Aii funded this project to address upstream emissions in raw material production by improving nitrogen use efficiency in cotton farming, a key emissions hotspot in the apparel value chain. The solution is low-cost, behavior-driven, and has strong potential to reduce nitrous oxide emissions while improving farmer outcomes.
This project designed, tested, and scaled a model for distributing and promoting the use of Leaf Color Charts (LCCs) among 40,000 cotton farmers in Maharashtra, India. LCCs are a low-cost tool that helps farmers optimize nitrogen fertilizer use by adjusting application timing and dosage based on crop needs. The project combined direct distribution, peer-sharing models, farmer training, and IVR-based advisory, reaching over 41,000 farmers across two growing seasons.
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This solution has strong scalability due to its low cost, simplicity, and ability to be delivered through existing agricultural extension systems and farmer networks. The peer-sharing model significantly improves cost-efficiency by allowing one tool to reach multiple farmers, while partnerships with local organizations enable large-scale distribution and training. Scaling is most effective in regions with higher baseline fertilizer overuse, where emissions reduction potential is greater. Additionally, scaling requires sustained farmer engagement, institutional support, and access to distribution channels such as farmer-producer organizations or agro-dealers. Given its applicability across cotton-growing regions and its integration potential into upstream supply chain interventions, the replication potential is high within the raw materials stage of the apparel value chain.
The project yielded four key learnings: impact is highly context-specific, as regions with lower baseline fertilizer use (like Maharashtra) produce smaller reductions than projected, making geography selection critical for future scaling; current IPCC Tier 2 measurement methods likely understate true impact by capturing only changes in nitrogen quantity rather than improvements in timing and frequency, with Tier 3 chamber-based sampling recommended to fill this gap; peer sharing proved a strong cost-efficiency lever, reducing the per-farmer seasonal cost from $2.01 to $0.30 and offering a scalable complement to institutional procurement; and farmer heterogeneity requires adaptive delivery, with sustained engagement beyond initial training found to be essential for correct tool use and lasting behavior change.
