Employing logistic model to predict the egg production of quails receiving digestibility enhancer supplementation

Abstract

This study aimed to predict the egg production of quails supplemented with a combination of betaine and silica+. Three hundred and fifty laying quails were divided into two dietary treatments and seven replicates of 25 quails. The treatments consisted of control (T0), and supplementation with digestibility enhancer mixture consisted of 0.12% betaine and 200 ppm silica+ (T1). Egg production data were collected for three periods of 28 days, and they were subjected to T-test. The data were plotted to obtain the egg production curve. A logistic regression model was employed to identify the trend of the egg production pattern. The T1 groups produced more eggs than T0 groups (P<0.05), which attributed to the higher egg production during period II and III (P<0.01). The egg production curves indicated that production rose sharply soon after the beginning of lay. The T1 groups had a higher peak production than T0 (76.43% vs 69.20%). Furthermore, production rate was 0.17 and 0.18 and prediction accuracy was 97% and 98% for T0 and T1, respectively. Thus, the logistic model proved to be employed to analyse the biological impact of egg production in quails with a high prediction accuracy.