Climate change has been affecting life on our planet in many minute and significant ways and scientific research is still on to map where global warming is going to take us. Climate change has also been blamed for affecting crop growth and food production, which, scientists have warned may lead to the extinction of many important crop plants. A new study has said that climate change has already affected the production of the world's top 10 crops in certain regions. Among these are, some of the major and most widely consumed grain crops like maize, wheat, barley and even rice! Wheat and barley are consumed almost on a daily basis in homes across the Indian subcontinent and rice is a common fixture in a good majority of Asian dishes.
Other crop plants, whose production has been affected due to global warming and climate change, include oil palm, rapeseed, sorghum, soybean, sugarcane and cassava. These make up for world's top 10 crop plants that provide 83 per cent of all calories produced on the cropland. The study was published in the journal PLOS ONE and it was conducted by researchers at Universities of Minnesota, Oxford and Copenhagen. They observed that climate change was responsible for causing a variation in the yields of the crops. They said that while the yields of oil palm decreased by 13.4 per cent, those of soyabean increased by 3.5 per cent.
This amounted to average reduction of approximately one percent of consumable food calories from these top 10 crops of the world. The study also mapped the impact of climate change on crops in different areas around the world and found that the effects were mostly negative in countries like Europe, Southern Africa, and Australia, while they were positive in Latin American countries and mixed in Asia and Northern and Central America. But what was shocking was that half of all countries that weren't food-secure were observed to be experiencing decrease in food production.
Study co-author Snigdhansu Chatterjee, University of Minnesota said, "This is a very complex system, so a careful statistical and data science modeling component is crucial to understand the dependencies and cascading effects of small or large changes."
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