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Agroforestry Systems

, Volume 4, Issue 4, pp 291–314 | Cite as

Multipurpose tree yield data — their relevance to agroforestry research and development and the current state of knowledge

  • Peter G. von Carlowitz
Article

Abstract

Agroforestry is not likely to be accepted, particularly by small-holders, unless it is proved superior to other forms of land use not only on ecological but also on economic grounds. It is therefore argued that economic parameters concerning the quantitative productivity of all agroforestry systems components have to be a matter of concern to both research and development in agroforestry.

In the process of screening selected relevant literature and as a result of a search of ICRAF's Multipurpose Tree and Shrub Data Case, the yawning gap between the high level of knowledge on agricultural crops on the one hand and the low level on woody perennials on the other is exposed as a serious obstacle to the analysis of agroforestry systems and to the further development of agroforestry. The lack of knowledge on woody perennials, as substantiated in this paper, concerns particularly quantitative production data on trees and shrubs used in agroforestry systems.

It is also argued in support of the views cited from other authors that what little there is by way of yield data on woody perennials is scattered and distributed over a vast amount of literature, and thus often difficult to access and to retrieve, and often difficult if not impossible to compare owing to different methods and parameters employed in attaining the data.

Although the difficulties of yield assessment are appreciated, increased efforts to obtain more — and more comparable — data on te productivity of woody perennials are advocated. In support of this call for stepping up appropriate activities some preliminary suggestions are presented on how to standardize parameter of yield assessments to achieve better comparability and how to increase accessibility of yield data and promote retrieval of data by the establishment of supplementary data bases.

Keywords

Yield Data Supplementary Data System Component Production Data Relevant Literature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Martinus Nijhoff/Dr W. Junk Publishers 1986

Authors and Affiliations

  • Peter G. von Carlowitz
    • 1
  1. 1.International Council for Research in AgroforestryNairobiKenya

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