Global Change Research Highlights: Climate, Irrigation, and Fertilization - Understanding U.S. Crop Yields

Results: Using corn and soybeans as their testing ground, researchers at Pacific Northwest National Laboratory devised methods to peer into the mechanisms that modulate crop yield variability. They used statistical models to examine how climate variability impacts yields of these popular bioenergy crops at the county level. Among climate factors, the team showed that temperature is predominant in corn-growing counties, both by volume and percentage of production. Precipitation has a similar impact. The amount of energy from the sun, or radiation, has a much smaller effect USA-wide on both soybeans and corn. To understand the impact of management practices, the research team designed and conducted numerical modeling to reveal how irrigation and fertilization affect crop yield variability. Averaged over the USA, fertilization has a larger impact than irrigation. The work demonstrated that dynamically determining fertilization timing and rates in their models can greatly improve the predictive capability for yields of both crops.

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Description

Results: Using corn and soybeans as their testing ground, researchers at Pacific Northwest National Laboratory devised methods to peer into the mechanisms that modulate crop yield variability. They used statistical models to examine how climate variability impacts yields of these popular bioenergy crops at the county level. Among climate factors, the team showed that temperature is predominant in corn-growing counties, both by volume and percentage of production. Precipitation has a similar impact. The amount of energy from the sun, or radiation, has a much smaller effect USA-wide on both soybeans and corn. To understand the impact of management practices, the research team designed and conducted numerical modeling to reveal how irrigation and fertilization affect crop yield variability. Averaged over the USA, fertilization has a larger impact than irrigation. The work demonstrated that dynamically determining fertilization timing and rates in their models can greatly improve the predictive capability for yields of both crops.

Classification
Resource Type
Format
Subject
Keyword Agriculture, Climate, fertilization, irrigation
Date Of Record Creation 2019-01-26 19:50:21
Education Level
Date Last Modified 1/26/2019 8:42
Language English
Date Record Checked: 1/26/2019 8:40 (W3C-DTF)

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