Short communication. Decision on germplasm choice to apply breeding within a local population of common vetch is affected by crowding

  • Th. Chatzoglou Department of Agricultural Development, Democritus University of Thrace. 682 00 Orestiada.
  • I. S. Tokatlidis Department of Agricultural Development, Democritus University of Thrace. 682 00 Orestiada.
Keywords: competitive ability, genetic heterogeneity, local population, Vicia sativa, yielding ability

Abstract

The value of a population as a potential gene pool on which to apply selection may be severely underestimated under competition conditions because of the negative correlation of competitive versus yielding ability. To address this issue, a vetch (Vicia sativa) local population along with a control cultivar was evaluated at densities ranging from 1.15 to 25 plants m-2. A hyperbolic increasing pattern as density declined was found for both grain and biomass yield. Nevertheless, at the highest density the control cultivar performance exceeded the population, whereas at the lowest density the opposite happened. The results were attributed to the heterogeneity of the population versus the homogeneity of the cultivar combined with the aforementioned negative relationship. It was concluded that severe crowding undervalues the potential of a population because plants representing high yielders cannot exhibit this capacity due to their competitive disadvantage. On the other side, the absence of competition optimizes the yield expression of individual plants. Therefore, absence of competition is recommended as the optimal condition to evaluate populations and make the right decision on the most promising one for breeding.

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Published
2012-06-21
How to Cite
Chatzoglou, T., & Tokatlidis, I. S. (2012). Short communication. Decision on germplasm choice to apply breeding within a local population of common vetch is affected by crowding. Spanish Journal of Agricultural Research, 10(3), 752-755. https://doi.org/10.5424/sjar/2012103-641-11
Section
Plant breeding, genetics and genetic resources