News Release

Skoltech supercomputer helps scientists reveal most influential parameters for crop

Peer-Reviewed Publication

Skolkovo Institute of Science and Technology (Skoltech)


image: A heatmap of the impact of key soil parameters on yield view more 

Credit: Pavel Odinev / Skoltech

Nowadays, agriculture is going to become AI-native: Skoltech researchers have used the Zhores supercomputer to perform a very precise sensitivity analysis to reveal crucial parameters for different crop yields in the chernozem region. Their paper was published in the proceedings of the International Conference on Computational Science 2020.

Farmers all over the world use digital crop models to predict crop yields; these models describe soil processes, climate, and crop properties and require environmental and agricultural management input data to calibrate them and improve the forecasts. In some countries, however, agrochemical data is not freely available for users of these models, and this calibration can become expensive and time-consuming.

A Skoltech team led by full professor Ivan Oseledets and assistant professor Maria Pukalchik used one of the popular open-source process-based model called MONICA and figured out a way to reveal only the most important parameters for crop yield based on historical data and process-modeling. Moreover, they sped up computational efficiency from one simulation per day to half a million model simulations per hour using Zhores, the flagship Skoltech supercomputer.

This stunning amount of simulations is necessary to perform high-quality sensitivity analysis that helps determine how the changes in certain input factors (such as soil parameters or fertilizer) influenced the output crop yield prediction.

The research team used field data from an experiment in the Russian chernozem region, with seasonal crop-rotation of sugar beet (Beta vulgaris), spring barley (Hordeum vulgare), and soybean (Glycine max) observed from 2011 to 2017. They picked six main soil parameters for sensitivity analysis and performed what's called Sobol sensitivity analysis (named after Ilya Sobol, a Russian mathematician who proposed it in 2001).

"Soil is a very complicated issue in this country. Unfortunately, the data about soil properties and crop yield are not published. We have found an opportunity to overcome this barrier and set up the Zhores supercomputer to solve this issue. Now we can simulate all possible variants and reveal the most crucial parameters without time-consuming and costly work. We hope that our achievements will help farmers digitalize their crop growth," said Maria Pukalchik.


Skoltech is a private international university located in Russia. Established in 2011 in collaboration with the Massachusetts Institute of Technology (MIT), Skoltech is cultivating a new generation of leaders in the fields of science, technology, and business, is conducting research in breakthrough fields, and is promoting technological innovation with the goal of solving critical problems that face Russia and the world. Skoltech is focusing on six priority areas: data science and artificial intelligence, life sciences, advanced materials and modern design methods, energy efficiency, photonics, and quantum technologies, and advanced research. Web:

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