Field evaluation of sensor-driven drip irrigation systems for eggplant production

Sensor-based precision agriculture (PA) is still relatively new in Bangladesh, and field circumstances have not yet been fully examined for its potential. The traditional agriculture practices often fluctuate due to the imbalanced use of water, fertilizers, and pesticides in production practices. Therefore, the objective of this study was to develop and evaluate the IoT-enabled sensor-based drip irrigation for saving water and fertilizers (urea, N and potash, K), and assess the financial analysis for eggplant production. The IoT-enabled sensor-based automated precision irrigation system (T1) was developed and compared with BARI-recommended practices (T2), drip fertigation (T3), and traditional farmers’ practices (T4) for eggplant production. The data on the soil water content, irrigation water, fertilizers and pesticides, fruit yield, and yield contributing characters of eggplant were recorded. Nutrient use efficiency (NUEN, K), water use efficiency (WUE), and benefit cost ratio (BCR) were also estimated for financial profitability and the feasibility of the IoT-based automated eggplant production. The results indicated that the treatment T1 produced (30.99 t/ha) nearly similar yields of T3 (31.73 t/ha), both of which were greater than T4 (30.08 t/ha), while using less water and fertilizers (N and K) than T4. T1 improved yield by 3%, saved 63% water, and enhanced 172.7% water use efficiency more than T4 without compromising yield. Nutrient use efficiency (NUEN, K) was also increased in T1 by 106.9% and 118%, respectively, more than in T4. T1 saved 50% urea and 53% potassium compared to T4. Over the gross costs, BCR was initially lower in T1 than in T4 during the first crop cycle. Considering variable costs, BCR was greater in T1 and T3 than in T4 due to reduced labor, irrigation, fertilizer, and pesticide expenses. The research reveals that an IoT-enabled sensor-based automatic drip irrigation system is an alternative and creative option for eggplant production. This system has the potential to increase yield, enhance the efficiency of water and fertilizer use (urea and potash), and encourage sustainable practices across the country using sensors. Internet of Things (IoT) based automatic drip irrigation and fertigation system improves irrigation water and fertilizer use efficiency without reduction in yield. Marketable fruits yield of eggplant is greater in IoT system than traditional practice although traditional practices use greater fertilizer, water and pesticides. IoT-based automated approach improves efficiency in irrigation water (63%), fertilizers (50%), pesticides (53%), and labors (33%) compared to traditional farming methods. Nutrient (N, K) use efficiency is greater in IoT system than traditional crop production practices. The IoT system is profitable based on variable costs compared to traditional practices.