Improved predictions of crop yields under climate change now possible

An improved calculation of crop response to variations in temperature reduces the uncertainty of crop yield predictions by up to 50 percent.

2017.08.02 | Janne Hansen

With improvement of the models, prediction of crop yield has now become more certain. Photo: Janne Hansen

When farmers, advisers and plant breeders explore which crops are best suited to present and future climatic and environmental conditions, it is important to investigate how the crops will perform.   

Researchers from, among others, Aarhus University have now developed models that can increase the certainty of such predictions. They have done so by improving the formulas for crop temperature response, thus reducing the uncertainty of yield predictions by up to 50 percent. This is reported by an international consortium of researchers in an article in the scientific journal Nature Plants.

Agriculture everywhere must plan for adaptation to climate change with an eye to ensuring global food security. Crop yield prediction is a key factor in this regard. To this end researchers use so-called process-based models. These models describe crop growth and development in all details from germination to harvest.  

The processes that can be included are, for example, photosynthesis, respiration, propagation and maturation. Each process is described in mathematical formulas according to results from experiments with live plants under various climate and growth conditions.  

Improved formulas for the effect of temperature

The models have been widely used to predict the effects of climate on yield, but have large uncertainties. The researchers in the international consortium found that variations in the temperature response functions were causing more than half of the uncertainty.  

They have therefore developed a new set of functions for temperature response, which has reduced the uncertainty of the models by an average of 42 percent – and in some cases up to 50 percent.

- Process-based modelling of crop growth is an efficient way to get a picture of how crop genotype, environment and management interactions affect crop production and is an important aid to tactical and strategic decision making. Process-based crop models are increasingly used to project the impact of climate change on crop yield, says one of the authors of the article, Professor Jørgen E. Olesen from the Department of Agroecology, Aarhus University. 


Read the article ”The uncertainty of crop yield projections is reduced by improved temperature response functions” in Nature Plants.


For more information please contact: Professor Jørgen E. Olesen, Department of Agroecology, email: jeo@agro.au.dk, telephone: +45 8715 7778, mobile: +45 4082 1659


Climate-Smart Agri-Food Systems is one of the research areas in which the Department of Agroecology is particularly strong and from which results are delivered in line with national and global societal challenges and goals.

Agro, DCA, Crops