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General Information

Document type
  • Peer-reviewed journal article
GE organism
  • cotton
GE trait
  • herbicide tolerance
Country
  • USA

Results

Equivalence
  • no effect

Principal variance component analysis of crop composition data: a case study on herbicide-tolerant cotton

Harrison, JM; Howard, D; Malven, M; Halls, SC; Culler, AH; Harrigan, GG; Wolfinger, RD
Journal of agricultural and food chemistry. 2013 May. 61(26):6412–6422

Link to full text (journal may charge for access)

PMID: 23647471 DOI: 10.1021/jf400606t ISSN: 0021-8561

Abstract

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.

Keywords

cotton (Gossypium spp.); genetically modified; genetically engineered; herbicide-tolerant; composition; principal variance component analysis; PVCA

Funding

Funding source
  • Monsanto
Funding country
  • United States
Funding type
  • industry: same

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Cite this study

MLA

Harrison, JM, D Howard, M Malven, SC Halls, AH Culler, GG Harrigan, RD Wolfinger. "Principal variance component analysis of crop composition data: a case study on herbicide-tolerant cotton." Journal of agricultural and food chemistry 61.26 (2013): 6412–6422. Web. 19 Nov. 2017.

APA

Harrison, JM., Howard, D., Malven, M., Halls, SC., Culler, AH., Harrigan, GG., & Wolfinger, RD. (2013). Principal variance component analysis of crop composition data: a case study on herbicide-tolerant cotton. Journal of agricultural and food chemistry, 61(26), 6412–6422. doi:10.1021/jf400606t

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