Production Of World’s Top 10 Food Crops Including Wheat, Rice Affected By Climate Change: Study
Climate change has affected life on Earth in various minor and significant ways. Scientific research is continuing to determine how global warming will likely lead us. Climate change is also blamed for impacting the growth of crops and the production of food and, as scientists have warned, could result in the death of several important crops. A new study suggests climate change already affects some of certain regions’ top 10 most popular crops. These include leading and popular grain crops, such as wheat, maize, and rice! Barley and wheat are eaten nearly daily in households all over the Indian subcontinent, and rice is an integral component of most Asian meals.
Other crops that have suffered from diminished production by climate change and global warming include rapeseed, oil palm, sugarcane, soybean, sorghum, and cassava. These are the top 10 crops that makeup 83 percent of all calories consumed from the land. This study was published by PLOS One and was carried out by researchers from the Universities of Minnesota, Oxford, and Copenhagen. They discovered that climate change was the reason for the variation concerning the yields from crops. They noted that while the results of oil palm dipped by 13.4 percent, the effects of soybean grew by 3.5 percent.
It was a reduction of about one percent in the calories consumed by food items from these top 10 food crops around the globe. The study also explored the effect of climate change on crop production worldwide and found that the results were mainly negative in areas such as Europe, Southern Africa, Australia, and Australia. In contrast, there were some positive effects for Latin American countries and mixed in Asia and Northern and Central America. However, what was most shocking was that a majority of countries that were not food-secure were seen to be experiencing an increase in food production.
Co-author of the study Snigdhansu Chatterjee of the 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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