Gupta et al. (2026) A Critical Review on Optimization of Water Use in Vegetable Crops Using IoT-Based Low-Cost Sensors

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Journal of Experimental Agriculture International
• Year: 2026
• Date: 2026-01-12
• Authors: Rupanshu Gupta, Surendra Kumar Chandniha, V Harithalekshmi
• DOI: 10.9734/jeai/2026/v48i13992

Research Groups

Not specified for the authors of this review; synthesizes work from a broad range of international research groups.

Short Summary

This review synthesizes 86 studies on IoT-based soil moisture sensor systems for vegetable crop irrigation, revealing 20-45% water savings and improved water use efficiency, while highlighting significant challenges and research gaps, particularly in black cotton soils.

Objective

• To synthesize insights from 86 studies (2007-2025) on IoT-based soil moisture sensor systems for vegetable crop irrigation, analyzing sensor technologies, calibration methods, IoT architectures, wireless communication protocols, and field applications, with a specific emphasis on challenges encountered in black cotton soils (Vertisols).

Study Configuration

• Spatial Scale: Global (synthesizes studies across multiple crops and regions).
• Temporal Scale: Review of studies published between 2007 and 2025.

Methodology and Data

• Models used: Not applicable; this is a review paper synthesizing existing research.
• Data sources: Synthesized insights and findings from 86 peer-reviewed studies published between 2007 and 2025.

Main Results

• IoT-based soil moisture sensor systems consistently reported 20-45% water savings and significant improvements in Water Use Efficiency (WUE) for various vegetable crops, including tomato, okra, spinach, cauliflower, coriander, and sweet corn.
• Capacitive sensors integrated with microcontrollers like NodeMCU ESP8266 and Arduino UNO were the most widely used due to their affordability and ease of deployment.
• Research on Vertisols (black cotton soils) remains limited, with sensor performance often compromised by clay mineralogy, necessitating soil-specific calibration, conductivity compensation, and sensor fusion approaches.
• Long-term multi-crop evaluations and economic feasibility studies for these systems are scarce.
• Emerging trends include the integration of IoT with Artificial Intelligence/Machine Learning (AI/ML) models, renewable energy systems, and climate-smart agriculture platforms to enable predictive irrigation scheduling and scalable adoption.

Contributions

• Provides a comprehensive synthesis of the current state of IoT-based soil moisture sensing for vegetable crop irrigation, identifying key technological advancements and practical applications.
• Highlights critical challenges and research gaps specific to black cotton soils, offering a focused perspective on an under-researched area.
• Outlines emerging trends and future directions, including the integration of AI/ML and renewable energy, to guide future research and development in precision agriculture.

Funding

Not specified in the provided text.

Citation

@article{Gupta2026Critical,
  author = {Gupta, Rupanshu and Chandniha, Surendra Kumar and Harithalekshmi, V},
  title = {A Critical Review on Optimization of Water Use in Vegetable Crops Using IoT-Based Low-Cost Sensors},
  journal = {Journal of Experimental Agriculture International},
  year = {2026},
  doi = {10.9734/jeai/2026/v48i13992},
  url = {https://doi.org/10.9734/jeai/2026/v48i13992}
}