A team of international scientists has developed new crop models that could help predict crop production, which in turn will provide an insight into how to feed the growing population.
The rapidly growing population and drastic climatic changes are two major concerns of scientists around the globe. Statistics show that the world population will soon reach the 9 billion mark. Agriculture has been one of the sectors most affected by these phenomenon and scientists are working hard to come up with solutions to feed the growing population of the planet.
A group of international scientists from Michigan State University has come up with crop models that predict crop productions, which in turn will give an insight into how to feed the large world population.
Earlier last week, members of the Agricultural Model Intercomparison and Improvement Project released an all-encompassing modeling system that incorporates multiple crop simulations with improved climate change models. This new system provides better global wheat yields predictions as well as reduces political and socio-economic influences that can skew data and planning efforts.
"Quantifying uncertainties is an important step to build confidence in future yield forecasts produced by crop models," said Bruno Basso, Michigan State University ecosystem scientist and AgMIP member in a press release. Basso is part of MSU's geological sciences department and Kellogg Biological Station. "By using an ensemble of crop and climate models, we can understand how increased greenhouse gases in the atmosphere, along with temperature increases and precipitation changes, will affect wheat yield globally."
These new crop models can also help both developed and developing countries deal with the emerging climatic changes and implement new techniques and policies that lead to more crop production.
Basso and this team were also instrumental in developing the System Approach for Land-Use Sustainability (SALUS) model. This new model can help forecast crop, soil, water and nutrient conditions in current and future climates.
"We can change the scenarios, run them simultaneously and compare their outcomes," Basso said. "It offers us a great framework to easily compare different land-management approaches and select the most efficient strategies to increase crop yield and reduce environmental impact such as nitrate leaching and greenhouse gas emission."
SALUS has already been added to projects that monitor grain yield and water use in water-sensitive areas such as the Ogallala aquifer (spanning from South Dakota to Texas), Siberia, India and Africa.
