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Computer model gives early warning of crop failure

by | 27-07-2013 06:44 recommendations 0

It occurs many a times that our land changes so slowly, we simply overlook the damage we cause it. However, now as we continue to evolve we develop new methods and technologies to benefit us. About a century ago, evolving technologies wrote the global warming future we are living today. Today, we must use these technologies to stop the threat that looms upon us. We must write a new future. With our human population growing at such exponential rates, we cannot afford to hurt our land the source of food, water and shelter. As the following article will illustrate technologies can only give us a warning or indication, the decisions are in our hands... 


An international team of researchers has developed a computer model to predict global crop failures several months before harvest


Since 2008, widespread drought in crop-exporting regions has resulted in large increases in food prices on global commodity markets. With climatic extremes also expected to become more common, being able to predict global crop failures could help developing nations that are reliant on food imports — making them more resilient to spikes in food prices.


The study, published in Nature Climate Change this week (21 July), involved analyzing 23 years of climate forecasts and satellite observations to develop a computer model for predicting crop yields. The researchers then tested how well their model predicted the actual yields at the end of each season for four staple crops: wheat, rice, maize and soybean.


They found that climate-induced crop failures were reliably predicted in up to a third of the global crop area. The results suggest that computer models such as this could be used to produce crop estimates up to five months before harvest and help establish a system to predict global crop failure.


"This presents the first assessment of the reliability of cropping prediction on a global scale," study co-author Toshichika Iizumi, a researcher at Japan's National Institute for Agro-Environmental Sciences, tells SciDev.Net. "It demonstrates that we can predict food production ahead of the harvest, which is a valuable food security tool for dealing with changing climates."


Yet the reliability of the model's predictions varied substantially by crop, with wheat and rice yields being the most predictable. For the major wheat-exporting countries, the model's forecasts were reliable for up to 35 per cent of the harvested area.


However, soybean and maize yields showed little predictability. Maize is a key crop across much of Africa and Latin America, suggesting more work is required to improve crop predictions for many developing nations.


But Chris Funk, a research geographer at the University of California Santa Barbara, United States, says these findings could still help the developing world mitigate at least some food price shocks.


"In most of the world, wheat and rice are the dominant food source for rapidly expanding populations of urban poor," he tells SciDev.Net. "These populations, who may spend up to 70 per cent of their income on food staples, are highly vulnerable to rapid price increases."


The model also showed varying predictive powers between regions and countries. For example, reliable crop predictions could only be made for three per cent of the harvested area of Thailand, the world's second-largest rice exporter.


Source: Environmental News Network

Rice fields Rice fields in Asia

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9 Comments

  • says :
    Thanks for sharing.
    Posted 25-12-2013 17:00

  • says :
    thanks for sharing Nitish
    Posted 23-12-2013 00:56

  • says :
    very interesting, thanks for sharing.
    Posted 31-07-2013 14:42

  • says :
    Thats great news
    Posted 31-07-2013 13:54

  • says :
    Thanks for sharing the useful information
    Posted 29-07-2013 14:06

  • says :
    this computer model can help in combating with the crop failure!!surely prediction of crop failure before several month of harvest seems useful.
    Posted 29-07-2013 12:41

  • says :
    Thanks for sharing Nitish..
    Posted 27-07-2013 21:14

  • Arushi Madan says :
    Good to know about it , thanks Nitish.
    Posted 27-07-2013 17:34

  • says :
    thanks for sharing!
    Posted 27-07-2013 17:20

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