Research Information System
Large Animal Review, vol.28, no.2, pp.93-99, 2022 (SCI-Expanded, Scopus)
The study aims to predict the cumulative egg production of Japanese quails’ by using linear regression, linear piecewise regres-sion, and multivariate adaptive regression splines algorithms including age at sexual maturity, weight at sexual maturity, average weight of the first ten eggs, and partial-egg records (20, 30, 40, 60, 80, 100, and 150 d partial-egg records). All the raw data were acquired from a total of 128 female quails. To compare prediction methods, the fit criterions of 15 different models were exam-ined, moreover the models were compared with the most common criterions. All prediction methods showed similar results, when the 40, 60, and 80 d partial-egg records included as independent variables in the models. Although the linear regression and the MARS algorithms inferred satisfying performance with 100 and 150 d of partial-egg records, the linear piecewise regression models gave a worse prophesying performance than others did. In conclusion, as an early (indirect) selection criterion, partial-egg records from d 100 can be successfully included as independent variable into the linear regression and MARS models to predict cumulative egg production.