Now – September 2021
The 2021 Producer-Led Innovation Challenge seeks to inspire innovators to create software to make it faster for farmers to aggregate the complex multi-year, multi-source data sets required to participate in Carbon markets.
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Indiana’s AgTech Innovation Challenge!
Innovation and Sustainability
The Producer-Led Innovation Challenge empowers innovators with a Producer view of the current Carbon market challenge and provides a $25,000 grand prize to the team who creates the most effective solution to simplify the data aggregation and packaging required in Carbon markets.
2021 Challenge Overview
Carbon markets provide an opportunity for companies to purchase Carbon credits generated from farm operations that sequester Carbon. While many companies have created platforms to make buying and selling Carbon credits possible, each requires farmers to conduct complex multi-year data assembly from multiple sources and types that are time consuming and create a significant barrier to entry for many farmers. This complex, and in some cases incomplete, data creates a significant barrier to Carbon market adoption as evidenced by the recent survey of Indiana farmers.
The Producer-Led Innovation Challenge is an 8-week opportunity for entrepreneurs, students, technologist, academics and agtech companies to create a solution that:
Makes it possible to integrate years of multiple data sources from across farm operations to create a market-ready data set with minimal farmer manual data entry (as defined by existing Carbon market provides, i.e., Indigo, TruTerra, Bayer, etc.); and
Provides a “good” and a “best” option that enables farmers to use field-level data from modern machinery (“best”) and aggregated farm operations data and publicly available data (climate, soil, farm-level yield, etc.) (“good”).
This Challenge is not creating a new marketplace or approach to Carbon markets; this Challenge seeks to significantly reduce the labor-intensive tasks that create a barrier to farmer participation today.
Each submission will be evaluated against the following equally-weighted criteria: