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International Journal of Poultry Science

Year: 2020 | Volume: 19 | Issue: 4 | Page No.: 176-185
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Authors

O.A. Oyewale

O.A. Oyewale

O.O. Ojebiyi

O.O. Ojebiyi

F.A. Adedeji

O. Bamidele

E.B. Sonaiya

Keywords

Background and Objective: The African Chicken Genetic Gain-Nigeria (ACGG-NG) project members decided to develop a software application to formulate feed rations (feed app) because the available (foreign) feed apps were either too complex for small holders to operate or the feed libraries in such apps could not be edited to include local feed ingredients. The web version of the app is available at http://acggng.com.ng/, whereas the Windows, iOS and Android versions are available at the respective app stores. Materials and Methods: Locally-available feed resources in the project states were compiled into a feed library. The ACGG-NG app formulates rations for growers and layers using 50% of their crude protein requirements. The feed formulations are computed via a Pearson square ration formulation procedure that is enhanced by machine learning. A 10-week feeding trial was conducted involving 24 rural households where scavenging birds received app-formulated supplementation (ScAS) and were compared with scavenging birds that received farmer-formulated supplementation (ScFS) or no supplementation (ScNS) as well as a control group of confined birds that were fed proprietary diets (CPD). Results: The app is interactive and offers a way to formulate lower target quantities of the supplements when the available quantity of an ingredient is insufficient. The average daily gain of the ScAS growers was 49, 121 and 510% of that of the CPD, ScFS and ScNS growers, respectively. Conclusion: The feedapp allowed the use of locally-available feed resources to generate supplementary diets and the app-formulated supplementary diets resulted in enhanced growth in scavenging chickens.
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