Agricultural and Biosystems Engineering Publications

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Applied Engineering in Agriculture





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Research Focus Area(s)

Advanced Machinery Engineering and Manufacturing Systems


An effective corn plant population and spacing sensing system may provide a key layer of field variability information useful for crop management. An algorithm was developed to count corn plants and to estimate plant location and intra-row spacing in segmented images of 6.1-m (20-ft) long row sections. Images were scanned to detect and determine the boundaries of top projected corn plant canopy objects using a chain code methodology. Plant objects were fused together based on a multi-step process that took into account the spatial structure of the crop row. Position, roundness, and area of plant canopies were used to distinguish between corn plants and weeds. Estimates of plant counts in row sections were compared with manual counts across three growth stages, three populations, and three tillage treatments. Overall, the system estimated the number of plants with an RMSE of 1.49 plants per row section, which corresponds to 6.2% RMSE or 3210 plants/ha (1300 plants/acre). No evidence of significant differences in mean plant spacing estimates was detected although significant, albeit small, increases in spacing variance were detected. These results demonstrate the importance of canopy shape and size analysis in the implementation of a machine vision plant population and intra-row spacing sensing system.


This journal paper of the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa, Project No. 3612, was supported by Hatch Act and State of Iowa funds. Additional research support was provided by the Iowa State University Center for Advanced Technology Development.

This article is from Applied Engineering in Agriculture, 21, no. 2 (2005): 295–303.

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American Society of Agricultural Engineers



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