Automation in plant growth monitoring using high-precision image classification and virtual height measurement techniques

Author(s):  
I.S. Akila ◽  
A. Sivakumar ◽  
S. Swaminathan
2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Joanna M. Nassar ◽  
Sherjeel M. Khan ◽  
Diego Rosas Villalva ◽  
Maha M. Nour ◽  
Amani S. Almuslem ◽  
...  

2006 ◽  
Vol 45 (11) ◽  
pp. 8832-8838 ◽  
Author(s):  
Ken Murayama ◽  
Satoshi Gonda ◽  
K. Kinoshita ◽  
Hajime Koyanagi ◽  
Tsuneo Terasawa ◽  
...  

2020 ◽  
Author(s):  
Nicolas Sobanski ◽  
Beat Schwarzenbach ◽  
Béla Tuzson ◽  
Lukas Emmenegger ◽  
Dave R. Worton ◽  
...  

<p>   Nitrogen dioxide (NO<sub>2</sub>) is an atmospheric pollutant whose emissions are mostly linked to anthropogenic activities. It is, with nitric oxide (NO), the most abundant member of the nitrogen oxides family in tropospheric urban air (mixing ratios up to hundreds of ppbv), with a lifetime ranging from hours to days. NO<sub>2</sub> is well known for its role as a boundary layer ozone and organic nitrates precursor and for affecting the oxidation capacity of the atmosphere. It has thus been subject to emissions mitigation policies and ambient air amount fraction monitoring for a few decades. The latter fully relies on the Chemiluminescence Detection technique (CLD), which is an indirect method measuring NO<sub>2</sub> after conversion to NO.<br>   Recent advances in spectroscopy led to the development of direct and more selective ways to measure NO<sub>2</sub>. The currently running European Metrology for Nitrogen Dioxide (MetNO2) project, involving more than 15 European academic and industrial partners, promises to fill the gap in reliable and complete datasets for laboratory and field testing of those measurement techniques.<br>Here we present the results of a performance investigation of a high precision Quantum Cascade Laser Absorption Spectrometer (QCLAS) for the selective measurement of NO<sub>2</sub> performed in the frame of the MetNO2 project. This instrument is based on a mid-IR QCL emitting at 6 μm and a custom-made, low noise astigmatic Herriott type multipass cell with an effective optical path length of 100 m to measure NO<sub>2</sub> concentration in the low pptv range. We focus on determining precision, long-term stability and potential biases related to sampling conditions such as ambient pressure, temperature and humidity. The QCLAS device is then compared to other direct spectroscopic (CAPS, CRDS, IBBCEAS) and indirect (CLD) techniques. We also report on the results of a three weeks side-by-side field comparison at an urban air monitoring station of the Swiss National Air Pollution Monitoring Network (NABEL), involving the newly developed QCLAS, and commercial CAPS and CLD instruments.<br>   We show that the QCLAS is well suited for monitoring of NO<sub>2</sub> concentration in ambient air and its performances in term of precision and stability surpass those of the CLD device and compete well with other direct measurement techniques.</p>


Author(s):  
Uoc Quang Ngo ◽  
Duong Tri Ngo ◽  
Hoc Thai Nguyen ◽  
Thanh Dang Bui

Increasingly <span>emerging technologies in agriculture such as computer vision, artificial intelligence technology, not only make it possible to increase production. To minimize the negative impact on climate and the environment but also to conserve resources. A key task of these technologies is to monitor the growth of plants online with a high accuracy rate and in non-destructive manners. It is known that leaf area (LA) is one of the most important growth indexes in plant growth monitoring system. Unfortunately, to estimate the LA in natural outdoor scenes (the presence of occlusion or overlap area) with a high accuracy rate is not easy and it still remains a big challenge in eco-physiological studies. In this paper, two accurate and non-destructive approaches for estimating the LA were proposed with top-view and side-view images, respectively. The proposed approaches successfully extract the skeleton of cucumber plants in red, green, and blue (RGB) images and estimate the LA of cucumber plants with high precision. The results were validated by comparing with manual measurements. The experimental results of our proposed algorithms achieve 97.64% accuracy in leaf segmentation, and the relative error in LA estimation varies from 3.76% to 13.00%, which could meet the requirements of plant growth monitoring </span>systems.


2019 ◽  
Vol 12 (12) ◽  
pp. 6803-6826
Author(s):  
Tesfaye A. Berhanu ◽  
John Hoffnagle ◽  
Chris Rella ◽  
David Kimhak ◽  
Peter Nyfeler ◽  
...  

Abstract. Carbon dioxide and oxygen are tightly coupled in land biosphere CO2–O2 exchange processes, whereas they are not coupled in oceanic exchange. For this reason, atmospheric oxygen measurements can be used to constrain the global carbon cycle, especially oceanic uptake. However, accurately quantifying small (∼1–100 ppm) variations in O2 is analytically challenging due to the very large atmospheric background which constitutes about 20.9 % (∼209 500 ppm) of atmospheric air. Here we present a detailed description of a newly developed high-precision oxygen mixing ratio and isotopic composition analyzer (Picarro G2207) that is based on cavity ring-down spectroscopy (CRDS) as well as to its operating principles; we also demonstrate comprehensive laboratory and field studies using the abovementioned instrument. From the laboratory tests, we calculated a short-term precision (standard error of 1 min O2 mixing ratio measurements) of < 1 ppm for this analyzer based on measurements of eight standard gases analyzed for 2 h, respectively. In contrast to the currently existing techniques, the instrument has an excellent long-term stability; therefore, calibration every 12 h is sufficient to get an overall uncertainty of < 5 ppm. Measurements of ambient air were also conducted at the Jungfraujoch high-altitude research station and the Beromünster tall tower in Switzerland. At both sites, we observed opposing and diurnally varying CO2 and O2 profiles due to different processes such as combustion, photosynthesis, and respiration. Based on the combined measurements at Beromünster tower, we determined height-dependent O2:CO2 oxidation ratios varying between −0.98 and −1.60; these ratios increased with the height of the tower inlet, possibly due to different source contributions such as natural gas combustion, which has a high oxidation ratio, and biological processes, which have oxidation ratios that are relatively lower.


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