Coconuts are a crucial global food crop, consumed by around 30% of the world's population. Anecdotal observations suggest that the yield of coconut trees depends on climatic conditions and is particularly sensitive to drought. In light of increasing climate uncertainties, there is an urgent need to identify and promote the cultivation of genetically drought-resistant trees, especially in regions prone to drought.
For this project, I leveraged climate and yield data from the Ivory Coast. The Ivory Coast, with its diverse climatic patterns, offers a rich dataset that can provide valuable insights into the interplay between climatic factors and coconut yields.
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Feature Engineering: I used rainfall and temperature data to engineer distinct features aimed at capturing the effects of drought on coconut yields.
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Modeling Sensitivity: I then used generalised additive models to analyse the sensitivity of individual coconut trees to drought.
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Identification: Post analysis, I identified trees that exhibit drought-sensitive or drought-resistant traits. This classification was then used to recommend cultivation strategies in varying climatic conditions.
By understanding which trees are naturally more drought-resistant, agricultural strategies can be refined to ensure consistent yields, even in adverse climatic conditions. This project not only holds the potential to stabilise the coconut supply in drought-prone regions but also supports the livelihoods of countless farmers and communities dependent on this crop.