How to deploy AI to boost food production in Nigeria – Expert

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How to deploy AI to boost food production in Nigeria – Expert

 

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An Information Technology expert, Oluseun Onigbinde has called on Nigerian government and other stakeholders in agricultural sector to deploy technology in the sector for efficient production and ensure food security in the country.

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Onigbinde, who is Director, BudgIT, identified the use of Artificial Intelligence (AI), big data and Blockchain, as some of the technological means to drive Agri-conomy in the country.

Onigbinde, made the call in a lecture he delivered at the 25th Annual Convention and 24th Annual Lecture Series of the Alumni Association of the Federal University of Agriculture, Abeokuta, Ogun State, noted that deployment of technologies can transform the agriculture industry and enable farmers to make more informed decisions about crop management, improve crop yields, and reduce waste.

 

He added that the efficacy of technology-driven agriculture is centered on collection of data in volumes for making intuitive decisions.

He said, “if agriculture is to become a business and to make meaning in our lives, it must be at the forefront of cutting-edge technology”.

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“Artificial Intelligence (AI) has the potential to revolutionize the agricultural industry, which has been a primary source of food and livelihood for centuries. AI technology can increase crop yields, reduce waste, and help farmers make better decisions, increasing efficiency and profitability”.

 

“The impact of AI on agriculture can be seen in various aspects, ranging from crop management to livestock care, from supply chain management to precision agriculture”.

 

Speaking on the importance of Big data in agricultural revolution, Onigbinde noted that it has the potential to revolutionize agriculture by enabling farmers to make more informed decisions and optimize their operations.

 

He said, “by collecting and analyzing large amounts of data, farmers can gain insights into everything from soil health and weather patterns to crop yields and market trends”.

 

Blockchain technology on its part, can enable smart contracts, which are self-executing contracts, with the terms of the agreement between buyer and seller directly written into lines of code, stressing that this can automate processes and reduce the need for intermediaries, increasing efficiency and reducing costs.

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“Farmers can collect and analyze data from sensors, satellites, and drones with Artificial Intelligence to determine their crops’ best course of action. AI algorithms can help farmers identify areas of their land that need more or less water, fertilizer, or other materials. This information enables farmers to use resources more efficiently and make more informed decisions”.

 

Big data analytics can create precision farming techniques, such as precision irrigation and planting. This allows farmers to optimize resources like water and fertilizer and increase crop yields”.

 

“By using sensors to monitor soil moisture levels, farmers can adjust irrigation systems to deliver water only where and when needed, reducing water waste and improving crop yields”.

 

“Precision farming can predict the optimal time to harvest crops based on crop maturity and weather conditions using sensors and machine learning algorithms.

This can help farmers to maximize crop yields and reduce waste. Big data analytics can analyze data from sensors, GPS, and other sources to monitor crop yields”.

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“This information can help farmers identify areas of the field performing well or poorly and make informed decisions about crop management. Overall, precision farming can help farmers optimize crop production, reduce waste, and improve sustainability by leveraging technology to collect and analyze data on crop growth, soil health, and weather conditions”.

 

“Big data can help farmers predict weather patterns and other environmental factors affecting their crops. This information can help with adjusting planting schedules and making other management decisions”.

Big data can be used to optimise the supply chain, from tracking inventory levels to predicting demand for different crops. This can help farmers reduce waste and increase profitability”.

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