Path and Ridge Regression Analysis of Seed Yield and Seed Yield Components of Russian Wildrye (Psathyrostachys juncea Nevski) under Field Conditions
The correlations among seed yield components, and their direct and indirect effects on the seed yield (Z) of Russina wildrye (Psathyrostachys juncea Nevski) were investigated. The seed yield components: fertile tillers m-2 (Y1), spikelets per fertile tillers (Y2), florets per spikelet- (Y3), seed nu...
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| Format: | Online |
| Language: | English |
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Public Library of Science
2011
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3078908/ |
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pubmed-30789082011-04-29 Path and Ridge Regression Analysis of Seed Yield and Seed Yield Components of Russian Wildrye (Psathyrostachys juncea Nevski) under Field Conditions Wang, Quanzhen Zhang, Tiejun Cui, Jian Wang, Xianguo Zhou, He Han, Jianguo Gislum, René Research Article The correlations among seed yield components, and their direct and indirect effects on the seed yield (Z) of Russina wildrye (Psathyrostachys juncea Nevski) were investigated. The seed yield components: fertile tillers m-2 (Y1), spikelets per fertile tillers (Y2), florets per spikelet- (Y3), seed numbers per spikelet (Y4) and seed weight (Y5) were counted and the Z were determined in field experiments from 2003 to 2006 via big sample size. Y1 was the most important seed yield component describing the Z and Y2 was the least. The total direct effects of the Y1, Y3 and Y5 to the Z were positive while Y4 and Y2 were weakly negative. The total effects (directs plus indirects) of the components were positively contributed to the Z by path analyses. The seed yield components Y1, Y2, Y4 and Y5 were significantly (P<0.001) correlated with the Z for 4 years totally, while in the individual years, Y2 were not significant correlated with Y3, Y4 and Y5 by Peason correlation analyses in the five components in the plant seed production. Therefore, selection for high seed yield through direct selection for large Y1, Y2 and Y3 would be effective for breeding programs in grasses. Furthermore, it is the most important that, via ridge regression, a steady algorithm model between Z and the five yield components was founded, which can be closely estimated the seed yield via the components. Public Library of Science 2011-04-18 /pmc/articles/PMC3078908/ /pubmed/21533153 http://dx.doi.org/10.1371/journal.pone.0018245 Text en Wang et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Wang, Quanzhen Zhang, Tiejun Cui, Jian Wang, Xianguo Zhou, He Han, Jianguo Gislum, René |
| spellingShingle |
Wang, Quanzhen Zhang, Tiejun Cui, Jian Wang, Xianguo Zhou, He Han, Jianguo Gislum, René Path and Ridge Regression Analysis of Seed Yield and Seed Yield Components of Russian Wildrye (Psathyrostachys juncea Nevski) under Field Conditions |
| author_facet |
Wang, Quanzhen Zhang, Tiejun Cui, Jian Wang, Xianguo Zhou, He Han, Jianguo Gislum, René |
| author_sort |
Wang, Quanzhen |
| title |
Path and Ridge Regression Analysis of Seed Yield and Seed Yield
Components of Russian Wildrye (Psathyrostachys juncea Nevski)
under Field Conditions |
| title_short |
Path and Ridge Regression Analysis of Seed Yield and Seed Yield
Components of Russian Wildrye (Psathyrostachys juncea Nevski)
under Field Conditions |
| title_full |
Path and Ridge Regression Analysis of Seed Yield and Seed Yield
Components of Russian Wildrye (Psathyrostachys juncea Nevski)
under Field Conditions |
| title_fullStr |
Path and Ridge Regression Analysis of Seed Yield and Seed Yield
Components of Russian Wildrye (Psathyrostachys juncea Nevski)
under Field Conditions |
| title_full_unstemmed |
Path and Ridge Regression Analysis of Seed Yield and Seed Yield
Components of Russian Wildrye (Psathyrostachys juncea Nevski)
under Field Conditions |
| title_sort |
path and ridge regression analysis of seed yield and seed yield
components of russian wildrye (psathyrostachys juncea nevski)
under field conditions |
| description |
The correlations among seed yield components, and their direct and indirect
effects on the seed yield (Z) of Russina wildrye (Psathyrostachys
juncea Nevski) were investigated. The seed yield components:
fertile tillers m-2 (Y1), spikelets per fertile tillers
(Y2), florets per spikelet- (Y3), seed
numbers per spikelet (Y4) and seed weight (Y5) were
counted and the Z were determined in field experiments from 2003 to 2006 via big
sample size. Y1 was the most important seed yield component
describing the Z and Y2 was the least. The total direct effects of
the Y1, Y3 and Y5 to the Z were positive while
Y4 and Y2 were weakly negative. The total effects
(directs plus indirects) of the components were positively contributed to the Z
by path analyses. The seed yield components Y1, Y2,
Y4 and Y5 were significantly (P<0.001) correlated
with the Z for 4 years totally, while in the individual years, Y2
were not significant correlated with Y3, Y4 and
Y5 by Peason correlation analyses in the five components in the
plant seed production. Therefore, selection for high seed yield through direct
selection for large Y1, Y2 and Y3 would be
effective for breeding programs in grasses. Furthermore, it is the most
important that, via ridge regression, a steady algorithm model between Z and the
five yield components was founded, which can be closely estimated the seed yield
via the components. |
| publisher |
Public Library of Science |
| publishDate |
2011 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3078908/ |
| _version_ |
1611449719981080576 |