Automatic Primary Echo Position Detection on Ultrasound in Plant Stem with Mixed Difference of Akaike Information Criterion
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    Abstract:

    Detecting the primary echo position is the basis of ultrasonic detection for plant stems. Due to the inhomogeneity and strong attenuation of plant stems,the ultrasonic propagation paths in them are more complex than those in the homogeneous medium, which makes the primary ultrasonic echo position difficult to detect. An improved Akaike of information criterion (AIC) was proposed to detect the position of the ultrasonic primary echo in plant stems. First of all, the improved algorithm was analyzed and its accuracy was verified by a set of simulated signals. Then, a set of cutting wood samples was taken to the ultrasonic detection in the process of the water absorption. The results showed that ultrasonic primary echo positions dynamically indicated changes of water content in wood. Finally, living sunflowers with different soil moistures were set to the ultrasonic detection from 09:00 to 19:00 in situ. The results showed that the soil moisture and the primary ultrasonic echo position had the positive correlation. Meanwhile, the results showed the ultrasonic detection of sunflower stems with different soil moistures were significantly distinct. When the soil was short of water, the primary echo position and the soil moisture both fluctuated greatly and accordantly, which was consistent with the physiological activities, switching from drought resistance regulation to normal water absorption and transpiration. In contrast, when the soil moisture was filling, the primary echo position and the soil moisture both vitiated slightly. Under this condition, it was found that the soil moisture reached minimum value and the primary echo position reached maximum values in 11:00—12:00, which were consistent with the dropped water content in stems to the minimum caused by the strongest transpiration at that time. Therefore, the primary echo position of plant stems detected by mixed difference AIC can be a feature to the dynamic detection of the growth status of plant stems.

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History
  • Received:November 30,2017
  • Revised:
  • Adopted:
  • Online: July 10,2018
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