a lack of insulated containers. Seafood can spoil if traders purposefully delay their purchases, particularly if they leave the fish out in the heat(Jeyanthi, 2020). The scarcity of ice, cold storage, and processing equipment exacerbates losses during bumper harvests, when catch is high. Market-related problems like limited consumer spending power, delayed market access, and insufficient marketing information can also lower fish value, resulting in both quality and physical loss as well as financial (market) loss(Pererat et al., 2000). Using damaged or subpar fish at the processing and packing stage causes additional deterioration. Insect infestations and microbiological contamination might result from unhygienic manufacturing conditions. Traditional drying techniques frequently expose fish to infection and harm, such as placing them on unhygienic surfaces like rocks or bare ground. Inadequate packing and excessive smoking because of unregulated smoking temperatures also result in quality and quantity losses(Keerthana et al. 2022). Microbial growth, discoloring chemical reactions, and insect or animal infestations are the most typical causes of storage-related losses. Inadequate or badly maintained storage facilities frequently exacerbate these problems. These issues collectively drastically lower the total value, safety, and usability of fish products at every level of marketing, processing, and storage(Kaminski et al., 2020).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003ctable id=\"Tab2\" border=\"1\"\u003e \u003ccaption\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCauses of Post-Harvest Fish Loss During Marketing, Processing, and Storage\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003c/colgroup\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\"\u003e \u003cp\u003eStage of Loss\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eCause\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eType of Loss\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" rowspan=\"7\"\u003e \u003cp\u003eMarketing Fresh Fish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eInsufficient ice and no insulated container\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical, Quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTraders delaying seafood purchases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eQuality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eLimited preservation during bumper catches (ice, processing machines)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical, Quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eInadequate cold storage and ice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical, Quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMarket timing issues\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMarket\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eLow consumer and buyer purchasing power\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMarket\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eLack of market info or oversupply\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMarket, Physical, Quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" rowspan=\"5\"\u003e \u003cp\u003eFish Processing \u0026amp; Packaging\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUse of already spoiled or poor-quality fish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical, Quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUnsanitary processing leading to insect infestation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical, Quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eDrying fish on unsanitary surfaces; poor packing techniques\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical, Quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eOver-smoking due to improper temperature control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical, Quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eDamaged due to poor packaging materials\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical, Quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" rowspan=\"4\"\u003e \u003cp\u003eStorage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMicrobial spoilage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eQuality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eChemical discoloration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eQuality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eAnimal/insect infestations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical, Quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eInadequate storage facilities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysical, Quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eResource: (Getu et al., 2015)\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Species Composition and Primary Stocks of Tuna in Somalia\u003c/h2\u003e \u003cp\u003eThe Somali Exclusive Economic Zone (EEZ) covers approximately 1.2\u0026nbsp;million km² and is home to some of the most productive tuna fishing grounds in the Western Indian Ocean. According to the \u003cem\u003eSomalia National Report to the (IOTC, 2025)\u003c/em\u003e, the primary species harvested by the artisanal fleet include Yellowfin tuna (\u003cem\u003eThunnus albacares\u003c/em\u003e), Skipjack tuna (\u003cem\u003eKatsuwonus pelamis\u003c/em\u003e), Kawakawa (\u003cem\u003eEuthynnus affinis\u003c/em\u003e), Bigeye tuna (\u003cem\u003eThunnus obesus)\u003c/em\u003e, Longtail tuna (\u003cem\u003eThunnus tonggol) and\u003c/em\u003e Spanish mackerel (\u003cem\u003eScomberomorus commerson)\u003c/em\u003e, as shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003ctable id=\"Tab3\" border=\"1\"\u003e \u003ccaption\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimary Tuna Stocks in Somalia\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003c/colgroup\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\"\u003e \u003cp\u003eScientific Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eCommon Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eLocal Importance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eThunnus albacares\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eYellowfin tuna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigh (Primary export \u0026amp; local market)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eKatsuwonus pelamis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSkipjack tuna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigh (Abundant in upwelling zones)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eEuthynnus affinis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eKawakawa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigh (Artisanal sector staple)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eThunnus obesus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBigeye tuna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eModerate (Pelagic stock)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eThunnus tonggol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eLongtail tuna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eCommon in coastal landings\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eScomberomorus commerson\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSpanish mackerel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigh (Often classified with pelagic)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eSource: (\u003cem\u003eIOTC, 2025)\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Annual Tuna Catch in Somalia\u003c/h2\u003e \u003cp\u003eOver the period, total reported tuna landings increased steadily, rising from approximately 18,000 t in 2019 to nearly 33,000 t in 2024. Yellowfin tuna consistently dominated the catch, accounting for the largest share in all years and showing a particularly sharp increase in 2024. Skipjack tuna remained an important component of the catch, although its contribution fluctuated, with a decline observed in 2023 followed by a recovery in 2024. Bigeye tuna landings increased gradually, indicating either improved targeting, changes in stock availability, or enhanced reporting coverage. Longtail tuna contributed relatively small but stable quantities throughout the period. The pronounced rise in total tuna catch in 2024 should be interpreted cautiously, as it likely reflects a combination of increased fishing effort, improved data collection, and expanded monitoring rather than stock-driven growth alone (Ministry of Fisheries and Blue Economy, 2025). According to the Ministry of Fisheries and Blue Economy 2025, Annual Tuna Catch by Species in Somalia (2019–2024) amount indicated to 18,049 with Yellowfin tuna contributing the largest share at 8,049 (about 44.6%), followed by Skipjack tuna with 6,500 (36.0%). Bigeye tuna accounts for 2,800 (around 15.5%), while Longtail tuna represents the smallest portion at 700 (about 3.9%). Yellowfin and Skipjack tuna dominate the catch, together making up more than 80% of the total, whereas Bigeye and Longtail contribute relatively smaller proportions. See the Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e of Annual Tuna Catch by Species in Somalia (2019–2024) (Ministry of Fisheries and Blue Economy, 2025\u003cem\u003e).