Automatic Measurement of Plant Height and Stem Thickness of Maize Based on Terrestrial Laser Scanning
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    Abstract:

    Plant height and stem thickness are important phenotypic parameters in the plant type of maize, which can reflect the growth status and vigor of maize. Terrestrial laser scanning can realize the rapid and automatic measurement of phenotypic parameters. Firstly, the three-dimensional point cloud data of two varieties of maize in four growth periods were obtained by using terrestrial laser scanning. Secondly, the point cloud processing software was used to match and segment the collected maize point cloud data, artificial measurement of maize phenotype in point cloud. Then, the maize point cloud was processed by down sampling, through filtering, plane segmentation algorithm based on random sampling consistency, statistical filtering and cylinder segmentation. The results showed that the method can segment individual maize, remove ground point cloud, filter outliers, layer plant point cloud and extract stem point cloud to be measured. The highest point extraction and ground point segmentation were used to measure maize plant height, and the long axis and short axis of stem thickness were measured by ellipse fitting. Compared the artificial point cloud measurement value with the artificial field measurement value, the root mean square error (RMSE) of Jingnongke 728 plant height, long axis and short axis were 2.15cm, 1.24mm and 1.86mm, respectively. The RMSE of Nongda 84 plant height, long axis and short axis were 2.36cm, 1.56mm and 1.23mm, respectively. Compared the automatic point cloud measurement value with the artificial point cloud measurement value, the RMSE of Jingnongke 728 plant height, long axis and short axis were 1.02cm, 6.65mm and 3.45mm, respectively. The RMSE of Nongda 84 plant height, long axis and short axis were 0.71cm, 4.95mm and 3.26mm, respectively. The results showed that the method of measuring plant height and stem thickness with terrestrial laser scanning point cloud data can be widely used in different maize varieties with different growth periods. The result of this method was highly consistent with that of the artificial measurement method and it can replace the artificial measurement method. It can provide a fast, automatic and accurate measurement scheme for breeders and crop phenotypists.

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History
  • Received:July 08,2021
  • Revised:
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  • Online: November 10,2021
  • Published: December 10,2021
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