ADAPTIVE LASSO ANALYSIS FOR GRAIN YIELDAND YIELD COMPONENTS IN TWO-ROWEDBARLEY UNDER RAINFED CONDITIONS
Yazarlar (3)
Van Yüzüncü Yıl Üniversitesi, Türkiye
Van Yüzüncü Yıl Üniversitesi, Türkiye
Prof. Dr. Mehmet YAĞMUR
Kırşehir Ahi Evran Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Comptes Rendus De L Academie Bulgare Des Sciences | ||
| Dergi ISSN | 1310-1331 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2018 |
| Cilt / Sayı / Sayfa | 71 / 9 / 1279–1287 | DOI | 10.7546/CRABS.2018.09.17 |
| Özet |
| The goal of this study was to determine the yield components related to grain yield in order to improve barley yield under rainfed conditions of Turkey (Van). Stepwise and Adaptive Lasso methods were performed for selection of most significant yield components. As cohesion criteria to compare Stepwise and Adaptive Lasso methods, the adjusted coefficient of determination and Akaike Information Criterion were used. Results revealed that when there were dependencies between independent variables stepwise and Adaptive Lasso achieved the same results. It has been determined that spike number per m(2) and grain weight per spike can be used as the most effective selection criteria for barley breeding studies due to their significant effects on grain yield. |
| Anahtar Kelimeler |
| lasso regression | variable selection | shrinkage methods | two rowed barley | grain yield |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| WoS | 1 |
| SCOPUS | 2 |
| Google Scholar | 4 |