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This experiment was carried out to respectively evaluate the nutritive and anti-nutritive constituents of some feedstuffs and forages that are abundantly found in Kenya and Industrial rice milling wastes and Umucass 36 cassava plant meal abundantly found in Nigeria with the aim of producing them in commercial quantity for the enhancement of livestock development and feeding in Kenya and Nigeria and the entire African continent. The forages obtained in Kenya are Napier grass, Guatemala giant panicum, Boma Rhodes, Giant setaria, Mulatto and Green leaf desmodium. Rose coco, Green grams pea and Sorghum are livestock grains obtained from Kakamega County market. Rice milling waste and Umucass 36 cassava root meal (gari) were obtained from Abia State, Nigeria. They were all evaluated for their nutritive content using internationally acceptable stands. The results showed that these feedstuffs are rich in dietary nutrients and the digestibility coefficients of the forages and the feedstuffs are encouraging. Processing or non-processing of Rose coco, Green gram peas and Sorghum showed no definite pattern of response that can be traced to the processing methods used in this trial. In conclusion, the richness of these feedstuff has the potential of enhancing livestock feeding and production in these two countries if properly applied.
Ojewola, G.S, Baraza, D.L, Olwenyo, G, Mugun, G, Unah, U.L, Adedokun, O.O. 2020. "Evaluation of Some Kenyan and Nigerian Livestock Feedstuffs". Global Journal of Science Frontier Research - D: Agriculture & Veterinary GJSFR-D Volume 20 (GJSFR Volume 20 Issue D2).
Crossref Journal DOI 10.17406/GJSFR
Print ISSN 0975-5896
e-ISSN 2249-4626
v1.2
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Total Score: 111
Country: Nigeria
Subject: Global Journal of Science Frontier Research - D: Agriculture & Veterinary
Authors: Ojewola, Baraza, Olwenyo, Mugun, Unah, Adedokun, O.O, Onabanjo, R.S, Adeniji, C.A. (PhD/Dr. count: 0)
View Count (all-time): 346
Total Views (Real + Logic): 920
Total Downloads (simulated): 39
Publish Date: 2020 03, Mon
Monthly Totals (Real + Logic):
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