Our interdisciplinary team blends engineers, biologists and mathematicians to quantify and model the small scale spread of cassava’s most damaging pathogen in sub-Saharan Africa. We will refine our multispectral scanning device (MSI) and model to accommodate field conditions, where other plant stresses may affect the underlying signals detected by the MSI. We will experimentally monitor the spread of CBSD in experimental fields with both susceptible and tolerant cultivars of cassava. We will develop models of how different detection methods affect the amount of CBSD in a cassava clean seed system that will be applicable to any vegetatively propagated crop, including the US potato clean seed system. Finally we will model how an improved clean seed system and judicious use of an MSI or molecular testing could improve the security of small stakeholder farmers over multiple harvest seasons.
We are confident that our MSI tool and our models will be of wide use for other agricultural pathosystems. In the process of obtaining the parameters needed for accurate models, we will uncover key data about the biology and evolvability of CBSIs. The proposed research would be a significant advance in agricultural technology (Grieve et al 2019), provide useful and adaptable models for agricultural problems in both developing and developed nations and be a large step towards assuring food security of this critical crop in sub-Saharan Africa.