Selecting the ideotype of improved rice cultivars using multiple regression and multivariate models
Plant breeders require a classification of the limitations and the capabilities that exist in plants by appropriate statistical methods; this issue leads to the concept of the ideotype. Therefore, the aim of this research was to determine the ideotype of improved rice cultivars. The experiment was c...
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Published in: | Archiv für Acker- und Pflanzenbau und Bodenkunde Vol. 66; no. 8; pp. 1134 - 1153 |
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Main Authors: | , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Abingdon
Taylor & Francis
02-07-2020
Taylor & Francis Ltd |
Subjects: | |
Online Access: | Get full text |
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Summary: | Plant breeders require a classification of the limitations and the capabilities that exist in plants by appropriate statistical methods; this issue leads to the concept of the ideotype. Therefore, the aim of this research was to determine the ideotype of improved rice cultivars. The experiment was carried out based on a randomized complete blocks design with three replications and 13 improved rice cultivars in northern Iran in 2016 and 2017, the required data for determining ideotype was collected. The results demonstrated that the optimal values of six important traits which selected by the multiple regression model explained 64% of the paddy yield (PY). The determined ideotype would increase PY from 6,623 kg ha
−1
to 8764-9685 kg ha
−1
. Selection of desirable phenological traits revealed the highest correlation with the first canonical variable, can cause of selection of superior cultivars with the best agronomic traits. The most genetic distance was observed between cv. 'Kados', 'Shiroodi' and 'Dasht' using mahalanobis method. It was concluded that the methods used in this study, owing to its concern with the genetic variations between cultivars, can be used in determining plant ideotypes in conjunction with other methods and it can guide plant breeders to move through ideotype crops. |
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ISSN: | 0365-0340 1476-3567 |
DOI: | 10.1080/03650340.2019.1658866 |