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Submission: On August 13 via api from DE — Scanned from AU
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* News * Jobs * Funding * Experts * Organizations * Menu * About us * Membership plans * Advertise Join DevexSign in Devex is the media platform for the global development community Join Devex Sign in NEWS * Latest news * News search * Career center * Health * Finance * Food * Newsletters * Focus areas * Try Devex Pro JOBS * Job search * Post a job * Find employers * Upcoming career events * Top employers * CV Writing * Career Account FUNDING * Funding search * Funding center * Find partners * Get funding access EXPERTS * Experts search * Recruiting Insight * Candidate Sourcing * Executive Search * Employer Branding * Talent Advisory * Recruitment Account ORGANIZATIONS * Organization search EVENTS * Upcoming and Past Events * Partner on an Event ENGAGE WITH US * Membership plans * Partner with us * Advertise * Sponsor an event * About us * Support * Careers at Devex CONTENT SERIES WOMEN RISING ROOTS OF CHANGE CTRL SHIFT EQUALITY TALKING TB MATERNITY MATTERS * View profile * My Devex * Update my profile % complete * Account & privacy settings * My saved jobs * Manage newsletters * Support * Sign out Latest newsNews searchCareer centerHealthFinanceFoodNewslettersFocus AreasTry Devex Pro * Inside Development * Techonlogy THE AI APPS HELPING THE WORLD'S LOW-INCOME FARMERS WORK SMARTER Smartphone apps and chatbots are diagnosing pests and farm animal diseases and dispensing crop-specific advice based on the weather — even for farmers with limited literacy or internet connectivity. By Alessio Perrone // 23 July 2024 Christina Matsenga had a problem: her goat had stopped eating. The farmer from Ndodo, a village in Malawi’s Lilongwe district, knew a smartphone-based chatbot could help — even if she didn’t have a smartphone herself. Matsenga turned to an in-person farmer support agent who opened WhatsApp on her own smartphone, took photos of the goat, and sent them to a number linked to a chatbot called Ulangizi. Normally, Matsenga would have to travel 25 miles to the capital to her local government agricultural extension officer. But within seconds, the chatbot sent recommendations on how to treat the animal in Chichewa, the local language, which the agent read aloud to Matsenga. Ulangizi, which means “advice” in Chichewa, is an AI chatbot developed by Chicago nonprofit Opportunity International that provides real-time answers to farmers’ queries in Malawi. It pulls information from the Malawian government’s agricultural manual to recommend good agricultural practices. Ulangizi is one of several examples of how farmers in lower-income countries are using AI to improve crop yields and assist with their livestock. “If these AI technologies are designed with an ecosystem development approach, they can be extremely powerful,” Gladys Morales, the global head of innovation at the International Fund for Agricultural Development, told Devex. IFAD finances and supports this kind of innovation and made it a central theme of its annual meeting this year. “We have seen that they can help increase agricultural productivity threefold. Farmers’ incomes can increase as much as five times.” AI innovations can already increase crop yields in several different ways, Morales said. They can help farmers adopt precision agriculture methods — strategies and tools allowing farmers to optimize the use of resources and increase soil quality and productivity — improving efficiency. AI can improve their management of pests and diseases, as in the case of Ulangizi, or give them weather-related advice. Or AI could help optimize agricultural supply chains, resource management, and data-driven decision-making. Of course, there are challenges, too. Like Matsenga, many farmers in lower-income countries, especially in Africa, lack access to the technology that would enable them to tap into the solutions being developed. Only 37% of Africans regularly used the internet in 2023, and connectivity costs can be steep, according to the International Telecommunication Union. Smartphones are also relatively rare in rural parts of the continent. Literacy, too, is a problem for some farmers, as they can’t type their questions or read the chatbot’s answers. “There are also other barriers that people talk less about,” Morales said, such as language. “Most tech companies think they can solve the language barrier by providing advisory services in official languages. But often, local communities use a particular jargon, and if you don't use it, they won't trust you or the advice you’re providing.” Devex delved into three promising apps leveraging AI to help farmers and explored how the challenges associated with the technology might be overcome. Detecting and diagnosing diseases in banana crops It can be hard for farmers to distinguish between various diseases affecting banana trees around the world. Now, there’s an app for that. “Fungi and bacteria symptoms can look similar, leaving farmers confused,” Michael Selvaraj, a scientist at the International Center for Tropical Agriculture, or CIAT, told Devex. Left to their own devices, he said, farmers will try to guess and err on the side of caution, spraying pesticides or fungicides at the first sight of symptoms. “But that might not be the best course of action, or it might not be necessary for certain conditions that don’t affect a tree’s yield,” he said. “And it’s not environmentally beneficial.” To help farmers detect and diagnose diseases in their banana trees, CIAT’s team collected more than 50,000 images of banana plants — sick, healthy, young, and old, from all over the world — and used them to train an AI model to classify those diseases. It turned that data into an app called Tumaini, which has been downloaded 15,000 times across India, Latin America, and a few countries in Africa, such as the Democratic Republic of Congo, Uganda, Ethiopia, and Tanzania. Tumaini means “hope” in Swahili. The app asks users to scan the plant’s symptoms and provide additional information or photos. Then, drawing from published scientific literature, it gives them a diagnosis, treatment recommendations specific to their region, as well as information