Germplasm Development of Underutilized Temperate U.S. Tree Crops
In the Midwest U.S. dominated corn-soybean landscape, agroforestry systems can be particularly valuable for increasing the provisioning and regulatory capacity of the agricultural landscape. However, these systems have not yet been broadly integrated into the landscape of this region since they are...
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Veröffentlicht in: | Sustainability 2019, Vol.11 (6), p.1546 |
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Sprache: | eng |
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Zusammenfassung: | In the Midwest U.S. dominated corn-soybean landscape, agroforestry systems can be particularly valuable for increasing the provisioning and regulatory capacity of the agricultural landscape. However, these systems have not yet been broadly integrated into the landscape of this region since they are mostly relegated to marginal lands. A growing body of literature suggests a path to increase the adoption of agroforestry in the Midwest U.S. lies in the incorporation of low-input food-producing tree species that provide economic incentives for farmers. Studies of the system-level integration of such approaches have proceeded by using the currently available cultivars and breeding selections of various tree nut and fruit species. While existing varieties and breeding selections provide the opportunity for initial system development and integration, their broad adaptability to the Midwest U.S. and its marginal land-types is unexplored. Thus, a second tier of research includes the genetic improvement and adaptation of tree crop selections to their respective target environments throughout the Midwest U.S. Fortunately, select tree crops of interest are amendable to systematic breeding and have wild relatives that are endemic across the region. In this paper, we discuss the value of these wild relatives for broadening the adaption of cultivated tree crop selections by using the hazelnut as an example species. We present a framework using geospatial tools to define and prioritize target environments for breeding and, in turn, exploiting wild relative germplasm. |
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ISSN: | 2071-1050 2071-1050 |
DOI: | 10.3390/su11061546 |