PS 53-18 - Cover crop matrix: A plant penology based tool for crop species selection and agroecosystem decision making

Thursday, August 7, 2008
Exhibit Hall CD, Midwest Airlines Center
Jude Maul, USDA-ARS, Sustainable Agriculture Systems Laboratory, Beltsville, MD
Background/Question/Methods

Cover crops perform a wide variety of roles in agroecosystems that include nitrogen fixation, erosion control and building soil organic matter.  The large number of cover crops available and the broad range of crop functional diversity can be overwhelming for land managers and farmers attempting to choose the correct crop for their particular site or system.  A number of researchers and extension offices have produced publications that have attempted to clarify this decision making process by providing compendiums and searchable websites to aid in crop selection for agroecosystems.  The cover crop matrix is a synthesis of over 40 publications that describe cover crop phonological states and integrate these characteristics into a graphical decision making tool aimed at providing researchers, land managers and farmers an intuitive approach to cover crop selection for a wide variety of agroecosystems. 

Results/Conclusions

We synthesized cover crop penological data from multiple publications to create a data matrix that includes the seasonal time frames for germination, emergence, periods of maximal growth, onset of flowering, seed set, and senescence.  To this data matrix we added time points for critical management actions commonly used in conservation and organic farming systems. This combined database was used as input for the graphical authoring program Flash.  The output resulted in a chart that depicts up to 10 cover crops on one page arranged in a temporal fashion that allows quick comparison between multiple crops.  Overlaid on the crop phonological data are time points for agricultural management actions.  Informal surveys with land managers and farmers have confirmed that graphical representation of cover crop phonological traits in combination with agricultural management actions are helpful for making crop selection choices.  Future plans include a web-based interface that will allow users to enter crop data as new cover crops become available.

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