Sensing corn population – another variable in the yield equation

J. W. Hummel, United States Department of Agriculture
B. M. Lobdell, University of Illinois
K. A. Sudduth, United States Department of Agriculture
Stuart J. Birrell, Iowa State University

This proceeding is published as Hummel, J. W., B. M. Lobdell, K. A. Sudduth, and S. J. Birrell. "Sensing corn population — another variable in the yield equation." In Proceedings of the 2001 InfoAg Conference, Indianapolis, IN (August 7-9, 2001).


Crop yield maps are required to evaluate the economic efficiency of spatial production systems and are an important part of the site-specific decision-making process. However, plant population has a significant effect on yield potential and with the exception of climatic conditions, plant population can be the predominant factor limiting crop yields. Therefore, sensor-derived maps of plant population can be useful for interpreting the effect of other limiting factors on yield, and can provide important information for developing site-specific management plans.

We designed and fabricated a mechanical sensor that counted corn plants as they entered the gathering chains of a combine header. We evaluated the performance of this corn population sensor over multiple years and locations. When compared to hand counts obtained at harvest, the sensors tended to slightly underestimate actual population. Errors were minimized when the combine header was operated close to the ground surface and at speeds no greater than 4.5 mph. Sensor evaluation in corn seeded at various rates revealed an increasing underestimation error with increasing population. This error was a linear function of the corn stalk feed rate past the sensor. After compensation was applied, sensed population was an excellent estimator of actual, hand-counted population (r2 = 0.93, zero mean error). Standard errors of population estimates were 802 plants/ac at feed rates below 9 plants/s and 1700 plants/ac at feed rates above 9 plants/s.

A photoelectric sensor, capable of estimating plant diameter and plant spacing as well as population, was developed and field tested on a 4-row combine corn head. An emitter and receiver pair produced the signal used to measure the in-row distance between plants to provide information on plant spacing, skips, and doubles. An air-jet system was fitted onto the header to move corn leaves and other debris away from the sensor area. Data were collected at harvest with the sensor and compared with manually collected plant distance and diameter data. Plant spacing and stalk diameter were used in software filtering to remove erroneous plant counts due to weeds and plant leaves. Data were post-processed to compare with manually collected plant diameters and spacings, and filtering techniques were developed to improve diameter, spacing, and population estimation. The higher air speed levels decreased false optical counts caused by leaves and weeds and produced more accurate estimates of plant population.