Muchaonyerwa et al. (2026) Assessing the Potential of Multispectral UAV-Derived Vegetation Indices for Estimating Water Use of Taro (Colocasia esculenta) Under Different Weed Management Practices

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Identification

• Journal: Plants
• Year: 2026
• Date: 2026-09-18
• Authors: Knowledge Muchaonyerwa, Maqsooda Mahomed, Shaeden Gokool, Alistair David Clulow, Gary Denton, Kyle Reddy, Richard P. Kunz
• DOI: 10.3390/plants15182857

Research Groups

• Department of Agricultural Engineering, University of Nairobi
• International Water Management Institute (IWMI)
• Kenya Agricultural and Livestock Research Organisation (KALRO)

Short Summary

This study evaluates the viability of a vegetation index-based empirical model to estimate actual evapotranspiration (ETa) of taro under different weed management practices in smallholder farms using multispectral UAV imagery.

Objective

• Investigate the potential of VI-based empirical models to improve water use efficiency through integrated weed management (IWM) in smallholder farming systems.

Study Configuration

• Spatial Scale: Smallholder farm in sub-Saharan region
• Temporal Scale: Growing season

Methodology and Data

• Models used: Empirical model using Enhanced Vegetation Index 2 (EVI2) as a proxy for crop coefficient (Kc)
• Data sources: Multispectral UAV imagery, reference evapotranspiration (ETo)

Main Results

• The weeded plot used 27.0% less water compared to the intermediate field.
• The unweeded plot used 35.5% more water than the intermediate field.

Contributions

• This study contributes to understanding the association between reduced crop-weed competition, lower evapotranspiration, and increased taro yield in smallholder farming systems.
• The results support the potential of VI-based empirical models derived from multispectral UAV imagery for promoting water use efficiency through IWM.

Funding

• This research was supported by the Bill and Melinda Gates Foundation (grant number: OPP1183651)
• Funded by the CGIAR Research Program on Water, Land and Ecosystems (WLE)

Citation

@article{Muchaonyerwa2026Assessing,
  author = {Muchaonyerwa, Knowledge and Mahomed, Maqsooda and Gokool, Shaeden and Clulow, Alistair David and Denton, Gary and Reddy, Kyle and Kunz, Richard P.},
  title = {Assessing the Potential of Multispectral UAV-Derived Vegetation Indices for Estimating Water Use of Taro (Colocasia esculenta) Under Different Weed Management Practices},
  journal = {Plants},
  year = {2026},
  doi = {10.3390/plants15182857},
  url = {https://doi.org/10.3390/plants15182857}
}