\u003c/em\u003e See Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e: Annual Tuna Catch by Species in Somalia (2019–2024)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Tuna Catch Monthly Trend Analysis\u003c/h2\u003e \u003cp\u003eThe data reveal a significant upward trajectory in tuna catches over the three years, characterized by distinct seasonal volatility. The initial period (late 2018 through 2019) shows relatively low activity, bottoming out in September 2019 with nearly zero catches. However, starting in early 2020, the volume shifted to a higher baseline, with the peak occurring in February 2021 at approximately 98 units. While the graph shows sharp month-to-month fluctuations, likely due to migration patterns or weather conditions, the valleys in 2021 remain higher than the peaks of 2019, suggesting a long-term growth trend or increased fishing efficiency. The data concludes with a strong recovery in late 2021 after a mid-year dip, maintaining the overall elevated volume compared to the start of the study. See Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, monthly Tuna catch trends (Ministry of Fisheries and Blue Economy, 2025).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Spatial Distribution of Fishing Effort in the Somali waters\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e below, it illustrates the distribution of fishing activity along the coast of Somalia for the period 2020–2021, showing apparent fishing hours per unit area. Fishing effort is widespread across the Exclusive Economic Zone (EEZ), but it is unevenly distributed, with the highest concentrations observed along the northern coast in the Gulf of Aden and in selected central and southern offshore areas. The map also highlights important maritime boundaries, including the EEZ and 12 and 24 nautical mile coastal buffer zones, which are critical for fisheries management. Additionally, bathymetric data indicate deeper offshore waters where some fishing activity occurs. Overall, the map suggests that fishing pressure is particularly intense in northern and nearshore regions, pointing to key areas that require focused monitoring, control, and sustainable management interventions (Global Fishing Watch, 2021.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Somali Regional Tuna Catch Species Distribution Analysis (Nov 2018 – Oct 2021 Project Kalluun)\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e below shows the frequency of catches across all eight species and highlights where the most fishing activity is occurring. This fish catch data reveals that Bosaso and Berbera are the primary hubs for fishing activity, collectively accounting for over 69% of the total volume with 573 and 568 units, respectively. Yellowfin Tuna (YFT) is the most dominant species across all regions, particularly in Mogadishu, which leads in YFT yield (184) despite having a lower overall species diversity. While Berbera stands out as the most balanced port, recording catches across all eight species, Kismayo shows significantly lower output at only 60 units. Overall, the northern regions maintain a high-volume, diverse catch, while southern regions like Mogadishu are more specialized toward high-value tuna varieties. On the other hand, the species Bigeye Tuna (BET), Albacore (ALB), Bullet Tuna (BLT), and Frigate Tuna (FRI) are missing from the Biomass Series for Comparative Graph (Total Weight in kg) table because the data provided focuses only on the top four species contributing the largest total biomass across all regions: Yellowfin Tuna (YFT), Skipjack Tuna (SKJ), Kawakawa (KAW), and Longtail Tuna (LOT) (Ministry of Fisheries and Blue Economy, 2025).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003ctable id=\"Tab4\" border=\"1\"\u003e \u003ccaption\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCatch Volume (Number of Individuals)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003c/colgroup\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eYFT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eSKJ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eKAW\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eLOT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eBET\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eALB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eBLT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eFRI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eTotal Count\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBerbera\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e568\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBosaso\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e573\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMogadishu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e451\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eKismayo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1,652\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure 5: indicates the map of distribution of fishing catch, by species, for the national fisheries, in the IOTC area of competence (average of the 5 previous years, 2020–2024).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Tuna Catch Biomass\u003c/h2\u003e \u003cp\u003eThe Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e below indicates the total weight for the four-primary species. It highlights the economic and nutritional value of the catch. The Somali fishing sector is defined by a high-volume northern corridor and a high-biomass southern hub. Bosaso and Berbera lead in activity, managing 69% of the total catch count (1,141 fish). However, Mogadishu is the economic heavyweight; despite catching only 27% of the total individuals (451 fish), it produces 40% of the total biomass (4,348.1 kg). This is driven by Yellowfin Tuna (YFT), which is the industry’s anchor, accounting for 50% of total weight (5,420.5 kg) and 30% of total count. While the north, specifically Berbera, shows the highest ecological diversity by harvesting all eight recorded species (including rare Albacore and Frigate tuna), the south specializes in larger, more mature specimens. Mogadishu’s average fish weight is nearly double that of Berbera’s, indicating a specialised deep-water pelagic fishery. Kismayo remains a minor contributor, representing only 3% of total volume (345 kg), focusing primarily on Yellowfin and Longtail tuna. In summary, the northern ports provide diverse regional food security, while the southern ports drive commercial value through high-mass tuna exports (Ministry of Fisheries and Blue Economy, 2025). See the Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e below.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" class=\"colspec\"\u003e\u003c/div\u003e\u003ctable id=\"Tab5\" border=\"1\"\u003e \u003ccaption\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCatch Biomass (Weight in kg)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003c/colgroup\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eYFT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eSKJ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eKAW\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eLOT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eTotal Weight (kg)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBerbera\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1,025.