APA 6th Edition Mlay, P.S., Pereka, A., Chikula Phiri, E., Balthazary, S., Igusti, J., Hvelplund, T., ... Madsen, J. (2006). Feed value of selected tropical grasses, legumes and concentrates. Veterinarski arhiv, 76 (1), 53-63. Retrieved from https://hrcak.srce.hr/5085
MLA 8th Edition Mlay, Paul Sebastian, et al. "Feed value of selected tropical grasses, legumes and concentrates." Veterinarski arhiv, vol. 76, no. 1, 2006, pp. 53-63. https://hrcak.srce.hr/5085. Accessed 26 Sep. 2020.
Chicago 17th Edition Mlay, Paul Sebastian, Appolinaria Pereka, Eliot Chikula Phiri, Sakurani Balthazary, Jelantik Igusti, Torben Hvelplund, Martin Riis Weisbjerg and Jřrgen Madsen. "Feed value of selected tropical grasses, legumes and concentrates." Veterinarski arhiv 76, no. 1 (2006): 53-63. https://hrcak.srce.hr/5085
Harvard Mlay, P.S., et al. (2006). 'Feed value of selected tropical grasses, legumes and concentrates', Veterinarski arhiv, 76(1), pp. 53-63. Available at: https://hrcak.srce.hr/5085 (Accessed 26 September 2020)
Vancouver Mlay PS, Pereka A, Chikula Phiri E, Balthazary S, Igusti J, Hvelplund T, et al. Feed value of selected tropical grasses, legumes and concentrates. Veterinarski arhiv [Internet]. 2006 [cited 2020 September 26];76(1):53-63. Available from: https://hrcak.srce.hr/5085
IEEE P.S. Mlay, et al., "Feed value of selected tropical grasses, legumes and concentrates", Veterinarski arhiv, vol.76, no. 1, pp. 53-63, 2006. [Online]. Available: https://hrcak.srce.hr/5085. [Accessed: 26 September 2020]
Abstracts Feed value is the potential of the feed to supply the nutrients required by an animal both quantitatively and qualitatively in order to support a desired type of production. Where chemical composition and digestibility of a given feed is known it is possible to calculate its energy content by using appropriate regression equations. Eleven tropical grass species and mixed grass hay, seven legumes and browse trees, and six concentrates were evaluated in terms of chemical composition (CP, EE, OM, CHO and NDF), digestibility (in vitro organic matter digestibility -IVOMD and enzyme solubility of organic matter- EZOM) and calculated energy values. The grass species were: Andropogon timorensis (Kunth), Rev. Gram., Brachiaria brizantha, (A.Rich) Stapf, Bothriochloa radicans (Lehm) A. camus, Chloris guyana Kunth, Cynodon dactylon (L.) Pers, Hyparrhenia rufa (Nees) Stapf, Panicum maximum (Jacq.), Pannisetum purpureum (Schumacher), Setaria sphacelata Stapf & C. E. Hubb, and Tripsacum fasciculatum Trin. ex Aschers. Most of the grasses were cut at an advanced stage of growth. The legumes and browses included Acacia catechu (L. f.) Willd., Gliricidia sepium (Jacq.) Kunth ex Walp, Leucaena leucocephala (Lam.) de Wit, Lannea grandis Lannea grandis Engl., Macroptilium atropurpureum (DC.) Urban, Sesbania grandiflora (L.) Poir and Zyziphus Mauritania (Lam.). The concentrates were: cotton seed cake, fishmeal, maize bran, soybean meal and sunflower cake. Mean CP and EE content (g/kg DM) were highest with the concentrates (310 and 97, respectively), followed by the legumes and browse trees (183 and 33, respectively) and lowest in the grasses (65 and 15, respectively). The OM and the CHO content varied least between the feed types. Mean NDF content (g/kg DM) was lower in the legumes/browse trees (378) and concentrates (314) compared to the grasses (698). The metabolic energy (ME) content (MJ/kg DM) in the feeds was highest with concentrate (11.9) and nearly of the same order in the grasses and legumes/browse trees (7.0). The organic matter digestibility using the conventional Tilley and Terry method and the enzymatic methods varied greatly among the feeds. The enzymatic method showed overall higher OM solubility values with some feeds compared to the in vitro organic matter digestibility method (overall mean of 63.4 Vs 53.2%). However, there was good agreement between the two methods with grasses (r2 = 0.80) compared to legumes/browse trees (r2= 0.34) and concentrates (r2=0.22). It is concluded that with increasing modernisation of ruminant livestock production in the tropics, there is a need to evaluate locally available feed resources and place the data in feedstuff tables in order that producers can select the feeds for optimal productivity.