Open Access
Climate variability in areas of the world with high production of soya beans and corn: its relationship to crop yields
Author(s) -
Llano María Paula,
Vargas Walter,
Naumann Gustavo
Publication year - 2012
Publication title -
meteorological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 59
eISSN - 1469-8080
pISSN - 1350-4827
DOI - 10.1002/met.270
Subject(s) - crop , precipitation , agriculture , environmental science , yield (engineering) , crop yield , adaptability , growing season , agronomy , geography , biology , meteorology , ecology , materials science , metallurgy , archaeology
Abstract An important goal of this work is to study the variability of corn and soya bean crop yields in four countries with large production and substantial commercial trade in these commodities. This problem can be investigated in terms of the role that these two crops play in food programmes and in terms of the use of both crops for energy production. Four countries were chosen and divided into six production areas. A climatic summary was made of the annual cycles of extreme temperatures and precipitation. Their assessment in agriculture programmes was likewise summarized. It is seen that the variability range of the temperatures and precipitation are broad and different for each region. This finding indicates the high adaptability of these crops. This concept of adaptability is used to compare the coefficients for precipitation and crop yield. Results of the study show that corn crops show less year‐to‐year variability than do soya bean crops. The United States and the northern part of China are the regions that best use the rain supply with respect to crop yield. Soya bean crops show a greater year‐to‐year variability in the ratio of precipitation to crop yields. Argentina, the United States and northern China are the areas that best use the rain supply. To compare crop yields with climatic variables in the different regions, three types of regression model were used. The best fit is obtained by using the maximum temperatures and accumulated precipitation for each growth stage over the growing season. Copyright © 2011 Royal Meteorological Society