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So, as AI technologies advance, what impacts will they have on agri-food value chains? From advisory tools increasing supplychain efficiency to gene editing and predictive breeding speeding up R&D cycles, industry leaders are leveraging AI models to transform agriculture at scale into a more resilient and sustainable system.
A recent report by McKinsey revealed that while Africa has large amounts of untapped agricultural land that could be used to increase production, much of this land is in unreachable areas. The lack of infrastructure, conflict zones, forest cover, and large conservation areas has made lots of arablelands inaccessible.
In other words, bigger is better and yield is king. Greenhouses and vertical farms, widely known as trusted methods of year-round agricultural production, seem to be context-agnostic solutions to agri-food supplychain disruptions, desertification, and other climate change-related problems.
These synthetic polymer products have often been used to help boost yields up to 60 percent and make water and pesticide use more efficient. Mitigation requires slashing production and consumption, he adds, and increasing recycling and reuse all along the supplychain. As contamination rose, crop yields fell by 15 percent.
xiii] Yields are dropping, with large proportions of the UK’s soils moderately or severely degraded. xvi] Regenerative agriculture is key to flood resilience and prevention of the decimation of crop yields. Because of this lack of confidence, all farming sectors are expecting to decrease production over the next year.
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