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2021
DOI: 10.22271/09746315.2021.v17.i2.1462
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Multivariate analysis of maize genotypes grown under waterlogging stress

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Cited by 2 publications
(3 citation statements)
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“…To accurately examine phenotypic traits produced by highly computational modelling of multidimensional data and to offer a more thorough knowledge of the complex mechanisms under salt stress, a combination of analyses must be used (Singh & Sastry 2011; Sanwal et al, 2022). To preserve as much information as possible, PCA, for example, lowers the number of variables in a data collection and uses an orthogonal transformation to turn a set of observations of potentially correlated variables into a set of values of uncorrelated variables (Kumawat et al, 2021; Sabouri et al, 2022).…”
Section: Introductionmentioning
confidence: 99%
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“…To accurately examine phenotypic traits produced by highly computational modelling of multidimensional data and to offer a more thorough knowledge of the complex mechanisms under salt stress, a combination of analyses must be used (Singh & Sastry 2011; Sanwal et al, 2022). To preserve as much information as possible, PCA, for example, lowers the number of variables in a data collection and uses an orthogonal transformation to turn a set of observations of potentially correlated variables into a set of values of uncorrelated variables (Kumawat et al, 2021; Sabouri et al, 2022).…”
Section: Introductionmentioning
confidence: 99%
“…The effectiveness of multivariate analysis and selection by CSI was examined as well as the outcomes of both analyses. Different stress indices, correlation analysis, and multivariate analysis of variance are examples of screening techniques with their advanced forms that may be used as a combined method of screening tests and for identifying sources of variation (Kumawat et al, 2021; Sabouri et al, 2022). The main objectives of this research were: (1) to create a screening procedure to know the effect of salt stress on morpho‐physio and seed quality traits, (2) to create a procedure for selection of best indices to pinout the salt tolerant lines based on association study, (3) to assess 250 RILs for multivariate analysis based on 54 STI, (4) to exploit a new index: CSI and compare its results with PCA for final screening of RILs mapping population to select salt tolerate RILs.…”
Section: Introductionmentioning
confidence: 99%
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