Publications by authors named "S Bedhiaf-Romdhani"

This study investigated the impact of temperature and humidity on milk production traits in Tunisian dairy cows, analysing population-level trends and individual cow responses using various modelling techniques and heat stress (HS) indices. Two distinct datasets were used for this purpose: the first included 551,139; 331,654 and 302,396 test-day records for milk, fat and protein yields, respectively. The second supplemented the production information with daily average (THIavg) and maximum (THImax) temperature-humidity index (THI) data.

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Introduction: The development of reproducible tools for the rapid genotyping of thousands of genetic markers (SNPs) has promoted cross border collaboration in the study of sheep genetic diversity on a global scale.

Methods: In this study, we collected a comprehensive dataset of 239 African and Eurasian sheep breeds genotyped at 37,638 filtered SNP markers, with the aim of understanding the genetic structure of 22 North African (NA) sheep breeds within a global context.

Results And Discussion: We revealed asubstantial enrichment of the gene pool between the north and south shores of the Mediterranean Sea, which corroborates the importance of the maritime route in the history of livestock.

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The gene encodes αs2-casein, the third most abundant protein in camel milk. Despite its importance in foals, human nutrition, and dairy processing, the gene in camels has received little attention. This study presents the first complete characterization of the gene sequence in Old-World camels ( and ).

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Fecundity gene introgression has become an economical method to improve sheep prolificacy in developing countries. The FecX and FecGH mutations are variants of the BMP15 and GDF9 sheep genes, respectively, identified in Tunisian Barbarine sheep prolific line "W-INRAT," created through a prolificacy-based selection program. The first mutation caused increased prolificacy in heterozygous state and sterility in homozygous ewes.

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This study aimed to find the parsimonious random regression model (RRM) to evaluate the genetic potential for milk yield (MY), fat content (FC), and protein content (PC) in Tunisian Holstein cows. For this purpose, 551,139; 331,654; and 302,396 test day records for MY, FC, and PC were analysed using various RRMs with different Legendre polynomials (LP) orders on additive genetic (AG) and permanent environmental (PE) effects, and different types of residual variances (RV). The statistical analysis was performed in a Bayesian framework with Gibbs sampling, and the model performances were assessed, mainly, on the predictive ability criteria.

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