English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The Louisiana Department of Agriculture and Forestry (LDAF) conducts sweetpotato weevil (SPW) ( Cylas formicarius  Fabricius) monitoring as part of the statewide SPW quarantine program. This activity involves a statewide pheromone-based trapping program that monitors sweetpotato beds and production fields. We conducted GIS analysis of SPW trap data, collected over three years, to assess the potential use of publicly available GIS tools in managing and interpreting the data. Trap data was mapped to specific beds and fields in each of three years, generating layers that clearly showed fields and parishes that reported high trap counts. GIS analysis showed potential SPW hotspots in each year, indicating that certain beds or fields are predisposed to SPW infestation than others. This information can be useful in planning SPW management strategies by growers and other stakeholders. The GIS database also provides the foundation for the development of descriptive and predictive models of SPW occurence not only in Louisiana, but in other states where SPW is a potential pest. For example, using presence data for Louisiana and Genetic Algorithm for Rule Set Prediction (GARP), a GIS-based ecological niche modelling tool, we were able to generate predicted distribution using mean minimum temperature for January as the predictor variable. Although additional work is needed to identify other predictor variables and verify the models, the results demonstrate the potential use of GIS-based tools for generating warnings or advisories related to SPW.

USING GIS TO ANALYZE SWEET POTATO WEEVIL TRAP DATA IN LOUISIANA