about what causes the disease. Tumaini also has an offline version available for farmers with low connectivity. It also asks users to report the problem and aggregates the data into a map that scientists and governments can use for risk mapping and prevention. Weather-related advice in India By combining information held across different databases and leveraging large language models, AI algorithms can also provide farmers with agronomic recommendations based on the weather in their area and its potential impact on their crops. That’s the approach of Meghdoot, a free Android and iOS app in 13 languages whose name means “messenger from the sky” in Hindi. It was initially developed by CGIAR’s International Crops Research Institute for the Semi-Arid Tropics, based in Hyderabad, India, with funding from India’s Ministry of Earth Sciences. The app has piloted the use of large-language models and AI to provide targeted, crop-specific information at the district level in India. It provides farmers with an easy interface to access weather data and forecasts from the India Meteorological Department as well as crop-specific agricultural advisories from India’s Agro-Met Field Units. The app aggregates these advisories, as well as recorded weather and weather forecasts, to help farmers make decisions. “After you download the app, you can pick your district, and in some cases, a subdistrict, and see what the weather was like in the last five days, a forecast of the next seven days, and recommended actions for specific crops where you are,” Ram Dhulipala, a senior scientist at the International Livestock Research Institute, another CGIAR research center, told Devex. For example, if the weather forecast is likely very dry, the app could advise farmers to spray fertilizer like zinc sulfate on wheat crops. For livestock, it might recommend that animals be kept in a shed and that the surrounding areas be cleaned to avoid housefly infestations. Dhulipala said the app has already been downloaded by 500,000 farmers across more than 600 Indian districts, and showcased the potential of “faceless” AI — artificial intelligence that the user might not be aware of because it’s applied to back-office processes or to pull information from different silos. Crop advice for Malawian farmers Across sub-Saharan Africa, smallholder farmers still only produce 20% to 30% of their potential yields, according to Tim Strong, the head of agriculture finance at Opportunity International. The Malawian government has published a good agricultural practices manual and distributed it to agricultural extension officers in the country to support farmers in their decision-making processes. But the document is only available in English and is 700 pages long. There is one agricultural extension officer for up to 3,000 farmers, which means that it can be difficult for farmers to reach them, and it might entail a lengthy journey into a nearby town. Opportunity International’s Ulangizi chatbot tackles these problems by using AI to pull information from the manual to answer farmers’ questions, in English or Chichewa. “You befriend that number and can type, speak, or use the camera, point it at a plant, and say, ‘What's wrong with my groundnuts?’” Greg Nelson, Opportunity International’s chief technology officer, told Devex. “And Ulangizi will tell you and give you recommendations on how to solve it.” To solve the challenges posed by low smartphone use and digital literacy levels in Malawi’s rural communities, the nonprofit piloted the app by equipping 163 government extension officers and farmer support agents with smartphones, turning them into a bridge between farmers and the technology. Anna Chimalizeni, the farmer support agent who helped Matsenga with her goats, said she goes into the fields several times per week, meeting farmers and putting their questions to the app herself. Nelson said the conversational aspect of AI innovations such as Ulangizi has the potential to revolutionize access to information for farmers in Africa. “Many smallholder farmers are not particularly literate or numerate,” he told Devex. “So the ability to be conversational and to literally speak and hear can be transformative.” Christina Matsenga had a problem: her goat had stopped eating. The farmer from Ndodo, a village in Malawi’s Lilongwe district, knew a smartphone-based chatbot could help — even if she didn’t have a smartphone herself. Matsenga turned to an in-person farmer support agent who opened WhatsApp on her own smartphone, took photos of the goat, and sent them to a number linked to a chatbot called Ulangizi. Normally, Matsenga would have to travel 25 miles to the capital to her local government agricultural extension officer. But within seconds, the chatbot sent recommendations on how to treat the animal in Chichewa, the local language, which the agent read aloud to Matsenga. THIS STORY IS FORDEVEX PROMEMBERS Unlock this story now with a 15-day free trial of Devex Pro. With a Devex Pro subscription you'll get access to deeper analysis and exclusive insights from our reporters and analysts. Start my free trialRequest a group subscription Already a user? Sign in More reading: ► UN agriculture fund bets big on innovation to improve food security ► How the World Food Programme is using AI ► How AI and chatbots can boost crop yields * Agriculture & Rural Development * Economic Development * Environment & Natural Resources * Innovation & ICT * Consultative Group for International Agricultural Research (CGIAR) * Opportunity International * Devex Pro Week 2024 * Malawi * India Printing articles to share with others is a breach of our terms and conditions and copyright policy. Please use the sharing options on the left side of the article. Devex Pro members may share up to 10 articles per month using the Pro share tool ( ). Should your team be reading this? Contact us about a group subscription to Pro. ABOUT THE AUTHOR * ALESSIO PERRONE Alessio Perrone is a freelance editor and reporter at Devex. Throughout his career, he has reported on issues at the intersection of policy, environment and human interest for outlets including The Guardian, Scientific American, TIME, and others. He’s based in Milan, Italy. 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