Farmer interest in organic or reduced input no-till soybean production systems planted into roller-crimped cereal rye residues is steadily increasing. Such systems are good for improving the sustainability of soybean production, through soil quality improvements and decreased hand labor requirements for weed management. However, adoption has been limited by farmer concerns about how to predict, and respond to, the impact of variable planting date and weather on the timing of spring rye development and biomass production. Will the system produce enough biomass early enough in a given year to support a rolled-crimped system, or should the cover crop be turned under as a green manure? Our team’s recent advances in the quantitative understanding of cereal rye phenology and biomass production in relation to local environmental and management factors will allow stronger support of adaptive management strategies for effective use of cereal rye cover crops in no-till soybeans. We propose to develop an online decision support tool for managing cereal rye phenology and growth, and to work with a farmer advisory council and the IDEA Farm Network, to undergo an iterative evaluation and design process to improve the tool for public release. In addition to a core group of 30 farmers who will take on-farm measurements of spring rye phenology and biomass and weed growth, over 200 farmers will evaluate the tool, improving farmer understanding of adaptive rye management, improving adoption rates of this soil building, labor saving approach to organic and reduced input no-till soybean production.
Project objectives from proposal:
1) Learning: Over 200 farmers will learn how soil and environmental variability at regional scales causes variation in timing of rye development.
2) Action: Beta version of web-based decision support tool will be used by at least 50 growers to optimize their planting and termination dates for adaptive use of cereal rye in organic and conventional no-till soybean.
3) System-wide: Constructing and evaluating the decision support tool with the IDEA Farm Network will help over 200 farmers understand and act on regional-scale variation in cover crop performance, demonstrating how learning communities can synergize ongoing improvement in sustainable farming practices.