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Closing Yield Gaps with GxExM and Precision Agriculture
1C. Walthall, 2J. Hatfield, 1S. Schneider, 3M. Vigil
1. USDA ARS Office of National Programs
2. USDA ARS National Laboratory for Agriculture and the Environment
3. USDA ARS Central Great Plains Research Station

There are many challenges to be faced by agriculture if the global population of nine billion people projected for 2050 is to be fed and clothed, especially given the effects of changing climate.  A focus on the interactions of genetics x environment x management (GxExM) offers potential for meeting the yield, and environment and economic sustainability goals that are integral to these challenges.  The yield gap –defined as the difference between current farmer yields and potential yields offered by advances of genetics and breeding, addresses all factors affecting yields and also when these factors affect yield during the growing season. A fundamental tenet of precision agriculture is that the dominant factors affecting yield gap are different for each growing region, landscape or within-field location and that there are temporal considerations when addressing these factors.  Precision agriculture is thus a way to close yield gaps using a GxExM approach.  However, understanding and quantifying yield gaps through a GxExM approach requires transdisciplinary teams of agronomists, engineers, soil scientists, geneticists, plant pathologists, entomologists, weed scientists, and human nutritionists to comprehensively evaluate all factors limiting production. Precision agriculture with a broadened participation by these and other disciplines will enable greater synthesis and integration of new knowledge into production systems that can be implemented via precision farming.  Further, aspirational production systems that include all we have learned about farming on the edge of the future, developed by transdisciplinary teams employing our best technology, may accelerate advances of agriculture to better meet the challenges of the future. 

Keyword: Genetics, water management, nutrient management, photosynthetic efficiency, yield gap, climate change, intensification, soil degradation, crop simulation models, phenotyping, precision agriculture, decision support, sustainable agriculture, environment, soil biology, soil management