Dependence of the crop yields of maize, wheat, barley and rye on temperature and precipitation in Hungary

Temperature and precipitation are the most important meteorological variables influencing crop yields of cereals. In the paper we use and compare two procedures, namely Factor analysis with special transformation and multiple linear regression analysis with stepwise method in determining the influen...

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Czibolya Lili
Makra László
Pinke Zsolt László
Horváth József
Csépe Zoltán
Dokumentumtípus: Cikk
Megjelent: 2020
Sorozat:CARPATHIAN JOURNAL OF EARTH AND ENVIRONMENTAL SCIENCES 15 No. 2
Tárgyszavak:
doi:10.26471/cjees/2020/015/136

mtmt:31602899
Online Access:http://publicatio.bibl.u-szeged.hu/28726
Leíró adatok
Tartalmi kivonat:Temperature and precipitation are the most important meteorological variables influencing crop yields of cereals. In the paper we use and compare two procedures, namely Factor analysis with special transformation and multiple linear regression analysis with stepwise method in determining the influence of monthly mean temperatures and monthly precipitation amounts of April, May, June, July and August for determining the crop yields of maize, wheat, barley and lye. When comparing the results received on the two methods, those variables were retained that were concurrently significant for determining the crop yields for both cases. It is found that for maize yield the most important variables in decreasing order are August mean temperature with negative, as well as July and June precipitation amounts with positive association. For wheat yield, June and May mean temperatures, while for barley yield the same but in reverse order are the most important variables, all with negative relationship. Concerning rye yield, April precipitation amount with positive and June mean temperature with negative association are the decisive variables. Among the examined cereals, maize yield is the most sensitive to precipitation. The here-mentioned significant relationships may have a predictive power in projecting the actual crop yield.
Terjedelem/Fizikai jellemzők:359-368
ISSN:1842-4090