|Mueller Warrant, George|
|ANDERSON, NICOLE - Oregon State University|
|SULLIVAN, CLARE - Oregon State University|
Submitted to: International Journal of Applied Earth Observation and Geoinformation
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/21/2017
Publication Date: 4/20/2017
Citation: Mueller Warrant, G.W., Trippe, K.M., Whittaker, G.W., Anderson, N.P., Sullivan, C.S. 2017. Spatial methods for deriving crop rotation history. International Journal of Applied Earth Observation and Geoinformation. 60:22-37.
Interpretive Summary: Crop rotations are both challenging and rewarding to study. Traditional field plot techniques limit researchers to a very small number of all possible rotations among crops of interest in a region, and even then require an intensive, long-term commitment of resources. We used remote sensing classification as the basis for studying patterns in sequences of crops over an 11 year period in western Oregon, ultimately deriving a long list of crop rotations that growers use to transition from one grass seed crop to the next, showing results for new perennial ryegrass stands in this paper. This study indicated that growers do not randomly select rotation crops between successive grass seed stands. Instead, their choices are deliberately made up to five years out from eventual establishment of new stands of perennial ryegrass seed crops. The wide range in crop rotation lengths when changing from an old grass seed crop to a new perennial ryegrass stand suggests the existence of multiple ways to achieve the same goal, each with its own compelling set of benefits and drawbacks. Winter wheat was the most commonly grown rotational crop, independent of the number of years available for crop production between grass seed stands. Crop rotation patterns available for each specific period between grass seed stands rapidly increased in complexity as the number of intervening years increased from zero to four. At a bare minimum, there would be two, three, seven, 19 and 22 crop rotations of importance for the range from 2-year to 6-year long crop rotations.
Technical Abstract: Converting multi-year remote sensing classification data into crop rotations is beneficial by defining length of crop rotation cycles and the specific sequences of intervening crops grown between the final year of a grass seed stand and establishment of a new perennial ryegrass seed crop. Markov model testing found that year-to-year cropping sequences did not match average frequencies for transitions among all crops grown in western Oregon, instead showing that rotations into new stands of perennial ryegrass must be influenced by growers’ desires to achieve specific objectives. The two most common crop rotation lengths were three years and six or more years between established grass seed crops, while 18% of fields were immediately planted back to what must have been the same variety if the seed was certified. Three-year rotations allowed production of a single intervening crop between old and new grass seed stands, with winter wheat being grown more often than alternatives such as unknown summer annuals, beans, full-year fallow, and meadowfoam. Four-year rotations allowed use of separate break and setup crops in the two intervening years, with winter wheat used more often for both purposes than the other less common intervening crops (unknown summer annuals, clover seed, beans, and Brassicaceae seed crops). New perennial ryegrass stands were fall-planted an average of 10.6-times as often as they were spring-planted. Numerous rotations existed where attempts to establish new perennial ryegrass stands failed, highlighting one of the most problematic aspects of current grass seed production systems.