Drip irrigation systems controlled by soil moisture sensors and a soil water balance model for cassava grown in soils of two different textures

Abstract

Cassava (Manihot esculenta Crantz) yield could be improved by drip irrigation if irrigation scheduling is correctly organized. Soil moisture content is an important factor for controlling irrigation. It can be directly monitored by soil moisture sensors or predicted by soil water balance (SWB) models. Field experiments were conducted to investigate cassava production under drip irrigation and to determine the relationship between soil moisture content predicted from SWB models and actual measurements from soil moisture sensors. Treatments were carried out in a randomized complete block design with four replications including: T1: rainfed; T2: drip irrigation controlled by soil moisture sensors; T3: drip irrigation controlled by a SWB model. The results showed that cassava yield and water use efficiency in irrigated treatments were higher than in rainfed treatments but there were no significant differences between T2 and T3. The predicted soil moisture content (SMCp) was slightly higher than the measured soil moisture content (SMCm). The difference between SMCp and SMCm was consistently the same throughout the measuring period. The overall results confirmed that the SWB model can be accurately used to predict soil moisture content. Drip irrigation controlled by the SWB model achieved a high cassava yield and WUE values similar to those produced using drip irrigation controlled by a soil moisture sensor.