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Toward evidence-based decision support systems to optimize pollination and yields in highbush blueberry

Highbush blueberry (Vaccinium spp.) is a globally important fruit crop that depends on insect-mediated pollination to produce quality fruit and commercially viable yields. Pollination success in blueberry is complex and impacted by multiple interacting factors including flower density, bee diversity and abundance, and weather conditions. Other factors, including floral traits, bee traits, and economics also contribute to pollination success at the farm level but are less well understood. As blueberry production continues to expand globally, decision-aid technologies are needed to optimize and enhance the sustainability of pollination strategies. The objective of this review is to highlight our current knowledge about blueberry pollination, where current research efforts are focused, and where future research should be directed to successfully implement a comprehensive blueberry pollination decision-making framework for modern production systems. Important knowledge gaps remain, including how to integrate wild and managed pollinators to optimize pollination, and how to provide predictable and stable crop pollination across variable environmental conditions. In addition, continued advances in pesticide stewardship are required to optimize pollinator health and crop outcomes. Integration of on- and off-farm data, statistical models, and software tools could distill complex scientific information into decision-aid systems that support sustainable, evidence-based pollination decisions at the farm level. Utility of these tools will require multi-disciplinary research and strategic deployment through effective extension and information-sharing networks of growers, beekeepers, and extension/crop advisors.