Integrating Field Data and a Modeling Approach to Inform Optimum Planting Date × Maturity Group for Soybeans under Current and Future Weather Conditions in Kansas

Emmanuela van Versendaal (), Ana J. P. Carcedo, Eric Adee, Gretchen Sassenrath, Scott Dooley, Jane Lingenfelser and Ignacio A. Ciampitti ()
Additional contact information
Emmanuela van Versendaal: Department of Agronomy, Kansas State University, 1712 Claflin Rd., Manhattan, KS 66506, USA
Ana J. P. Carcedo: Department of Agronomy, Kansas State University, 1712 Claflin Rd., Manhattan, KS 66506, USA
Eric Adee: Department of Agronomy, Kansas State University, 1712 Claflin Rd., Manhattan, KS 66506, USA
Gretchen Sassenrath: Department of Agronomy, Kansas State University, 1712 Claflin Rd., Manhattan, KS 66506, USA
Scott Dooley: Department of Agronomy, Kansas State University, 1712 Claflin Rd., Manhattan, KS 66506, USA
Jane Lingenfelser: Department of Agronomy, Kansas State University, 1712 Claflin Rd., Manhattan, KS 66506, USA
Ignacio A. Ciampitti: Department of Agronomy, Kansas State University, 1712 Claflin Rd., Manhattan, KS 66506, USA

Sustainability, 2023, vol. 15, issue 2, 1-12

Abstract: Optimizing planting date by maturity group (PD × MG) is critical to increase productivity and reduce production risks. Understanding the effect of management, not only under current, but also future weather conditions, is even more relevant for developing effective mitigation strategies. This paper provides an analysis of the optimum combinations of soybean PD × MG management in the central-eastern region of Kansas (United States) for both current and future weather conditions. Three geographical clusters illustrating the main environmental and management characteristics were defined within the central-eastern region of Kansas. The Agricultural Production Systems Simulator platform was employed to explore PD × MG combinations (PD from mid-April to mid-July; MG from III to VI) comparing current (2011–2021) and future (2042–2052) weather conditions. Overall, early planting dates produce greater yields, but reduce their stability over time (with a 15% increase in yield variation relative to late planting) across the clusters. Late planting dates resulted in a reduction close to 27% for soybean yields relative to those obtained by planting at early dates under current weather conditions. Furthermore, longer maturity groups (IV, V, and VI) resulted in a reduced yield penalty when planting time was delayed under the current weather conditions. However, this combination did not always represent the strategy that maximized yields.

Keywords: soybean seed yield; crop modeling; management practices; future weather (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/2/1081/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/2/1081/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:2:p:1081-:d:1027413

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().