Development of Sensor and Decision Support System (DSS)-based Automated Irrigation System for Enhancing Water Productivity of Tomato Crop

In India, given the rising trend of population growth, climate change and the need to increase agricultural production with efficient utilization of water, It is crucial to execute precise water management strategies in the farmland. In this study, efforts were made towards development of an automated system for irrigation scheduling on real-time basis considering the soil moisture conditions and crop parameters, and evaluation of performance under different irrigation methods in tomato crop. The soil moisture sensor was integrated with decision support system (DSS) and microcontroller using internet and global system for mobile communication (GSM) module for automated irrigation. The developed sensor was compared with Frequency Domain Reflectometer (FDR), tensiometer, and watermark sensor and was calibrated using the gravimetric method. The crop and irrigation water productivity of tomato crop ranged from 5.2–12.6 kg m-3 for control and automated systems, and 7.7–18.7 kg m-3 for the latter under different methods of irrigation. By using an automated drip irrigation system instead of a manually operated check basin irrigation system, cultivators of tomatoes were able to save 39.61% of the water. In terms of economics analysis, highest benefit cost ratio were obtained under manually operated drip irrigation (2.61) followed by automated drip irrigation system (2.50) in tomato crop.