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Closing the Information Gap Between the Field and Scientific Literature for Improved Disease Management, with a Focus on Rice and Bacterial Blight
Article de revue   Open Access   Avec comité de lecture

Closing the Information Gap Between the Field and Scientific Literature for Improved Disease Management, with a Focus on Rice and Bacterial Blight

Eliza P I Loo, Boris Szurek, Yugander Arra, Melissa Stiebner, Marcel Buchholzer, B N Devanna, Casiana M Vera Cruz et Wolf B Frommer
Molecular Plant-Microbe Interactions, Vol.38(2), p.134-141
01/2025
PMID: 39186001

Résumé

rice resistance genes plant-pathogen interactions management bacterial pathogenesis susceptibility
A path to sustainably reduce world hunger, food insecurity, and malnutrition is to close the crop yield gap and, particularly, lower losses due to pathogens. Breeding resistant crops is key to achieving this goal, which is an effort requiring collaboration among stakeholders, scientists, breeders, farmers, and policymakers. During a disease outbreak, epidemiologists survey the occurrence of a disease after which pathologists investigate mechanisms to stop an infection. Policymakers then implement strategies with farmers and breeders to overcome the outbreak. Information flow from the field to the lab and back to the field involves several processing hubs that require different information inputs. Failure to communicate the necessary information results in the transfer of meaningless data. Here, we discuss gaps in information acquisition and transfer between the field and laboratory. Using rice bacterial blight disease as an example, we discuss pathogen biology and disease resistance to point out the importance of reporting pathogen strains that caused an outbreak to optimize the deployment of resistant crop varieties. We examine differences between infection in the field and assays performed in the laboratory to draw awareness of possible misinformation concerning plant resistance or susceptibility. We discuss key data considered useful for reporting disease outbreaks, sampling bias, and suggestions for improving data quality. We also touch on the knowledge gap in the state-of-the-art literature regarding disease dispersal and transmission. We use a recent case study to exemplify the gaps mentioned. We conclude by highlighting potential actions that may contribute to food security and to closing the yield gap. [Formula: see text] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

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