Comparison of Three Nonlinear Models for Describing Japanese Quail Growth Curve
Yazarlar (2)
M. Sezer
Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Prof. Dr. Sefa TARHAN Tokat Gaziosmanpaşa Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
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| Dergi Adı | Journal of Animal and Feed Sciences (Q4) | ||
| Dergi ISSN | 1230-1388 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2005 |
| Cilt / Sayı / Sayfa | 14 / 2 / 317–326 | DOI | 10.22358/jafs/67020/2005 |
| UAK Araştırma Alanları |
Tarımsal Otomasyon
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| Özet |
| This study has focused on the comparison of Richards, Gompertz and Logistic growth models (functions) for describing the growth characteristics of three meat-type lines of Japanese quail. The live body weight data of wild-type, doted-white and extended-brown quail lines over time were collected and fitted to the three non-linear equations. The prediction performance of the models was evaluated by statistical error tests: mean percentage error (MPE), mean bias error (MBE), root mean square error (RMSE), and confidence interval test (CIT) using the data of three out bred lines of Japanese quails (dotted white, extended brown and wild in plumage colour). The prediction performance of the growth functions for the quail growth curves depends on the line and sex of quails as shown by the results of statistical error tests. In general, Richards function predicted the weight of quails better than other two growth functions. Commonly used statistical error tests (MPE, MBE and RMSE) may not reflect the prediction performance of growth models as accurately as confidence interval test. Confidence interval tests generated likeness percentage values between 82.35 and 100% for Richards growth function. |
| Anahtar Kelimeler |
| Growth functions | Model selection | Quail | Statistical error test |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 6 |
| Scopus | 6 |
| Google Scholar | 9 |