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Designing a Pest and Disease Outbreak Warning System for Farmers, Agronomists and Agricultural Input Distributors in East Africa.

Authors :
Brown, Molly E.
Mugo, Stephen
Petersen, Sebastian
Klauser, Dominik
Source :
Insects (2075-4450). Mar2022, Vol. 13 Issue 3, p232-N.PAG. 13p.
Publication Year :
2022

Abstract

Simple Summary: Designing early warning systems for threats to food crops in Africa must respond to the needs of potential users of the system. This paper provides evidence from professional distributors, retailers, researchers, and agronomists in East Africa who may be able to use and communicate the results of the predictive modeling of pest outbreaks. Understanding the timing and spatial extent of required warnings will help guide research and engagement in these rapidly commercializing countries. Early warnings of the risks of pest and disease outbreaks are becoming more urgent, with substantial increases in threats to agriculture from invasive pests. With geospatial data improvements in quality and timeliness, models and analytical systems can be used to estimate potential areas at high risk of yield impacts. The development of decision support systems requires an understanding of what information is needed, when it is needed, and at what resolution and accuracy. Here, we report on a professional review conducted with 53 professional agronomists, retailers, distributors, and growers in East Africa working with the Syngenta Foundation for Sustainable Agriculture. The results showed that respondents reported fall armyworm, stemborers and aphids as being among the most common pests, and that crop diversification was a key strategy to reduce their impact. Chemical and cultural controls were the most common strategies for fall armyworm (FAW) control, and biological control was the least known and least used method. Of the cultural control methods, monitoring and scouting, early planting, and crop rotation with non-host crops were most used. Although pests reduced production, only 55% of respondents were familiar with early warning tools, showing the need for predictive systems that can improve farmer response. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20754450
Volume :
13
Issue :
3
Database :
Academic Search Index
Journal :
Insects (2075-4450)
Publication Type :
Academic Journal
Accession number :
156019528
Full Text :
https://doi.org/10.3390/insects13030232