Own weather observation system

Own weather observation system

14 October 2021 News from the Company

The first stage of the project on installation of meteorological monitoring stations has been completed. 42 modern meteorological stations were installed and successfully put into operation at Ekosem-Agrar plants in Voronezh, Kursk, Kaluga, Orenburg, Ryazan and Novosibirsk regions, as well as in Tatarstan and Bashkortostan.


The project was launched in spring 2020. The modern iMETOS weather stations from the Austrian manufacturer Pessl Instruments provide locally accurate weather forecasts for up to 14 days. For example, iMETOS can stably determine the following data: Air temperature, wind speed and direction, barometric pressure and estimated precipitation. This allows field operations to be planned more accurately and informed management decisions to be made based on weather data.

"Accurate local weather forecasts help reduce production costs, for example, when applying crop protection products. If we see that precipitation is expected, we postpone the work to a more favorable period," says Sergey Kapustin, head of the Smart Farming Department at EkoNiva-APK Holding.

The weather stations collect data for their entire operating period, which provides the opportunity to analyze and plan future production activities.

"With the help of iMETOS, we analyze winter weather conditions, which allows us to select resistant winter crop varieties in different regions and more accurately predict the start of sowing and crop protection treatments. To choose the tillage strategy, we analyze weather data from the previous season," explains Aleksandr Anpilov, head of crop production at EkoNiva-APK Holding.

The information can be tracked via FieldClimate, a cloud-based service developed for weather station owners. Ekosem-Agrar employees can also get the latest climate station data through the EkoCrop app. EkoCrop is a proprietary development of the Group's for crop cultivation, which collects all information on field work and crop condition and enables quick decision-making based on this data.