Kylie Kiunguyu

Machine learning is offering useful insights in areas of land use, yields, and peak time for harvest, input distribution gaps, and other contextual monitoring aspects that would help struggling farmers improve crop yields considering the impact of the climate crisis on crops.

Scientists have deduced that West African countries are among the hardest hit by the climate crisis with populations that depend largely on agriculture losing their livelihoods due to worsening floods and droughts.

The Dakar Institute of Technology (DIT), which opened this year, is running its first 10-week boot camp in partnership with French AI school VIVADATA. The boot camp is focused on collecting and processing data using artificial intelligence to give farmers insight into maximising crop yields such as, when and where to add water or fertilizer and strengthening their understanding of crop losses.

Speaking on the Institute, DIT director Nicolas Poussielgue told Reuters that, “For models of climate change, the basic calculations use physics. Now you can add AI, which lets you have better results to know what is going to happen and where,”

“The idea of the school is to have students who will create their own start-ups and products.”

According to the Centre for Agriculture and Biosciences International, Africa farmers lose an estimated 49% of expected total crop yield per annum, which is the highest in the world.

Outside of West Africa data scientists across the continent are also experimenting with machine learning as a tool to help farmers cope with increasingly erratic weather.

  • Ivorian start-up ATA Solution uses machine learning to advise farmers on how to maximize scarce resources like land and water by collecting data such as soil PH, temperature and moisture levels.
  • A Yaoundé-based start-up In Cameroon, called ‘Agrix Tech’ diagnoses problems in crops and recommends both chemical and physical treatment as well as prevention measures using photographs uploaded by concerned farmers. According to its founder and CEO, Adamou Nchange Kouotou the innovation’s prototype has a 99% accuracy.
  • In Rwanda, a group of young entrepreneurs have formed ‘Charis Unmanned Aerial Solutions,’ which is using drones for agricultural purposes, in a pilot program with farmers. In addition to providing useful information the drones will be used to spray farms with pesticides among other activities. The start-up aims to contribute toward the development of agriculture by helping farmers make informed decisions during the entire farming process.
  • In Kenya AI technology is being utilized to monitor plant, soil and even weather conditions to outline and signify the most prominent times the produce will be ready or healthy, depending on the algorithm. It also alludes to it ensuring that farmers no longer have to engage in repetitive, tedious tasks that may induce human error

The impact that AI could have on agriculture would vastly improve food production and distribution thus positively impacting the livelihood of farmers and food security.

This is Africa