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Abstract

Field experiments were combined with a numerical model to optimize drip irrigation management based on soil matric potential (SMP) measurements. An experimental crop of eggplant was grown in Burkina Faso from December 2014 to March 2015 and plant response to water stress was investigated by applying four different irrigation treatments. Treatments consisted in using two different irrigation depths (low or high), combined with a water provision of 150%, 100% or 66% (150/100/66) of the maximum crop evapotranspiration (T150low, T66low, T100high, T66high). Soil matric potential measurements at 5, 10 and 15 cm depth were taken using a wireless sensor network and were compared with measurements of plant and root biomass and crop yields. Field data were used to calibrate a numerical model to simulate triggered drip irrigation. Different simulations were built using the software HYDRUS 2D/3D to analyze the impact of the irrigation depth and frequency, the irrigation threshold and the soil texture on plant transpiration and water losses. Numerical results highlighted the great impact of the root distribution on the soil water dynamics and the importance of the sensor location to define thresholds. A fixed optimal sensor depth of 10 cm was found to manage irrigation from the vegetative state to the end of fruit development. Thresholds were defined to minimize water losses while allowing a sufficient soil water availability for optimal crop production. A threshold at 10 cm depth of −15 kPa is recommended for the early growth stage and −40 kPa during the fruit formation and maturation phase. Simulations showed that those thresholds resulted in optimal transpiration regardless of the soil texture so that this management system can constitute the basis of an irrigation schedule for eggplant crops and possibly other vegetable crops in semi-arid regions.

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