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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

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