ompared to Thailand (1.39 tons/hectare) and Vietnam (1.69 tons/hectare), Ghana's rubber yields are relatively low at 0.88 tons/hectare. This is a concern for the Tree Crop Development Authority (TCDA) of Ghana, which aims to leverage tree crops, including rubber, to increase the cash crop sector's contribution to GDP and improve livelihoods. Despite a long gestation period, rubber presents a lucrative opportunity for farmers seeking to diversify beyond cocoa, coconut, and other tree crops. This research project proposes innovation (e.g. integration of artificial intelligence) to develop climate change adaptation and mitigation strategies for sustainable rubber production in Ghana. We will focus on three key ecological zones including the Wet Evergreen, Moist Evergreen and Moist Semi-deciduous SE). An on-farm approach will be employed to identify climate-smart rubber clones in Ghana. An approximately 30 fixed plots (50m x 50m) will be demarcated using GPS in rubber farms aged 10-30 years and vegetation, soil (MATE student focus), site and environmental characteristics will be measured. These plots will be established across the three ecological zones, considering both high and low altitude variations. Overall, this research can contribute to increased rubber production, support reforestation efforts, restore degraded lands and increased carbon sequestration.
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