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Automatic corn plant location and spacing measurement using laser line-scan technique

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Abstract

Identifying corn plant location and/or spacing is important for predicting yield potential and making decisions for in-season nitrogen application rate. In this study, an automatic corn stalk identification system based on a laser line-scan technique was developed to measure stalk locations during corn mid-growth stages. A laser line-scan technique is advantageous in this application because the line-scan data sets taken from various points of view of a plant stalk results in less interference and higher probability of plant recognition. Data were collected for two 10-meter-long corn rows at the growth stages of V8 and V10 using a mobile test platform in 2011. Each potential stalk cluster was identified in a scan and registered with the same stalks in previous scans. The final location of a stalk was the average of the measured locations in all scans. The current system setup with data processing algorithms achieved 24.0 and 10.0 % of mean total errors in plant counting at the V8 and V10 growth stages, respectively. The root-mean-squared error (RMSE) between system measured plant locations and manually measured ones were 2.3 and 2.6 cm at the V8 and V10 growth stages, respectively. The interplant spacing measured by the developed system had a good correlation with the manual measurement with an R 2 of 0.962 and 0.951 for the V8 and V10 growth stages, respectively. This system can be ultimately integrated in a variable-rate-spraying system to improve real-time, high spatial resolution variable-rate nitrogen applications.

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Acknowledgments

The authors would like to thank Jeremiah Mullock and Natasha Macnack in Department of Plant and Soil Sciences for their help in plot preparation and manual measurement. Appreciation also goes to Wesley Porter, Jorge Rascon, Marshall Oldham, Bin Li, Aaron Franzen and Yongbo Wan in Department of Biosystem and Agricultural Engineering for their help in field test which made this project successful.

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Authors and Affiliations

  1. Department of Biosystems and Agricultural Engineering, Oklahoma State University, 111 Agricultural Hall, Stillwater, OK, 74078, USA

    Yeyin Shi, Ning Wang, Randal K. Taylor & James A. Hardin

  2. Department of Plant and Soil Sciences, Oklahoma State University, 044 Agricultural Hall, Stillwater, OK, 74078, USA

    William R. Raun

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  1. Yeyin Shi
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  2. Ning Wang
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  3. Randal K. Taylor
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  4. William R. Raun
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  5. James A. Hardin
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Correspondence to Ning Wang.

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Shi, Y., Wang, N., Taylor, R.K. et al. Automatic corn plant location and spacing measurement using laser line-scan technique. Precision Agric 14, 478–494 (2013). https://doi.org/10.1007/s11119-013-9311-z

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