Adaptive Lasso Analysis for Grain Yield and Yield Components in Two-Rowed Barley Under Rainfed Conditions
dc.authorscopusid | 57190837087 | |
dc.authorscopusid | 57192097504 | |
dc.authorscopusid | 24467005900 | |
dc.authorwosid | Akkol, Suna/Abn-9576-2022 | |
dc.authorwosid | Yağmur, Mehmet/Jxn-8729-2024 | |
dc.contributor.author | Akkol, Suna | |
dc.contributor.author | Arpali, Digdem | |
dc.contributor.author | Yagmur, Mehmet | |
dc.date.accessioned | 2025-05-10T17:03:32Z | |
dc.date.available | 2025-05-10T17:03:32Z | |
dc.date.issued | 2018 | |
dc.department | T.C. Van Yüzüncü Yıl Üniversitesi | en_US |
dc.department-temp | [Akkol, Suna] Van Yuzuncu Yil Univ, Dept Anim Sci, Biometry & Genet Unit, Fac Agr, Van, Turkey; [Arpali, Digdem] Van Yuzuncu Yil Univ, Dept Field Crops, Fac Agr, Van, Turkey; [Yagmur, Mehmet] Ahi Evran Univ, Dept Field Crops, Fac Agr, Kirsehir, Turkey | en_US |
dc.description.abstract | 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. | en_US |
dc.description.woscitationindex | Science Citation Index Expanded | |
dc.identifier.doi | 10.7546/CRABS.2018.09.17 | |
dc.identifier.endpage | 1287 | en_US |
dc.identifier.issn | 1310-1331 | |
dc.identifier.issue | 9 | en_US |
dc.identifier.scopus | 2-s2.0-85055159623 | |
dc.identifier.scopusquality | Q3 | |
dc.identifier.startpage | 1279 | en_US |
dc.identifier.uri | https://doi.org/10.7546/CRABS.2018.09.17 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14720/5728 | |
dc.identifier.volume | 71 | en_US |
dc.identifier.wos | WOS:000451496900017 | |
dc.identifier.wosquality | Q4 | |
dc.language.iso | en | en_US |
dc.publisher | Publ House Bulgarian Acad Sci | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Lasso Regression | en_US |
dc.subject | Variable Selection | en_US |
dc.subject | Shrinkage Methods | en_US |
dc.subject | Two Rowed Barley | en_US |
dc.subject | Grain Yield | en_US |
dc.title | Adaptive Lasso Analysis for Grain Yield and Yield Components in Two-Rowed Barley Under Rainfed Conditions | en_US |
dc.type | Article | en_US |