Publication detail

Mathematical Modelling in Crop Production to Predict Crop Yields

Sadenova, M.A., Beisekenov, N.A., Rakhymberdina, M., Varbanov, P.S., Klemeš, J.J.

Original Title

Mathematical Modelling in Crop Production to Predict Crop Yields

Type

journal article in Scopus

Language

English

Original Abstract

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. © 2021, AIDIC Servizi S.r.l.

Keywords

mathematical; modelling; crop; production; predict; crop yields

Authors

Sadenova, M.A., Beisekenov, N.A., Rakhymberdina, M., Varbanov, P.S., Klemeš, J.J.

Released

15. 11. 2021

Publisher

Italian Association of Chemical Engineering - AIDIC

ISBN

2283-9216

Periodical

Chemical Engineering Transactions

Number

88

State

Republic of Italy

Pages from

1225

Pages to

1230

Pages count

6

URL

http://www.cetjournal.it/cet/21/88/204.pdf

BibTex

@article{BUT175971,
  author="Petar Sabev {Varbanov} and Jiří {Klemeš}",
  title="Mathematical Modelling in Crop Production to Predict Crop Yields",
  journal="Chemical Engineering Transactions",
  year="2021",
  number="88",
  pages="1225--1230",
  doi="10.3303/CET2188204",
  issn="2283-9216",
  url="http://www.cetjournal.it/cet/21/88/204.pdf"
}