Modeling perennial groundcover effects on annual maize grain crop growth with the Agricultural Production Systems sIMulator

dc.contributor.author Dixon, Philip
dc.contributor.author Bartel, C. A.
dc.contributor.author Archontoulis, Sotirios
dc.contributor.author Lenssen, Andrew
dc.contributor.author Moore, Kenneth
dc.contributor.author Huber, Isaiah
dc.contributor.author Lenssen, Andrew
dc.contributor.author Laird, D. A.
dc.contributor.author Fei, Shuizhang
dc.contributor.author Dixon, Philip
dc.contributor.department Agronomy
dc.contributor.department Statistics
dc.contributor.department Horticulture
dc.date 2020-06-10T14:29:53.000
dc.date.accessioned 2020-06-29T23:06:38Z
dc.date.available 2020-06-29T23:06:38Z
dc.date.copyright Tue Jan 01 00:00:00 UTC 2019
dc.date.embargo 2020-12-23
dc.date.issued 2019-12-23
dc.description.abstract <p>The inclusion of perennial groundcover (PGC) in maize production offers a tenable solution to natural resources-related concerns associated with conventional maize; however, insight into system management and key information gaps is needed to guide future research. We therefore extended the Agricultural Production Systems sIMulator (APSIM) to an annual and perennial intercrop by integrating annual and perennial APSIM modules. These were parameterized for Kentucky bluegrass (KB) (Poa pratensis L.) or creeping red fescue (CF) (Festuca rubra L.) as PGC using a three-year dataset. Our objectives for this intercropping modeling study were to: i) simultaneously model a PGC and annual cash crop using APSIM software; ii) utilize APSIM to understand interactive processes in the maize-PGC system; and iii) utilize the calibrated model to explore both production and environmental benefits via scenario modeling. For objective I, the integrated model successfully predicted maize total aboveground biomass (TAB) (relative root mean square error, RRMSE of 13- 27%) and PGC above- and belowground tissue N concentration (RRMSE of 11-18%). The calibrated model effectively captured observed trends in PGC biomass accumulation and soil nitrate (NO3). For objective II, model analysis showed that competition for light was the primary maize yield penalty factor from PGC, while water and N impacted maize yield later in the maize growing season. In objective III, we concluded that effective PGC suppression produces minimal maize yield loss and significant environmental benefits; conversely, poor groundcover suppression may produce unfavorable environmental consequences and decrease maize grain yield. Effective PGC suppression is key for long-term system success.</p>
dc.description.comments <p>This is a manuscript of an article published as Bartel, C. A., Sotirios V. Archontoulis, Andrew W. Lenssen, Kenneth J. Moore, Isaiah L. Huber, David A. Laird, S. Fei, and P. M. Dixon. "Modeling perennial groundcover effects on annual maize grain crop growth with Agricultural Production Systems sIMulator." <em>Agronomy Journal</em> 112 (2019): 1895-1910. doi: <a href="https://doi.org/10.1002/agj2.20108">10.1002/agj2.20108</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/agron_pubs/620/
dc.identifier.articleid 1665
dc.identifier.contextkey 16069705
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath agron_pubs/620
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/4992
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/agron_pubs/620/0-Permissions___Digital_Library.pdf|||Sat Jan 15 01:18:33 UTC 2022
dc.source.bitstream archive/lib.dr.iastate.edu/agron_pubs/620/2019_Lenssen_ModelingPerennialManuscript.pdf|||Sat Jan 15 01:18:34 UTC 2022
dc.source.uri 10.1002/agj2.20108
dc.subject.disciplines Agriculture
dc.subject.disciplines Agronomy and Crop Sciences
dc.subject.disciplines Horticulture
dc.subject.disciplines Statistical Models
dc.title Modeling perennial groundcover effects on annual maize grain crop growth with the Agricultural Production Systems sIMulator
dc.type article
dc.type.genre article
dspace.entity.type Publication
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