Though cassava is tolerant to droughts and capable of growing with minimal soil–making it an ideal crop in harsh weather conditions—it’s also susceptible to many diseases and pests. The symptoms of a diseased plant develops slowly, so it can be difficult for farmers to diagnose these problems in time.
PlantVillage and the International Institute of Tropical Agriculture (IITA) developed a solution using machine learning that could help farmers better identify and manage these diseases quickly. They annotated thousands of cassava plant images, identifying and classifying diseases to train a machine learning model using TensorFlow. Once the model was trained to identify diseases, it was deployed in the app. Farmers can wave their phone in front of a cassava leaf and if a plant had a disease, the app could identify it and give options on the best ways to manage it. Over 750,000 views.
Important Note
Content Editors rate, curate and regularly update what we believe are the top 11% of all AI resource and good practice examples and is why our content is rated from 90% to 100%. Content rated less than 90% is excluded from this site. All inclusions are vetted by experienced professionals with graduate level data science degrees.
In the broadest sense, any inclusion of content on this site is not an endorsement or recommendation of any service, product or content that may be discussed, recommended, endorsed or affiliated with the content, company or spokesperson. We are a 501(c)3 nonprofit and receive no website advertising monies or direct or indirect compensation for any content or other information on any of our websites. For more information, visit our TOS.
