Climate change and related weather events indirectly increase child malnutrition by increase food insecurity and decreasing dietary diversity. I am working with a multi-disciplinary team to to generate evidence linking climate change to malnutrition, we aim to co-develop mitigation strategies with communities that directly address the link between climate change and malnutrition.

This research is funded by the Wellcome Trust, led by Zvitambo Institute for Maternal and Child Health Research  in collaboration with the Food and Nutrition Council and Cornell University.

This project aims to identify when AI genuinely improves breeding decisions compared with conventional quantitative genetics approaches. It will develop an AI decision-support tool and shared workflow to help breeders use large phenotypic, genomic, environmental and socio-economic datasets to define target product profiles reflecting diverse smallholder farms needs, delineate target populations of environments, and optimise crossing and selection for on-farm genetic gain. 

This research is funded by FCDO (UK) in collaboration with Roslin (Edinburgh University), CBI (Zimbabwe), ZARI (Zambia), KALRO (Kenya), Chitedzi Agriculture Research Institute (Malawi), IIAM (Mozambique) and NARO (Uganda).

The project will examine how climate variability affects mental health by combining high-resolution environmental data, historical surveys, a new survey across eight districts and current climate data. Using human-centred design, it will co-develop community-led adaptation strategies and integrate them into community platforms such as the Friendship Bench. It will also work with policymakers and run public awareness campaigns so that mental health is built into Zimbabwe's climate policies and resilience strategies.

This research is funded by the Wellcome Trust, led by Zvitambo Institute for Maternal and Child Health Research in collaboration with the Food and Nutrition Council, Cornell University, Met Services Department (Zimbabwe)

The project aims to shorten the time needed to deliver climate-resilient, market-preferred dryland crop varieties. It will combine two approaches: using uantitative genetics methods, such as desired-gain selection indexes, for better parent selection, and applying breeding cycle acceleration techniques to advance generations rapidly. The innovations will be tested first in sorghum as a proof-of-concept before being extended to other dryland crops.

This research is funded by NNF, with ICRISAT, University of Queensland, ICAR, KARLO (Kenya), ZARI (Zambia), EIAR (Ethiopia), IIAM (Mozambique), NARO (Uganda) and TARI (Tanzania).

The project will screen maize root exudates for biological nitrification inhibition (BNI) using a high-throughput soil-based approach that tests activity against key soil nitrifiers, an ammonia-oxidising bacterium and archaeon, and a methanotroph, giving a more robust estimate of BNI capacity than earlier single-strain methods. The project will primarily focus on landraces from historically poor soil environments. The aim is to provide proof of concept that high-BNI maize to increase yield per unit of fertilizer in the field and help unlock future investment in genetic solutions for sustainable nitrogen use.

This research is in collaboration with the University of Alberta (Canada) in partnership with JIRCAS (Japan).