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Wyszukujesz frazę "Kim, S. S." wg kryterium: Autor


Wyświetlanie 1-3 z 3
Tytuł:
Simulated impacts of rainfall extremes on yield responses of various barley varieties in a temperate region
Autorzy:
Yoon, C.Y.
Kim, S.
An, K.N.
Powiązania:
https://bibliotekanauki.pl/articles/2083065.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Instytut Agrofizyki PAN
Tematy:
barley
rainfall
simulation
food cost
grain
yield
Opis:
As population rises, more people need to be fed. With increasing income, the potential exists for increases in the demand for cereals (i.e., barley). Since barley has a high level of tolerance to environmental stressors, this crop has been recommended as a potential crop for food security in marginal environments. In this study, a crop growth Agricultural Land Management Alternatives with Numerical Assessment Criteria model, was parameterized and used to simulate the yields of two barley types grown in a temperate environment at a latitude of 35°N. In order to apply this crop model to barley, 19 years of field data were used to model calibration and validation. As a result, the ALMANAC model accurately simulated yields for both barley types. The validated model was used to predict yields under three diverse seasonal rainfall scenarios associated with different patterns of the Central Pacific El Niño influence. According to the simulation results, excessively high seasonal rainfall decreased barley yields. Crop price and annual revenue of the two barley types were also evaluated using a non-linear regression model. For the malt type, the food price was higher with a higher rainfall, while naked barley had a higher revenue under the conditions of a lower rainfall.
Źródło:
International Agrophysics; 2021, 35, 2; 119-129
0236-8722
Pojawia się w:
International Agrophysics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Estimating parameters of empirical infiltration models from the global dataset using machine learning
Autorzy:
Kim, S.
Karahan, G.
Sharma, M.
Pachepsky, Y.
Powiązania:
https://bibliotekanauki.pl/articles/2083049.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Instytut Agrofizyki PAN
Tematy:
infiltration modelling
random forest
Soil Water
Infiltration Global database
Opis:
It is beneficial to develop pedotransfer relationships to estimate infiltration equation coefficients in site-specific conditions from readily available data. No systematic studies have been published concerning the relationships between the accuracy of the infiltration equation and the accuracy of the predicted coefficients in this equation. The objective of this work was to test the hypothesis that, for the same infiltration data, the accuracy of pedotransfer predictions for coefficients in an infiltration equation is greater for the infiltration equation that performs better. The hypothesis was tested using the commonly employed Horton and Mezencev (modified Kostiakov) infiltration equations with data from the Soil Water Infiltration Global database. The random forest machine learning algorithm was used to develop the pedotransfer model. The Horton and the Mezencev models performed better with 928 and 758 datasets, respectively. The accuracy of the estimates of the infiltration equation coefficients did not differ substantially between the estimates obtained from all data and from the data where the infiltration equation had lower root-mean-squared error values. The root-mean-squared error values of the pedotransfer estimates decreased by 2 to 25% when only datasets with the same infiltration measurement method were considered. The development of predictive pedotransfer equations with the data obtained from the same infiltration measurement method is recommended.
Źródło:
International Agrophysics; 2021, 35, 1; 73-81
0236-8722
Pojawia się w:
International Agrophysics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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