Quality monitoring of fish through histological assessment of their health status: Proposal for a New Scoring System.

The quality and health of fish are closely intertwined. This study aimed to unveil the effectiveness of histological techniques in characterizing fish health status and deducing their quality. A new classification scoring model was also proposed to provide a holistic assessment. A total of 80 silver carp (Hypophthalmichthys molitrix) specimens were collected from a freshwater dam, in two areas (Z1-Z2) at two periods (July and September), with twenty fish per sampling. The physico-chemical parameters of the water were measured, and a global pollution index (IGP) was calculated. Histological analysis was carried out on five vital organs (gills, kidneys, liver, intestines, and muscles) using a standard method, specifically the semi-quantitative system of Bernet et al. (1999), to determine the condition of each organ, enabling an organic index (OI) to be assigned (IG, IK, IL, II, IM). These indices were combined to obtain total scores for each specimen, named the IFish. The latter is explored as a biomarker of fish health status and quality to develop an innovative classification system. The results showed that the indices were generally notable in September in Z1, illustrating a significant spatio-temporal influence. A highly significant correlation was observed between the IFish and IGP (P = 0.0001). The proposed scoring system made it possible to classify fish according to their quality. To conclude, a healthy fish is a reliable indicator of its quality, and the use of histology, in particular through the IFish scoring, proved to be an effective biomarker to demonstrate this.

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Publication Details

Journal
PubMed
Published
2025-10-09
DOI
https://doi.org/10.12834/vetit.3767.35661.4
Primary Topic
Identification and Quantification in Food
Type
article
Field-Weighted Citation Impact
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article

Quality monitoring of fish through histological assessment of their health status: Proposal for a New Scoring System.

Omar Bennoune, Rahma Guelmamene, Rachid Elgroud, Nadir Aloui
PubMed
Identification and Quantification in Food
article

Quality monitoring of fish through histological assessment of their health status: Proposal for a New Scoring System.

Omar Bennoune, Rahma Guelmamene, Rachid Elgroud, Nadir Aloui
article en

Abstract

The quality and health of fish are closely intertwined. This study aimed to unveil the effectiveness of histological techniques in characterizing fish health status and deducing their quality. A new classification scoring model was also proposed to provide a holistic assessment. A total of 80 silver carp (Hypophthalmichthys molitrix) specimens were collected from a freshwater dam, in two areas (Z1-Z2) at two periods (July and September), with twenty fish per sampling. The physico-chemical parameters of the water were measured, and a global pollution index (IGP) was calculated. Histological analysis was carried out on five vital organs (gills, kidneys, liver, intestines, and muscles) using a standard method, specifically the semi-quantitative system of Bernet et al. (1999), to determine the condition of each organ, enabling an organic index (OI) to be assigned (IG, IK, IL, II, IM). These indices were combined to obtain total scores for each specimen, named the IFish. The latter is explored as a biomarker of fish health status and quality to develop an innovative classification system. The results showed that the indices were generally notable in September in Z1, illustrating a significant spatio-temporal influence. A highly significant correlation was observed between the IFish and IGP (P = 0.0001). The proposed scoring system made it possible to classify fish according to their quality. To conclude, a healthy fish is a reliable indicator of its quality, and the use of histology, in particular through the IFish scoring, proved to be an effective biomarker to demonstrate this.

PubMedVol. 61(4)
University Frères Mentouri Constantine 1 (DZ), University of Batna 1 (DZ)
Openalex Percentile: Top 74%
Identification and Quantification in Food
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