Methods, hardware and software for monitoring crops condition on early stages of vegetation

Lately, in addition to traditional methods of screening or selective crops inspection, instrumental means of monitoring, namely installed on unmanned aerial vehicles (UAV) video and photo-cameras, started to be implemented. The main advantage of conducting monitoring via UAV is that it does not mech...

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Vydáno v:Selʹskohozâjstvennye mašiny i tehnologii (Online) číslo 5; s. 33 - 37
Hlavní autor: Voronkov, I. V.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Federal Scientific Agroengineering Centre VIM 01.10.2017
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ISSN:2073-7599, 2618-6748, 2618-6748
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Shrnutí:Lately, in addition to traditional methods of screening or selective crops inspection, instrumental means of monitoring, namely installed on unmanned aerial vehicles (UAV) video and photo-cameras, started to be implemented. The main advantage of conducting monitoring via UAV is that it does not mechanically affects plants and maintains high productivity during the surveying. However, during screening inspection of large crops areas (tens of thousands of hectars), especially on the early stages of vegetation, a problem of receiving the surveying analysis results promptly emerges. To solve this problem it is necessary to develop automated methods of identification and geo-referencing of the problematic zones. To count the amount of shoots and measure distance between them it is necessary to use the methods of images recognition based on the plants’ spectral characteristics analysis. The methodology of plants signals selection is based on the comparison of measured values with specified values; after that compilation of series using algorithm of approximation of slopes. Basing on the gathered information, statistical indicators characterizing the qualities of completion of the work were estimated. Experimental researches of the hardware and software methodology development were conducted using maize crops in the Krasnodar Territory. Comparative assessment of the measurement in manual and automatic regime using the developed software for shoots recognition and counting was conducted. The results difference equals 3-5 percent.
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content type line 23
ISSN:2073-7599
2618-6748
2618-6748
DOI:10.22314/2073-7599-2017-5-33-37