Steering conservation biocontrol at the frontlines: A fuzzy logic approach unleashing potentials of climate-smart intercropping as a component within the integrated management of fall armyworm in Africa

This study introduces a computational index that employs fuzzy sets theory to identify potential deployment sites for push-pull as a component in the integrated management of Fall Armyworm (FAW) in Africa. The index, validated through known push-pull testing sites and informed by insights from field data and practical observations, is primarily based on companion plants (<i>Desmodium intortum</i> and <i>Brachiaria brizantha</i>), livestock, and maize as covariates. The study developed a set of rules linking each selected covariate to the output as membership functions, which are later combined using an algebraic operator. It identifies extensive maize farms across Africa potentially suitable for Push-Pull technology, although the suitability varies by region. Farms in the eastern and southern regions are predicted to be highly suitable, while the suitability of farms in West Africa is expected to improve over time due to the perennial nature and agronomic benefits of companion plants. The index is proposed as a metric for deploying push-pull technology, providing a roadmap for effective agronomic practices in Africa, and assisting farmers and decision-makers in the integrated management of FAW. Overall, our results indicate that the fuzzy-based computational index is an effective tool for identifying potential areas to maximise the benefits of push-pull technology as a key component of integrated FAW management. Our study identifies appropriate areas for application, allowing for the careful use of resources and increasing the likelihood of effective pest management. This approach will ultimately safeguard cereal crops, boost agricultural productivity, and aid in ensuring food security in Africa.