Přístupnostní navigace
E-přihláška
Vyhledávání Vyhledat Zavřít
Detail publikace
Sadenova, M.A., Beisekenov, N.A., Rakhymberdina, M., Varbanov, P.S., Klemeš, J.J.
Originální název
Mathematical Modelling in Crop Production to Predict Crop Yields
Typ
článek v časopise ve Scopus, Jsc
Jazyk
angličtina
Originální abstrakt
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.
Klíčová slova
mathematical; modelling; crop; production; predict; crop yields
Autoři
Vydáno
15. 11. 2021
Nakladatel
Italian Association of Chemical Engineering - AIDIC
ISSN
2283-9216
Periodikum
Chemical Engineering Transactions
Číslo
88
Stát
Italská republika
Strany od
1225
Strany do
1230
Strany počet
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" }