Feature Extraction on the Difference of Plant Stem Structure Based on Ultrasound Energy

Danju Lv (), Jiali Zi, Xin Huang, Mingyuan Gao, Rui Xi, Wei Li and Ziqian Wang
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Danju Lv: College of big data and intelligent engineering, Southwest Forestry University, Kunming 650224, China
Jiali Zi: College of big data and intelligent engineering, Southwest Forestry University, Kunming 650224, China
Xin Huang: College of big data and intelligent engineering, Southwest Forestry University, Kunming 650224, China
Mingyuan Gao: College of big data and intelligent engineering, Southwest Forestry University, Kunming 650224, China
Rui Xi: College of big data and intelligent engineering, Southwest Forestry University, Kunming 650224, China
Wei Li: College of big data and intelligent engineering, Southwest Forestry University, Kunming 650224, China
Ziqian Wang: College of big data and intelligent engineering, Southwest Forestry University, Kunming 650224, China

Agriculture, 2022, vol. 13, issue 1, 1-14

Abstract: Plant growth is closely related to the structure of its stem. The ultrasonic echo signal of the plant stem carries much information on the stem structure, providing an effective means for analyzing stem structure characteristics. In this paper, we proposed to extract energy features of ultrasonic echo signals to study the structure of the plant stem. Firstly, it is found that there are obvious different ultrasonic energy changes in different kinds of plant stems whether in the time domain or the frequency domain. Then, we proposed a feature extraction method, density energy feature, to better depict the interspecific differences of the plant stems. In order to evaluate the extracted 24-dimensional features of the ultrasound, the information gain method and correlation evaluation method were adopted to compute their contributions. The results showed that the mean density, an improved feature, was the most significant contributing feature in the four living plant stems. Finally, the top three features in the feature contribution were selected, and each two of them composed as 2-D feature maps, which have significant differentiation of the stem species, especially for grass and wood stems. The above research shows that the ultrasonic energy features of plant stems can provide a new perspective for the study of distinguishing the structural differences among plant stem species.

Keywords: online non-destructive detection; structure of plant stems; ultrasonic feature; feature extraction; feature contribution (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
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