Analyzing individual chickens' life data to predict egg and growth performance

Abstract

The 2022 ban on killing male chicks, implemented in Germany and France, tackled ethical problems within egg-laying hen farming. Because of this policy, alternative poultry production methods were created to better meet animal welfare guidelines. To meet this challenge, the University of Bonn launched research into dual-purpose chickens, specifically the British Ixworth breed. Integrating male and female chicken farming offers a new, innovative solution to ethical and sustainability issues in traditional farming by combining egg and meat production. The importance of this research for revolutionizing poultry farming cannot be overstated (Becker et al., 2023). A University of Bonn research team is studying this alternative farming method to determine its productivity and viability. To meet industry needs while prioritizing animal welfare, they evaluate dual-purpose chicken potential by analysing egg (number and weight) and meat (weight) yields. This thesis has four sections, exploring different facets of dual-purpose chickens across four generations via diverse statistical and machine learning methods. First, it examines existing research on various facets of analysing and forecasting individual chicken egg and growth data. It further explores Becker et al.’s 2023 study, “The British Ixworth: individual growth and egg production of a purebred dual-purpose chicken.” Moreover, the linear regression, SVR, KNN, and decision tree models were applied to this data for advanced analysis and prediction. The thesis’s second part details the methodology, including requirements analysis and dataset preparation. This thesis's third section details how data from four generations of chicken life were analysed to predict future egg production and individual chicken growth. Across generations, individual chickens' average body weight and egg weight all showed an increase in the results. Predictions from linear regression and decision tree models show an increase in individual chickens' growth across generations to come. Egg production forecasts were better with the KNN model. This research will use advanced statistical methods and machine learning to model and assess the generational performance of dual-purpose chickens. These tools will forecast future egg and meat production, thus giving key insights to enhance breeding programs. This research aims to optimize dual-purpose chicken production for growth and egg-laying performance. The researchers eagerly anticipate the results, which will help to shape their future poultry farming projects