scholarly journals The Platform A novel non-invasive fish monitoring method

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Yunjeong Yang ◽  
Ji Eun Kim ◽  
Hak Jin Song ◽  
Eun Bin Lee ◽  
Yong-Keun Choi ◽  
...  

Abstract Background Water content variation during plant growth is one of the most important monitoring parameters in plant studies. Conventional parameters (such as dry weight) are unreliable; thus, the development of rapid, accurate methods that will allow the monitoring of water content variation in live plants is necessary. In this study, we aimed to develop a non-invasive, radiofrequency-based monitoring system to rapidly and accurately detect water content variation in live plants. The changes in standing wave ratio (SWR) caused by the presence of stem water and magnetic particles in the stem water flow were used as the basis of plant monitoring systems. Results The SWR of a coil probe was used to develop a non-invasive monitoring system to detect water content variation in live plants. When water was added to the live experimental plants with or without illumination under drought conditions, noticeable SWR changes at various frequencies were observed. When a fixed frequency (1.611 GHz) was applied to a single experimental plant (Radermachera sinica), a more comprehensive monitoring, such as water content variation within the plant and the effect of illumination on water content, was achieved. Conclusions Our study demonstrated that the SWR of a coil probe could be used as a real-time, non-invasive, non-destructive parameter for detecting water content variation and practical vital activity in live plants. Our non-invasive monitoring method based on SWR may also be applied to various plant studies.


Author(s):  
Humaira Nisar ◽  
Zhen Yao Lim ◽  
Kim Ho Yeap

In this chapter we will discuss a simple non invasive automated heart rate monitoring method. Commonly heart rate is measured by using heart rate monitor devices. Many patients do not feel comfortable when they use contact devices for diagnostic purposes. Our algorithm gives a non-invasive way of heart rate measurement. The first step is to record a video. After 5 frames of the video are captured, the face is detected. A total of 300 frames will be used for further processing. At this stage, ROI (part of forehead) will be cropped out automatically. All image frames are in RGB color model, so these will be separated into 3 channels. For analysis, graph normalization is applied, which uses mean and standard deviation. Fast Fourier transform is used to plot the power spectrum of the traces. This power spectrum will have a peak if the heart rate is detected. We used RGB, HSI, YCbCr, YIQ, and CIE LAB color models for analysis. The best result is achieved with RGB color model followed by CIELab. The average accuracy is 95.32%.


Author(s):  
A. Ragauskas ◽  
G. Daubaris ◽  
V. Petkus ◽  
R. Sliteris ◽  
R. Raisutis ◽  
...  

Microsurgery ◽  
2013 ◽  
Vol 33 (5) ◽  
pp. 350-357 ◽  
Author(s):  
Jens Rothenberger ◽  
Amro Amr ◽  
Hans-Eberhard Schaller ◽  
Afshin Rahmanian-Schwarz

Sign in / Sign up

Export Citation Format

Share Document