Agricultural extension in India has followed the same model for decades: a government extension worker, trained at an agricultural university, visits a village and demonstrates a new technique to a group of farmers. The problem is not with the technique. The problem is with the demonstrator.
The extension worker is not a farmer. He has been trained in conditions that are not these conditions, for crops that may not be these crops, by instructors who have studied farming rather than practiced it. The farmer watching the demonstration knows something the demonstrator does not: what it is like to bet your family's food security on a new practice that might fail.
Digital Green's insight was precise and actionable: the most persuasive agricultural educator is a farmer from the same village, speaking the same language, facing the same risks, demonstrating a technique that actually worked on land similar to yours. Not a university-trained expert. A peer.
Who They Are
Digital Green is an international non-profit founded in India in 2008, working with local partners to produce short videos of farmers — from the same community, in the same language — demonstrating agricultural practices that have worked for them. These videos are screened in village groups using basic equipment, discussed collectively, and evaluated for adoption.
The model has been independently evaluated multiple times. The landmark J-PAL (Abdul Latif Jameel Poverty Action Lab) controlled evaluation found Digital Green's approach to be ten times more cost-effective than traditional extension services, with uptake of new agricultural practices seven times higher than classic training-and-visit approaches. In a 13-month trial across 16 villages, Digital Green increased adoption of specific agricultural practices sevenfold over the standard extension approach.
By the time of their most recent scale documentation, Digital Green had reached more than 7.2 million small-scale farmers in India and internationally.
The Video Methodology
What makes a Digital Green video different from an instructional farming video on YouTube is the identity of the presenter. The farmer on screen is from the same kind of community as the farmer watching. She faced the same land constraints, the same credit limitations, the same uncertainty about whether a new practice would work or fail. She speaks the local language, references local varieties, addresses local conditions.
This identity match — the presenter and the audience sharing social, economic, and ecological context — produces adoption rates that technically superior content from outside the community cannot. The evidence from Digital Green's own monitoring: in India, the recorded adoptions per viewer was 3.03 — every farmer who watched a video adopted, on average, three of the practices demonstrated. Female farmer viewership in India reached 90 percent, significantly above comparable programmes elsewhere.
The COCO (Collect, Organize, and Connect) system that Digital Green uses for data management enables real-time tracking of video dissemination, farmer attendance, and adoption verification. This data infrastructure is what makes the approach evaluable — and evaluation is what has made it fundable and scalable.
The Evidence Base at Scale
Digital Green's approach has been evaluated through multiple randomised controlled trials in India, Ethiopia, and other geographies. The J-PAL case study documents that the approach was leveraged from RCT findings to scale — a classic evidence-to-policy translation pathway.
A specific Bihar evaluation, conducted in partnership with Jeevika (Bihar's rural livelihoods mission), tested Digital Green's video approach with female farmers adopting System of Rice Intensification (SRI), a climate-smart technique. The evaluation found farmers increased yields and estimated profits. The researchers noted that surveys may not have captured partial adoption of the multi-step technique, suggesting the actual adoption impact was even larger than measured.
The IDinsight technical report from 2023 reviewing Digital Green's evidence base confirmed the sustained effectiveness of the video-mediated extension approach across multiple geographies and crop types.
The Odisha Connection
Digital Green has documented presence in Odisha through multiple programme partnerships. In the context of Ama Krushi — Odisha's AI-enabled agricultural advisory system that reached 6.5 million farmers via SMS, IVR, and call centres at Rs 0.18 per farmer per year — Digital Green's video-based approach represents the complementary high-engagement intervention that digital advisory systems need.
The Peer Video Extension Practice Note in JaBaSu's Knowledge Commons draws directly on Digital Green's methodology. The model is directly applicable to Odisha's Millet Mission extension challenges — where new crop varieties and practices need to reach tribal farmers in multiple local languages across 177 blocks. Digital Green's community-produced, language-appropriate, farmer-presenter video approach addresses exactly this challenge.
The 7.2 Million Farmer Scale
The J-PAL documentation credits Digital Green with reaching more than 7.2 million small-scale farmers globally. This number needs context: 7.2 million individual farmers who have watched a community video, discussed it collectively, and had their adoption of specific practices verified by a trained frontline worker. This is not a passive outreach number — it represents documented engagement and verified behavioural change.
The cost-effectiveness that underpins this scale: ten times more cost-effective than traditional extension means that for the same investment, Digital Green reaches ten times more farmers who actually change their practices. This is the efficiency argument that agricultural development funders respond to — not just reach, but verifiable impact per rupee.
Contact and Further Reading
Website: digitalgreen.org | For Odisha partnerships: contact via the India programme team
Key evidence:
- J-PAL Case Study: Video-Based Support for Small-Scale Farmers Around the World — documents 7.2 million farmers and the 10x cost-effectiveness finding
- J-PAL Evaluation: Digital Green's agricultural extension programme in India (Bihar SRI evaluation)
- IDinsight Evidence Review, 2023: Summary of Evidence Review of Digital Green's Video-Mediated Farmer Extension Approach
- SPRING Nutrition: Digital Green impact summary — 500,000 farmers, 6,500 villages, 28 languages, controlled evaluation
JaBaSu Knowledge Commons · knowledge@jabasu.org · jabasu.org/knowledge