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Phytopathology
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Phytopathology
Article . 2017 . Peer-reviewed
Data sources: Crossref
Phytopathology
Article . 2017
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Preventative Disease Management and Grower Decision Making: A Case Study of California Wine-Grape Growers

Authors: Mark Lubell; Kendra Baumgartner; Jonathan D. Kaplan; Vicken Hillis;

Preventative Disease Management and Grower Decision Making: A Case Study of California Wine-Grape Growers

Abstract

Preventative disease management is challenging to farmers because it requires paying immediate costs in the hopes of returning uncertain future benefits. Understanding farmer decision making about prevention has the potential to reduce disease incidence and minimize the need for more costly postinfection practices. For example, the grapevine trunk-disease complex (esca, Botryosphaeria dieback, Eutypa dieback, and Phomopsis dieback) significantly affects vineyard productivity and longevity. Given the chronic nature of the infections and inability to eradicate the fungal pathogens, the preventative practices of delayed pruning, applications of pruning-wound protectants, and double pruning (also known as prepruning) are the most effective means of management. We surveyed wine-grape growers in six regions of California on their use of these three practices. In spite of acknowledging the yield impacts of trunk diseases, a substantial number of respondents either choose not to use preventative practices or incorrectly adopted them in mature vineyards, too late in the disease cycle to be effective. Growers with more negative perceptions of cost efficacy were less likely to adopt preventative practices or were more likely to time adoption incorrectly in mature vineyards. In general, preventative management may require strong intervention in the form of policy or extension to motivate behavioral change.

Keywords

Decision Making, California, Ascomycota, Vitis, Plant Diseases

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    17
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Average
Top 10%
hybrid