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e852.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e412.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e492.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e2,781.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBosaso\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1,411.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e930.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e409.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e591.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e3,342.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMogadishu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e2,822.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e819.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e387.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e319.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e4,348.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eKismayo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e162.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e35.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e123.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e345.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e5,420.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e2,636.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1,234.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e1,526.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\"\u003e \u003cp\u003e10,816.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e3. Export Values of Tuna Fishery Products\u003c/h3\u003e\n\u003cp\u003eTuna and tuna-like species constitute a central pillar of Somalia’s fisheries export economy, with the majority of export earnings derived from minimally processed products. As shown in Fig.\u0026nbsp;5, exports of fresh or chilled fish generated the highest revenues throughout the period, increasing steadily from USD 1.05\u0026nbsp;million in 2016 to USD 1.68\u0026nbsp;million in 2019 and averaging 32% of total fisheries export value. This trend reflects strong regional demand, particularly from Middle Eastern markets, and the limited domestic capacity for large-scale value addition. Exports of frozen fish also exhibited consistent growth, rising from USD 0.89\u0026nbsp;million in 2016 to USD 1.34\u0026nbsp;million in 2019 and contributing approximately 25% of total export earnings. Frozen products offer greater flexibility in storage and transport and are increasingly important for stabilising export flows amid infrastructure and cold-chain constraints. Higher value-added products, including fish fillets and meat and prepared or preserved fish, contributed a relatively smaller share of export value, averaging 10% and 4%, respectively. Although these categories showed gradual growth over the study period, their limited contribution highlights structural constraints within Somalia’s fisheries value chain, such as inadequate processing facilities, quality assurance systems, and compliance with international sanitary and phytosanitary standards. The export structure indicates a strong dependence on raw and semi-processed fish products, underscoring the need for targeted investments in processing infrastructure, cold storage, and certification systems to enhance value addition, diversify export products, and increase foreign exchange earnings from tuna and tuna-like fisheries (Ministry of Fisheries and Blue Economy, 2025).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003e4. Storage Infrastructure and Market Gaps in Mogadishu Fish Markets\u003c/h3\u003e\n\u003cp\u003eIn Mogadishu, a city of over 4\u0026nbsp;million people, the storage landscape is characterized by a significant mismatch between demand and modern infrastructure. While large fishing companies exist, they mostly use standard refrigerators, which often fail to maintain the deep-freeze temperatures required for tuna. A few companies possess cold storage, but these are used strategically to store fish during \"bumper harvests\" and sell back during scarcity; they do not cover the city's total needs. Consequently, small-scale traders rely on fiber-made containers with non-standardized ice, which can only preserve fish for a week or less. This infrastructure gap contributes to post-harvest losses that are estimated to be as high as 60% in some artisanal sectors (Ministry of Fisheries and Blue Economy, 2025).\u003c/p\u003e\n\u003ch3\u003e5. Estimated Annual IUU Fishing in Somali Waters and Economic Value\u003c/h3\u003e\n\u003cp\u003eBetween 2019 and 2022, Somali waters experienced significant illegal, unreported, and unregulated (IUU) fishing, with an estimated 250 to 520 vessels operating annually. These vessels, both foreign and domestic, primarily targeted tuna, tuna-like species, sharks, reef, shallow-water finfish, and squid using gillnets, trawls, and mixed gear types. Total annual catches from IUU fishing were estimated at 25,940 to 105,920 metric tons, resulting in substantial economic losses. Iran and Yemen accounted for the largest portion of tuna and tuna-like catches, contributing 22,000 to 92,000 metric tons per year, with a potential landed value of \u003cspan\u003e$\u003c/span\u003e44 to \u003cspan\u003e$\u003c/span\u003e184\u0026nbsp;million annually. Other foreign fleets, including China and Egypt, focused on reef and shallow-water species, while domestic IUU activity in Somalia contributed 500 to 2,000 metric tons per year of reef species. Overall, the estimated total landed value of all IUU fishing in Somali waters ranged from \u003cspan\u003e$\u003c/span\u003e49.9 to \u003cspan\u003e$\u003c/span\u003e203.8\u0026nbsp;million per year, highlighting the considerable threat it poses to the national fisheries sector and coastal livelihoods (Ministry of Fisheries and Blue Economy, Somalia, 2023). See Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e below.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003ctable id=\"Tab6\" border=\"1\"\u003e \u003ccaption\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e– estimated annual average IUU fishing (2019 to 2022) in Somali waters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003c/colgroup\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\"\u003e \u003cp\u003eFlag State\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eKey Species\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eGear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eVessels\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eTotal Catch (mt/year)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eValue (USD/year)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTuna \u0026amp; tuna-like\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eGillnet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e120–260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e12,000–52,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e24M–104M\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eYemen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTuna, sharks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e100–200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e10,000–40,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e20M–80M\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eEgypt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eReef finfish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTrawl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e10–20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e1,000–4,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e1M–4M\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSquid \u0026amp; finfish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTrawl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e5–10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e500–2,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e0.5M–2M\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSomalia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eReef