Remote sensing of pastures to predict sheep productivity
https://doi.org/10.26897/0021-342X-2022-3-129-137
Abstract
This article discusses the prospects for the use and rapid development of modern satellite systems and observation technologies in pasture farming. The main possibilities of constructing a predictive model for planning the productivity of pasture herbage on the basis of multivariate analysis of remote sensing are presented. The obtained data are used to build a technological map of animal grazing. Currently, the data obtained as a result of satellite observation and associated technologies are increasingly used in tasks related to obtaining reliable objective information about the state of agricultural land and the possibility of their industrial use. To solve the set tasks, specialized information systems and models of various levels of predicting the productivity of the land used and the productivity of pasture animals are rapidly being developed and implemented. As objectively observable data on the current state of pastures in our studies, we used multispectral images of the Copernicus Sentinel-2 Earth remote sensing satellite of the European Space Agency (ESA). The data obtained made it possible to establish the relationship between the productivity of rangelands and the vegetation index obtained by the remote method and verified by the contact method during field trials. Studies of the chemical composition and nutritional value of forage grazing plants made it possible to assess the yield of nutrients and energy from 1 m2 . According to the results of accounting for the live weight of the controlled animals, it was found that the live weight of sheep grazed on pasture No. 1 statistically significantly exceeded this indicator by 6.2% in analogues that were grazed on pasture No. 2. Based on the results obtained, recommendations were made to substantiate the periods of optimal use of pasture areas, based on the use of digital methods of remote monitoring.
About the Authors
Vladimir I. TrukhachevRussian Federation
Sergey A. Oliynyk
Russian Federation
Tatyana S. Lesnyak
Russian Federation
Dmitry B. Litvin
Russian Federation
Artem V. Lesnyak
Russian Federation
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Review
For citations:
Trukhachev V.I., Oliynyk S.A., Lesnyak T.S., Litvin D.B., Lesnyak A.V. Remote sensing of pastures to predict sheep productivity. IZVESTIYA OF TIMIRYAZEV AGRICULTURAL ACADEMY. 2022;(3):129-137. (In Russ.) https://doi.org/10.26897/0021-342X-2022-3-129-137