Accumulation of heavy metals in fish and their impacts on human health: A Systematic Literature Review

Aarabi, Samar; Chauiyakh, Oussama; Ninich, Oumaima; Kettani, Kamal; Ettahir, Aziz

doi:10.52711/0974-360x.2023.00039

Cited by 4 publications

(1 citation statement)

References 47 publications

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“…It is located between the cities of Rabat and Salé on the Atlantic coast in the northwest of the country. 15 This estuary is very important ecologically because it supports a wide variety of animal and plant species, including migratory birds that stop here on their annual migration. 16 Additionally, the port activity in the estuary makes a substantial contribution to the expansion of the local economy.…”

Section: Selection Of Sample Locationsmentioning

confidence: 99%

Bioaccumulation of Heavy Metals in Five Species of Fish Obtained from the Estuary of Rabat, Morocco

2024

TJNPR

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In recent years, there has been a dramatic fall in the fish population. This is due to habitat destruction, overfishing, diseases, climate change, and metal contamination. Despite the advantages of eating aquatic foods, hazardous metals can bioaccumulate in fish, posing a threat to human health and marine ecosystems. There is a need to evaluate the danger to human health posed by several heavy metals linked to eating popular edible fish species that are readily available to consumers in the Rabat-Sale region. The study aimed to evaluate the concentrations and accumulation of heavy metals in the various organs of fresh fish obtained from the Bouregreg estuary. During the winter and spring of 2023, fish belonging to five different genera (Anguilla, Diplodus, Solea, Mullet, and Lophius) were collected in the Bouregreg estuary at three different locations: My Youssef, Hassan II, and Mohammed VI Bridges. The concentrations of heavy metals (Cr, Zn, Cd, Pb, Fe, and Cu) in the muscles, livers, and gills were determined using an ULTIMA2 type inductively coupled emission spectroscopy plasma (ICP-AES). The results showed that all of the fish samples examined were contaminated with the six metallic trace elements. The fish samples meet the World Health Organization's recommended standards, especially for the Anguilla species, which, in contrast to Lophius, are recognized to be the healthiest fish and have the lowest metallic levels. The findings of the study revealed that the Bouregreg estuary is contaminated with heavy metals, necessitating regular fish awareness, monitoring, and assessment due to the significant reliance of the surrounding communities on fish.

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Section: Selection Of Sample Locationsmentioning

confidence: 99%

Bioaccumulation of Heavy Metals in Five Species of Fish Obtained from the Estuary of Rabat, Morocco

2024

TJNPR

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Accumulation of heavy metals in water and sediments Moroccan Atlantics estuary

Aarabi,

Chauiyakh,

Ninich

et al. 2023

RJPT

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The strong popularity and tourist potential of the Rabat/Salé region of northern Morocco plays an important socio-economic role, asking the question of monitoring its environmental quality. This study provides a preliminary dataset for concentrations of dissolved heavy metals in water and sediment. Concentrations of six metal elements (Fe, Zn, Cu, Cr, Pb, and Cd) were measured in water and sediment to understand the level of heavy metals and their source distributions, that could be distributed through anthropogenic activities. The samples were taken at five stations in the Bouregreg estuary of the Rabat/Salé region in August 2022.The pollution of the estuary remains important despite the measures taken by the local authorities since 2006 in the context of ecological conservation, such as the closure of the Oulja landfill on the side of the city of Salé and the pre-treatment of wastewater on the side of the city of Rabat.

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Recognition of Mushrooms and Classification of Edible and Toxic Families using Hardware Implementation of CNN Algorithms on an Embedded system

Bouganssa,

Salbi,

Aarabi

et al. 2024

RJPT

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In this work, new ideas in the realm of picture identification and classification are developed and implemented on hardware. This entails putting new algorithms into practice, whether for color, texture, or shape identification for AI (Artificial Intelligence) and picture recognition applications. We concentrate on identifying edible mushrooms in the harvesting and food manufacturing processes. Our proposal for an embedded system based on a Raspberry-Pi4 type microcomputer employing a combination of hardware and software components has helped with the recognition and classification of items in the image. Our object recognition system is built on a novel neighborhood topology and a cutting-edge kernel function that enables the effective embedding of image processing-related characteristics. We tested the suggested CNN-based object recognition system using a variety of challenging settings, including diverse fungus species, uncontrolled environments, and varying backdrop and illumination conditions. The outcomes were superior to various state-of-the-art outcomes. On the other hand, our contribution relating to the dynamic mode integrates a CNN network to accurately encode the temporal information with an attention mask allowing us to focus on the characteristics of an edible mushroom according to the state of the art, and guarantee the robustness of the recognition. We implemented our algorithm on a Raspberry Pi400-based embedded system connected to a CMOS camera-type image sensor plus an HMI human-machine interface for the instantaneous display of results for the rapid classification of edible and inedible mushrooms.

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Accumulation of heavy metals in fish and their impacts on human health: A Systematic Literature Review

Cited by 4 publications

References 47 publications

Bioaccumulation of Heavy Metals in Five Species of Fish Obtained from the Estuary of Rabat, Morocco

Bioaccumulation of Heavy Metals in Five Species of Fish Obtained from the Estuary of Rabat, Morocco

Accumulation of heavy metals in water and sediments Moroccan Atlantics estuary

Recognition of Mushrooms and Classification of Edible and Toxic Families using Hardware Implementation of CNN Algorithms on an Embedded system

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