Mathematical Modelling in Crop Production to Predict Crop Yields
Sadenova M.A. Beisekenov N.A. Rakhymberdina M. Varbanov P.S. Klemeš J.J.
2021Italian Association of Chemical Engineering - AIDIC
Chemical Engineering Transactions
2021#881225 - 1230 pp.
In this study, for remote recognition of crops of agroecosystems in Kazakhstan by methods of comparative and historical analogy with the active use of mathematical modelling, the yield indicator of agricultural crops was determined, their dynamic characteristics were studied to predict productivity. The parameters of the dynamicstatistical biomass model were determined separately for each region of the Republic of Kazakhstan based on training data for 21 y (2000 - 2021). The correlation coefficient between the calculated yield values and the official statistics is 0.84. According to the results of cross-validation, the correlation coefficient between the actual and predicted yield of spring wheat was ∼0.70, which indicates a sufficient resistance of the model to the variability of meteorological conditions for the formation of the crop.
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Center of Excellence «Veritas», D. Serikbayev East Kazakhstan technical university, 19 Serikbayev str., Ust-Kamenogorsk, 070000, Kazakhstan
Sustainable Process Integration Laboratory, NETME Centre, FME, Brno University of Technology - VUT Brno, Technická 2896/2, Brno, 616 00, Czech Republic
Center of Excellence «Veritas»
Sustainable Process Integration Laboratory
10 лет помогаем публиковать статьи Международный издатель
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