Evaluation of IoT based smart drip irrigation and ETc based system for sweet corn

Abstract

Smart irrigation is one form of precision irrigation that can help farmers maximize crop production while preserving water and energy. Many different types of smart irrigation system can be used, but there is no scientific consensus about which type is the finest. The purpose of this study was to compare various irrigation methods: an IoT-based soil moisture monitoring (IoT-SM) method using moisture sensors and an ET–based strategy. The best irrigation scheduling strategy should be determined by commercial production: keeping the soil water content near field capacity will result in a better fresh yield but not a more dry matter. Sweet corn was chosen as the crop under study. Growth characteristics (plant height, yield, and water productivity) were compared for each of the two approaches. For IoT based soil moisture monitoring method, two irrigation regimes were used: 43.5 per cent and 34.8 per cent (as field capacity (FC) of soil and 80% of FC, respectively) and crop evapotranspiration (ETc 100 per cent) for the ET-based method. The results showed that the IoT-SM 43.5 per cent could produce higher yields of about 12.05% and water savings by 11% compared to the ETc 100 per cent-based irrigation method. The developed IoT system was durable and water-resistant, allowing it to be deployed in outdoor agriculture. At the same time, a solar power supply eliminates the need for cabling and reduces sensor node maintenance.

Keywords

• IoT platform
• ThingSpeak
• Irrigation, Smart farming
• Automatic irrigation
• Soil moisture
• ESP 32