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This article in CS

  1. Vol. 50 No. 2, p. 467-477
     
    Received: Feb 20, 2009


    * Corresponding author(s): p.setimela@cgiar.org
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doi:10.2135/cropsci2009.02.0089

Toward a Cost-Effective Fingerprinting Methodology to Distinguish Maize Open-Pollinated Varieties

  1. Marilyn L. Warburtona,
  2. Peter Setimela *b,
  3. Jorge Francoc,
  4. Hugo Cordovad,
  5. Kevin Pixleyd,
  6. Marianne Bänzigere,
  7. Susanne Dreisigackerd,
  8. Claudia Bedoyad and
  9. John MacRobertb
  1. a USDA ARS CHPRRU, Box 9555, Mississippi State, MS 39762
    b Maize Program, CIMMYT, P.O. Box MP 163, Harare, Zimbabwe
    c Facultad de Agronomía, Univ. de la Republica, Ave. Garzón 780, Montevideo, Uruguay
    d CIMMYT, Apdo. Postal 6-641, 06600 Mexico, D.F., Mexico
    e Maize Program, CIMMYT, P.O. Box 1041, Village Market-00621, ICRAF House, United Nations Ave., Kenya

Abstract

In Africa, many smallholder farmers grow open-pollinated maize (Zea mays L.) varieties (OPVs), which allow seed recycling and outyield traditional unimproved landraces. Seeds of productive OPVs are provided to farmers, often by nongovernmental organizations (NGOs) that help farmers access improved seeds, particularly following disasters in which original seed is lost. However, NGOs often rely on local seed suppliers to provide seed, and in some years the seeds provided to the farmers are suspected not to be of the promised variety. Here we present methodology to prove within a high level of confidence if two samples of seeds are the same genetic population or not, despite the difficulties involved in fingerprinting heterologous populations. In addition to heterogeneity within populations, difficulties can include sampling errors, differences in the fields or years in which the seeds were multiplied, and seed mixing. Despite these confounding sources of variation, we show the possibility to conclusively differentiate each of the populations used in this work. This methodology will allow breeders, seed companies, government agencies, and NGOs to ensure the purity and identity of high-yielding, locally adapted OPVs reach farmers so they can generate the highest yields possible in their fields.

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