| Autor: |
Loo EPI; Heinrich-Heine-Universitat Dusseldorf, Duesseldorf, Germany; loo@hhu.de., Szurek B; IRD, UMR 5096 CNRS-UP-IRD , 911, Avenue Agropolis BP 64501, Montpellier , France, Cedex 5.; France; Boris.Szurek@ird.fr., Arra Y; Heinrich-Heine-Universitat Dusseldorf, Duesseldorf, Germany; arrayugander@gmail.com., Stiebner M; Heinrich-Heine-Universitat Dusseldorf, Duesseldorf, Germany; melissa.stiebner@hhu.de., Buchholzer M; Heinrich-Heine-Universitat Dusseldorf, Duesseldorf, Germany; marcel.buchholzer@uni-duesseldorf.de., Devanna BN; Heinrich-Heine-Universitat Dusseldorf, Duesseldorf, Germany; devnova2460@gmail.com., Vera Cruz CM; International Rice Research Institute, Manila, Philippines; nollie.veracruz@gmail.com., Frommer WB; Heinrich-Heine-Universitat Dusseldorf, Universitätstr. 1, Duesseldorf, Germany, 40225; frommew@hhu.de. |
| Abstrakt: |
A path to sustainably reduce world hunger, food insecurity, and malnutrition is to close the crop yield gap, particularly, losses due to pathogens. Breeding resistant crops is key to achieving this goal, 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 of the yield gap. |
