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Dr Joseph Mhango

Senior Lecturer in Applied Data Science

Researcher Profile

I leverage big data from satellite imagery, unmanned earial vehicles and proximal soil sensors to generate prediction models for decision support in agriculture. My research interests include high throughput plant phenotyping and the use of deep learning methods for predictive modelling and automating perception tasks in agriculture.

Academic Department: Agriculture and Environment

Research: Centre for Agricultural Data Science

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Office: G44 Jubilee Adams, Tudor Lodge and NW Building

Research profile:

Publications

Other publications

Olivia C. Kacheyo; Kanthu J. Mhango; Michiel E. de Vries; Hannah M. Schneider; Paul C. Struik (2024) Bed, ridge and planting configurations influence crop performance in field-transplanted hybrid potato crops Field Crops Research
Joseph K. Mhango; Ivan G. Grove; William Hartley; Edwin W. Harris; James Monaghan (2022) Applying colour-based feature extraction and transfer learning to develop a high throughput inference system for potato (Solanum tuberosum L.) stems with images from unmanned aerial vehicles after canopy consolidation Precision Agriculture
J. K. Mhango; W. Hartley; W. E. Harris; James Monaghan (2021) Comparison of potato (Solanum tuberosum L.) tuber size distribution fitting methods and evaluation of the relationship between soil properties and estimated distribution parameters The Journal of Agricultural Science
Joseph K. Mhango; W. Edwin Harris; James Monaghan (2021) Relationships between the Spatio-Temporal Variation in Reflectance Data from the Sentinel-2 Satellite and Potato (Solanum Tuberosum L.) Yield and Stem Density Remote Sensing
Joseph K. Mhango; Edwin W. Harris; Richard Green; James Monaghan (2021) Mapping Potato Plant Density Variation Using Aerial Imagery and Deep Learning Techniques for Precision Agriculture Remote Sensing

Research projects

Tuberscan: Using deep learning and data science to improve agronomy decisions in the potato industry - Researcher

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