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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #167223

Title: SITE-SPECIFIC RELATIONSHIPS BETWEEN CORN POPULATION AND YIELD

Author
item Sudduth, Kenneth - Ken
item BIRRELL, STUART
item BOLLERO, GERMAN
item BULLOCK, DONALD
item Hummel, John
item Kitchen, Newell

Submitted to: International Conference on Precision Agriculture Abstracts & Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 7/13/2004
Publication Date: 7/1/2005
Citation: Sudduth, K.A., Birrell, S.J., Bollero, G.A., Bullock, D.G., Hummel, J.W., Kitchen, N.R. 2005. Site-specific relationships between corn population and yield. In: Mulla, D.J., editor. Proceedings of the 7th International Conference on Precision Agriculture, July 25-28, 2004. Precision Agriculture Center, University of Minnesota, St. Paul, MN. [unpaginated CDROM]

Interpretive Summary: Precision agriculture is a crop management strategy that seeks to address within-field variability. Understanding how variability in crop yield relates to variability in other plant, soil, and landscape factors is an important step toward developing appropriate precision management plans. Research has documented varying relationships of corn yield to plant population ' some studies have found little if any effect, while others have reported a strong relationship. Using a combine-mounted sensor we previously developed, we collected corn population data at harvest, and assessed the yield-population relationship for individual fields. We collected population data over multiple years on fields in Missouri and Illinois. We also obtained corn yield monitor data and measured soil and landscape properties to compare with the population data. Variability of corn population at harvest was large, and population levels were often much lower than the target planting rate, meaning that many plants did not emerge, or died during the growing season. Population was not strongly related to measured soil and landscape properties. Other, unmeasured factors (for example, insects or diseases) may have been responsible for the variable emergence and/or loss of plants during the season. Only for fields and years where growing conditions were good and where average population was not high did population variation have a significant effect on corn yield. This study can benefit researchers, consultants, and producers who want to understand yield-population relationships as a step toward developing variable-rate seeding strategies. Unfortunately, the data collected here did not show strong and stable relationships of population to yield and to soil and landscape properties. However, applying similar methods to data from refined sensors, operated over more fields, may better define these relationships, so that they can be used to guide variable-rate seeding.

Technical Abstract: Corn yield, harvest population, and soil and landscape data were collected for 8 site-years in Missouri and Illinois. Population was measured with mechanical sensors on the combine and provided data at the same spatial density as the yield map. Population variability within fields was large, and harvest populations were as much as 40% lower than seeding rate. Population and stand loss were not strongly related to soil (i.e., fertility, organic matter, and apparent soil electrical conductivity, ECa) and landscape (i.e., slope, elevation) properties. However, the fraction of missing plants in a grid was related to ECa, organic matter, P, and K during the one site-year where missing plant data was available. Relationships between corn yield and population were variable, with population representing at most 15% of the yield variability within a field. Using a boundary line analysis, significant relationships between maximum yield and population were found for 4 out of 8 site-years. Mapped harvest population can help interpret within-field variations in yield. However, for the site-years investigated here, the relationships of population to yield and soil and landscape properties were not strong or stable enough to suggest using these data to develop variable-rate seeding strategies.