Identifying research priorities through decision analysis: A case study for cover crops

IntroductionIn Midwestern maize (Zea-mays L.)-based systems, planting an over-wintering cover crop such as rye (Secale cereale L.) following fall harvests of summer crops maintains continuous soil cover, offering numerous environmental advantages. However, while adoption of cover crops has increased...

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Main Authors: Gina A. Nichols, Cameron A. MacKenzie
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-03-01
Series:Frontiers in Sustainable Food Systems
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fsufs.2023.1040927/full
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author Gina A. Nichols
Gina A. Nichols
Cameron A. MacKenzie
author_facet Gina A. Nichols
Gina A. Nichols
Cameron A. MacKenzie
author_sort Gina A. Nichols
collection DOAJ
description IntroductionIn Midwestern maize (Zea-mays L.)-based systems, planting an over-wintering cover crop such as rye (Secale cereale L.) following fall harvests of summer crops maintains continuous soil cover, offering numerous environmental advantages. However, while adoption of cover crops has increased over the past decade, on a landscape-scale it remains low. Identifying where agronomic research could be most impactful in increasing adoption is therefore a useful exercise. Decision analysis (DA) is a tool for clarifying decision trade-offs, quantifying risk, and identifying optimal decisions. Several fields regularly utilize DA frameworks including the military, industrial engineering, business strategy, and economics, but it is not yet widely applied in agriculture.MethodsHere we apply DA to a maize-soybean [Glycine max (L.) Merr.] rotation using publicly available weather, management, and economic data from central Iowa.ResultsIn this region, planting a cover crop following maize (preceding soybean) poses less risk to the producer compared to planting following soybean, meaning it may be a more palatable entry point for producers. Furthermore, the risk of reduced maize yields when planting less than 14 days following rye termination substantially contributes to the overall risk cover crops pose to producers, but also has significant potential to be addressed through agronomic research.DiscussionIn addition to identifying research priorities, DA provided clarity to a complex problem, was performed using publicly available data, and by incorporating risk it better estimated true costs to the producer compared to using input costs alone. We believe DA is a valuable and underutilized tool in agronomy and could aid in increasing adoption of cover crops in the Midwest.
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spelling doaj.art-df9880eb03ab4d52a97afb1c56b213a82023-03-23T06:30:35ZengFrontiers Media S.A.Frontiers in Sustainable Food Systems2571-581X2023-03-01710.3389/fsufs.2023.10409271040927Identifying research priorities through decision analysis: A case study for cover cropsGina A. Nichols0Gina A. Nichols1Cameron A. MacKenzie2Department of Plant Sciences, University of California, Davis, Davis, CA, United StatesDepartment of Agronomy, Iowa State University, Ames, IA, United StatesDepartment of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, IA, United StatesIntroductionIn Midwestern maize (Zea-mays L.)-based systems, planting an over-wintering cover crop such as rye (Secale cereale L.) following fall harvests of summer crops maintains continuous soil cover, offering numerous environmental advantages. However, while adoption of cover crops has increased over the past decade, on a landscape-scale it remains low. Identifying where agronomic research could be most impactful in increasing adoption is therefore a useful exercise. Decision analysis (DA) is a tool for clarifying decision trade-offs, quantifying risk, and identifying optimal decisions. Several fields regularly utilize DA frameworks including the military, industrial engineering, business strategy, and economics, but it is not yet widely applied in agriculture.MethodsHere we apply DA to a maize-soybean [Glycine max (L.) Merr.] rotation using publicly available weather, management, and economic data from central Iowa.ResultsIn this region, planting a cover crop following maize (preceding soybean) poses less risk to the producer compared to planting following soybean, meaning it may be a more palatable entry point for producers. Furthermore, the risk of reduced maize yields when planting less than 14 days following rye termination substantially contributes to the overall risk cover crops pose to producers, but also has significant potential to be addressed through agronomic research.DiscussionIn addition to identifying research priorities, DA provided clarity to a complex problem, was performed using publicly available data, and by incorporating risk it better estimated true costs to the producer compared to using input costs alone. We believe DA is a valuable and underutilized tool in agronomy and could aid in increasing adoption of cover crops in the Midwest.https://www.frontiersin.org/articles/10.3389/fsufs.2023.1040927/fullcover cropsoybeanriskdecision analysis (DA)Iowa (USA)maize (Zea mays L.)
spellingShingle Gina A. Nichols
Gina A. Nichols
Cameron A. MacKenzie
Identifying research priorities through decision analysis: A case study for cover crops
Frontiers in Sustainable Food Systems
cover crop
soybean
risk
decision analysis (DA)
Iowa (USA)
maize (Zea mays L.)
title Identifying research priorities through decision analysis: A case study for cover crops
title_full Identifying research priorities through decision analysis: A case study for cover crops
title_fullStr Identifying research priorities through decision analysis: A case study for cover crops
title_full_unstemmed Identifying research priorities through decision analysis: A case study for cover crops
title_short Identifying research priorities through decision analysis: A case study for cover crops
title_sort identifying research priorities through decision analysis a case study for cover crops
topic cover crop
soybean
risk
decision analysis (DA)
Iowa (USA)
maize (Zea mays L.)
url https://www.frontiersin.org/articles/10.3389/fsufs.2023.1040927/full
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