Agricultural Sciences
Adaptive Irrigation Scheduling for Smallholder Farms Using Low-Cost Soil Sensors
A field study showing 27% water savings from sensor-guided irrigation on smallholder farms in South-East Nigeria.
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Abstract
Smallholder farms in sub-Saharan Africa face growing water stress from irregular
rainfall, yet most irrigation decisions are still made by intuition. This study
evaluates a low-cost, sensor-guided irrigation schedule against conventional
practice across twelve smallholder plots in Anambra State, Nigeria, over a single
dry-season cropping cycle. Using capacitive soil-moisture sensors and a simple
threshold controller, the sensor-guided group reduced total water application by
27% while maintaining equivalent yield. We discuss the cost model, sensor drift
over the season, and the practical barriers to adoption. The results suggest that
sub-US$40 sensor kits can deliver meaningful water savings without specialised
training, offering a scalable path to climate-resilient smallholder agriculture.
rainfall, yet most irrigation decisions are still made by intuition. This study
evaluates a low-cost, sensor-guided irrigation schedule against conventional
practice across twelve smallholder plots in Anambra State, Nigeria, over a single
dry-season cropping cycle. Using capacitive soil-moisture sensors and a simple
threshold controller, the sensor-guided group reduced total water application by
27% while maintaining equivalent yield. We discuss the cost model, sensor drift
over the season, and the practical barriers to adoption. The results suggest that
sub-US$40 sensor kits can deliver meaningful water savings without specialised
training, offering a scalable path to climate-resilient smallholder agriculture.
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View ProfileEmmanuel Emelie
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