species\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTrawl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e5–10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e500–2,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e0.5M–2M\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMixed species\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e10–20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e1,940–5,920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e3.9M–11.8M\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e250–520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e25,940–105,920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eSource: \u003cem\u003e(Ministry of Fisheries and Blue Economy, Somalia, 2023)\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTuna Fisheries Policy Landscape in Somalia\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSomalia’s tuna fisheries policy landscape is gradually evolving as the Federal Government works to reassert control over marine resources, curb illegal fishing, and align national governance with regional conservation frameworks (Somali Magazine, 2025; World Bank, 2019). Somalia’s large and productive EEZ supports valuable stocks of Yellowfin tuna, Skipjack tuna, Kawakawa, Bigeye tuna, Longtail tuna and Spanish mackerel, which are vital for livelihoods and export potential; however, prolonged weak governance has historically enabled widespread IUU fishing and significant economic losses. The Fisheries Law enacted in 2023 (N0.008 2023) provides the legal foundation for tuna management, including licensing, conservation, and monitoring, control, and surveillance, though implementation has been constrained by limited capacity, fragmented federal–state roles, and weak enforcement (IOTC, 2015). Recent reforms led by the Ministry of Fisheries and Blue Economy have introduced standardized licensing procedures to improve transparency, reduce IUU fishing, and encourage greater participation by Somali entities (MFBE, 2024). Somalia’s engagement with the Indian Ocean Tuna Commission further shapes policy direction, particularly through advocacy for equitable tuna allocation for coastal states (MFBE, 2024). Support from international partners such as FAO and the World Bank has strengthened data systems and institutional capacity (FAO, 2025; World Bank, 2019). While progress has been made toward more structured and internationally aligned tuna governance, challenges remain in enforcement, data quality, and coordination, which must be addressed to ensure sustainable tuna fisheries and maximize economic benefits (FAO, 2025; World Bank, 2019).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003ctable id=\"Tab7\" border=\"1\"\u003e \u003ccaption\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSomalia Tuna Fisheries Policy Landscape\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003c/colgroup\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\"\u003e \u003cp\u003ePolicy Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eKey Instruments\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eRelevance to Tuna Fisheries\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNational Vision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNational Transformation Plan (2025–2029) \u0026amp; Blue Economy Strategy (2023–2027)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePositions tuna as key for growth, jobs, and food security\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSector Planning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eFisheries Master Plan \u0026amp; Food Safety Policy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eGuides sustainable use, investment, and value chains\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eLegal Framework\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eFisheries Law No. 008 (2023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eProvides legal basis for management, licensing, and conservation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eRegulations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eFisheries Food Safety Regulations (2025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eEnsures hygiene, certification, and export compliance\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eFisheries MCS Strategy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eStrengthens control, monitoring, and IUU prevention\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eInternational Alignment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eIndian Ocean Tuna Commission \u0026amp; Codex Alimentarius Commission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eEnsures compliance, market access, and global standards\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e "},{"header":"3.0 METHODOLOGY","content":"\u003cp\u003eThe study was conducted at the Urubo and Lido fish landing centres in Mogadishu, Somalia. Urubo fish landing centre, established in 1990s, locates in Bondere district with coordinates of (Lat 2̊ 1’ 59. 27’ N; Long. 45̊ 20’ 37.74’ E) while Lido fish landing site, founded in the late 1930s by Italian residents in Mogadishu with Lat: 2° 2'20.44\"N, long: 45°21'44.60\"E locates in the Abdiaziz district southeast of Mogadishu. The study used a survey research approach to look into the many kinds of tuna fish losses at the Urubo and Lido fish landing sites in Mogadishu, as well as their causes, effects, and ways to mitigate them. Field visits were carried out every day (except Fridays), and structured and semi-structured questionnaires, interviews, and direct observations were used as data gathering methods. The study was conducted at two important fish landing sites in Mogadishu that are well-known for their high levels of fish production and commercial activity, Urubo in the Bondere district and Lido in the Abdiaziz district. Fish processors, retail and export fish vendors, and fishermen made up the target population. Through the use of simple random sampling, 369 respondents in all, 300 who answered surveys and 59 who took part in in-depth interviews, were chosen. The Improved Loss Assessment Methodology (ILAM) and Load Tracking (LT) were used to gather data on tuna fish losses at various supply chain stages from both Lido and Urubo fish landing sites. Data analysis was done using Microsoft Excel, producing tables and graphical summaries with descriptive statistics like percentages and frequencies. Through informed consent, participant confidentiality, and obtaining required approvals, ethical issues were upheld.\u003c/p\u003e"},{"header":"4.0 RESULTS AND DISCUSSION","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Demographic information\u003c/h2\u003e \u003cp\u003eAbout two-thirds (69%) of all responders are Lido, and one-third (31%) are Urubo. A modest absolute movement in Urubo can appear enormous in percentage terms; this imbalance is only a reflection of the sample frame and should be considered when comparing percentages. Although men make up the majority of fishermen's livelihoods (76%) in both locations, women still make up about 25% of the workforce and work in jobs ranging from processing to the fish trade. Urubo's slightly greater male share (77%) than Lido's (75%) is negligible and might be due to work divides specific to each location rather than intentional exclusion. Although the industry is young, it nevertheless has seasoned older workers. About 42% are between the ages of 21 and 30, providing essential labour, and 21% are over 40, maintaining institutional memory. Similar age distributions at the two locations point to comparable employment retention and entry routes. Nearly half of the participants, particularly in Urubo (58%), report only informal education. Because artisanal fisheries mostly rely on implicit, passed-down information, this does not imply a lack of skill. Formal training shortages, however, may make it more difficult to adopt new technology or adhere to export regulations. The industry has a solid knowledge base because about one-third of respondents have more than ten years of experience. However, a fifth are new hires (less than three years old), indicating a high labour turnover rate and chances for focused capacity building. Fishers account for around 69% of the sample, reflecting the survey\u0026rsquo;s focus. Processors and traders together account for the remaining 31%, highlighting their importance to the value chain. The almost exact occupational division between the locations points to similar market functions. Married people make up the majority (61%) in line with local demographics. Intervention designs should take family responsibilities into account because they can affect risk tolerance and investment capacity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic information\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLido no\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLido %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUrubo n\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUrubo %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLanding site\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e77.