Principal variance component analysis of crop composition data: a case study on herbicide-tolerant cotton
| Autor: | Jay M. Harrison, Steven C. Halls, George G. Harrigan, Delia Howard, Marianne Malven, Angela Hendrickson Culler, Russell D. Wolfinger |
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| Rok vydání: | 2013 |
| Předmět: |
Germplasm
Crops Agricultural Multivariate statistics Gossypium Principal Component Analysis business.industry Genetically engineered Herbicides Principal (computer security) Variance component analysis Drug Resistance General Chemistry Plants Genetically Modified United States Biotechnology Crop Frequentist inference Seeds Analysis of variance General Agricultural and Biological Sciences business Mathematics |
| Zdroj: | Journal of agricultural and food chemistry. 61(26) |
| ISSN: | 1520-5118 |
| Popis: | Compositional studies on genetically modified (GM) and non-GM crops have consistently demonstrated that their respective levels of key nutrients and antinutrients are remarkably similar and that other factors such as germplasm and environment contribute more to compositional variability than transgenic breeding. We propose that graphical and statistical approaches that can provide meaningful evaluations of the relative impact of different factors to compositional variability may offer advantages over traditional frequentist testing. A case study on the novel application of principal variance component analysis (PVCA) in a compositional assessment of herbicide-tolerant GM cotton is presented. Results of the traditional analysis of variance approach confirmed the compositional equivalence of the GM and non-GM cotton. The multivariate approach of PVCA provided further information on the impact of location and germplasm on compositional variability relative to GM. |
| Databáze: | OpenAIRE |
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