Laid Dardabou
Laid Dardabou MSc.
Institut Institute of Animal Nutrition, Livestock Products, and Nutrition Physiology (TTE)
Location Muthgasse 11, 1190 Wien
Email laid.dardabou@boku.ac.at
Tel: +43 1 47654-97606
Career
- 2022 University assistant / doctoral student - University of Natural Resources and Life Sciences, Vienna
- 2021 - 2021 V Introductory Course on Poultry Production and Feeding. Production and Feeding. USSEC-FEDNA-CESFAC
- 2020 - 2021 Researcher: Promoting U.S. Soy Advantages to Technical Audiences
- 2020 - 2020 MSc. Animal nutrition - Universidad Politécnica de Madrid
- 2019 - 2020 MSc. Animal nutrition - Mediterranean Agronomical Institute of Zaragoza - CIHEAM
- 2015 - 2015 Animal Breeding Courses - Technical Institute of Animal Breeding, Algiers
- 2010 - 2015 Engineer in agronomic sciences, specialized in animal production - ENSA Algiers
- 2010 - 2015 MSc. agronomic sciences, specialized in animal production techniques - ENSA Algiers
Projects
0 Projects found.
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Publications
Knowledge Transfer to Society
Media
Lectures
(2023) Einfluss steigender Anteile löslicher Faser im Futter auf die Mast- und Schlachtleistung von Mastschweinen
Autoren: Schiborra, A., Dardabou, L.; Gierus, M.
Forum angewandte Forschung in der Rinder- und Schweinefütterung
(2023) Multilinear regression for estimation of KOH-solubility and TIA in soybeans
Autoren: Schedle K., Dardabou L., Slama J., Puntigam R., Trimmel M.
World Soybean Research Conference 11
(2023) Effect of increasing soluble-dietary-fibre content in diets of fattening pigs on growth performance
Autoren: Schiborra, A.; Dardabou, L.; Gierus, M.
Jahrestagung der Gesellschaft für Ernährungsphysiologie
(2023) Assessment of the Accuracy of NIRS Technology for Determining the Proximate Composition and Amino Acid Content of Commercial Soybean Meal Samples
Autoren: L; Dardabou
8th International Feeding Meeting “Present and Future Challenges”
(2022) Carbohydrates in Livestock Feeding - Current Research and Future Challenges
Autoren: L; Dardabou
FFoQSI Academy Seminar Series FASS 2022/II
Assessment of the Accuracy of NIRS Technology for Determining the Proximate Composition and Amino Acid Content of Commercial Soybean Meal Samples
Autoren: L; Dardabou