K
K. El-Shazly
Researcher at Alexandria University
Publications - 31
Citations - 467
K. El-Shazly is an academic researcher from Alexandria University. The author has contributed to research in topics: Rumen & Population. The author has an hindex of 12, co-authored 31 publications receiving 450 citations.
Papers
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Journal ArticleDOI
Effect of absence of ciliate protozoa from the rumen on microbial activity and growth of lambs.
A. R. Abou Akkada,K. El-Shazly +1 more
TL;DR: It was concluded that the rumen ciliate protozoa are essential for the metabolism and growth of young lambs.
Journal ArticleDOI
Studies on the nutritive value of some common Egyptian feedingstuffs. I. Nitrogen retention and ruminal ammonia curves
TL;DR: In this paper, the nutritive values of the nitrogenous constituents of some concentrates used in Egypt as supplements in summer rations (decorticated cottonseed cake, linseed-oil meal and beans (Vicia faba)) and of animal proteins (meat meal, fish meal and casein) and of barseem (Trifolium alexandrinum).
Journal ArticleDOI
Effect of presence or absence of rumen ciliate protozoa on some blood components, nitrogen retention, and digestibility of food constituents in lambs.
A. R. Abou Akkada,K. El-Shazly +1 more
TL;DR: The inoculated lambs have higher blood haemoglobin, protein N, and lower reducing sugars, ammonia N,, and urea N values than those of the uninoculate lambs.
Journal ArticleDOI
Effect of early establishment of ciliate protozoa in the rumen on microbial activity and growth of early weaned buffalo calves.
TL;DR: There was a tendency for higher VFA and ammonia-N concentrations in the rumen of inoculated calves and there was no difference between inoculated and uninoculated calves in blood urea and blood reducing sugars.
Journal ArticleDOI
The prediction of the nutritive value of animal feeds from chemical analyses.
M. A. Naga,K. El-Shazly +1 more
TL;DR: In this article, a protein index for animal feeds is suggested as a basis for the criteria relating nutritive value to chemical composition, and regression equations for predicting the nutritive values gave a reasonable level of accuracy (0·18−14·74% error).