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This article in CS

  1. Vol. 48 No. 1, p. 203-212
     
    Received: Mar 26, 2007


    * Corresponding author(s): bhorneb@gwdg.de
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doi:10.2135/cropsci2007.03.0170

Crop Adaptation in On-Farm Management by Natural and Conscious Selection: A Case Study with Lentil

  1. Bernd Horneburg * and
  2. Heiko C. Becker
  1. Dep. of Crop Sciences, Univ. of Göttingen, Von-Siebold-Str. 8, 37075 Göttingen, Germany

Abstract

On-farm management of landraces or older cultivars of crop plants is often recommended to combine conservation and use of genetic resources, but experimental studies on on-farm management are hard to find, particularly in industrialized countries. To investigate whether on-farm management results in regional adaptation and enhances crop biodiversity, an experiment with lentils (Lens culinaris Medik.) was designed. Lentil production has almost ceased to exist in central Europe, but lentils may still be found in gene banks and have remained a popular food. Three landraces were evaluated on three farms in Germany; at each farm, three populations evolved, based on three selection methods: (i) natural selection, (ii) visual mass selection, and (iii) selection for yield of single plant progenies. These selection methods were applied for two to four years. The nine populations developed for each landrace (three methods × three locations) were grown in a comparative trial on two of the farms. In most cases, populations selected at a specific location were at this location superior in yield to populations selected at other locations, indicating that on-farm management can result in site-specific adaptation. Significant changes in morphological and phenological traits occurred. For one landrace, natural selection increased seed weight. The response to different selection methods largely depended on landrace and selection site, and no method was generally superior. In conclusion, on-farm management is a useful approach to maintain, use, and develop plant genetic resources. Natural selection as the most cost-efficient method is recommended.

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