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[其他] Plackett-Burman (PB) design;统计分析 [推广有奖]

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nihaohc 发表于 2016-11-12 08:48:32 |AI写论文

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以下是投稿编辑给的回复,请问如何回复编辑的问题??The current work describes the investigation of the factors influencing chromosome doubling induced by in vitro colchicines treatment in axillary buds of a Eucalyptus hybrid clone (DH201-2, between Eucalyptus grandis × E. tereticornis). The most significant factors influencing tetraploidy induction were determined by fractional factorial design Plackett-Burman. Response surface methodology, using the Uniform design, was employed to model the data and estimate potential maximum effectiveness of chemically inducing polyploidy in the hybrid genotype.
Concerning the methodological aspects of the manuscript, there are some crucial issues:
Inconsistencies in the statistical methods employed to analyze/model the data for colchicines mediated genome doubling in the Eucalyptus hybrid:
1. Plackett-Burman (PB) design - in chemically induced genome doubling, the factors in PB design proposed by the author have been demonstrated to have significant (non negligible) interactions, e.g. anti-mitotic agent concentration x treatment duration, anti-mitotic agent concentration x treatment temperature, anti-mitotic agent concentration x explants developmental stage, etc. In the presence of significant interactions, PB designs are subjected to aliasing or confounding, thus, it is not possible to distinguish between main effects and interactions for all tested factors.
2. Plackett-Burman (PB) design - besides the aliasing present in the design, the number of factors (7) is at the highest limit for the lowest acceptable number of runs (12), so that each combination of two factors is present only three times in the design.
3. Response Surface Methodology (RSM) - modeling was performed using data from a single experiment (Material and Methods, page 5, lines 184-185) with 50 explants. It is not possible to estimate the variability associated to the biological process. Moreover, RSM requires iterative and sequential experiments for realistic results in data modeling. Fit to higher order models is not presented in the manuscript.
4. Whole genome duplication using chemical agents is a multiple response process (at least, two responsive variables: plant survival and chromosome number doubling). The single responsive variable analyzed in the work (induction rate %, Material and Methods, pages 5-6, lines199-212), does not an accurately represent the biological process under investigation.

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关键词:Design 统计分析 lack sign ESI describes potential between current factors

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blushpeony 发表于 2016-11-14 13:45:15
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