Skip to content
VuFind
    • English
    • Español
Advanced
  • Soybean rust early warning sys...
  • Cite this
  • Text this
  • Print
  • Export Record
    • Export to RefWorks
    • Export to EndNoteWeb
    • Export to EndNote
  • Permanent link
Cover Image
QR Code

Soybean rust early warning system in East and Southern Africa

Bibliographic Details
Main Authors: Gachoki, S., Muthoni, F., Mureithi, H., Tripathi, L.
Format: Informe técnico
Language:Inglés
Published: International Institute of Tropical Agriculture 2024
Subjects:
modelling
climate change
species
distribution
models
machine learning
Online Access:https://hdl.handle.net/10568/159926
  • Description
  • Similar Items
  • Staff View
Description
Description not available.

Similar Items

  • Mapping aflatoxin risk using machine learning and remote sensing in East and Southern Africa
    by: Gachoki, S., et al.
    Published: (2024)
  • Predicting aflatoxin risk in maize using machine learning and satellite data in East and Southern Africa
    by: Gachoki, Stella, et al.
    Published: (2024)
  • Predicting aflatoxin risk in maize using machine learning and satellite data in East and Southern Africa
    by: Gachoki, S., et al.
    Published: (2025)
  • Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands
    by: Irvin, Jeremy, et al.
    Published: (2021)
  • Drivers of maize yield variability at household level in northern Ghana and Malawi
    by: Gachoki, S., et al.
    Published: (2023)

© Copyright 2026, Todos los Derechos Reservados UNA