Organic producers in the mid-Atlantic region of the USA are interested in reducing tillage, labor and time requirements for grain production. Cover crop-based, organic rotational no-till grain production is one approach to accomplish these goals. This approach is becoming more viable with advancements in a system for planting crops into cover crop residue flattened by a roller–crimper. However, inability to consistently control weeds, particularly perennial weeds, is a major constraint. Cover crop biomass can be increased by manipulating seeding rate, timing of planting and fertility to achieve levels (>8000 kg ha−1) necessary for suppressing summer annual weeds. However, while cover crops are multi-functional tools, when enhancing performance for a given function there are trade-off with other functions. While cover crop management is required for optimal system performance, integration into a crop rotation becomes a critical challenge to the overall success of the production system. Further, high levels of cover crop biomass can constrain crop establishment by reducing optimal seed placement, creating suitable habitat for seed- and seedling-feeding herbivores, and impeding placement of supplemental fertilizers. Multi-institutional and -disciplinary teams have been working in the mid-Atlantic region to address system constraints and management trade-off challenges. Here, we report on past and current research on cover crop-based organic rotational no-till grain production conducted in the mid-Atlantic region.

Using the Farm Energy Analysis Tool (FEAT), we compare energy use and greenhouse gas (GHG) emissions from the cultivation of different crops, highlight the role of sustainable management practices, and discuss the impact of soil nitrous oxide (N 2 O) emissions and the uncertainty associated with denitrification estimates in the northeastern United States. FEAT is a transparent, open-source model that allows users to choose parameter estimates from an evolving database. The results show that nitrogen fertilizer and N 2 O emissions accounted for the majority of differences between crop energy use and GHG emissions, respectively. Integrating sustainable practices such as no tillage and a legume cover crop reduced energy use and GHG emissions from corn production by 37% and 42%, respectively. Our comparisons of diverse crops and management practices illustrate important trade-offs and can inform decisions about agriculture. We also compared methods of estimating N 2 O emissions and suggest additional research on this potent GHG.

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Root water uptake is an essential component of crop models since it affects plant growth and, through its effect on the soil water balance, multiple soil and nutrient cycling processes. Several methods to simulate water uptake exist; however, the differences among them have not been evaluated. We compared the water uptake methods implemented in six crop models: APSIM, CropSyst, DSSAT, EPIC, SWAP and WOFOST. These methods range from simple empiric approaches (WOFOST) to mechanistic approaches based on the water potential gradient and root distribution in the soil-plant system (CropSyst). We compared the six models' water uptake algorithms in scenarios with different evaporative demand, soil texture, and water distribution with depth. The main difference among methods derived from the degree to which each model enabled the use of water in the subsoil (below ~0.5 m). In a rooted, 1-m deep silt loam soil in which the root density decreased geometrically with depth and which was subjected to an evaporative demand of 5 mm d-1 for 60 days, APSIM, EPIC, DSSAT and SWAP transpired about 83% of the total plant available water while SWAP and CropSyst transpired about 65% of it. When methods were compared with initially dry bottom soil layers, cumulative transpiration became similar for all methods, while the opposite initial condition exacerbated differences. All methods, except CropSyst, increased transpiration as the evaporative demand rose to relatively high rates (10 mm d-1) because they lack a feedback mechanism that reduces transpiration when the demand exceeds the plant's ability to conduct water. CropSyst, DSSAT, EPIC and SWAP developed a "drying front", as usually observed in field conditions, while APSIM and WOFOST showed relatively uniform water depletion with depth in the soil profile. In conclusion, the models differ meaningfully in their simulation of water uptake and careful consideration of these differences is needed to properly use and interpret the outcome of model simulations.