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAge (yr)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt; 20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInformal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e49.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eExperience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3 yr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u0026ndash;6 yr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u0026ndash;10 yr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u0026ndash;20 yr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;20 yr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eOccupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFisher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e68.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProcessor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrader\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e61.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e39.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e4.2.1 Type of Postharvest Tuna Fish Loss recorded\u003c/h2\u003e \u003cp\u003eAs Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e indicates, four types of postharvest tuna fish losses were discovered in Lido and Urubo, physical loss is the most common form, making about 33% of losses in Lido and 15% in Urubo. This suggests that handling, storage, and transportation, particularly in Lido, have serious problems. Following this, there is a 20% quality drop in Lido and an 8% loss in Urubo, indicating that Lido has more impaired seafood freshness and marketability. Economic loss is also more common in Lido (10%) than in Urubo (4%), indicating a decline in revenue as a result of poorer product quality and inefficient markets. Despite being the least recorded, market loss nevertheless presents difficulties, with 6% in Lido and 4% in Urubo. Lido experiences more postharvest losses overall in all categories, underscoring the necessity of focused enhancements in market accessibility, cold chain systems, and infrastructure to promote fish value retention and fisher livelihoods. In fisheries, these losses comprise material losses of harvested fish resulting from spoilage, grading, size breakage, bycatch discards, and operational losses(Assefa et al., 2018, Cheke \u0026amp; Ward, 1998). The study which is the first of its kind conducted Mogadishu fish landing sites assessed the types of postharvest loss of fish, more specifically tuna fish, the causes of postharvest losses of tuna fish, impact of postharvest loss of tuna fish in both Lido and Urubo fish landing sites in Mogadishu. The Somali government has made concerted paper work efforts to address gaps in fisheries regulations through the development of key policy documents, including the National Blue Economy Strategy (2023), the Fisheries Law No. 008 (2023), and the Fisheries Master Plan (2023). These initiatives prioritize infrastructure development, capacity building, and regulatory frameworks, fisheries sector investment attractions to minimize losses and improve the value chain. For instance, the Fisheries Law emphasizes sustainable practices, co-management, and fish quality assurance systems​​​. The Master Plan underscores the need for modern fish handling, storage, and national and international market access improvements, while the National Blue Economy Strategy integrates these efforts into a broader framework of sustainable economic growth and environmental stewardship (Somalia Fisheries Law, 2023, Somalia Blue Economy Strategy, 2023, \u003cem\u003eMinistry of Fisheries, 2023\u003c/em\u003e).\u003c/p\u003e \u003cp\u003eIn the global context, FAO addressed post-harvest fish loss through the Voluntary Guidelines for Securing Sustainable Small-Scale Fisheries in the Context of Food Security and Poverty Eradication, developed in 2015. These guidelines emphasise minimising post-harvest losses and waste by promoting investments in infrastructure, capacity development, and environmentally sustainable practices. The FAO encouraged the to use best practices for reducing post-harvest fish loss, emphasising the importance of cold chains, hygiene, and proper handling techniques, use of traditional, cost-efficient technologies, equitable market access, and value addition while ensuring the participation of women and marginalised groups in decision-making processes. These national and international efforts were part of a broader strategy to enhance food security, equitable development, and sustainable fisheries management​ (May \u0026amp; Bueno, 2023). On the other hand, several studies related to the same issues documented from Mogadishu landing sites have been done by (Krist\u0026oacute;fersson, 2012), assessing the cost-effective management strategy to reduce dagaa post-harvest loss in Tanzania and found a high level of post-harvest loss (comprising physical and quality losses with approximately 59%, while (Gyan et al., 2020) studied the post-harvest fish losses in the case study of Albert Bosomtwi-Sam fishing harbour, Western Region, Ghana. An estimated 92 tons of fish were lost postharvest, and three different forms of losses were identified, namely, quality losses (50%), physical losses (32%), and Market losses (12%), which are slightly different from the current study due to seasonal, geographical or technological differences.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eType of Postharvest Tuna Fish Loss\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRow Labels\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLido (respondents)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLido %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUrubo (respondents)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUrubo %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarket loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEconomic loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuality loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec21\" class=\"Section4\"\u003e \u003ch2\u003e4.2.1.1 Fish loss generated through load tracking records\u003c/h2\u003e \u003cp\u003eThe data in Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e presents information regarding various species of fish, including their initial and final weights, weight loss during a specified period, and the initial internal and external temperatures recorded for each species. The species listed are Bigeye tuna (jedar-ilweyn), Yellowfin tuna (balcagar), Kawakawa (dhiglow), and Skipjack tuna (sanuuro). Weight loss analysis was done as follows: The Initial Weight of Bigeye tuna was 45.1 Kg, and the Final Weight was 24.7 Kg, whereas the total loss was 20.4 Kg. Yellowfin tuna (balcagar) had an Initial Weight of 55.2 Kg and a final weight was 31.2 Kg, resulting in loss was 24.4 Kg. Kawakawa (dhiglow)\u0026rsquo;s Initial Weight was 10.9 Kg and its final weight was 5.8 kg, resulting then a loss was 5.1 Kg. Skipjack Tuna (sanuuro)\u0026rsquo;s initial weight was 10.3 Kg and final weight was 5.2 Kg as well as a loss which was 5.1 Kg. From this analysis, it is evident that the Yellowfin tuna experienced the highest weight loss at 24.4 Kg, followed by the Bigeye tuna with a loss of 20.4 Kg. Temperature analysis was also providing initial internal and external temperatures for each species with the following results: Bigeye Tuna\u0026rsquo;s internal temperature was 13.1 ∘\u0026deg;C and external temperature was 12.2∘\u0026deg;C, Yellowfin tuna (balcagar)\u0026rsquo;s internal temperature was 14.7∘\u0026deg;C while external Temp was 18.7∘\u0026deg;C. Kawakawa (dhiglow)\u0026rsquo;s internal temperature was 17.6∘\u0026deg;C, and its external temperature was 16.9∘\u0026deg;C. Last but not least, Skipjack tuna (sanuuro)\u0026rsquo;s internal temperature was 15.1∘\u0026deg;C while the external temperature was 16.9∘\u0026deg;C. The temperature data indicate that there is variability in both internal and external temperatures among different species, which could potentially influence their metabolic rates and weight changes over time.