294-4 Temporal and Spatial Trends in Winter Wheat Yields Monitored Via Multiple Online Data Sources.

Poster Number 226

See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: Biometry and Statistical Computing: II

Tuesday, November 17, 2015
Minneapolis Convention Center, Exhibit Hall BC

Peter Claussen, 307 4th Street, Gylling Data Management, Brookings, SD
Abstract:
Recent studies have suggested that crop yields gains have slowed or stagnated in many regions globally. However, a simple analysis of winter wheat yield in the central United States shows that while yield gains have slowed for some (southern) regions, relative to mid-century gains, yield improvement have accelerated in other (northern) regions. This implies a shift in winter wheat productions zones, perhaps related to climate change. Determining the real effect of climate change requires correlating yield changes with many other spatially based covariates. These include variables relating to fertility, innovation and policy, and economics in addition to climate data. These factors should be analyzed at the most detailed geographical scale possible.

Yield data at the county level is available from the USDA NASS (National Agricultural Statistics Service) via a web based SQL query. Integration of yield data with other available data, taken at the county level, is more difficult. Environmental data are available from the CDC (Centers for Disease Control and Prevention) using a web browser interface. Similar climate data can be obtained using FTP from the NOAA (National Oceanic and Atmospheric Administration). The IPNI (International Plant Nutrition Institute) provides soil fertility data in in single large Microsoft Excel file format, while yearly summary data for wheat variety testing in the Hard Winter Wheat Performance Nursery program are available in single Excel or PDF files, one per year.

The availability of large, county level data sets provides opportunities for study of factors influencing agronomic performance of a wide range of crops, but lack of common data structure hinders repeated analysis of such data. A geospatial analysis of winter wheat yield trends and associated covariates is presented to illustrate the benefits and challenges of an integrated analysis of multiple data sets.

See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: Biometry and Statistical Computing: II

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