Spring Wheat Yield Forecast Using Machine Learning Methods

Author:

Kizimova TatyanaORCID,Riksen VeraORCID

Publisher

Springer Nature Singapore

Reference32 articles.

1. Orlova, N., Serova, E., Nikolaev, D., Hvorostjanaya, A., Novikova, Yu., Yavkina, E., Bobkova, E., Ragozin, P., Yanbyh, R., Sokolov, A., Chulok, A.: Innovative development of the agro-industrial complex in Russia. HSE University report, p. 128. National Research University “Higher School of Economics”, Moscow (2020)

2. Khaki, S., Wang, L., Archontoulis, S.V.: A CNN-RNN framework for crop yield prediction. Front. Plant Sci. 10, 1750 (2020)

3. Chen, K., O’Leary, R., Evans, F.: A simple and parsimonious generalised additive model for predicting wheat yield in a decision support tool. Agric. Syst. 173, 140–150 (2019)

4. Vartanyan, A., Petrova, A.: Design and implementation of a decision support system at an agro-industrial enterprise. Horiz. Econ. 6(65), 46–51 (2021)

5. Ivanyo, Ya., Popkova, Yu., Stolopova, Yu.: On the issue of predicting the yield of grain crops. In: Climate, Ecology, Agriculture of Eurasia: Proceedings of the VII International Scientific and Practical Conference, pp. 201–209. Irkutsk State Agrarian University, Irkutsk (2018)

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