Bridging Animal, Veterinary, and Human Nutrition Science to Fight Human Malnutrition
This Challenge is
An estimated two billion people worldwide suffer from malnutrition, with poor nutrition contributing to more than a third of the deaths of children under age of five. Moreover, lack of proper nutrition during the critical period of conception to two years of age can result in lifelong adverse health and development outcomes.
In this exciting project, we leveraged our worldwide reach and novel methodology to merge insights and innovations from the animal, veterinary, and human nutrition science communities. These fields share common scientific underpinnings, but often operate in discrete silos which undermine the potential for research-sharing and collaboration.
Working with our development partner Lybba, we designed a robust question-and-answer crowdsourcing function on our web platform. A network of diverse participants was invited to participate in a 45-day crowdsourcing event in search of ideas that might offer promising, untapped opportunities for collaboration. Hundreds of users, from 61 different countries, posed questions and evaluated and engaged with each other’s ideas in nearly 2,000 exchanges – many more people and perspectives than would typically inform a traditional agenda-setting or convening process.
We shared these crowd-sourced insights with leaders from the private sector, government, NGOs, and academia, asking them to build upon the ideas, identify critical innovation gaps and new collaboration models, and strategize on eliminating barriers to progress.
What emerged was the idea that innovation across the dairy value chain in developing countries presents both a critical need and a huge opportunity. We issued a $7,500 open innovation challenge to students across the globe, inviting them to submit solutions for advancing human health, nutrition outcomes and economic benefits resulting from smallholder dairy farming in developing countries.
After reviewing 40 proposals from 19 countries, our independent panel of judges selected two winning solutions:
- “Dairy Surveillance for the Future” from Veena S. Katikineni, a medical student at the University of Maryland School of Medicine, and Alejandra Leyton, a masters of public health student at Tulane University
- “Dairy Calendar” from Adnan Naim, a doctoral student at the Eskitis Institute for Drug Discovery at Griffith University in Queensland, Australia.
Expert Judging Panel
First Place Proposal: “Dairy Surveillance for the Future”
Proposal summary: “Dairy Surveillance for the Future” proposes suggests using community-based “reward circles,” in which smallholder farmers form groups to collect and report dairy data via a common questionnaire and shared SMS mobile device. In turn, the data can be analyzed by researchers and policy makers.
First Place Winners: Veena S. Katikineni, a medical student at the University of Maryland School of Medicine and Alejandra Leyton, a masters of public health student at Tulane University
To increase the amount and quality of data collected regarding dairy production and consumption for smallholder farms by utilizing:
- Simple survey questionnaire delivered by a trained community member moderator
- Moderated co-dependent community focus groups accessible in rural areas with reward incentives for participation
- Increasingly available SMS text technology to send questionnaire results to a capital city data aggregator
- Local partners: community members, governments, NGOs, non-profit organizations, academic institutions, and private enterprise
The proposed technology makes the following assumptions:
Each locality has a very specific set of social, cultural, and technological circumstances that local community members know best.
SMS text technology is increasingly available across the globe, though not yet universal.
The expense of livestock feed is the main factor limiting profit-generating dairy production, especially to peri-urban farms which don’t have sufficient land for feed/fodder production, and therefore purchase it (FAO, p. 140, 142).
Small shareholder farmers live in poverty, with most making less than $1 per day (FAO, p. 142).
As demonstrated by the Grameen community model (Bangladesh), social pressure and co-dependence for reward increase frequency of self-reported data; however, a level of risk regarding sentiments of coercion within the co-dependent group must be acknowledged, prevented, and planned for in the unfortunate event that it arises.
Most shareholder farmers are not dependent on the income they get from dairy production for survival; instead they use this income to improve livelihood (heating, etc.) (FAO, p. 144, 148).
Second Place Proposal: “Dairy Calendar”
Proposal Summary: The “Dairy Calendar” uses an intuitive calendar paired with pictures to report details related to the dairy animal, feed, volume of milk, and destination of the product. Data would be uploaded to a cloud storage system and accessible to researchers and policymakers.
Second Place Winner: Adnan Naim, a PhD student at the Eskitis Institute for Drug Discovery at Griffith University in Queensland, Australia
Understanding the current problem with the collection, maintenance, and sharing of data associated with smallholder farmer dairy production in developing countries, I would like to put forward an innovative approach to solve this problem. I think that the flow of information directly from smallholder farmers to the data collection centre is difficult and may have a possibility of losing it, therefore I will propose that information should move step by step from smallholder farmers to consumers/dairy product manufacturer and gets updated there and from there should pass on to regional data collection centre.
