Mathematical Modelling in Crop Production to Predict Crop Yields
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F21%3APU143078" target="_blank" >RIV/00216305:26210/21:PU143078 - isvavai.cz</a>
Výsledek na webu
<a href="http://www.cetjournal.it/cet/21/88/204.pdf" target="_blank" >http://www.cetjournal.it/cet/21/88/204.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3303/CET2188204" target="_blank" >10.3303/CET2188204</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Mathematical Modelling in Crop Production to Predict Crop Yields
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Mathematical Modelling in Crop Production to Predict Crop Yields
Popis výsledku anglicky
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.
Klasifikace
Druh
J<sub>SC</sub> - Článek v periodiku v databázi SCOPUS
CEP obor
—
OECD FORD obor
20704 - Energy and fuels
Návaznosti výsledku
Projekt
<a href="/cs/project/EF15_003%2F0000456" target="_blank" >EF15_003/0000456: Laboratoř integrace procesů pro trvalou udržitelnost</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2021
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Chemical Engineering Transactions
ISSN
2283-9216
e-ISSN
—
Svazek periodika
neuveden
Číslo periodika v rámci svazku
88
Stát vydavatele periodika
IT - Italská republika
Počet stran výsledku
6
Strana od-do
1225-1230
Kód UT WoS článku
—
EID výsledku v databázi Scopus
2-s2.0-85122486264