Digital agriculture platforms have gained traction in addressing food security challenges in Africa's rural areas. In Ethiopia's highlands, where climate variability and resource scarcity pose significant hurdles to agricultural productivity, these platforms promise improved yield gains and more efficient use of resources. A mixed-methods approach incorporating surveys, field observations, and statistical modelling was employed. Data collected from 100 randomly selected farmers were analysed using a Linear Regression Model (LM) to estimate yield gains and resource utilization efficiency. The LM revealed that digital agriculture platforms contributed significantly to crop yields by an average of 25% compared to traditional methods, with a 95% confidence interval. Farmers utilising the platforms reported a 10% reduction in water usage per hectare, demonstrating enhanced resource management strategies. The findings suggest that digital agriculture platforms enhance both yield gains and resource efficiency in Ethiopian highlands, promising sustainable agricultural development through improved technology adoption. Further research should focus on scalability of these platforms across different regions and socio-economic contexts. Policy recommendations include subsidizing digital infrastructure to facilitate broader farmer access. Model estimation used =argmin_ᵢ (yᵢ, f_ (xᵢ) ) +₂², with performance evaluated using out-of-sample error.
Mekdes Gebreab (Sat,) studied this question.
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