Washington, July 6 : Researchers at Missouri University of Science and Technology in the US are working on a method that could help government planners and relief agencies better prepare for future shortages by predicting the variability of food supplies for specific nations or regions.
Employing a statistical method used by manufacturers to improve product quality, Missouri S and T graduate student Parthiv Shah and his advisor, Dr. Elizabeth Cudney, evaluated two years' worth of agricultural yields from a dozen industrialized nations to predict the output for a third year.
The Missouri S and T researchers' model is relatively simple.
It uses only a dozen factors - the yields of a dozen different food products - and pulls that data from a dozen industrialized nations, whereas the U.N. and World Bank concerns lie more with food shortages in developing nations.
The results of their research were accurate to within 95 percent of the actual yields for the third year.
"Using just two years of data, we are able to get fairly accurate predictions with this method," said Cudney, an assistant professor of engineering management and systems engineering at Missouri S and T.
The method in question is known as the Mahalanobis-Taguchi System, one of several statistical techniques devised by Genichi Taguchi, a Japanese engineer and statistician.
MTS is also named after Prasanta Chandra Mahalanobis, who introduced a method for measuring correlations between variables and the different patterns that can be identified via this approach.
The researchers' estimates of food supplies for 12 nations were extremely accurate, despite being based on only two years' worth of data from just 12 categories of agricultural products.
Working with 2001 and 2002 data on the yield of 12 types of agricultural products - including grains, wheat, meat and dairy products, and fruits and vegetables - the researchers were able to forecast 2003 agricultural yields for a dozen nations with 95 percent accuracy.
To test MTS beyond product development, Shah and Cudney conducted an earlier study to forecast rainfall based on earlier data.
Working with engineering management student Vivek Jikar; Dr. David Drain, assistant professor of mathematics and statistics at Missouri S and T; and Hiroshi Shibano of Japanese printer manufacturer Konica Minolta, the researchers used monthly precipitation data for a particular city from 1970 to 2006 to forecast future rain amounts.
Analyzing data from 1970 through 1999, the researchers were able to accurately forecast rain amounts with 87.7 percent accuracy.
According to Cudney, this same method could be used to help the World Bank, government planners and relief agencies better forecast where food shortages may occur in future years.