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Genetic fingerprinting using AFLP cannot distinguish traditionally classified baobab morphotypes

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Abstract

Baobab (Adansonia digitata L.) is one of the predominant tree species in West African agroforestry systems. A local morphological classification system is used by farmers, identifying trees with desired or undesired combinations of traits. This study evaluates the genetic significance of these morphotypes by comparing local identification with AFLP marker information. Eight morphotypes were recognized by seven ethnic groups from Benin, Ghana and Senegal, among 182 sampled baobab trees. Five primer pairs were used for DNA fingerprinting, resulting in a total of 254 scored bands, of which between 94.1% and 100% was polymorphic within morphotypes. Generally, genetic fingerprinting did not correlate with the traditional morphological identification of Adansonia digitata. Probably, AFLP markers are not directly linked to the differences in phenotype or the traits used for the traditional classification are largely dependent on environmental factors. Since no genetic differentiation is found between the morphotypes, a morphotype-based approach in the collection of genetic variation for conservation programs is not advisable.

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Acknowledgements

This work was supported by Bioversity International and Pioneer Hi-Bred International Inc., a Dupont Company, through the receipt of a Vavilov-Frankel Fellowship. We also thank DADOBAT-Project (EU-Funding) and The Rufford Maurice Laing Foundation for its additional financial support through The Rufford Small Grant for Nature Conservation as well as The King Leopold III Fund for Nature Conservation and Exploration for its financial support for the fieldwork in West Africa. We thank all these institutions and their donors. Our acknowledgements also go to local people of Benin, Ghana and Senegal and to Ir. Hugues Akpona (LEA-FSA-Benin), Dr. Dogo Seck (CERRAS-Senegal), Dr. Macoumba Diouf (ISRA-Senegal) and Mr. Joseph Mireku (FORIG-Ghana).

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Authors and Affiliations

  1. Laboratory of Applied Ecology, Faculty of Agronomic Sciences, University of Abomey-Calavi, 05 BP 1752, Cotonou, Benin

    A. E. Assogbadjo, F. J. Chadare & B. Sinsin

  2. Department of Molecular Biotechnology, Ghent University (UGent), Coupure Links 653, 9000, Ghent, Belgium

    T. Kyndt & G. Gheysen

  3. Institute for Plant Biotechnology for Developing Countries (IPBO), Ghent University, K.L. Ledeganckstraat 35, 9000, Ghent, Belgium

    T. Kyndt & G. Gheysen

  4. Bioversity International, c/o IITA, 08 BP 0932, Cotonou, Benin

    O. Eyog-Matig

  5. Laboratory of Tropical and Subtropical Agriculture and Ethnobotany, Department of Plant Production, Ghent University (UGent), Coupure links 653, 9000, Ghent, Belgium

    P. Van Damme

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  1. A. E. Assogbadjo
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  2. T. Kyndt
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  3. F. J. Chadare
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  5. G. Gheysen
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  6. O. Eyog-Matig
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  7. P. Van Damme
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Correspondence to T. Kyndt.

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A. E. Assogbadjo and T. Kyndt equally contributed to this work.

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Assogbadjo, A.E., Kyndt, T., Chadare, F.J. et al. Genetic fingerprinting using AFLP cannot distinguish traditionally classified baobab morphotypes. Agroforest Syst 75, 157–165 (2009). https://doi.org/10.1007/s10457-008-9157-y

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