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ADAPTIVE LASSO ANALYSIS FOR GRAIN YIELDAND YIELD COMPONENTS IN TWO-ROWEDBARLEY UNDER RAINFED CONDITIONS     
Yazarlar
Suna Akkol
Van Yüzüncü Yıl Üniversitesi, Türkiye
Diğdem Arpali
Van Yüzüncü Yıl Üniversitesi, Türkiye
Prof. Dr. Mehmet YAĞMUR Prof. Dr. Mehmet YAĞMUR
Kırşehir Ahi Evran Üniversitesi, Türkiye
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
Makale Türü Özgün Makale
Makale Alt Türü SSCI, AHCI, SCI, SCI-Exp dergilerinde yayımlanan tam makale
Dergi Adı COMPTES RENDUS DE L ACADEMIE BULGARE DES SCIENCES
Dergi ISSN 1310-1331
Dergi Tarandığı Indeksler SCI-Expanded
Makale Dili İngilizce
Basım Tarihi 01-2018
Cilt No 71
Sayı 9
Sayfalar 1279 / 1287
Doi Numarası 10.7546/CRABS.2018.09.17