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFish loss generated through load tracking\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies of fish\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInitial weight (Kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFinal weight (Kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLoss (Kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInitial temperature\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFinal external Temperature\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBigeye tuna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYellow fin tuna (balcagar)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKawakawa (dhiglow)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSkipjack tuna (sanuuro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section4\"\u003e \u003ch2\u003e4.2.1.2 Fish Value Chain Loss\u003c/h2\u003e \u003cp\u003eThe Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e shows the overall fish value chain loss in Urubo and Lido fish landing sites. A significant portion of fish is lost across various stages of the supply chain for both Lido and Urubo. The total loss is quite high, indicating a need for improvement in fish handling and distribution practices. The highest loss for both Lido and Urubo occurs during the Market, waiting customers wait to purchase the fish. This suggests that there were issues with market infrastructure, storage, and handling practices. The loss during Sea (after catch before landing site) was also substantial, indicating potential issues with fishing practices, vessel conditions, and post-catch handling. Losses during transportation and distribution, and during landing before the market, were also significant and require attention. There were differences; while both Lido and Urubo experienced significant losses, the distribution of losses across different stages varies slightly. Lido seems to have a higher percentage of losses during the market stage, while Urubo has a more evenly distributed loss across stages.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFish value chain loss\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFish value chain loss\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (Lido)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency (Urubo)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage loss (Lido)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePercentage loss (Urubo)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSea (after catch before landing site)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuring landing before the market\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuring transportation and distribution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuring the Market waiting customers to purchase the fish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther, please specify\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e4.2.2 Major causes of post-harvest loss of tuna fish\u003c/h2\u003e \u003cp\u003eAs shown Table\u0026nbsp;\u003cspan refid=\"Tab12\" class=\"InternalRef\"\u003e12\u003c/span\u003e, long hours of setting gear before hauling the catch were a significant cause of tuna fish loss, particularly in Lido (21%), making it the largest single factor. Lack of knowledge on fish handling practices 18% in Lido and 11% in Urubo. Irregular use of ice for fish preservation was another major factor, contributing around 20%, with the majority from Lido. Other factors, such as high temperature, hygiene, and lack of cold storage facilities, contribute smaller percentages individually (1\u0026ndash;3%). Long hours of setting gear, lack of knowledge on fish handling practices and irregular use of ice accounted for the majority of postharvest losses, making up 75% of the total loss. Similar studies carried out by (Gyan et al, 2020) identified that the leading causes of postharvest fish losses in their study included inadequate ice (10%), extended stay at the harbour (33%), poor processing technique (30%) and gear-related injuries (28%). On the other hand, in Mogadishu, the storage landscape is characterized by a significant gap between demand and available infrastructure. While several large fishing companies operate within the city, their reliance on standard refrigerators for fish storage often falls short of maintaining the necessary deep-freeze temperatures required for long-term tuna preservation. A small number of companies possess dedicated cold storage facilities, but these are frequently noted for poor operational standards. These companies typically utilize their capacity strategically, storing surplus fish during high-landing periods and re-introducing them to the market during seasons of scarcity. However, this capacity is insufficient to meet the needs of Mogadishu\u0026rsquo;s growing population, which now exceeds 4\u0026nbsp;million people according to the government report. Consequently, small-scale fish traders and informal fish businesspeople are forced to rely on makeshift solutions. They commonly store tuna for a week or less using fibre-made containers filled with large quantities of non-standardized ice, as well as limited refrigerators. This lack of standardized cooling, combined with irregular icing practices, which currently account for more than 20% of total losses, significantly increases the risk of both physical and qualitative spoilage before the product reaches the final consumer.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab12\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 12\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMajor causes of post-harvest loss of tuna fish\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor causes of post-harvest loss of tuna fish\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFreq, Lido\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%, Lido\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFreq, Urubo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%Urubo\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh temperature (weather conditions)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHygiene and sanitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFishing-gear for predatory damage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLack of ice-cooling techniques when transporting fish to suppliers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLack of fish cold-storage facilities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLack of fish-preservation tools used by small retailers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIrregular use of ice by fishers during fishing and landing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLack of knowledge of correct fish-handling practices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLong hours of setting gear before hauling the catch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec24\" class=\"Section4\"\u003e \u003ch2\u003e4.2.2.1 Types of boats operating in Lido and Urubo Fish landing sites\u003c/h2\u003e \u003cp\u003eAs Table\u0026nbsp;\u003cspan refid=\"Tab13\" class=\"InternalRef\"\u003e13\u003c/span\u003e indicates, different types of boats operating in Mogadishu landing sites, along with their specifications