Cover crop adoption and intensity on Wisconsin's organic vegetable farms

Cover crop adoption varies across agroecological contexts, both in terms of the number of farmers using cover crops and in the ways that farmers use them. Most assessments of cover crop adoption treat adoption as a binary variable, rather than as a continuum of practices, and do not use regression a...

Full description

Saved in:
Bibliographic Details
Published in:Agroecology and sustainable food systems 2016-08, Vol.40 (7), p.693-713
Main Authors: Moore, Virginia M., Mitchell, Paul D., Silva, Erin M., Barham, Bradford L.
Format: Article
Language:English
Subjects:
Agriculture
Biodiversity
Cover crops
Crops
Farms
organic agriculture
Organic gardening
Regression analysis
Technology adoption
vegetable production
Wisconsin
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Cover crop adoption varies across agroecological contexts, both in terms of the number of farmers using cover crops and in the ways that farmers use them. Most assessments of cover crop adoption treat adoption as a binary variable, rather than as a continuum of practices, and do not use regression analysis to identify the drivers of adoption. In 2014, we surveyed organic vegetable farmers in Wisconsin to assess their use of cover crops in terms of cover crop acreage, species diversity, and complexity of management practices. We also used regression analysis to identify key drivers of cover crop use and assessed farmer and farm characteristics and perceptions of cover crops. Survey results and regression analysis show that cover crops are widely used by Wisconsin's organic vegetable farmers, but acreage, diversity, and complexity of cover crop use varied and have different explanatory factors. Cover cropping extent is negatively correlated with dependence on vegetable revenue, while cover crop species diversity and complexity are positively linked to more educated and experimental farmers. By using different measures of adoption and regression analysis, we can better understand how and why farmers are using cover crops, providing opportunities for improved adoption through research and policy interventions.
ISSN:2168-3565
2168-3573
DOI:10.1080/21683565.2016.1181694