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Background <p>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.</p> Methods <p>The IoT-enabled sensor-based automated precision irrigation system (T<sub>1</sub>) was developed and compared with BARI-recommended practices (T<sub>2</sub>), drip fertigation (T<sub>3</sub>), and traditional farmers’ practices (T<sub>4</sub>) 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 (NUE<sub>N, K</sub>), 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.</p> Results <p>The results indicated that the treatment T<sub>1</sub> produced (30.99 t/ha) nearly similar yields of T<sub>3</sub> (31.73 t/ha), both of which were greater than T<sub>4</sub> (30.08 t/ha), while using less water and fertilizers (N and K) than T<sub>4</sub>. T<sub>1</sub> improved yield by 3%, saved 63% water, and enhanced 172.7% water use efficiency more than T<sub>4</sub> without compromising yield. Nutrient use efficiency (NUE<sub>N</sub>, <sub>K</sub>) was also increased in T<sub>1</sub> by 106.9% and 118%, respectively, more than in T<sub>4</sub>. T<sub>1</sub> saved 50% urea and 53% potassium compared to T<sub>4</sub>. Over the gross costs, BCR was initially lower in T<sub>1</sub> than in T<sub>4</sub> during the first crop cycle. Considering variable costs, BCR was greater in T<sub>1</sub> and T<sub>3</sub> than in T<sub>4</sub> due to reduced labor, irrigation, fertilizer, and pesticide expenses.</p> Conclusions <p>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.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月4日

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  • Khokan Kumer Sarker,
  • Nazmun Nahar Karim,
  • AFM Tariqul Islam,
  • Istiak Ahmed,
  • Md Nazim Uddin,
  • Saad Hasan,
  • Mohammad Rashedul Hoque,
  • M. Tanseer Ali,
  • Md Shahriar Kabir,
  • Sujit Kumar Biswas,
  • Md Anower Hossain,
  • M. Golam Mahboob

摘要

Background

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.

Methods

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.

Results

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.

Conclusions

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.