and operational details, are three distinct types of boats, namely Volvo, Skiffs (farboorto), and Houri. Each has unique characteristics that cater to different fishing needs. The lengths of the boats vary 8.8 m (Volvo), 6.5 m (Skiffs-farboorto), and 3\u0026ndash;4 m (Hour). The length correlates with its capacity, stability, and suitability for various fishing conditions. The materials used for constructing these boats are primarily made of (Volvo), which is from the fibre class, known for durability and resistance to corrosion, Skiffs (farboorto), constructed from the fibre class, and Houri from the wood/fibre class, suggesting a blend that may offer traditional aesthetics alongside modern performance features. Volvo operates multi-day fishing trips, suggesting it is designed for longer excursions, Skiffs (farboorto) for daily fishing activities, indicating quick turnaround times mostly targeting local fish stocks less than 12nm, while Houris operate daily but with a shorter length, which limits its range or capacity compared to the other two types. The other bigger fishing boats (Xariin) can operate for months and harvest a large number of fish for several weeks. More than seventy-six Volvo and 390 skiffs are available in Lido, suggesting a significant investment in larger vessels capable of extended trips. There are 180 Skiffs (farboorto) and nearly 15 Houris operating recorded in Lido, indicating that big boats cannot operate in Urubo fishing. As (SHELEMO, 2024), (Moge et al. 2018), (UNIDO, 2020b) indicate, the types of boats are mostly similar in Somalia. On the other hand, several studies, including, (Munga et al., 2014), and (Eissler \u0026amp; Heckert, 2024) in the East African region, indicate that most types of fishing technologies/gears are similar.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab13\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 13\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eboats operating in Lido and Urubo Fish landing sites\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of Boat\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLength of Boat\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaterial of Boat\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFishing Activities\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo. Boats (Lido)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo. Boats (Urubo)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVolvo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.8 meters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiberglass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMulti-day fishing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSkiffs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.5 meters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiberglass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDaily fishing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHouri\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026ndash;4 meters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWooden/Fiberglass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDaily fishing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section4\"\u003e \u003ch2\u003e4.2.2.2 Types of fishing gear used by fishermen\u003c/h2\u003e \u003cp\u003eTuna alone, there are several fishing gears recorded in both Lido and Urubo fishing communities, including Floating gillnet (FG), Handline (HL), Longline (LL), Bottom gillnet (BG) and Horizontal longline (HLL). Gill nets are the most widely used gear, accounting for 50% of the total, with significant usage in both Lido (32%) and Urubo (19%). Long lines are the second most commonly used, accounting for 24% of the total, with higher usage in Lido (22%) than in Urubo (7%). Handlines are also a notable gear type, contributing 21% overall, with most usage in Lido (16%). Somali fishermen usually operate in territorial waters close to the offshore. They are characterised by the use of gillnets (shabaag), longlines (jeesto), handline (fiilo) and small fishing boats (skiffs, volvo, and a very small number of houris boats). Several studies made by (Maklago et al., 2024, Munga et al., 2014, Eissler \u0026amp; Heckert, 2024) in the region indicate that most types of fishing technologies/gears are similar. See Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003e below of fishing gear technologies available in Urubo and Lido Fish landings\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003e4.2.3 The Impact of Postharvest Loss of Tuna Fish\u003c/h2\u003e \u003cp\u003eReduction in income for fisheries people, which leads to increased poverty levels, is the most significant impact, accounting for 38% overall, with a major portion (32%) from Lido. Fish products failing to meet international quality standards are another major issue, particularly in Urubo (11%), contributing 17% overall. Wastage of catch due to excess and lack of market, leading to discarding, is also significant, making up 14% of the total impact. Other notable impacts include fish value losses (6%) and rapid deterioration of fish quality, resulting in market price reductions and forced discard (10%). As (Getu et al. 2015; Torell et al. 2020) studied, postharvest fish losses lead to reduced fish quality, low availability of fish products, and low societal income. It also results in a low diet or low nutritional value, which gives an unhealthy and poor population. One of the PHFL impacts included insect infestation by house fly, blowfly, and beetle fly larvae, which up to 30% of the fish product being lost, which seems similar to these findings, may be due to the similarity of the technological and handling skills gaps. See Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003e, indicating the impacts of postharvest fish loss. According to the regional fish loss and waste impact analysis, almost all information from the research data and the previous information matches. For instance, at the Kuruwitu landing location in Kenya (Molla, 2023), the socioeconomic effects and causes of post-harvest fish losses (PHL) were examined, and PHL data showed a high correlation between income and handling habits. The research directed fishermen and processors toward more economical, efficient handling methods. (Bukola, 2018) modelled PHL for croaker, catfish, and shrimp by surveying 400 small-scale fishermen in 20 localities in Ondo State, Nigeria. Average losses during transportation were 8.15%, 7.76%, and 7.57%, respectively, due to a lack of ice, covers, and storage. Fishing trip length, age, education, experience, credit availability, previous training, and storage/transport availability were all significant predictors of PHL, according to regression analysis. In northeastern Nigeria, Segun et al. (2022) confirmed that artisanal losses were considerable, with 23.15% of daily catch ruined. Reduced infrastructure, low literacy, poor management, longer fishing cycles, little packaging, and more fishing days per week were all associated with increased PHL, according to multiple linear regression. To prevent losses and lower expensive fish imports, the authors reiterated (Acharjee et al, 2021) in urging regulations, infrastructure, and ongoing fisher training. In Zambia, (Kaminski et al, 2020) used a combination of approaches to investigate gendered PHL. Compared to men, women suffered much greater losses, mostly from handling and processing. Though technological limitations and constrictive gender norms increased loss disparities, flexible choices (fresh vs. dry sales) helped reduce risk. See Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e: Impact of postharvest loss of fish.