Firat Guder and Tony Cass of Imperial College London in the United Kingdom along with George Mahuku and James Legg at the International Institute of Tropical Agriculture in Tanzania will develop a smartphone-based electrochemical lateral flow assay to rapidly diagnose crop viruses in the field and relay the results. Viral crop diseases like maize lethal necrosis and cassava brown streak disease can destroy up to 30% of crops and are the main threat to food security in East Africa. Most diagnostic tests are laboratory-based and slow, hampering efforts to stop the diseases from spreading. They will develop a system that combines cutting edge chemistry and widely-used smartphone technology to quickly test field samples and upload the results to the cloud for immediate sharing with farmers and agricultural partners. Their approach is based on chemical amplification and detection of nucleic acid aptamers: as few as a hundred virus particles can be detected without the need for complex genetics or fragile and expensive antibodies. They will identify aptamers that selectively recognize the viruses, optimize the lateral flow assay in the lab, and then field-test it in Tanzania and the Democratic Republic of Congo. Once validated, they plan to develop a simpler, disposable version and scale-up the technology to other crops and countries.

Rachel Sklar of Pit Pumpers Ltd. in Rwanda will develop an interactive SMS messaging platform to increase community use of companies to safely empty pit latrines in Rwanda by using communication to increase demand and thereby decrease cost and wait-times for service calls. Pit latrines, used by nearly two billion people worldwide, must be emptied regularly to avoid public health risks associated with fecal contamination of groundwater. Companies in Rwanda provide an emptying service with cost-saving opportunities when several households book together. However, this is more difficult to arrange for users in remote areas, and households may resort to unsafe dumping. They will improve coordination of service requests among remote communities by using local shop owners (duka agents) to identify households needing an emptying service. These leads will be followed up with targeted SMS marketing, and the agents paid a commission for those converted to customers. The interactive SMS messaging platform will provide households with a referral code to invite neighbors to join the service call, and the resulting cluster of customers pay a reduced rate for emptying. It will further include educational messages explaining the negative impacts of manual dumping of fecal sludge to promote behavior change. They will develop the platform and test their approach by training agents in Kigali, Rwanda.

Molly Brown of Syngenta Foundation for Sustainable Agriculture in the U.S. will develop an early warning system for crop diseases for rural farmers in Africa by gathering data using existing infrastructure and mobile tools from commercial partners and applying machine learning pest models. Insect pests cause almost half of crop losses in Africa each year, which impacts both food supply and the economy. An effective disease and pest surveillance system provides early warning to minimize crop loss but is often unavailable to rural farmers in poor countries who lack tools for sufficient pest data collection. To address this, they propose to leverage the existing infrastructure, including demonstration farms, retailers, and mobile tools, of a commercial partner to gather the required data, such as field photographs, data on pest prevalence, and satellite weather data. Mobile tools will be available on computer and Android devices with off-line modes. They will pilot test their approach in Zambia focusing on damage to maize crops caused by the fall armyworm. Real-time data will be uploaded to a freely available, public portal with information on geography, pest populations, and affected crops.

William Martin of the International Food Policy Research Institute in the U.S. will combine existing, high-quality survey data collected from individual households in rural Ethiopia and Nigeria with agricultural information from the Global Agro-Ecological Zone (GAEZ) database to model the impact of specific investments on poor communities to better inform policy decisions. National Agricultural Investment Plans (NAIPS) shape policy development by outlining investments required to stimulate growth in Africa through transformation of the agricultural sector. However, they rarely consider the impact on individual households. To address this, they will use existing household survey data from the Living Standards Measurement Study – Integrated Services on Agriculture (LSMS-ISA), which was designed to dissect the relationship between agriculture and poverty. These data will be combined with the publicly available GAEZ database, which assesses agricultural resources and potential, to model the direct impact of policy decisions, such as investments in research and rural infrastructure (irrigation, electrification), on households. Results of the analysis will help prioritize future agricultural investments for maximum impact on the poorest families.