Artificial intelligence and machine learning have taken on the challenge of forecasting crops.
Problem-solving computer programs based on AI can provide solutions to weather forecasting, crop choice, how to prepare soil, when to plant, increasing yields, improving quality, and optimal harvest timelines.
And while various forecasting systems have been in use for years, Gary Hawkins, founder and CEO of the Los Angeles-based Center for Advancing Retail & Technology, LLC, says newer AI systems can significantly boost accuracy.
Beginning with the roots of the supply chain, deep learning (a subdivision of machine learning, also referred to as deep structured learning) can compile a decade of data and predict what is likely to occur in the future.
This type of machine learning can parse the climate where a crop was grown along with its inherited characteristics, then forecast which genes will create the most beneficial characteristics in a plant. Once the crop is harvested, it is given careful attention to make sure the targeted qualities are exhibited.
This is the fourth in a series of six stories on Applied Technology. To read the whole series, click here.