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Conclusion and Recommendations\u003c/h2\u003e \u003cp\u003eAt the Lido and Urubo landing sites in Somalia, post-harvest fish loss (PHFL) continues to be a major bottleneck. This study, which surveyed 369 fishermen, merchants, and processors and analysed mixed-method data in MS Excel, discovered that over half of the landed tuna is lost physically (48%) and qualitatively (23%), with market-driven and direct economic losses contributing an additional 11%. The main causes are operational, uneven icing (20%), inadequate handling skills (28%), and equipment left soaking for an extended period (28%), combined with low market demand (14%). These reductions lower household income by 38%, cut supply along the value chain by 11%, and keep 17% of items from meeting export requirements. Skiff operators rarely carry ice, fish are dragged across the ground, and landings remain un-iced until purchasers arrive, all of which prevent entry to prestigious international markets. These observations verified the lack of quality-control mechanisms. Unplanned shading (41%), speedy sale (52%), and basic gut-and-chill (8%) are the mainstays of current mitigation, although they are insufficient to stop degradation. Somalia can reduce fish losses after harvest by: (1) increasing research to determine loss levels and cost-effective solutions throughout the country; (2) training fishers and processors in on-board icing, hygienic handling, and rapid chilling; (3) implementing a politically supported PHFL policy with enforceable quality standards; (4) installing fishing jetties, enhancing ice plants, and cold stores at landing sites; (5) daily catch logs for traceability; (6) simplifying export certification and connecting traders with international fish markets; and (7) providing microcredit, particularly to low income and women\u0026rsquo;s organizations, for fuel-wood plots, renewable-energy dryers, and small refrigeration units.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eAuthor Contributions\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBoth Nor Daud Ibrahim and Dayah Abdi Kulmie collaborated on the conceptualization, methodology, validation, formal analysis, investigation, data curation, review and editing, visualization, and supervision of Mr Dayah Abdi Kulmie, and project management. Each author made an equal contribution to this work, and they have both read and approved the manuscript's final draft.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis research did not receive any financial support from any funding agency, organization, or individual ethical approval was not required for this review article, as it does not involve direct data collection from human participants or animals.\u003c/p\u003e\n\u003cp\u003eData Availability\u003c/p\u003e\n\u003cp\u003eSince no new data were generated or examined for this paper, data sharing is not applicable. The manuscript properly cites all previously published data and literature, which form the basis of this investigation.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors of this review gratefully acknowledge everyone who contributed to the research or manuscript, including technical support, material donation, reviewers and editors\u003c/p\u003e\n\u003cp\u003eConflicts of Interest\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors in this review declare that there is no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003e(SAPPHIRE), W. I. O. L. M. E. S. A. P. P. H. and I. R. (2019). \u003cem\u003eThe Republic of Somalia Country Profile\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eAbelti, A. L., \u0026amp; Teka, T. A. (2024). 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(2018). \u003cem\u003eSOMALI COASTAL D E V ELOPM ENT OPPORTUNITIES PROJECT BADWEYN PAPER SERIES : OPPORTUNITIES\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eMunga, C. N., Omukoto, J. O., Kimani, E. N., \u0026amp; Vanreusel, A. (2014). Propulsion-gear-based characterisation of artisanal fisheries in the Malindi-Ungwana Bay, Kenya and its use for fisheries management. \u003cem\u003eOcean and Coastal Management\u003c/em\u003e, \u003cem\u003e98\u003c/em\u003e, 130\u0026ndash;139. https://doi.org/10.1016/j.ocecoaman.2014.06.006\u003c/li\u003e\n\u003cli\u003ePererat, W. M. K., Jayasooriyai, S., Achchi, H., Nara, A., \u0026amp; Island, C. (2000). \u003cem\u003eHandling practices and post-harvest losses of tuna catches from multi-day boats operating from fish landing site Negombo ,; Sri Lanka and Development\u003c/em\u003e. \u003cem\u003e5\u003c/em\u003e, 87\u0026ndash;95.\u003c/li\u003e\n\u003cli\u003eRacioppo, A., Speranza, B., Campaniello, D., Sinigaglia, M., Corbo, M. 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Assessing the economic impacts of post-harvest fisheries losses in Malawi. \u003cem\u003eWorld Development Perspectives\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(June), 100224. https://doi.org/10.1016/j.wdp.2020.100224\u003c/li\u003e\n\u003cli\u003eUNFPA. (2014). \u003cem\u003ePOPULATION ESTIMATION SURVEY 2014\u003c/em\u003e (Issue October).\u003c/li\u003e\n\u003cli\u003eUNIDO. (2020a). \u003cem\u003eMapping \u0026amp; Value Chain Analysis of the Fishery Sub-Sector in Somalia\u003c/em\u003e. \u003cem\u003eJanuary\u003c/em\u003e, 1\u0026ndash;43.\u003c/li\u003e\n\u003cli\u003eUNIDO. (2020b). \u003cem\u003eMapping \u0026amp; Value Chain Analysis of the Fishery Sub-Sector in Somalia\u003c/em\u003e. \u003cem\u003eJanuary\u003c/em\u003e, 1\u0026ndash;43. https://open.unido.org/api/documents/21174737/download/2_UNIDO_MoCI Report Fishery subsector_final.pdf\u003c/li\u003e\n\u003cli\u003eUNIDO. (2022). \u003cem\u003eTraining Manual on Improved Fish Handling and Preservation Techniques Funded by : The European Union UNIDO Project on Enhanced Local Value Addition and\u003c/em\u003e.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Tuna value chain, Cold-chain management, Urubo, Lido, Fish handling practices, Market access, Income loss, Quality standards, Somalia","lastPublishedDoi":"10.21203/rs.3.rs-9498967/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9498967/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePost-harvest fish losses (PHFL) of tuna at Somalia\u0026rsquo;s Urubo and Lido landing sites seriously erode food supplies and fishing incomes, as they are major landing sites in the city. This mixed-methods study, combining structured interviews with 369 fishers, processors and traders, FGD, KII, field observations, and spreadsheet analysis, measured the magnitude and categories of loss, traced causal factors, assessed the economic and quality repercussions, and reviewed existing mitigation measures. Four types of loss dominate, including spoilage from delayed processing, physical damage or downgrading owing to size and handling, discarding of by-catches, and operational or market wastage when supply outstrips demand. Prolonged gear-soak times and limited handling knowledge each contribute 28% of total losses; irregular icing accounts for 20%, and limited buyers for surplus catch accounts for 14%. Consequences ripple along the value chain, reducing usable fish by 11%, depressing household earnings by 38%, and causing 17% of products to fail export quality standards. Current countermeasures remain rudimentary, including shading catches from sun and rain (41%), rapid sale while still fresh (52%), and minimal gut-and-chill practice (8%). PHFL thus represents a critical constraint demanding systemic action. The study recommends instituting a national PHFL and fish-quality policy, providing targeted training for all value-chain actors, constructing jetties equipped with reliable ice and cold-storage capacity, enforcing vessel registration with daily catch logs, and strengthening national and international market linkages to stimulate investment and sustainably curb losses and waste, improved governance and community participation are also vital for lasting results at every stage.\u003c/p\u003e","manuscriptTitle":"Post-Harvest Loss of Tuna in Urubo and Lido Fish Landing Centres, Mogadishu, Somalia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-14 02:13:48","doi":"10.21203/rs.3.rs-9498967/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5a914948-24ce-4917-92e8-a468fa2af287","owner":[],"postedDate":"May 14th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewersInvited","content":"19","date":"2026-05-05T05:52:48+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T02:13:49+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-14 02:13:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9498967","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9498967","identity":"rs-9498967","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}