Authors Michelle A. Sherwood, Yu Takeuchi, Worrel A.Diedrick, Kathy M. Dalip Vyjayanthi F. Lopez, Deshaune Martin, Jacqueline M. Spence and Dahlia Fletcher , The Beet Armyworm Pest Forecast Model: A Decision-Making Tool for Pest Management in Jamaica
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The Beet Armyworm Pest Forecast Model: A Decision-Making Tool for Pest Management in Jamaica
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Authors
Michelle A. Sherwood, Yu Takeuchi, Worrel A.Diedrick, Kathy M. Dalip
Vyjayanthi F. Lopez, Deshaune Martin, Jacqueline M. Spence and Dahlia Fletcher
,
The Beet Armyworm Pest Forecast Model: A Decision-
Making Tool for Pest Management in Jamaica
Beet Armywom outbreak in 2009-2012 FAO-TCP-3401 “Strengthening the National Beet armyworm
(Spodoptera exigua) Programme” was approved in 2012 Two Years Oct 2012 to Oct 2014 Valued at US$ 213,000 Implemented: by MOA&F, R&D (Bodles) / Rural Agricultural Development
Authority (RADA) Beneficiaries: farmers of St. Elizabeth, Partners: ACDI/VOCA (complementary activities FFS, ODK training) Project Lead by TWG lead by Research and Development Division in
collaboration with RADA, Met. Office and ALMD.
ACDI/VOCA received a 4-year, $14 million award from USAID to implement the Jamaica Rural Economy and Ecosystems Adapting to Climate cHange (Ja-REEACH) program (formerly MAJIC program that focused on transforming Jamaica’s agriculture sector into a market-driven, competitive industry) http://www.acdivoca.org/site/ID/jamaica-ja-reeach
(1) Monitoring and surveillance programme for beet armyworm strengthened and a monitoring tool established and institutionalized in appropriate agencies Evaluate and improve data collection and analysis
programme Formulate a forecasting tool including assessment
of GIS requirements Review institutional arrangements for operating
the forecasting tool Train 10 personnel from key agencies to maintain
the tool
Activities Progress to date
• Development and establishment of BAW forecasting tool (FT):
Expert consultant recruited to develop FT based on• Analysis of weather patterns in
Jamaica• Development of a Degree-day
Model• Pest Population Dynamics
One Mission completed (2013)1. Evaluation of information, IT and
2. Installation of selected FT and training of 15 national personnel in R&D, RADA, Met. Office, ICT, ALMD, PQ were trained
3. the use and maintenance of selected FT
Third Mission (July 20-24, 2015) 4. Final workshop & institutionalization of FT
FAO Consultant Pest Forecasting
Specialist - Ms. Yu Takeuchi
DEGREE DAY MODEL
The total amount of heat required between the upper and lower thresholds for an organism to develop from one point to another in its lifecycle is calculated in Units called Degree days
Data generated by R&D and NCU under local conditions and data gaps filled by published data from North America
Degree days recorded during April and May for 2010 to 2013 ranged from 1289.01 to 1850.14 which means there were 2-3 BAW lifecycle per month. This resulted in outbreaks and flare up of the population during these periods. This data provides a guide for warning farmers when to expect an outbreak using degree days. June i
Degree Days at Barton Isles during outbreak periods January - April, May & June 2010 to 2015
April May June
Deg
ree
days
at B
arto
n is
les
BAW POPULATION DURING PERIOD
AREA-WIDE MONITORING & SURVEILLANCE OF BEET ARMYWORM
Monitoring: Pest monitoring by RADA from 8 -10
locations across the affected areas in the Parish of St. Elizabeth using ODK App.
Used to determine when population exceed the damage threshold of 5 larvae per plant or 1 larvae in 5 plant to guide timing of management programme
Same population data needed to validate BAW Pest Forecasting System (PFS) by comparing field populations against predictions of the BAW PFS
DECISION OPTIONS Pest management Strategy: The advisory may
No intervention required continue monitoring Interventions required: Dependent on pest population
& stage of pest Include information re the various Integrated
Pest Management components to be used e.g. Monitoring, Cultural, Mechanical, Biological and, Chemical to be applied in an environmentally friendly
and sustainable manner.
DISSEMINATION OF INFORMATION
Once the degree day prediction is generated it can be shared with other institutions to develop advisories for farmers as to decision making re BAW
Advisories can then be prepared by the interpretation of the forecast and disseminated through various media to farmers for their action, Texting via phone Print or electronic media Weather report