Sallam Mohammed

• Sallam applies statistical methods to analyze phenotypic, genotypic, and pedigree data in farm animals to enhance genetic improvements in health, production, and welfare, both national and international levels.
• Sallam utilizes machine learning and computer vision for digital phenotyping of emerging traits. 

Genome analysis BK0002

• New digital and genetic tools to reduce keel bone damage in laying hens, Quantitative Genetics section-HGEN, PI Dirk-Jan de Koning, SLU, 2021-present.
• International genomic evaluation of Brown Swiss and Holstein dairy cattle: multi-trait vs. single-trait approach, Interbull Centre, SLU, 2019-2020.

• 2025, PhD, Swedish University of Agricultueral Sciences 
• 2020,  MSC, Swedish University of Agricultueral Sciences 
• 2014,  MSC, Animal Husbandry, University of Sadat City
• 2009, DVM, University of Sadat City (Former Monofiya University)

• Sallam, M., et al. (2025). Genomic prediction of bone strength using differnt information sources. Animal.
• Sallam, M., et al. (2024). A deep learning method segments chicken keel bones from whole-body X-ray images. Poultry Science.
• Sallam, M., et al. (2024). Comparisons among longitudinal radiographic measures of keel bones, tibiotarsal bones, and pelvic bones versus post-mortem measures of keel bone damage in Bovans Brown laying hens housed in an aviary system. Frontier in Veterinary Science.
• Sallam, M., et al. (2024). Genetics of digital phenotypes of keel bones in laying hens. Genetics Selection Evolution. [Under review]
• Sallam, M., et al. (2023). Genetic markers associated with bone composition in laying hen. Genetics Selection Evolution.
• Sallam, M., et al. (2022). Across-countries genomic prediction using national breeding values or multitrait across-countries evaluation breeding values. Journal of dairy sciences.

National and international animal ranking. Why we need it and How we do it ? (56:00 into the recording)