Standing tree decay detection by using acoustic tomography images

Espinosa, Luis; Arciniegas, Andres; Prieto, Flavio; Cortes, Yolima; Brancheriau, Loïc

doi:10.1117/12.2182915

Cited by 1 publication

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The water content of plant stems is a major index of the physiological activity of plant water, especially in precision agriculture [ 1 , 2 , 3 ]. Methods for detecting stem water content include drying [ 4 ], gamma rays [ 5 ], nuclear magnetic resonance (NMR) [ 6 , 7 , 8 ], X-ray computed tomography [ 9 ], resistance [ 10 ], time-domain reflectometry (TDR) [ 11 ], frequency-domain (FD) capacitance [ 12 , 13 , 14 ] and infrared detection [ 15 ]. Of the above methods, drying constitutes in vitro detection, which cannot detect the dynamic changes in the stem water content.…”

Section: Introductionmentioning

confidence: 99%

“…However, due to stems being non-metal materials with anisotropic heterogeneous features, there were widely different and complicated acoustic impedance interfaces [ 33 ]. The interfaces lead to multiple refractions and reflections when the ultrasonic wave spreads in plant stems [ 9 , 10 ]. Therefore, the complex propagation in stems made it challenging to extract the location of the primary ultrasonic echo [ 11 , 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Detection of Water Changes in Plant Stems In Situ by the Primary Echo of Ultrasound RF with an Improved AIC Algorithm

Gao

et al. 2022

Sensors

View full text Add to dashboard Cite

The detection of water changes in plant stems by non-destructive online methods has become a hot spot in studying the physiological activity of plant water. In this paper, the ultrasonic radio-frequency echo (RFID) technique was used to detect water changes in stems. An algorithm (improved hybrid differential Akaike’s Information Criterion (AIC)) was proposed to automatically compute the position of the primary ultrasonic echo of stems, which is the key parameter of water changes in stems. This method overcame the inaccurate location of the primary echo, which was caused by the anisotropic ultrasound propagation and heterogeneous 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 samples from stems were taken for ultrasonic detection in the process of water absorption. The correlation between the moisture content of stems and ultrasonic velocities was computed with the algorithm. It was found that the average correlation coefficient of the two parameters reached about 0.98. Finally, living sunflowers with different soil moistures were subjected to ultrasonic detection from 9:00 to 18:00 in situ. The results showed that the soil moisture and the primary ultrasonic echo position had a positive correlation, especially from 12:00 to 18:00; the average coefficient was 0.92. Meanwhile, our results showed that the ultrasonic detection of sunflower stems with different soil moistures was significantly distinct. Therefore, the improved AIC algorithm provided a method to effectively compute the primary echo position of limbs to help detect water changes in stems in situ.

show abstract