Considering different types of barriers (language, literacy, geographical constraints etc.) associated with the smallholder farmers, my Idea is to design a picture based DAIRY_CALENDAR, similar to a normal YEAR_CALENDAR but with dairy related special features. The DAIRY_CALENDAR will have the information required to be filled in by the smallholder farmer about the animals they have, number of milk producing animals, timing of milking, the amount of milk produced, consumption at household level, neighbours and finally quantity of milk sold to consumers/Dairy Product Manufacturer and at what cost.
There will be 3 identical copies of this DAIRY Calendar which will move from smallholder farmer to dairy product manufacturer and then finally to the regional Data Collection Centre. Once a copy of this DAIRY_CALENDAR reaches the Dairy Product Manufacturer, he will update the information with other details about the milk. The details will be more like the transportation of the milk, amount of milk bought, cost at which the milk was bought, quality of the milk (protein, lipid content etc), how the milk is used. Considering that, the consumer or Dairy Product manufacturer is much more educated and aware of the latest communication technologies; after updating the calendar they can post or upload a Copy of the Calendar to the Regional Data Collection centre using different available electronic options (email). This sharing of data can make the best use of the latest available smart phones, different apps available for sending text messages, photos, videos (e.g. Whatsapp).
Once the data on the calendar has reached the Regional Data Collection Centre, it can now be made available to different other regional, state and National Data collection centres. This sharing can be done at a common platform making use of other technological tools like DropBox. Having data on such common platforms can easily be accessed by different public and private agencies for study and research purpose.
Agricultural Development: Livestock Overview and Strategy. Bill & Melinda Gates Foundation April 2012. www.gatesfoundation.org/agriculturaldevelopment/Documents/agricultural-development-strategy-overview.pdf.
The importance of milk and other animal-source foods for children in low-income countries. Daphna K. Dror and Lindsay H. Allen. Food and Nutrition Bulletin, vol. 32, no. 3, 2011. http://docserver.ingentaconnect.com/deliver/connect/nsinf/03795721/v32n3/s7.pdf?expires=1368114247&id=74130187&titleid=41000042&accname=Guest+User&checksum=5A23D5EA1CF3ADBEA162E48DC8AECD16
Labor Markets. Workers in the Informal Economy. The World Bank. http://web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTSOCIALPROTECTION/EXTLM/0,,contentMDK:20224904~menuPK:584866~pagePK:148956~piPK:216618~theSitePK:390615,00.html
Rethinking the Informal Economy: Linkages with the Formal Economy and the Formal Regulatory Environment. Martha Alter Chen. DESA Working Paper No. 46. July 2007. http://www.un.org/esa/desa/papers/2007/wp46_2007.pdf.
Small-scale dairy production: a way out of poverty. New study assesses global perspectives for smallholder milk production. Food and Agricultural Organization of the United Nations (FAO), http://www.fao.org/news/story/en/item/44582/. April 18, 2013
Smallholder farmers in India: Food Security and agricultural policy. Why the Small-Holder Farmer? http://www.fao.org/docrep/005/ac484e/ac484e04.htm
Status and Prospects for Smallholder Milk Production A Global Perspective. Torsten Hemme and Joachim Otte. FAO June 2010. http://www.fao.org/docrep/012/i1522e/i1522e.pdf.
Value Chains for Nutrition. Corinna Hawkes and Marie T. Ruel. 2020 Conference Paper 4 Updated June 2011. IFPRI 2020 International Conference. http://www.ifpri.org/sites/default/files/publications/2020anhconfpaper04.pdf.
Country omnibus data portals
- TotoAgriculture: A comprehensive log of African agriculture conditions
- AdaptMap: Tracking plant genomics for food security
- The Food Security Portal: Run by IFPRI, the portal offers a dashboard that can track data including on prices, volatility, and epidemics
- Plantwise a knowledge bank to serve plant clinics in low-resource settings
- The Rice Bowl Index: Syngenta’s foray into investments, trade policies, soil, flooding, etc. that can impact food security
- The Research Data Alliance looks at standards, practices, and repositories that can enhance data collection and sharing. They have a working group on agricultural data.